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The Lancet Series: Physical Activity (Published July 18, 2012)

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As London counts down the final days before the beginning of the 2012 Olympic Games, The Lancet publishes a Series on physical activity, including a new analysis that quantifies the global impact of physical inactivity on the world's major non-communicable diseases. The Series will also review current levels of physical activity and trends worldwide, why some people are active and why some are not, evidence-based strategies for effective physical activity promotion, and how a multi-sector and systems-wide approach that goes way beyond health will be critical to increase population-levels of activity worldwide.
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Comment www.thelancet.com Vol 380 July 21, 2012 189 Rethinking our approach to physical activity of physical activity are far-reaching and extend beyond health alone. Being physically active is a major contributor to one’s overall physical and mental wellbeing. Positive outcomes include a sense of purpose and value, a better quality of life, improved sleep, and reduced stress, as well as stronger relationships and social connectedness. Additionally, promoting active modes of travel, such as walking and cycling, are good for the environment, which in turn also has a positive impact on health. But how do we encourage a behaviour that should be part of everyday life? For too long the focus has been on advising individuals to take an active approach to life. There has been far too little consideration of the social and physical environments that enable such activity to be taken. Regular activity must, of course, be done by the individual but, as this Series shows, efforts beyond the health sector through social and environmental change will be necessary if we are to see greater uptake of this healthier behaviour in people’s lives. One might conclude that this Series should not be published in The Lancet. Physical activity is not a medical or pathological predicament but more a cultural challenge: to create a lifestyle inclusive of activity. It could be argued that this Series would be better placed in a national newspaper, a women’s magazine, or a television or radio programme. But the first step in what must be a social revolution towards an active, and away from a Published Online July 18, 2012 http://dx.doi.org/10.1016/ S0140-6736(12)61024-1 See Editorial page 188 See Articles page 219 See Series pages 247, 258, 272, 282, and 294 Children’s Games (Kinderspiele), 1560 (oil on panel), Bruegel, Pieter the Elder (c.1525–69)/ Kunsthistorisches Museum, Vienna, Austria/The Bridgeman Art Library “Lack of activity destroys the good condition of every human being while movement and methodical physical exercise save it and preserve it” Plato This Series on physical activity is not about sport and it is about more than just exercise. It is about the relationship between human beings and their environment, and about improving human wellbeing by strengthening that relationship. It is not about running on a treadmill, whilst staring at a mirror and listening to your iPod. It is about using the body that we have in the way it was designed, which is to walk often, run sometimes, and move in ways where we physically exert ourselves regularly whether that is at work, at home, in transport to and from places, or during leisure time in our daily lives. There is substantial evidence to show that physical inactivity is a major contributor to death and disability from non-communicable diseases (NCDs) worldwide. Since 2005, The Lancet has been part of a worldwide effort to implement action on NCDs. Increasing levels of physical activity is one such priority. 1 However, unlike other NCD risk factors, such as tobacco, diet, and alcohol, the importance of physical activity has been slow to be recognised, and the emphasis to tackle it at a population level has not been forthcoming. Physical activity is a neglected dimension of prevention and intervention worldwide, especially in low-income and middle-income countries. One problem is that physical activity is often perceived only in the context of controlling obesity, and therefore physical inactivity is regarded as a minor or secondary risk factor for NCDs. But an Article in this Series by I-Min Lee and colleagues 2 should cause us to rethink. The authors quantify the ill-effects of inactivity in the first study of its kind with detailed data for each country, where available. They estimate that physical inactivity causes 6–10% of all deaths from the major NCDs (coronary heart disease, type 2 diabetes, and breast and colon cancers). Furthermore, they show that inactivity causes 9% of premature mortality, or more than 5·3 of the 57 million deaths that occurred worldwide in 2008. 3 This figure equates to as many deaths as tobacco causes globally, which is uniformly regarded as a major NCD risk factor. 4 But it is a mistake to view physical activity only in terms of its disease-specific associations. The benefits
Transcript

Comment

www.thelancet.com Vol 380 July 21, 2012 189

Rethinking our approach to physical activity of physical activity are far-reaching and extend beyond health alone. Being physically active is a major contributor to one’s overall physical and mental wellbeing. Positive outcomes include a sense of purpose and value, a better quality of life, improved sleep, and reduced stress, as well as stronger relationships and social connectedness. Additionally, promoting active modes of travel, such as walking and cycling, are good for the environment, which in turn also has a positive impact on health.

But how do we encourage a behaviour that should be part of everyday life? For too long the focus has been on advising individuals to take an active approach to life. There has been far too little consideration of the social and physical environments that enable such activity to be taken. Regular activity must, of course, be done by the individual but, as this Series shows, eff orts beyond the health sector through social and environmental change will be necessary if we are to see greater uptake of this healthier behaviour in people’s lives.

One might conclude that this Series should not be published in The Lancet. Physical activity is not a medical or pathological predicament but more a cultural challenge: to create a lifestyle inclusive of activity. It could be argued that this Series would be better placed in a national newspaper, a women’s magazine, or a television or radio programme. But the fi rst step in what must be a social revolution towards an active, and away from a

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61024-1

See Editorial page 188

See Articles page 219

See Series pages 247, 258, 272, 282, and 294

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“Lack of activity destroys the good condition of every human being while movement and methodical physical exercise save it and preserve it”

Plato

This Series on physical activity is not about sport and it is about more than just exercise. It is about the relationship between human beings and their environment, and about improving human wellbeing by strengthening that relationship. It is not about running on a treadmill, whilst staring at a mirror and listening to your iPod. It is about using the body that we have in the way it was designed, which is to walk often, run sometimes, and move in ways where we physically exert ourselves regularly whether that is at work, at home, in transport to and from places, or during leisure time in our daily lives.

There is substantial evidence to show that physical inactivity is a major contributor to death and disability from non-communicable diseases (NCDs) worldwide. Since 2005, The Lancet has been part of a worldwide eff ort to implement action on NCDs. Increasing levels of physical activity is one such priority.1 However, unlike other NCD risk factors, such as tobacco, diet, and alcohol, the importance of physical activity has been slow to be recognised, and the emphasis to tackle it at a population level has not been forthcoming.

Physical activity is a neglected dimension of prevention and intervention worldwide, especially in low-income and middle-income countries. One problem is that physical activity is often perceived only in the context of controlling obesity, and therefore physical inactivity is regarded as a minor or secondary risk factor for NCDs. But an Article in this Series by I-Min Lee and colleagues2 should cause us to rethink. The authors quantify the ill-eff ects of inactivity in the fi rst study of its kind with detailed data for each country, where available. They estimate that physical inactivity causes 6–10% of all deaths from the major NCDs (coronary heart disease, type 2 diabetes, and breast and colon cancers). Furthermore, they show that inactivity causes 9% of premature mortality, or more than 5·3 of the 57 million deaths that occurred worldwide in 2008.3 This fi gure equates to as many deaths as tobacco causes globally, which is uniformly regarded as a major NCD risk factor.4

But it is a mistake to view physical activity only in terms of its disease-specifi c associations. The benefi ts

Comment

190 www.thelancet.com Vol 380 July 21, 2012

passive, physical and mental life should be to assemble the best experts in the fi eld and the best evidence to understand what we know about the relationship between human health and physical activity. This goal is the purpose of our Series.

Pamela Das, Richard HortonThe Lancet, London NW1 7BY, UK

We warmly thank Pedro Hallal for devising and leading this Series, and I-Min Lee, Adrian Bauman, Mike Pratt, Harold Kohl III, and Gregory Heath for their contributions and support as The Lancet Series steering committee.

Physical activity: more of the same is not enoughFor millennia, exercise has been recommended by physicians and scholars. For more than 60 years, science has shown that the health benefi ts of a physically active lifestyle are extensive and robust. In 1953, The Lancet published landmark papers by Jerry Morris and colleagues on the associations between physical activity at work and coronary heart disease.1,2 Sedentary London Transport Authority bus drivers were at a higher risk of cardiac events than were their more active conductor peers. These publications laid the groundwork for physical activity epidemiology and stimulated the development of substantial research linking inactivity to increased risk of many non-communicable diseases.

We now know that physical inactivity is a signifi cant predictor of cardiovascular disease, type 2 diabetes mellitus, obesity, some cancers, poor skeletal health, some aspects of mental health, and overall mortality, as

well as poor quality of life. Men and women of all ages, socioeconomic groups, and ethnicities are healthier if they achieve the public health recommendation of at least 150 min per week of moderate-intensity aerobic physical activity, such as brisk walking.3 Immediate and future health benefi ts are also clearly described for children and adolescents, for whom at least 60 min per day of vigorous or moderate-intensity physical activity is recommended.4,5 Muscular strengthening physical activities are also recommended for health improvement.3

In 2008, 63% of deaths worldwide were due to non-communicable diseases, mainly diseases of the heart and vascular system, diabetes mellitus, cancers, and obstructive pulmonary disease. Physical activity was recently considered a cornerstone for combating non-communicable diseases by the UN.6 WHO recognises physical inactivity as one of the leading global risk factors for morbidity and premature mortality.7 Further, physical inactivity directly aff ects many risk factors for morbidity and mortality including adiposity, raised blood glucose concentrations, high blood pressure, and a poor lipid profi le. Furthermore, people benefi t from even modest activity. Compared with inactive individuals, those who were active but at levels less than recommended (about 1·5 h per week), lived 3 years longer.8

Clearly, physical activity has vast potential to improve health throughout the world. As the scientifi c contributions of exercise science and public health have advanced our understanding of the health eff ects and consequences, the specialty of physical activity and public health has emerged. Public health practice

1 Beaglehole R, Bonita R, Horton R, et al, for The Lancet NCD Action Group and the NCD Alliance. Priority actions for the non-communicable disease crisis. Lancet 2011; 377: 1438–47.

2 Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, for the Lancet Physical Activity Series Working Group. Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)61031-9.

3 WHO. Global Health Observatory Data Repository. 2011. http://apps.who.int/ghodata (accessed June 26, 2012).

4 WHO. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization, 2009.

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)61027-7

AFP/

Gett

y Im

ages

Comment

190 www.thelancet.com Vol 380 July 21, 2012

passive, physical and mental life should be to assemble the best experts in the fi eld and the best evidence to understand what we know about the relationship between human health and physical activity. This goal is the purpose of our Series.

Pamela Das, Richard HortonThe Lancet, London NW1 7BY, UK

We warmly thank Pedro Hallal for devising and leading this Series, and I-Min Lee, Adrian Bauman, Mike Pratt, Harold Kohl III, and Gregory Heath for their contributions and support as The Lancet Series steering committee.

Physical activity: more of the same is not enoughFor millennia, exercise has been recommended by physicians and scholars. For more than 60 years, science has shown that the health benefi ts of a physically active lifestyle are extensive and robust. In 1953, The Lancet published landmark papers by Jerry Morris and colleagues on the associations between physical activity at work and coronary heart disease.1,2 Sedentary London Transport Authority bus drivers were at a higher risk of cardiac events than were their more active conductor peers. These publications laid the groundwork for physical activity epidemiology and stimulated the development of substantial research linking inactivity to increased risk of many non-communicable diseases.

We now know that physical inactivity is a signifi cant predictor of cardiovascular disease, type 2 diabetes mellitus, obesity, some cancers, poor skeletal health, some aspects of mental health, and overall mortality, as

well as poor quality of life. Men and women of all ages, socioeconomic groups, and ethnicities are healthier if they achieve the public health recommendation of at least 150 min per week of moderate-intensity aerobic physical activity, such as brisk walking.3 Immediate and future health benefi ts are also clearly described for children and adolescents, for whom at least 60 min per day of vigorous or moderate-intensity physical activity is recommended.4,5 Muscular strengthening physical activities are also recommended for health improvement.3

In 2008, 63% of deaths worldwide were due to non-communicable diseases, mainly diseases of the heart and vascular system, diabetes mellitus, cancers, and obstructive pulmonary disease. Physical activity was recently considered a cornerstone for combating non-communicable diseases by the UN.6 WHO recognises physical inactivity as one of the leading global risk factors for morbidity and premature mortality.7 Further, physical inactivity directly aff ects many risk factors for morbidity and mortality including adiposity, raised blood glucose concentrations, high blood pressure, and a poor lipid profi le. Furthermore, people benefi t from even modest activity. Compared with inactive individuals, those who were active but at levels less than recommended (about 1·5 h per week), lived 3 years longer.8

Clearly, physical activity has vast potential to improve health throughout the world. As the scientifi c contributions of exercise science and public health have advanced our understanding of the health eff ects and consequences, the specialty of physical activity and public health has emerged. Public health practice

1 Beaglehole R, Bonita R, Horton R, et al, for The Lancet NCD Action Group and the NCD Alliance. Priority actions for the non-communicable disease crisis. Lancet 2011; 377: 1438–47.

2 Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, for the Lancet Physical Activity Series Working Group. Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)61031-9.

3 WHO. Global Health Observatory Data Repository. 2011. http://apps.who.int/ghodata (accessed June 26, 2012).

4 WHO. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization, 2009.

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)61027-7

AFP/

Gett

y Im

ages

Comment

www.thelancet.com Vol 380 July 21, 2012 191

is an action-oriented discipline that seeks to move populations towards health. After more than 60 years of scientifi c research, technological advancements that nudge us towards physical inactivity make it urgently necessary to take actions. Labour-saving devices such as motor vehicles and other transportation aids have had the unintended consequence of reducing the minimum daily energy expenditure necessary for living. This issue is of particular concern in countries with low-to-middle incomes undergoing substantial social and physical transitions. More of the same (in terms of research and practice) will not be enough. The global challenge is clear: make physical activity a public health priority throughout the world to improve health and reduce the burden of non-communicable diseases. However, to achieve such a goal, much work remains, as this Lancet Series emphasises.

With the upcoming 2012 Olympic Games, sport and physical activity will attract tremendous worldwide attention. Publication of this Series on physical activity and health at the same time as the Olympic Games is not a coincidence. Although the world will be watching elite athletes from many countries compete in sporting events requiring tremendous training, skill, and fi tness, most spectators will be quite inactive. The popularity of the Olympic Games and elite sports such as professional soccer has not been, and will not be, translated into mass participation in exercise and physical activity that will improve the health of the world’s population. Although the International Olympic Committee and the Olympic Movement have expressed concerns about rising inactivity in young people and recognised the importance of physical activity and sports for a healthy lifestyle,9,10 physical inactivity continues to be a substantial concern needing public health action.

The global challenge of making physical activity a public health priority will not be easy to undertake, nor should it be taken lightly. Lessons can be learned from advances made in nutrition and tobacco control, but physical activity should be a separate and equal concern, and recognised as a unique specialty in public health. We trust this Series in The Lancet will initiate travel down that road.

It is especially important to address physical activity and non-communicable diseases in low-income and middle-income countries. Although more than 80% of the world’s population lives in low-income and middle-income countries and more than 80% of the global burden

of non-communicable diseases lies here, only a small fraction of research on physical activity has been focused in these countries. The gap between where research is done and where public health problems are located is striking. Studies on the health benefi ts of physical activity, its correlates, and strategies for eff ective promotion are heavily concentrated in a few countries, most of which have stable or falling rates of non-communicable diseases. The largest increases and burden of non-communicable diseases are now seen in low-income countries, where our understanding of evidence-based strategies for increasing physical activity is poor. Altering this situation must be a priority in the next decade

*Pedro C Hallal, Adrian E Bauman, Gregory W Heath, Harold W Kohl 3rd, I-Min Lee, Michael PrattFederal University of Pelotas, Pelotas 96030002, Brazil (PCH); Prevention Research Collaboration, School of Public Health, Sydney University, Sydney, NSW, Australia (AEB); University of Tennessee at Chattanooga and University of Tennessee College of Medicine, Chattanooga, TN, USA (GWH); University of Texas Health Science Center, Houston School of Public Health, and University of Texas at Austin Department of Kinesiology and Health Education, Austin, TX, USA (HWK); Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA (I-ML); National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA (MP)[email protected]

We declare that we have no confl icts of interest. The fi ndings and conclusions in this report are those of the authors and do not necessarily represent the offi cial position of the US Centers for Disease Control and Prevention.

1 Morris JN, Heady JA, Raffl e PA, Roberts CG, Parks JW. Coronary heart-disease and physical activity of work. Lancet 1953; 262: 1111–20.

2 Morris JN, Heady JA, Raffl e PA, Roberts CG, Parks JW. Coronary heart-disease and physical activity of work. Lancet 1953; 262: 1053–57.

3 Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report, 2008. Washington, DC: US Department of Health and Human Services, 2008.

4 Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007; 116: 1081–93.

5 WHO. Global recommendations on physical activity for health. Geneva: World Health Organization, 2011.

6 UN. 2011 High level meeting on prevention and control of non-communicable diseases. General Assembly. New York, NY: United Nations, 2011.

7 WHO. Physical inactivity: a global public health problem. Geneva: World Health Organization, 2011.

8 Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet 2011; 378: 1244–53.

9 International Olympic Committee. The 2006 Havana Sport for All Declaration. Havana: International Olympic Committee, 2006.

10 Mountjoy M, Andersen LB, Armstrong N, et al. International Olympic Committee consensus statement on the health and fi tness of young people through physical activity and sport. Br J Sports Med 2011; 45: 839–48.

Comment

192 www.thelancet.com Vol 380 July 21, 2012

Stressing harms of physical inactivity to promote exerciseExercise has been called a miracle drug1 that can benefi t every part of the body2 and substantially extend lifespan.3 Yet it receives little respect from doctors or society.4 Socially, being inactive is perceived as normal, and in fact doctors order patients to remain on bed rest far more often than they encourage exercise.5 This passive attitude towards inactivity, where exercise is viewed as a personal choice, is anachronistic, and is reminiscent of the battles still being fought over smoking.

Physical inactivity burdens society through the hidden and growing cost of medical care and loss of product-ivity. Getting the public to exercise is a public health priority because inactive people are contributing to a mortality burden as large as tobacco smoking. To individuals, the failure to spend 15–30 min a day in brisk walking increases the risk of cancer, heart disease, stroke, and diabetes by 20–30%,3,5 and shortens lifespan by 3–5 years.3 Although the benefi ts of exercise and the harms of inactivity might seem like two sides of a coin, the benefi ts message emphasised so far has not worked well for most of the population. In tobacco control, doctors did not emphasise the benefi ts of non-smoking, but the harms of smoking. Similarly, armed with credible global and national data, we should emphasise the harms of inactivity and not merely the benefi ts of exercise.

Smoking and physical inactivity are the two major risk factors for non-communicable diseases around the globe. Of the 36 million deaths each year from non-communicable diseases,6 physical inactivity5 and smoking each contribute about 5 million.7 Physical inactivity

and smoking have similar population attrib utable risks, although their relative risks8,9 and prevalence are some-what diff erent (fi gure). For smoking, intensive and coordinated tobacco control eff orts have been organised through WHO’s Framework Convention on Tobacco Control (FCTC), a treaty already ratifi ed by 175 countries.10 By contrast, we have few organised eff orts to combat physical inactivity. Governmental programmes to move people from sedentary living to meeting recommended levels of exercise are very limited, in both developed and developing countries. Where available, these programmes are viewed as useful but not as essential as, say, anti-smoking programmes, partly owing to a failure to emphasise the colossal harms of inactivity. Furthermore, treatment of physical inactivity is not a reimbursable item under most health insurance programmes, and few fi nancial incentives exist for health-care providers to spend time discussing exercise during medical visits.

Estimates of the eff ect of inactivity on non-communicable diseases, such as a 6–10% contribution, are very conservative as reported by one of the papers5 in this Series. First, the minimally active population might not be separated from those who are completely inactive, with a 3-year gap in life expectancy reported between the two groups.3 The largest health gain occurs for the fi rst 15–29 min per day of exercise by inactive people.3,11 Second, the prevalence of inactivity could be underestimated substantially, particularly in Asian countries where up to 80% national prevalence for inactivity has been reported.3,12 Third, if the life expectancy gap between active and inactive people were to be derived from summary risk estimates, underestimation would occur if adjusted rather than unadjusted relative risks were used, or if mortality risks were not constant across age groups.13 Finally, the small increase in the estimated life expectancy gap8 should be read with caution as it is relevant to the population as a whole, and is not limited to inactive people.

There is much to learn from tobacco control strategies to reduce the harms of inactivity. WHO introduced the MPOWER measures to assist in reducing smoking harms at the country level.14 MPOWER includes monitoring behaviour, protecting people from smoke, off ering treatment, warning of harms, enforcing the law, and raising the price. Applying MPOWER to physical

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)60954-4

See Articles page 219

Global deaths per yearPrevalence

Smoking Inactivity Smoking Inactivity Smoking Inactivity Smoking Inactivity

26%

35%

1·571·28 8·7% 9·0%

5·1million

5·3million

Hazard ratio PAR

Figure: Comparison of global burden between smoking and physical inactivityPrevalence of smoking, population attributable risk (PAR), and global deaths for smoking were obtained from WHO.7 Hazard ratio for all-cause mortality of smoking was obtained from meta-analysis studies.8,9 All inactivity data were obtained from Lee and colleagues.5

Comment

www.thelancet.com Vol 380 July 21, 2012 193

Physical activity for people with disabilitiesThere are more than a billion people with disabilities worldwide,1 many of whom face substantial barriers to participating in physical activity.2 Engaging in a healthy lifestyle with a disability can be a daunting task—physical activity generally requires elements of strength, endurance, balance, and coordination that are taken for granted. In people with disabilities, one or more physical attributes might be aff ected by disability, which limits access to sport, fi tness, and work or household-related physical activity.

Lack of exercise is a serious public health concern for all people, but people with disabilities are at much greater risk of the serious health problems associated with physical inactivity.3 In the USA, adults with disability were twice as likely to be physically inactive

than were those with no disability.4 Increased rates of physical inactivity were also reported in adults with disabilities from Canada5 and Norway,6 and in children with disabilities in Hong Kong.7

Personal and environmental barriers associated with disability restrict access to physical activity venues and services. Personal barriers include pain, lack of energy, self-consciousness about exercising in public, and the perception that exercise is too diffi cult.8 Environmental barriers include lack of transportation; lack of access-ible exercise equipment; unqualifi ed staff who cannot modify or adapt individual and group exercise classes for people with disabilities; programme and equipment costs; and discriminatory practices at fi tness centres and other recreational venues.9 Among children

inactivity, we will need to monitor inactivity prevalence and factors behind it; protect the safety of the exercisers and their built environment;15 off er services to the inactive to gain skills for sustainable and enjoyable exercise; warn the public of the hazards of inactivity through repeated campaigns; ensure that the medical community fulfi ls its responsibility to reduce inactivity; and, fi nally, raise money or provide funding to encourage physical activity and discourage inactivity.

In addition to doctors’ traditional advocacy of the health benefi ts of exercise, stressing the harms of inactivity could strengthen our battle against inactivity. We need to view the inactive population as abnormal and consider them at high risk of disease. If we accept this view, governmental programmes modelled on MPOWER to diminish physical inactivity could be justifi ed, with commensurate resources committed in each country to tackle the major threat to human health of non-communicable diseases.

*Chi Pang Wen, Xifeng WuNational Health Research Institutes and China Medical University Hospital, Zhunan, Taiwan (CPW); and Department of Epidemiology, Division of Cancer Prevention and Population Sciences, the University of Texas MD Anderson Cancer Center,Houston, TX, USA (XW)[email protected]

We declare that we have no confl icts of interest.

1 Pimlott N. The miracle drug. Can Fam Physician 2010; 56: 407–09.

2 Centers for Disease Control and Prevention. Surgeon General’s Report on Physical Activity and Health. 1996. http://www.cdc.gov/nccdphp/sgr/index.htm (accessed June 4, 2012).

3 Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet 2011; 378: 1244–53.

4 Walsh JM, Swangard DM, Davis T, McPhee SJ. Exercise counseling by primary care physicians in the era of managed care. Am J Prev Med 1999; 16: 307–13.

5 Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, for the Lancet Physical Activity Series Working Group. Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)61031-9.

6 WHO. United Nations high-level meeting on noncommunicable disease prevention and control: NCD summit to shape the international agenda 2011. http://www.who.int/nmh/events/un_ncd_summit2011/en (accessed June 4, 2012).

7 WHO. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization, 2009.

8 Shavelle RM, Paculdo DR, Strauss DJ, Kush SJ. Smoking habit and mortality: a meta-analysis. J Insur Med 2008; 40: 170–78.

9 Wen CP, Tsai SP, Chen CJ, Cheng TY, Tsai MC, Levy DT. Smoking attributable mortality for Taiwan and its projection to 2020 under diff erent smoking scenarios. Tob Control 2005; 14 (suppl 1): i76–80.

10 WHO. WHO Framework Convention on Tobacco Control 2012. http://www.who.int/fctc/en (accessed June 4, 2012).

11 Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies. Int J Epidemiol 2011; 40: 121–38.

12 Wai JP, Wen CP, Chan HT, et al. Assessing physical activity in an Asian country: low energy expenditure and exercise frequency among adults in Taiwan. Asia Pac J Clin Nutr 2008; 17: 297–308.

13 Wen CP, Tsai MK, Tsai SP, et al. Exercise and life expectancy—Authors’ reply. Lancet 2012; 379: 800–01.

14 WHO. Research for International Tobacco Control. WHO report on the global tobacco epidemic, 2008: the MPOWER package. Geneva: World Health Organization, 2008.

15 National Research Council (US) Committee on Physical Activity Health Transportation and Land Use, National Research Council (US) Transportation Research Board, Institute of Medicine (US). Does the built environment infl uence physical activity?: examining the evidence. Washington, DC: Transportation Research Board, 2005.

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61028-9

Comment

www.thelancet.com Vol 380 July 21, 2012 193

Physical activity for people with disabilitiesThere are more than a billion people with disabilities worldwide,1 many of whom face substantial barriers to participating in physical activity.2 Engaging in a healthy lifestyle with a disability can be a daunting task—physical activity generally requires elements of strength, endurance, balance, and coordination that are taken for granted. In people with disabilities, one or more physical attributes might be aff ected by disability, which limits access to sport, fi tness, and work or household-related physical activity.

Lack of exercise is a serious public health concern for all people, but people with disabilities are at much greater risk of the serious health problems associated with physical inactivity.3 In the USA, adults with disability were twice as likely to be physically inactive

than were those with no disability.4 Increased rates of physical inactivity were also reported in adults with disabilities from Canada5 and Norway,6 and in children with disabilities in Hong Kong.7

Personal and environmental barriers associated with disability restrict access to physical activity venues and services. Personal barriers include pain, lack of energy, self-consciousness about exercising in public, and the perception that exercise is too diffi cult.8 Environmental barriers include lack of transportation; lack of access-ible exercise equipment; unqualifi ed staff who cannot modify or adapt individual and group exercise classes for people with disabilities; programme and equipment costs; and discriminatory practices at fi tness centres and other recreational venues.9 Among children

inactivity, we will need to monitor inactivity prevalence and factors behind it; protect the safety of the exercisers and their built environment;15 off er services to the inactive to gain skills for sustainable and enjoyable exercise; warn the public of the hazards of inactivity through repeated campaigns; ensure that the medical community fulfi ls its responsibility to reduce inactivity; and, fi nally, raise money or provide funding to encourage physical activity and discourage inactivity.

In addition to doctors’ traditional advocacy of the health benefi ts of exercise, stressing the harms of inactivity could strengthen our battle against inactivity. We need to view the inactive population as abnormal and consider them at high risk of disease. If we accept this view, governmental programmes modelled on MPOWER to diminish physical inactivity could be justifi ed, with commensurate resources committed in each country to tackle the major threat to human health of non-communicable diseases.

*Chi Pang Wen, Xifeng WuNational Health Research Institutes and China Medical University Hospital, Zhunan, Taiwan (CPW); and Department of Epidemiology, Division of Cancer Prevention and Population Sciences, the University of Texas MD Anderson Cancer Center,Houston, TX, USA (XW)[email protected]

We declare that we have no confl icts of interest.

1 Pimlott N. The miracle drug. Can Fam Physician 2010; 56: 407–09.

2 Centers for Disease Control and Prevention. Surgeon General’s Report on Physical Activity and Health. 1996. http://www.cdc.gov/nccdphp/sgr/index.htm (accessed June 4, 2012).

3 Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet 2011; 378: 1244–53.

4 Walsh JM, Swangard DM, Davis T, McPhee SJ. Exercise counseling by primary care physicians in the era of managed care. Am J Prev Med 1999; 16: 307–13.

5 Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, for the Lancet Physical Activity Series Working Group. Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)61031-9.

6 WHO. United Nations high-level meeting on noncommunicable disease prevention and control: NCD summit to shape the international agenda 2011. http://www.who.int/nmh/events/un_ncd_summit2011/en (accessed June 4, 2012).

7 WHO. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization, 2009.

8 Shavelle RM, Paculdo DR, Strauss DJ, Kush SJ. Smoking habit and mortality: a meta-analysis. J Insur Med 2008; 40: 170–78.

9 Wen CP, Tsai SP, Chen CJ, Cheng TY, Tsai MC, Levy DT. Smoking attributable mortality for Taiwan and its projection to 2020 under diff erent smoking scenarios. Tob Control 2005; 14 (suppl 1): i76–80.

10 WHO. WHO Framework Convention on Tobacco Control 2012. http://www.who.int/fctc/en (accessed June 4, 2012).

11 Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies. Int J Epidemiol 2011; 40: 121–38.

12 Wai JP, Wen CP, Chan HT, et al. Assessing physical activity in an Asian country: low energy expenditure and exercise frequency among adults in Taiwan. Asia Pac J Clin Nutr 2008; 17: 297–308.

13 Wen CP, Tsai MK, Tsai SP, et al. Exercise and life expectancy—Authors’ reply. Lancet 2012; 379: 800–01.

14 WHO. Research for International Tobacco Control. WHO report on the global tobacco epidemic, 2008: the MPOWER package. Geneva: World Health Organization, 2008.

15 National Research Council (US) Committee on Physical Activity Health Transportation and Land Use, National Research Council (US) Transportation Research Board, Institute of Medicine (US). Does the built environment infl uence physical activity?: examining the evidence. Washington, DC: Transportation Research Board, 2005.

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61028-9

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and adolescents with disabilities, engaging in physical activity can be even more challenging than for adults.10 Sports venues and physical education classes are often used for competitive sports.11 Children with limitations in balance, strength, coordination, power, and aerobic fi tness can struggle to compete, and a lack of success often leads to sedentary behaviour.

Society has to promote an inclusive approach to com-munity programmes and services that recognises and supports the needs of people with disabilities. Although there will always be a need for more separate or adapted physical activity services, the fact that these programmes are off ered sparingly in most communities throughout the world, especially in poorer countries where there are limited resources devoted to the care and wellbeing of people with disabilities,12 lends itself to the need for more inclusive physical activity programmes that provide elements of adaptation for people with disabilities.

There is a sense of urgency in promotion of physical activity among people with disabilities worldwide. Policy and infrastructure changes to promote active living have not placed a high priority on information or resources tailored for people with disabilities. Similarly, although primary prevention eff orts have expanded to include health communication, social media, and community health policies, stakeholders involved in these programmes rarely, if ever, address the needs of people with disabilities.

Disability advocates and service providers, health professionals with specialisations in adapted physical activity, and physical activity planners need to work

together to establish a policy setting agenda that supports inclusion of people with disabilities. Physical activity services funded by government agencies and private foundations should require recipients to make their programmes accessible to people with disabilities.

What can be done to promote inclusion of people with disabilities in physical activity initiatives? First, local and national networks should provide technical support and training in inclusive physical activity. Communities should bear the responsibility of identifying where people with disabilities live, what issues they experience in accessing physical activity programmes and venues, and what support services are needed to increase participation. With the globalisation of online learning, there is greater opportunity to train professionals in developing inclusive physical activity communities that support people with disabilities.

Second, in many developed and developing countries, there are existing local disability associations and net-works.1 These entities should be made aware of local and national physical activity planning initiatives and be asked to participate. Similarly, people with disabilities or family carers should be invited to comment on any new initiatives associated with physical activity promotion.

Third, all sectors of public health, including schools, workplaces, and health-care facilities, should represent the needs of children and adults with disabilities. In schools, for example, improving physical education for all children should consider what programme accommodations are needed for children with dis-abilities. A new fi tness centre should consider ways to make the facility accessible to people with disabilities.13 Planners designing new cycle and walking paths should include ramps and other design modifi cations appropriate for people with disabilities.

Fourth, there should be ongoing monitoring of approaches that support physical activity programmes and venues for people with disabilities. Solutions to existing challenges should be collected and dis-seminated through various physical activity networks. Epidemiological research should include disability identifi ers so that new strategies to promote physical activity can be assessed for their eff ectiveness.

Finally, Article 31 of the Convention on the Rights of Persons with Disabilities14 states that adults and chil-dren with disabilities must have access to recreational,

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leisure, and sporting activities in both inclusive and disability-specifi c settings. The outcome of inclusive physical activity communities is a society that respects and values the rights of all to have equal access to physical activity.

*James H Rimmer, Alexandre C MarquesUniversity of Alabama at Birmingham and Lakeshore Foundation, Birmingham, AL 35294–1212, USA (JHR); and Federal University of Pelotas, Pelotas, Brazil (ACM)[email protected]

We declare that we have no confl icts of interest.

1 WHO. World report on disability. Geneva: World Health Organization. 2011.2 Rimmer JH. The conspicuous absence of people with disabilities in public

fi tness and recreation facilities: lack of interest or lack of access? Am J Health Promot 2005; 19: 327–29, ii.

3 Rimmer J, Schiller W, Chen M-D. Eff ects of disability-associated low energy expenditure deconditioning syndrome. Exerc Sport Sci Rev 2012; 40: 22–29.

4 Centers for Disease Control and Prevention. Physical activity among adults with a disability—United States, 2005. MMWR Morb Mortal Wkly Rep 2007; 56: 1021–24.

Policies to promote physical activity in BrazilNon-communicable diseases (NCDs) are the leading cause of mortality in Brazil and accounted for 72% of all deaths in 2007.1 The burden of NCDs in Brazil refl ects accelerated epidemiological, demographic, and nutri tional changes in the past few decades. In 1930, 46% of all deaths in Brazilian state capitals were caused by infectious diseases, but by 2007 this fi gure had fallen to 10%.1 During the same period, mortality from cardiovascular diseases increased from 11% to 31%.1–3 The country’s demographic transition is the result of declines in premature mortality and fertility rates, alongside a rapidly ageing population.1–3 Increased income, industrialisation, urbanisation, and globalisation have led to much economic and social change in Brazil. One consequence has been a rise in unhealthy diets and physical inactivity; the prevalence of men who were overweight increased from 18·6% in 1974 to 50·1% in 2008.1,4

NCDs and their risk factors aff ect people from all socioeconomic groups, but especially individuals who are most vulnerable, such as older adults and those with low educational attainment or from low-income families.1,5 Surveys in Brazil have shown that smoking, obesity, and unhealthy diets are more frequent in individuals with low educational attainment.4,6 Among Indian populations living in Brazil, the prevalence of obesity reached 25%

in men and 41% in women in 1989, particularly due to westernised diets and reductions in physical activity.7

The Brazilian phone surveillance system shows that leisure-time physical activity is most frequent in young adults, men, those with high educational attainment, and people who live near public spaces with equipment for physical activity.7–9 The proportion of adults who reported no engagement in physical activity declined from 16% in 2009 to 14·1% in 2011.6,8 This progress in physical activity refl ects improvements in active transportation, health education, and communication strategies, and the launch of physical activity inter ventions funded by the Brazilian Ministry of Health in more than 1000 cities.2,8

The Brazilian Government launched a strategic plan to tackle NCDs in 2011. The plan aims to decrease the burden of NCDs by 2% per year and reduce exposure to such risk factors as smoking, consumption of alcohol, physical inactivity, and salt intake.2,3 During the development of this national plan, the Brazilian Government took account of the results of evaluation studies of community interventions to promote physical activity, particularly physical activity classes in community settings through programmes such as the Academia da Cidade in Recife, Aracaju, and Belo Horizonte. These evaluation studies were undertaken through the project Guide for Useful

5 Martin Ginis K, Hicks A. Considerations for the development of a physical activity guide for Canadians with physical disabilities. Appl Physiol Nutr Metab 2007; 32: S135–47.

6 Nortvedt M, Riise T, Maeland JG. Multiple sclerosis and lifestyle factors: the Hordaland health study. Neurol Sci 2005; 26: 334–39.

7 Sit C, McManus A, McKenzie TL, Lian J. Physical activity levels of children in special schools. Prev Med 2007; 45: 424–31.

8 Phillips M, Flemming N, Tsintzas K. An exploratory study of physical activity and perceived barriers to exercise in ambulant people with neuromuscular disease compared with unaff ected controls. Clin Rehab 2009; 23: 746–55.

9 Rimmer JH, Riley B, Wang E, Rauworth A, Jurkowski J. Physical activity participation among persons with disabilities: barriers and facilitators. Am J Prev Med 2004; 26: 419–25.

10 Murphy N, Carbone P, Council on Children With Disabilities. Promoting the participation of children with disabilities in sports, recreation, and physical activities. Pediatrics 2008; 121: 1057–61.

11 Rimmer JH, Rowland JL. Physical activity for youth with disabilities: a critical need in an underserved population. Dev Neurorehabil 2008; 11: 141–48.

12 Barnes C, Sheldon A. Disability, politics and poverty in a majority world context. Dis & Soc 2010; 25: 771–82.

13 Riley B, Rimmer JH, Wang E, Schiller WJ. A conceptual framework for improving the accessibility of fi tness and recreation facilities for people with disabilities. J Phys Act Health 2008; 5: 158–68.

14 UN Convention on the rights of persons with disabilities and optional protocol 2006. New York, NY: United Nations, 2006.

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61041-1

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leisure, and sporting activities in both inclusive and disability-specifi c settings. The outcome of inclusive physical activity communities is a society that respects and values the rights of all to have equal access to physical activity.

*James H Rimmer, Alexandre C MarquesUniversity of Alabama at Birmingham and Lakeshore Foundation, Birmingham, AL 35294–1212, USA (JHR); and Federal University of Pelotas, Pelotas, Brazil (ACM)[email protected]

We declare that we have no confl icts of interest.

1 WHO. World report on disability. Geneva: World Health Organization. 2011.2 Rimmer JH. The conspicuous absence of people with disabilities in public

fi tness and recreation facilities: lack of interest or lack of access? Am J Health Promot 2005; 19: 327–29, ii.

3 Rimmer J, Schiller W, Chen M-D. Eff ects of disability-associated low energy expenditure deconditioning syndrome. Exerc Sport Sci Rev 2012; 40: 22–29.

4 Centers for Disease Control and Prevention. Physical activity among adults with a disability—United States, 2005. MMWR Morb Mortal Wkly Rep 2007; 56: 1021–24.

Policies to promote physical activity in BrazilNon-communicable diseases (NCDs) are the leading cause of mortality in Brazil and accounted for 72% of all deaths in 2007.1 The burden of NCDs in Brazil refl ects accelerated epidemiological, demographic, and nutri tional changes in the past few decades. In 1930, 46% of all deaths in Brazilian state capitals were caused by infectious diseases, but by 2007 this fi gure had fallen to 10%.1 During the same period, mortality from cardiovascular diseases increased from 11% to 31%.1–3 The country’s demographic transition is the result of declines in premature mortality and fertility rates, alongside a rapidly ageing population.1–3 Increased income, industrialisation, urbanisation, and globalisation have led to much economic and social change in Brazil. One consequence has been a rise in unhealthy diets and physical inactivity; the prevalence of men who were overweight increased from 18·6% in 1974 to 50·1% in 2008.1,4

NCDs and their risk factors aff ect people from all socioeconomic groups, but especially individuals who are most vulnerable, such as older adults and those with low educational attainment or from low-income families.1,5 Surveys in Brazil have shown that smoking, obesity, and unhealthy diets are more frequent in individuals with low educational attainment.4,6 Among Indian populations living in Brazil, the prevalence of obesity reached 25%

in men and 41% in women in 1989, particularly due to westernised diets and reductions in physical activity.7

The Brazilian phone surveillance system shows that leisure-time physical activity is most frequent in young adults, men, those with high educational attainment, and people who live near public spaces with equipment for physical activity.7–9 The proportion of adults who reported no engagement in physical activity declined from 16% in 2009 to 14·1% in 2011.6,8 This progress in physical activity refl ects improvements in active transportation, health education, and communication strategies, and the launch of physical activity inter ventions funded by the Brazilian Ministry of Health in more than 1000 cities.2,8

The Brazilian Government launched a strategic plan to tackle NCDs in 2011. The plan aims to decrease the burden of NCDs by 2% per year and reduce exposure to such risk factors as smoking, consumption of alcohol, physical inactivity, and salt intake.2,3 During the development of this national plan, the Brazilian Government took account of the results of evaluation studies of community interventions to promote physical activity, particularly physical activity classes in community settings through programmes such as the Academia da Cidade in Recife, Aracaju, and Belo Horizonte. These evaluation studies were undertaken through the project Guide for Useful

5 Martin Ginis K, Hicks A. Considerations for the development of a physical activity guide for Canadians with physical disabilities. Appl Physiol Nutr Metab 2007; 32: S135–47.

6 Nortvedt M, Riise T, Maeland JG. Multiple sclerosis and lifestyle factors: the Hordaland health study. Neurol Sci 2005; 26: 334–39.

7 Sit C, McManus A, McKenzie TL, Lian J. Physical activity levels of children in special schools. Prev Med 2007; 45: 424–31.

8 Phillips M, Flemming N, Tsintzas K. An exploratory study of physical activity and perceived barriers to exercise in ambulant people with neuromuscular disease compared with unaff ected controls. Clin Rehab 2009; 23: 746–55.

9 Rimmer JH, Riley B, Wang E, Rauworth A, Jurkowski J. Physical activity participation among persons with disabilities: barriers and facilitators. Am J Prev Med 2004; 26: 419–25.

10 Murphy N, Carbone P, Council on Children With Disabilities. Promoting the participation of children with disabilities in sports, recreation, and physical activities. Pediatrics 2008; 121: 1057–61.

11 Rimmer JH, Rowland JL. Physical activity for youth with disabilities: a critical need in an underserved population. Dev Neurorehabil 2008; 11: 141–48.

12 Barnes C, Sheldon A. Disability, politics and poverty in a majority world context. Dis & Soc 2010; 25: 771–82.

13 Riley B, Rimmer JH, Wang E, Schiller WJ. A conceptual framework for improving the accessibility of fi tness and recreation facilities for people with disabilities. J Phys Act Health 2008; 5: 158–68.

14 UN Convention on the rights of persons with disabilities and optional protocol 2006. New York, NY: United Nations, 2006.

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61041-1

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Interventions for Activity in Brazil and Latin America (GUIA) in partnership with the Brazilian Ministry of Health, the US Centers for Disease Control and Prevention, and universities in Brazil and the USA. The studies found that participants in these programmes are more active than their peers.10,11 This fi nding led to the category “physical activity classes in community settings” being identifi ed as useful in policy to improve physical activity among Latin American populations.10,11

This body of evidence lent support to the launch of the Academia da Saúde (Health Academy) programme by the Brazilian Ministry of Health, which aims to off er physical activity classes in community settings at no cost to participants in 4000 Brazilian municipalities—more than 80% of all cities in the country—by 2015. The health academies are spaces with infrastructure, equipment, and human resources to stimulate and guide people in physical activity. The programme is integrated with primary care and US$150 million was invested in the fi rst year.2,3 The objective for the health academies programme is to overcome structural barriers to physical activity and healthy habits, especially among vulnerable populations.2,3

The strategic plan to tackle NCDs also encourages in-creased provision of physical activity in schools through partnerships with the Ministry of Sports and the Ministry of Education.2,3 Furthermore, educational measures that foster healthy habits and the practice of daily physical activity are underway as part of the legacy of two major sporting events that will be held in Brazil: the 2014 World Cup and the Olympic Games in 2016.2,3

The goals of the national plan will be monitored by Brazil’s system of NCD surveillance, household population surveys every 5 years, annual telephone surveys, information systems, and other studies. The Brazilian Ministry of Health has sponsored universities to evaluate the eff ectiveness of the Academia da Saúde programme. Additionally, there will be three household surveys on the impact of the programme; telephone inquiries for the managers of the municipalities; quali tative evaluation of implementation of the programme; and studies of the levels of physical activities in the spaces provided by the health academies and other settings.3 Brazil’s plan aims to prepare the country to tackle NCDs whilst contributing to global mobilisation towards this goal.12

*Deborah Carvalho Malta, Jarbas Barbosa da SilvaSecretaria de Vigilância em Saúde, Ministério da Saúde do Brasil, Brasília 70070–600, Brazil (DCM, JBdS); and Universidade Federal de Minas Gerais, Belo Horizonte, Brazil (DCM) [email protected]

DCM and JBdS coordinated the elaboration of the strategic action plan to tackle chronic non-communicable diseases in Brazil 2011–2022 and participated in the team to develop the proposed Academia da SaÚde programme. We declare that we have no confl icts of interest.

1 Schmidt MI, Duncan BB, Silva GA, et al. Chronic non-communicable diseases in Brazil: burden and current challenges. Lancet 2011; 377: 1949–61.

2 Brasil Ministério da Saúde. Strategic action plan to tackle chronic noncommunicable diseases in Brazil 2011–2022 . Brasília: Ministério da Saúde, 2011 (in Portuguese). http://portal.saude.gov.br/portal/saude/profi ssional/area.cfm?id_area=1818 (accessed June 19, 2012).

3 Malta DC, Morais Neto OL, Silva Junior JB. Presentation of the strategic action plan for coping with chronic diseases in Brazil from 2011 to 2022. Epidemiol Serv Saúde 2011; 20: 425–38.

4 Ministerio do Planejamento, Orcamento e Gestao, Instituto Brasileiro de Geografi a e Estatistica, Diretoria de Pesquisas, Coordenacao de Trabalho e Rendimento. Pesquisa de orcamentos familiares 2008–2009 antropometria e estado nutricional de criancas, adolescentes e adultos no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografi a e Estatistica, 2010 (in Portuguese).

5 WHO. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization, 2011.

6 Brasil Ministério da Saúde. Secretaria de Vigilância em Saúde. Vigitel Brasil 2011: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Brasília: Ministério da Saúde, 2011 (in Portuguese).

7 Welch JR, Ferreira AA, Santos RV, et al. Nutrition transition, socioeconomic diff erentiation, and gender among adult Xavante Indians, Brazilian Amazon. Hum Ecol 2009; 37: 13–26.

8 Hallal PC, Knuth AG, Reis RS, et al. Tendências temporais de atividade física no Brasil (2006–2009). Rev Bras Epidemiol 2011; 4 (suppl 1): 53–60 (in Portuguese).

9 Malta DC, Moura EC, de Castro AM, et al. Padrão de atividade física em adultos brasileiros: resultados de um inquérito por entrevistas telefônicas, 2006. Epidemiol Serv Saúde 2009; 18: 7–16.

10 Simoes EJ, Hallal P, Pratt M, et al. Eff ects of a community-based, professionally supervised intervention on physical activity levels among residents of Recife, Brazil. Am J Public Health 2009; 99: 68–75.

11 Reis RS, Hallal PC, Parra DC, et al. Promoting physical activity through community-wide policies and planning: fi ndings from Curitiba, Brazil. J Phys Act Health 2010; 7 (suppl 2): S137–S45.

12 UN General Assembly 66th Session. Political declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases. A/66/L.1. Sept 16, 2011. New York: United Nations, 2011.

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Lancet 2012; 380: 219–29

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)61031-9

See Comment page 192

*Members listed at end of paper

Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA (I-M Lee ScD); Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA (E J Shiroma MSc); Global Health Promotion Offi ce, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA (F Lobelo MD); National Institute for Health and Welfare, Helsinki, Finland (P Puska MD); Department of Exercise Science and Department of Epidemiology/Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA (S N Blair PED); and Pennington Biomedical Research Center, Baton Rouge, LA, USA (P T Katzmarzyk PhD)

Correspondence to:Dr I-Min Lee, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, [email protected]

Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancyI-Min Lee, Eric J Shiroma, Felipe Lobelo, Pekka Puska, Steven N Blair, Peter T Katzmarzyk, for the Lancet Physical Activity Series Working Group*

SummaryBackground Strong evidence shows that physical inactivity increases the risk of many adverse health conditions, including major non-communicable diseases such as coronary heart disease, type 2 diabetes, and breast and colon cancers, and shortens life expectancy. Because much of the world’s population is inactive, this link presents a major public health issue. We aimed to quantify the eff ect of physical inactivity on these major non-communicable diseases by estimating how much disease could be averted if inactive people were to become active and to estimate gain in life expectancy at the population level.

Methods For our analysis of burden of disease, we calculated population attributable fractions (PAFs) associated with physical inactivity using conservative assumptions for each of the major non-communicable diseases, by country, to estimate how much disease could be averted if physical inactivity were eliminated. We used life-table analysis to estimate gains in life expectancy of the population.

Findings Worldwide, we estimate that physical inactivity causes 6% (ranging from 3·2% in southeast Asia to 7·8% in the eastern Mediterranean region) of the burden of disease from coronary heart disease, 7% (3·9–9·6) of type 2 diabetes, 10% (5·6–14·1) of breast cancer, and 10% (5·7–13·8) of colon cancer. Inactivity causes 9% (range 5·1–12·5) of premature mortality, or more than 5·3 million of the 57 million deaths that occurred worldwide in 2008. If inactivity were not eliminated, but decreased instead by 10% or 25%, more than 533 000 and more than 1·3 million deaths, respectively, could be averted every year. We estimated that elimination of physical inactivity would increase the life expectancy of the world’s population by 0·68 (range 0·41–0·95) years.

Interpretation Physical inactivity has a major health eff ect worldwide. Decrease in or removal of this unhealthy behaviour could improve health substantially.

Funding None.

IntroductionAncient physicians—including those from China in 2600 BC and Hippocrates around 400 BC—believed in the value of physical activity for health. By the 20th century, however, a diametrically opposite view—that exercise was dangerous—prevailed instead.1 During the early 20th century, complete bed rest was prescribed for patients with acute myocardial infarction. And, at the time of the 100th boat race between the Universities of Oxford and Cambridge, UK, in 1954, the senior health offi cer of Cambridge University undertook a study to investigate the alleged dangers of exercise by comparing university sportsmen with intellectuals.1

One of the pioneers whose work helped to change that tide of popular opinion was Jerry Morris, who undertook the fi rst rigorous, epidemiological studies investigating physical inactivity and chronic disease risk, published in 1953.2 Since then, much evidence has clearly documented the many health benefi ts of physical activity (panel 1).3–5 Despite this knowledge, a large proportion of the world’s population remains physically inactive. To quantify the eff ect of physical inactivity on the world’s major non-communicable diseases, we estimated how much of

these diseases could be averted in the population if inactive people were to become active, as well as how much gain in life expectancy could occur at the population level. We focus on the major non-com-municable diseases emphasised by the UN as threats to global health:6 coronary heart disease; cancer, specifi cally breast and colon cancers, which are convincingly related to physical inactivity; and type 2 diabetes.

MethodsPopulation attributable fractionThe population attributable fraction (PAF) is a measure used by epidemiologists to estimate the eff ect of a risk factor on disease incidence in a population.7,8 It estimates the proportion of new cases that would not occur, absent a particular risk factor. Thus, it provides policy makers with useful quantitative estimates of the potential eff ect of interventions to reduce or eradicate the risk factor.

PAF is related to prevalence of the risk factor and its associated relative risk (RR). At least two formulae are available to calculate PAF (panel 2). Formula 1 provides an unbiased estimate when there is no confounding of the relation between the risk factor and disease, and

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requires knowledge of the prevalence of the risk factor in the population and the RR not to be adjusted for confounders (crude RR). Formula 2 is preferred when there is confounding;8 it requires knowledge of the prevalence of the risk factor in people eventually developing the disease (cases) and the adjusted RR. Because some confounders (eg, hypertension in coronary heart disease, overweight in diabetes) are exacerbated by inactivity, formula 2 might overadjust, whereas formula 1 can add perspective. Thus, we sought prevalence estimates of inactivity for the whole population and unadjusted RRs to estimate PAF using formula 1, and

prevalence estimates of inactivity for cases and adjusted RRs to estimate PAF using formula 2.

Estimation of prevalence of physical inactivityWe defi ned physical inactivity to be an activity level insuffi cient to meet present recommendations.5 WHO obtains data, by country, for the prevalence of physical inactivity in the population using two similar stand-ardised questionnaires; the latest data are for 2008.9 For calculation of PAFs with RRs adjusted for confounding factors, the prevalence of physical inactivity at baseline in cases of the outcome of interest was needed. These data proved diffi cult to obtain for countries outside North America and Europe. Further, data for prevalence of inactivity depended on the instrument used for assess-ment and varied according to whether a study assessed physical activity during leisure only (most commonly), or also included activities in occupation, transportation, or home-based activities.

Thus, to estimate the prevalence of inactivity in cases, we contacted several large cohort studies throughout the world using input from the Lancet Physical Activity Series Working Group, attempting particularly to gather data outside North America and Europe. For each study, we obtained the prevalence of physical inactivity in all participants at baseline, and in those eventually developing coronary heart disease, type 2 diabetes, and breast and colon cancer and those who died (appendix). For each outcome, we calculated an adjustment factor, representing the added extent to which physical inactivity occurred in cases compared with the overall population of the cohort study. For example, in the Shanghai Women’s Health Study (appendix), the prevalence of inactivity in all women at baseline was 45·4% versus 51·6% in women who died, yielding an adjustment factor of 1·14 (51·6 / 45·4 = 1·14). For each outcome, we calculated the adjustment factor in every study, and averaged this factor across studies. We applied the average adjustment factor to the prevalence of physical inactivity, by country, to estimate the prevalence of inactivity in cases of coronary heart disease, type 2 diabetes, breast and colon cancer, and death from any cause.

Estimation of RRs associated with physical inactivityWe searched electronic databases (Medline and Embase) using keywords related to physical activity (“physical activity”, “motor activity”, “energy expenditure”, “walk-ing”, and “exercise”) and the outcomes of interest (“breast cancer”, “breast carcinoma”, “colon cancer”, “colorectal cancer”, “colon carcinoma”, “colorectal carcinoma”, “diabetes”, “type 2 diabetes”, “all-cause mortality”, “mortality”, “cardiovascular disease”, “coronary heart disease”, and “heart disease”) for peer-reviewed reviews of adults published in English, selecting the most recent one as of June 30, 2011. For all outcomes apart from breast cancer, published meta-analyses of the pooled RR were available.10–13 For breast cancer, no comprehensive

See Online for appendix

Panel 1: Health benefi ts of physical activity in adults3–5

Strong evidence of reduced rates of:• All-cause mortality• Coronary heart disease• High blood pressure• Stroke• Metabolic syndrome• Type 2 diabetes• Breast cancer• Colon cancer• Depression• Falling

Strong evidence of:• Increased cardiorespiratory and muscular fi tness• Healthier body mass and composition• Improved bone health• Increased functional health• Improved cognitive function

Panel 2: Formulae for calculation of population attributable fraction (PAF)

Formula 1, using unadjusted relative risk:

Where Pe is the proportion of inactive people in the source population, and RRunadj is the relative risk of disease, comparing inactive with active people, unadjusted for confounding factors.

Formula 2, using adjusted relative risk:

Where Pd is the proportion of inactive people among cases, and RRadj is the relative risk of disease, comparing inactive with active people, adjusted for confounding factors.

PAF(%)Pd(RRadj – 1)

=RRadj

× 100

PAF(%)Pe(RRunadj – 1)

=Pe(RRunadj – 1) + 1

× 100

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meta-analysis was found (one of only case-control studies is available14), so we selected the most recent qualitative review15 and did a meta-analysis of their primary studies.

All the meta-analyses calculated only pooled RRs adjusted for potential confounders (generally selecting maximally adjusted RRs from individual studies); no pooled estimates of crude RRs were reported. Thus, we obtained the primary papers to identify the crude RRs. For most papers, this information was not reported; for several, data were provided that allowed its calculation. When the crude RR was unavailable or could not be calculated, the age-adjusted RR was often available. Thus, to obtain a pooled estimate of the crude RRs, we used either crude RRs or age-adjusted RRs, calling this value the unadjusted RR. This method enabled use of data from a larger number of studies, and a closer parallel between studies used to calculate the pooled unadjusted and adjusted RRs. In sensitivity analyses that compared results using only crude RRs with those using both crude and age-adjusted RRs, estimates were generally similar; thus, bias using unadjusted instead of crude RRs is unlikely. We used simple, random-eff ects meta-regres sion to account for heterogeneity across studies, using MIX 2.0.

Calculation of PAFs and gains in life expectancyWe calculated PAFs for each outcome, by country, and used Monte Carlo simulation techniques (10 000 simu-lations) to estimate 95% CIs. We assumed normal dis-tributions for physical inactivity prevalence and the log of the RRs. We used life-table analysis to estimate gains in life expectancy that could be expected if physical inactivity were eliminated, using life tables published by WHO that provide age-specifi c death rates, by country; the latest data are for 2009.16

Since the country-specifi c PAF for all-cause mortality estimates how much premature mortality can be removed from the population if physical inactivity were

eliminated, we assumed that the age-specifi c death rates for a country would be decreased by an amount equal to this PAF (calculated using the adjusted RR) if inactivity were eliminated. Studies of physical activity and all-cause mortality have mainly been in people aged 40 years and older, with few data available for those aged 80 years and older, which also suggest benefi t.3 Thus, we con ser-vatively decreased age-specifi c death rates by the PAF only for ages 40–79 years, and calculated the revised life expectancy from birth, by country. In a sensitivity analysis, we did parallel analyses that decreased age-specifi c death rates for all ages 40 years and older.

Role of the funding sourceNo funding organisation had any role in the writing of the report or the decision to submit for publication. The corresponding author had full access to all data in the study and fi nal responsibility for the decision to submit for publication.

ResultsWe estimated the prevalence of physical inactivity in cases of the outcomes studied, by country, using adjust-ment factors of 1·20 (SE 0·03) for coronary heart disease, 1·23 (0·05) for type 2 diabetes, 1·05 (0·09) for breast cancer, 1·22 (0·08) for colon cancer, and 1·22 (0·07) for all-cause mortality. The highest prevalence was noted in people who went on to develop type 2 diabetes, followed by those who died and those who developed colon cancer, coronary heart disease, and breast cancer (table 1, appendix).

Table 1 sum marises the RRs associated with physical inactivity, unadjusted and adjusted for confounders, for the outcomes studied. Sattelmair and colleagues10 investi-gated the dose-re sponse relation between leisure-time energy expenditure and incidence of coronary heart disease. The pooled RR associated with energy expen-diture that fulfi lled present recommendations compared

Coronary heart disease

Type 2 diabetes Breast cancer* Colon cancer All-cause mortality

Prevalence of inactivity in population (%)† 35·2% (22·3–40·5) 35·2% (22·3–40·5) 38·8% (23·3–44·3) 35·2% (22·3–40·5) 35·2% (22·3–40·5)

Prevalence of inactivity in people eventually developing the outcome (%)†

42·2% (23·0–56·2) 43·2% (23·6–57·6) 40·7% (22·5–56·7) 42·9% (23·4–57·1) 42·9% (23·4–57·1)

RR, unadjusted‡ 1·33 (1·18–1·49) 1·63 (1·27–2·11) 1·34 (1·25–1·43) 1·38 (1·31–1·45) 1·47 (1·38–1·57)

RR, adjusted‡ 1·16 (1·04–1·30) 1·20 (1·10–1·33) 1·33 (1·26–1·42) 1·32 (1·23–1·39) 1·28 (1·21–1·36)

PAF with unadjusted RR (%)§ 10·4% (7·2–13·4) 18·1% (10·8–22·8) 11·6% (6·8–15·5) 11·8% (6·8–15·1) 14·2% (8·3–18·0)

PAF with adjusted RR (%)§ 5·8% (3·2–7·8) 7·2% (3·9–9·6) 10·1% (5·6–14·1) 10·4% (5·7–13·8) 9·4% (5·1–12·5)

Physical inactivity was defi ned as insuffi cient physical activity to meet present recommendations. RR=relative risk. PAF=population attributable fraction. *Women only. †Data are overall median (range of medians for WHO regions); details of country-specifi c values for the population are available from reference 9; country-specifi c values for people eventually developing these diseases are provided in the appendix. ‡Data are RR (95% CI); for details of calculation of unadjusted RRs, see appendix; the unadjusted RRs pooled both crude and age-adjusted RRs, since the crude RR was often unavailable; the adjusted RR of coronary heart disease was obtained from Sattelmair and colleagues,10 for type 2 diabetes from Jeon and colleagues,11 for breast cancer and all-cause mortality see appendix, and for colon cancer from Wolin and co-workers.12 §Data are overall median (range of medians for WHO regions); details of country-specifi c values calculated with unadjusted RRs are provided in appendix; country-specifi c values calculated with adjusted RRs are shown in table 2.

Table 1: Summary of estimates of the prevalence of physical inactivity, RRs, and PAFs for coronary heart disease, type 2 diabetes, breast cancer, colon cancer, and all-cause mortality associated with physical inactivity

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222 www.thelancet.com Vol 380 July 21, 2012

Coronary heart disease Type 2 diabetes Breast cancer Colon cancer All-cause mortality

Africa

Algeria 6·7% (2·4 to 11·2) 8·3% (4·2 to 12·9) 12·8% (5·9 to 20·0) 12·0% (6·8 to 17·2) 10·8% (8·6 to 13·1)

Benin 1·5% (0·5 to 2·5) 1·9% (0·9 to 2·9) 2·9% (1·3 to 4·6) 2·7% (1·5 to 3·9) 2·4% (1·9 to 3·0)

Botswana 5·8% (2·1 to 9·7) 7·2% (3·6 to 11·3) 11·5% (5·4 to 18·0) 10·4% (5·9 to 15·1) 9·4% (7·5 to 11·4)

Burkina Faso 2·6% (–0·2 to 6·1) 3·2% (–0·3 to 7·2) 4·3% (–1·0 to 9·5) 4·6% (–0·8 to 9·9) 4·1% (–0·1 to 8·6)

Cameroon 6·7% (1·0 to 13·9) 8·3% (1·8 to 16·2) 12·6% (1·8 to 23·8) 12·0% (2·3 to 22·1) 10·9% (3·4 to 18·6)

Cape Verde 3·4% (1·3 to 5·7) 4·2% (2·1 to 6·6) 7·7% (3·5 to 11·8) 6·1% (3·4 to 8·9) 5·5% (4·3 to 6·8)

Chad 4·1% (0·0 to 9·3) 5·0% (–0·2 to 11·0) 6·8% (–0·8 to 14·4) 7·3% (–0·3 to 15·1) 6·5% (0·4 to 12·9)

Comoros 1·4% (–0·3 to 3·6) 1·7% (–0·4 to 4·2) 2·8% (–0·9 to 6·4) 2·5% (–0·8 to 5·7) 2·2% (–0·5 to 5·0)

Congo (Brazzaville) 8·0% (1·4 to 16·4) 10·0% (2·2 to 19·1) 13·8% (2·8 to 24·9) 14·4% (3·0 to 26·2) 13·0% (4·4 to 22·0)

Côte d’Ivoire 5·4% (0·6 to 11·9) 6·7% (0·8 to 13·9) 9·6% (0·7 to 19·0) 9·7% (0·7 to 18·5) 8·8% (2·0 to 16·1)

Democratic Republic of the Congo 7·5% (2·8 to 12·4) 9·3% (4·7 to 14·5) 13·6% (6·5 to 21·1) 13·4% (7·3 to 19·4) 12·1% (9·6 to 14·6)

Eritrea 6·7% (2·4 to 11·2) 8·3% (4·2 to 12·8) 14·3% (6·7 to 22·4) 12·0% (6·7 to 17·1) 10·8% (8·6 to 13·0)

Ethiopia 3·2% (–0·1 to 7·6) 4·0% (–0·1 to 8·9) 5·8% (–0·9 to 12·7) 5·7% (–0·6 to 12·1) 5·2% (0·2 to 10·5)

Gabon 6·1% (0·5 to 13·3) 7·5% (0·6 to 15·5) 12·1% (0·7 to 23·6) 10·8% (0·6 to 21·5) 9·8% (1·8 to 18·2)

Ghana 2·9% (1·1 to 4·8) 3·6% (1·8 to 5·7) 5·4% (2·5 to 8·4) 5·2% (2·9 to 7·5) 4·7% (3·7 to 5·7)

Guinea 2·0% (–0·2 to 5·0) 2·5% (–0·2 to 5·6) 4·7% (–0·7 to 10·2) 3·6% (–0·6 to 7·7) 3·2% (–0·1 to 6·7)

Kenya 2·7% (–0·4 to 6·8) 3·4% (–0·6 to 7·9) 4·7% (–1·1 to 10·6) 4·9% (–1·0 to 10·9) 4·4% (–0·3 to 9·3)

Madagascar 3·9% (1·4 to 6·4) 4·8% (2·4 to 7·5) 7·4% (3·5 to 11·5) 6·9% (3·9 to 10·0) 6·2% (4·9 to 7·5)

Malawi 1·7% (0·6 to 2·8) 2·1% (1·0 to 3·3) 3·4% (1·6 to 5·3) 3·0% (1·7 to 4·4) 2·7% (2·1 to 3·3)

Mali 3·5% (–0·1 to 8·0) 4·3% (–0·2 to 9·5) 6·2% (–0·7 to 13·4) 6·2% (–0·7 to 13·1) 5·6% (0·2 to 11·1)

Mauritania 7·3% (1·5 to 14·3) 9·0% (2·2 to 16·9) 12·4% (3·3 to 21·8) 13·0% (3·0 to 23·0) 11·7% (4·5 to 19·2)

Mauritius 6·4% (0·7 to 13·5) 7·9% (1·3 to 15·9) 10·2% (0·8 to 20·0) 11·4% (1·2 to 21·6) 10·3% (2·6 to 18·2)

Mozambique 1·2% (0·4 to 2·0) 1·5% (0·7 to 2·3) 1·9% (0·9 to 3·0) 2·1% (1·1 to 3·1) 1·9% (1·5 to 2·4)

Namibia 9·7% (2·3 to 18·9) 12·0% (3·5 to 22·2) 17·0% (4·6 to 29·5) 17·3% (5·0 to 29·9) 15·6% (7·0 to 24·8)

Niger 4·9% (1·8 to 8·0) 6·0% (3·0 to 9·3) 8·9% (4·2 to 14·1) 8·7% (4·8 to 12·6) 7·8% (6·2 to 9·5)

São Tomé and PrÍncipe 3·1% (1·1 to 5·2) 3·9% (2·0 to 6·0) 6·9% (3·1 to 10·6) 5·6% (3·1 to 8·2) 5·1% (4·0 to 6·2)

Senegal 3·8% (0·0 to 8·8) 4·7% (0·1 to 10·1) 6·7% (–0·7 to 14·2) 6·8% (–0·3 to 13·7) 6·2% (0·5 to 12·0)

Seychelles 3·7% (1·3 to 6·1) 4·6% (2·3 to 7·2) 5·8% (2·6 to 9·2) 6·6% (3·7 to 9·6) 6·0% (4·7 to 7·3)

Sierra Leone 3·3% (1·1 to 5·4) 4·1% (2·0 to 6·3) 6·2% (2·9 to 9·5) 5·9% (3·3 to 8·5) 5·3% (4·2 to 6·5)

South Africa 8·7% (3·1 to 14·5) 10·7% (5·4 to 16·8) 14·7% (6·7 to 23·1) 15·5% (8·8 to 22·4) 14·0% (11·1 to 16·9)

Swaziland 11·4% (3·2 to 21·5) 14·2% (4·7 to 25·1) 18·8% (5·9 to 32·4) 20·4% (7·3 to 33·7) 18·4% (9·4 to 27·7)

The Gambia 4·1% (1·5 to 6·7) 5·0% (2·5 to 7·8) 7·5% (3·5 to 11·7) 7·3% (4·1 to 10·5) 6·5% (5·2 to 7·9)

Zambia 2·9% (–0·3 to 7·0) 3·5% (–0·5 to 8·2) 5·0% (–1·2 to 11·3) 5·1% (–1·0 to 11·4) 4·6% (–0·2 to 9·6)

Zimbabwe 3·9% (0·0 to 9·0) 4·9% (–0·1 to 10·7) 6·7% (–0·8 to 14·3) 7·0% (–0·4 to 14·6) 6·4% (0·6 to 12·4)

Median for region 3·9% 4·8% 7·1% 7·0% 6·3%

Latin America and Caribbean

Argentina 11·3% (3·1 to 21·0) 14·0% (4·8 to 24·7) 18·5% (5·9 to 31·7) 20·2% (6·8 to 33·5) 18·2% (9·5 to 27·7)

Barbados 7·8% (2·8 to 13·0) 9·6% (4·8 to 15·0) 14·5% (6·8 to 22·7) 13·9% (7·6 to 20·1) 12·5% (9·9 to 15·1)

Brazil 8·2% (1·5 to 16·4) 10·1% (2·4 to 18·9) 13·4% (2·3 to 24·7) 14·6% (2·9 to 26·1) 13·2% (4·8 to 21·7)

Colombia 7·3% (0·9 to 15·6) 9·0% (1·3 to 18·2) 12·5% (1·2 to 23·9) 13·0% (1·3 to 24·8) 11·7% (2·8 to 21·0)

Dominica 4·0% (1·7 to 16·6) 5·0% (2·7 to 19·9) 9·0% (4·2 to 26·1) 7·2% (4·2 to 27·5) 6·5% (5·3 to 23·0)

Dominican Republic 9·9% (1·7 to 16·6) 12·3% (2·7 to 19·9) 16·4% (4·2 to 26·1) 17·8% (4·2 to 27·5) 16·0% (5·3 to 23·0)

Ecuador 7·1% (1·0 to 14·6) 8·7% (1·5 to 17·2) 12·6% (1·5 to 23·7) 12·6% (2·1 to 23·5) 11·4% (3·5 to 19·7)

Guatemala 2·7% (–0·3 to 6·5) 3·3% (–0·5 to 7·8) 4·4% (–1·2 to 10·1) 4·8% (–1·1 to 10·6) 4·3% (–0·3 to 9·2)

Jamaica 7·9% (1·4 to 16·1) 9·8% (2·2 to 18·5) 13·4% (2·6 to 24·8) 14·1% (2·5 to 25·5) 12·8% (4·6 to 21·6)

Mexico 6·2% (0·8 to 13·2) 7·7% (1·0 to 15·8) 10·0% (0·8 to 19·8) 11·2% (1·1 to 21·3) 10·1% (2·5 to 18·2)

Paraguay 6·8% (1·0 to 14·2) 8·5% (1·4 to 16·8) 10·9% (1·0 to 21·2) 12·2% (1·6 to 22·9) 11·0% (3·0 to 19·1)

Saint Kitts and Nevis 6·3% (2·3 to 10·5) 7·9% (3·9 to 12·2) 12·5% (5·9 to 19·5) 11·3% (6·4 to 16·5) 10·2% (8·1 to 12·4)

Uruguay 5·6% (2·1 to 9·4) 7·0% (3·5 to 10·9) 10·5% (4·8 to 16·4) 10·1% (5·6 to 14·6) 9·1% (7·2 to 11·1)

Median for region 7·1% 8·7% 12·5% 12·6% 11·4%

(Continues on next page)

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Coronary heart disease Type 2 diabetes Breast cancer Colon cancer All-cause mortality

(Continued from previous page)

North America

Canada 5·6% (0·5 to 12·2) 7·0% (0·8 to 14·4) 9·2% (0·2 to 18·6) 10·0% (0·7 to 19·5) 9·1% (1·8 to 16·6)

USA 6·7% (2·5 to 11·1) 8·3% (4·2 to 12·9) 12·4% (5·8 to 19·2) 12·0% (6·7 to 17·4) 10·8% (8·6 to 13·1)

Median for region 6·2% 7·6% 10·8% 11·0% 9·9%

Eastern Mediterranean

Iran 6·1% (2·2 to 10·2) 7·6% (3·8 to 11·8) 12·2% (5·8 to 18·9) 10·9% (6·2 to 15·8) 9·9% (7·9 to 11·9)

Iraq 9·7% (3·5 to 15·8) 12·0% (6·0 to 18·7) 14·1% (6·6 to 21·9) 17·3% (9·7 to 25·1) 15·6% (12·5 to 18·8)

Kuwait 10·7% (3·9 to 17·7) 13·2% (6·6 to 20·7) 18·8% (8·8 to 29·2) 19·1% (10·6 to 27·7) 17·2% (13·7 to 20·8)

Lebanon 7·8% (2·9 to 12·9) 9·6% (4·7 to 14·9) 10·9% (5·1 to 16·9) 13·8% (7·6 to 20·0) 12·5% (9·9 to 15·1)

Libya 7·6% (2·8 to 12·5) 9·4% (4·7 to 14·7) 14·2% (6·6 to 21·9) 13·6% (7·4 to 19·5) 12·2% (9·7 to 14·8)

Pakistan 6·7% (1·0 to 14·0) 8·3% (1·4 to 16·3) 12·5% (1·9 to 23·6) 12·0% (1·6 to 22·0) 10·8% (3·2 to 18·8)

Saudi Arabia 11·4% (4·2 to 18·8) 14·1% (7·1 to 21·9) 19·9% (9·2 to 30·6) 20·4% (11·3 to 29·3) 18·4% (14·7 to 22·1)

Tunisia 5·9% (0·7 to 12·6) 7·4% (1·0 to 15·0) 10·5% (1·0 to 20·2) 10·6% (1·0 to 20·3) 9·6% (2·4 to 17·1)

United Arab Emirates 10·3% (2·6 to 19·9) 12·8% (3·8 to 23·6) 18·0% (5·9 to 30·9) 18·5% (5·2 to 31·7) 16·7% (7·3 to 26·2)

Median for region 7·8% 9·6% 14·1% 13·8% 12·5%

Europe

Austria 5·8% (0·6 to 12·1) 7·1% (1·0 to 14·5) 10·2% (0·8 to 20·1) 10·3% (1·1 to 19·4) 9·3% (2·3 to 16·5)

Belgium 7·1% (1·2 to 14·7) 8·8% (1·9 to 17·0) 11·7% (2·0 to 21·5) 12·6% (2·1 to 23·1) 11·4% (3·7 to 19·5)

Bosnia and Herzegovina 5·6% (0·4 to 12·1) 6·9% (0·8 to 14·1) 9·6% (0·4 to 19·2) 9·9% (0·7 to 19·4) 9·0% (1·8 to 16·5)

Bulgaria 4·4% (0·1 to 9·9) 5·5% (0·1 to 11·7) 7·5% (–0·4 to 15·6) 7·9% (–0·1 to 16·1) 7·2% (0·9 to 13·6)

Croatia 3·9% (0·0 to 8·9) 4·8% (–0·1 to 10·6) 5·5% (–0·6 to 11·6) 7·0% (–0·5 to 14·3) 6·3% (0·5 to 12·4)

Cyprus 9·2% (2·0 to 17·9) 11·4% (3·0 to 21·0) 16·3% (4·2 to 28·8) 16·4% (4·3 to 28·8) 14·8% (6·2 to 24·1)

Czech Republic 4·1% (0·3 to 9·3) 5·1% (0·2 to 10·9) 5·8% (–0·4 to 12·3) 7·4% (0·0 to 14·8) 6·7% (0·9 to 12·6)

Denmark 5·8% (0·6 to 12·4) 7·2% (0·8 to 14·7) 9·2% (0·2 to 18·4) 10·4% (1·0 to 19·9) 9·4% (2·2 to 17·1)

Estonia 2·9% (–0·2 to 6·9) 3·5% (–0·4 to 8·1) 4·9% (–0·9 to 10·9) 5·1% (–0·9 to 11·2) 4·6% (–0·2 to 9·4)

Finland 6·3% (0·8 to 13·2) 7·8% (1·3 to 15·6) 9·1% (0·2 to 18·4) 11·2% (1·1 to 21·2) 10·1% (2·6 to 17·8)

France 5·4% (1·9 to 8·9) 6·7% (3·3 to 10·3) 9·7% (4·6 to 15·1) 9·6% (5·4 to 13·8) 8·7% (6·9 to 10·5)

Georgia 3·7% (1·3 to 6·2) 4·6% (2·3 to 7·1) 6·1% (2·8 to 9·5) 6·6% (3·6 to 9·6) 6·0% (4·7 to 7·2)

Germany 4·6% (0·1 to 10·4) 5·7% (0·2 to 12·4) 7·4% (–0·3 to 15·5) 8·3% (–0·3 to 16·7) 7·5% (0·9 to 14·5)

Greece 2·6% (–0·2 to 6·2) 3·2% (–0·4 to 7·4) 3·8% (–1·1 to 8·7) 4·6% (–0·9 to 10·1) 4·2% (–0·2 to 8·7)

Hungary 4·3% (0·1 to 9·5) 5·3% (0·0 to 11·4) 6·7% (–0·2 to 13·7) 7·7% (–0·2 to 15·6) 6·9% (0·7 to 13·2)

Ireland 8·8% (2·0 to 17·4) 10·9% (2·9 to 20·2) 15·2% (3·5 to 27·3) 15·7% (4·1 to 27·6) 14·2% (6·0 to 22·9)

Italy 9·1% (1·9 to 18·0) 11·2% (3·0 to 20·9) 15·6% (4·2 to 28·0) 16·2% (3·9 to 28·1) 14·6% (5·8 to 23·7)

Kazakhstan 5·2% (0·4 to 11·5) 6·5% (0·6 to 13·4) 8·1% (–0·2 to 16·3) 9·3% (0·5 to 18·4) 8·4% (1·5 to 15·6)

Latvia 5·3% (0·3 to 11·5) 6·6% (0·5 to 13·6) 9·4% (0·1 to 18·7) 9·5% (0·2 to 18·6) 8·5% (1·4 to 15·8)

Lithuania 3·7% (1·3 to 6·3) 4·6% (2·3 to 7·2) 6·5% (2·9 to 10·1) 6·7% (3·7 to 9·8) 6·0% (4·7 to 7·5)

Luxembourg 7·9% (1·3 to 16·0) 9·8% (1·9 to 19·1) 11·9% (1·2 to 23·0) 14·1% (2·6 to 25·8) 12·7% (4·2 to 21·8)

Malta 11·9% (3·3 to 22·3) 14·7% (5·3 to 26·0) 19·1% (6·0 to 32·4) 21·3% (7·5 to 35·3) 19·2% (9·8 to 28·9)

Netherlands 3·0% (–0·1 to 7·1) 3·7% (–0·3 to 8·3) 4·0% (–1·1 to 9·2) 5·4% (–0·6 to 11·4) 4·9% (0·0 to 9·8)

Norway 7·3% (1·2 to 15·3) 9·1% (1·7 to 17·9) 11·7% (1·5 to 22·2) 13·1% (2·2 to 24·1) 11·8% (3·5 to 20·2)

Poland 4·6% (0·2 to 10·4) 5·7% (0·3 to 12·0) 8·2% (–0·2 to 17·0) 8·2% (–0·1 to 16·4) 7·4% (1·0 to 13·9)

Portugal 8·4% (1·7 to 17·3) 10·5% (2·6 to 20·2) 14·2% (3·1 to 25·9) 15·1% (3·6 to 27·0) 13·6% (5·2 to 22·6)

Romania 6·4% (0·7 to 13·6) 7·9% (1·2 to 15·8) 12·0% (1·2 to 23·2) 11·4% (1·3 to 21·9) 10·3% (2·6 to 18·4)

Russia 3·4% (–0·1 to 8·1) 4·3% (–0·2 to 9·5) 4·9% (–0·9 to 10·7) 6·2% (–0·6 to 13·1) 5·6% (0·2 to 11·0)

Serbia 11·3% (3·1 to 20·9) 14·0% (4·7 to 24·6) 19·1% (6·9 to 32·3) 20·2% (7·0 to 33·5) 18·2% (9·4 to 27·6)

Slovakia 3·7% (0·1 to 8·5) 4·6% (0·0 to 9·9) 5·5% (–0·9 to 12·1) 6·6% (–0·3 to 13·7) 5·9% (0·5 to 11·5)

Slovenia 5·0% (0·3 to 11·1) 6·2% (0·4 to 12·9) 8·8% (0·2 to 17·5) 8·9% (0·0 to 17·6) 8·0% (1·2 to 15·2)

Spain 8·3% (1·7 to 16·7) 10·3% (2·5 to 19·5) 13·8% (2·6 to 25·5) 14·9% (3·1 to 26·6) 13·4% (4·9 to 22·4)

Sweden 7·3% (1·2 to 15·1) 9·1% (1·9 to 17·4) 11·5% (1·6 to 21·7) 13·1% (2·1 to 24·1) 11·8% (3·8 to 20·2)

Turkey 9·3% (2·1 to 18·3) 11·5% (3·2 to 21·0) 16·3% (4·0 to 28·9) 16·6% (4·2 to 29·0) 15·0% (6·2 to 23·9)

(Continues on next page)

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with no leisure activity, adjusted for poten tial confounders, was 0·86 (95% CI 0·77–0·96). With increasing energy expenditure, cor onary heart disease incidence fell further, in a curvilinear fashion. For this report, we used the RR corresponding to an activity level that met minimum present rec ommendations (0·86). Taking the inverse of this number to obtain the adjusted RR for physical inactivity yielded 1·16 (95% CI 1·04–1·30). Although these data are from only North America and Europe (ie, studies with suffi cient infor mation to investi gate dose response),

they are congruent with fi ndings from the INTERHEART study17 under taken in 52 countries world wide, in which the adjusted odds ratio for myo cardial infarction associated with physical inactivity was identical (1·16, 95% CI 1·03–1·32). We did a parallel meta-analysis to obtain the corresponding pooled un adjusted RR (ie, pooling crude and age-adjusted RRs), which was 1·33 (95% CI 1·18–1·49; appendix). Crude RRs were avail able for only four studies and pooling of these yielded a value of 1·54 (95% CI 1·25–1·92); thus, the pooled unadjusted RR is conservative.

Coronary heart disease Type 2 diabetes Breast cancer Colon cancer All-cause mortality

(Continued from previous page)

Ukraine 3·1% (–0·2 to 7·3) 3·8% (–0·4 to 8·5) 4·3% (–0·8 to 9·3) 5·4% (–0·8 to 11·6) 4·9% (0·0 to 10·1)

UK 10·5% (4·0 to 17·3) 13·0% (6·4 to 20·2) 17·9% (8·5 to 27·8) 18·7% (10·5 to 27·1) 16·9% (13·6 to 20·3)

Median for region 5·5% 6·8% 9·3% 9·8% 8·8%

Southeast Asia

Bangladesh 0·8% (0·3 to 1·3) 1·0% (0·5 to 1·5) 1·7% (0·8 to 2·7) 1·4% (0·8 to 2·0) 1·3% (1·0 to 1·5)

Bhutan 8·7% (1·8 to 17·3) 10·7% (2·6 to 20·3) 16·6% (4·2 to 29·0) 15·5% (3·8 to 27·6) 14·0% (5·3 to 22·8)

Burma 2·1% (0·8 to 3·5) 2·6% (1·3 to 4·1) 3·9% (1·9 to 6·1) 3·8% (2·1 to 5·4) 3·4% (2·7 to 4·1)

India 2·6% (1·0 to 4·2) 3·2% (1·6 to 5·0) 4·8% (2·3 to 7·4) 4·6% (2·6 to 6·6) 4·2% (3·3 to 5·0)

Indonesia 4·9% (1·8 to 8·2) 6·1% (3·0 to 9·5) 7·3% (3·3 to 11·5) 8·8% (4·9 to 12·8) 8·0% (6·3 to 9·7)

Maldives 6·5% (0·7 to 13·9) 8·0% (1·0 to 16·1) 10·8% (0·5 to 21·4) 11·5% (1·0 to 22·1) 10·4% (2·6 to 18·5)

Nepal 2·6% (–0·3 to 6·2) 3·2% (–0·4 to 7·4) 4·4% (–1·0 to 10·1) 4·6% (–0·8 to 10·2) 4·1% (–0·2 to 8·7)

Sri Lanka 4·3% (1·6 to 7·1) 5·3% (2·7 to 8·3) 8·7% (4·2 to 13·5) 7·7% (4·2 to 11·1) 6·9% (5·5 to 8·3)

Thailand 3·2% (1·2 to 5·2) 3·9% (2·0 to 6·1) 5·6% (2·5 to 8·7) 5·7% (3·2 to 8·2) 5·1% (4·1 to 6·2)

Median for region 3·2% 3·9% 5·6% 5·7% 5·1%

Western Pacifi c

Australia 6·3% (0·8 to 13·1) 7·8% (1·0 to 15·4) 10·4% (0·9 to 20·2) 11·2% (1·4 to 21·2) 10·1% (2·8 to 18·0)

Cambodia 1·9% (0·7 to 3·1) 2·3% (1·1 to 3·6) 2·9% (1·3 to 4·5) 3·3% (1·8 to 4·8) 3·0% (2·4 to 3·6)

China 5·1% (1·9 to 8·5) 6·4% (3·2 to 9·8) 8·4% (4·0 to 13·0) 9·2% (5·2 to 13·1) 8·3% (6·6 to 10·0)

Cook Islands 11·9% (4·4 to 19·7) 14·8% (7·5 to 23·4) 19·1% (9·0 to 29·8) 21·3% (11·8 to 30·9) 19·2% (15·3 to 23·1)

Federated States of Micronesia 11·0% (4·1 to 18·3) 13·6% (6·8 to 21·1) 19·4% (9·1 to 30·5) 19·6% (11·0 to 28·6) 17·7% (14·1 to 21·3)

Japan 10·0% (2·4 to 19·0) 12·3% (3·6 to 22·5) 16·1% (3·9 to 29·1) 17·8% (5·0 to 30·9) 16·1% (7·2 to 25·4)

Kiribati 7·7% (2·7 to 12·8) 9·6% (4·8 to 15·0) 14·3% (6·9 to 22·3) 13·8% (7·7 to 20·0) 12·5% (9·8 to 15·1)

Laos 3·1% (–0·2 to 7·5) 3·9% (–0·4 to 8·7) 5·5% (–1·0 to 12·1) 5·6% (–0·8 to 12·0) 5·0% (–0·1 to 10·3)

Malaysia 10·2% (3·8 to 16·9) 12·6% (6·3 to 19·6) 17·1% (8·0 to 26·6) 18·2% (10·2 to 26·5) 16·4% (13·0 to 19·7)

Marshall Islands 8·2% (3·0 to 13·7) 10·2% (5·1 to 15·7) 14·5% (6·9 to 22·5) 14·7% (8·1 to 21·2) 13·2% (10·6 to 16·0)

Mongolia 1·6% (0·6 to 2·6) 1·9% (1·0 to 3·0) 2·5% (1·1 to 3·9) 2·8% (1·5 to 4·0) 2·5% (2·0 to 3·0)

Nauru 7·7% (2·9 to 12·9) 9·5% (4·8 to 14·8) 13·0% (6·2 to 20·3) 13·8% (7·6 to 19·8) 12·4% (9·8 to 14·9)

New Zealand 7·9% (2·9 to 13·1) 9·8% (4·9 to 15·2) 13·1% (6·2 to 20·3) 14·1% (7·9 to 20·3) 12·7% (10·2 to 15·4)

Papua New Guinea 3·2% (1·2 to 5·3) 4·0% (1·9 to 6·2) 5·6% (2·5 to 8·8) 5·7% (3·1 to 8·3) 5·2% (4·1 to 6·3)

Philippines 3·9% (–0·1 to 9·0) 4·9% (–0·1 to 10·7) 6·8% (–0·7 to 14·7) 7·0% (–0·5 to 14·4) 6·3% (0·4 to 12·4)

Samoa 8·5% (3·1 to 14·1) 10·5% (5·3 to 16·4) 17·0% (8·1 to 26·7) 15·1% (8·5 to 21·8) 13·6% (10·9 to 16·4)

Solomon Islands 7·2% (2·7 to 11·9) 9·0% (4·5 to 14·0) 12·9% (6·1 to 20·2) 12·9% (7·1 to 18·8) 11·7% (9·2 to 14·0)

Tonga 6·9% (2·5 to 11·5) 8·6% (4·2 to 13·4) 13·5% (6·4 to 21·1) 12·4% (6·8 to 18·0) 11·2% (8·8 to 13·6)

Vietnam 2·5% (–0·2 to 6·2) 3·1% (–0·4 to 7·3) 4·1% (–1·1 to 9·4) 4·5% (–0·8 to 9·8) 4·1% (–0·2 to 8·4)

Median for region 7·2% 9·0% 13·0% 12·9% 11·7%

Overall

Median 5·8% 7·2% 10·1% 10·4% 9·4%

Data are PAF (95% CI). PAF=population attributable fraction. *PAFs calculated with unadjusted relative risks are shown in the appendix.

Table 2: Estimated PAFs, calculated with adjusted relative risks,* for coronary heart disease, type 2 diabetes, breast cancer, colon cancer, and all-cause mortality associated with physical inactivity, by WHO region and country

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Gain in life expectancy (years)

Africa

Algeria 0·79 (0·62 to 0·96)

Benin 0·19 (0·15 to 0·24)

Botswana 0·81 (0·64 to 0·99)

Burkina Faso 0·31 (–0·01 to 0·66)

Cameroon 0·85 (0·26 to 1·49)

Cape Verde 0·46 (0·35 to 0·56)

Chad 0·46 (0·03 to 0·93)

Comoros 0·17 (–0·04 to 0·40)

Congo (Brazzaville) 1·06 (0·35 to 1·87)

CÔte d’Ivoire 0·72 (0·16 to 1·37)

Democratic Republic of the Congo 0·89 (0·70 to 1·09)

Eritrea 0·89 (0·70 to 1·08)

Ethiopia 0·43 (0·02 to 0·89)

Gabon 0·81 (0·15 to 1·55)

Ghana 0·40 (0·32 to 0·49)

Guinea 0·25 (–0·01 to 0·53)

Kenya 0·37 (–0·02 to 0·79)

Madagascar 0·52 (0·41 to 0·63)

Malawi 0·21 (0·17 to 0·26)

Mali 0·40 (0·14 to 0·81)

Mauritania 0·95 (0·35 to 1·60)

Mauritius 0·90 (0·22 to 1·62)

Mozambique 0·14 (0·11 to 0·17)

Namibia 1·45 (0·62 to 2·39)

Niger 0·57 (0·45 to 0·69)

São Tomé and PrÍncipe 0·36 (0·28 to 0·44)

Senegal 0·49 (0·04 to 0·97)

Seychelles 0·51 (0·40 to 0·63)

Sierra Leone 0·38 (0·30 to 0·46)

South Africa 1·26 (0·99 to 1·53)

Swaziland 1·56 (0·76 to 2·45)

The Gambia 0·52 (0·41 to 0·63)

Zambia 0·36 (–0·02 to 0·77)

Zimbabwe 0·56 (0·05 to 1·13)

Median for region 0·51

Latin America and Caribbean

Argentina 1·39 (0·71 to 2·14)

Barbados 0·91 (0·72 to 1·11)

Brazil 1·08 (0·38 to 1·81)

Colombia 0·82 (0·19 to 1·50)

Dominica 0·51 (0·41 to 1·86)

Dominican Republic 1·28 (0·41 to 1·87)

Ecuador 0·80 (0·24 to 1·41)

Guatemala 0·35 (–0·02 to 0·74)

Jamaica 1·01 (0·36 to 1·74)

Mexico 0·76 (0·18 to 1·40)

Paraguay 0·85 (0·23 to 1·51)

Saint Kitts and Nevis 0·77 (0·61 to 0·95)

Uruguay 0·70 (0·55 to 0·85)

Median for region 0·82

(Continues in next column)

Gain in life expectancy (years)

(Continued from previous column)

North America

Canada 0·55 (0·11 to 1·02)

USA 0·78 (0·62 to 0·94)

Median for region 0·66

Eastern Mediterranean

Iran 0·71 (0·57 to 0·87)

Iraq 1·30 (1·03 to 1·59)

Kuwait 1·12 (0·89 to 1·37)

Lebanon 0·95 (0·75 to 1·16)

Libya 0·93 (0·77 to 1·18)

Pakistan 0·85 (0·25 to 1·52)

Saudi Arabia 1·51 (1·19 to 1·84)

Tunisia 0·64 (0·16 to 1·16)

United Arab Emirates 1·11 (0·48 to 1·78)

Median for region 0·95

Europe

Austria 0·58 (0·14 to 1·03)

Belgium 0·73 (0·23 to 1·26)

Bosnia and Herzegovina 0·62 (0·12 to 1·16)

Bulgaria 0·58 (0·07 to 1·11)

Croatia 0·45 (0·04 to 0·91)

Cyprus 0·80 (0·33 to 1·33)

Czech Republic 0·48 (0·06 to 0·92)

Denmark 0·64 (0·15 to 1·19)

Estonia 0·38 (–0·02 to 0·78)

Finland 0·66 (0·17 to 1·17)

France 0·55 (0·44 to 0·67)

Georgia 0·52 (0·41 to 0·63)

Germany 0·47 (0·06 to 0·92)

Greece 0·23 (–0·01 to 0·49)

Hungary 0·61 (0·06 to 1·18)

Ireland 0·87 (0·36 to 1·42)

Italy 0·80 (0·31 to 1·32)

Kazakhstan 0·79 (0·14 to 1·50)

Latvia 0·77 (0·12 to 1·46)

Lithuania 0·53 (0·41 to 0·65)

Luxembourg 0·83 (0·27 to 1·45)

Malta 1·12 (0·56 to 1·71)

Netherlands 0·29 (0·00 to 0·59)

Norway 0·68 (0·20 to 1·18)

Poland 0·60 (0·08 to 1·14)

Portugal 0·86 (0·33 to 1·45)

Romania 0·87 (0·21 to 1·58)

Russia 0·52 (0·02 to 1·05)

Serbia 1·50 (1·02 to 2·33)

Slovakia 0·46 (0·04 to 0·92)

Slovenia 0·54 (0·08 to 1·05)

Spain 0·78 (0·28 to 1·32)

Sweden 0·67 (0·22 to 1·16)

Turkey 1·06 (0·43 to 1·74)

(Continues in next column)

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For the association of type 2 diabetes incidence with physical activity, Jeon and co-workers11 reported a pooled RR of 0·83 (95% CI 0·76–0·90), adjusted for several confounders including body-mass index (BMI). Taking the inverse to obtain the adjusted RR for inactivity, we calculated an RR of 1·20 (95% CI 1·10–1·33). We calculated the corresponding, pooled unadjusted RR, which was 1·63 (95% CI 1·27–2·11; appendix). This mag nitude of risk increase was similar

to that pooling only the crude RRs, which yielded 1·58 (95% CI 1·11–2·26).

We used the primary papers in the qualitative review by Friedenreich and colleagues15 to undertake a meta-analysis of the pooled adjusted and unadjusted RRs for breast cancer incidence (appendix). The adjusted RR for physical inactivity, including adjustment for BMI, was 1·33 (95% CI 1·26–1·42). This result was little diff erent from the unadjusted RR of 1·34 (95% CI 1·25–1·43; similar to that pooling only crude RRs, yielding 1·35, 95% CI 1·26–1·45).

For the association of colon cancer incidence and physical activity, Wolin and colleagues12 reported a pooled adjusted RR of 0·76 (95% CI 0·72–0·81). Taking the inverse of these results gave an adjusted RR of 1·32 (95% CI 1·23–1·39) for inactivity. Our calculation of the pooled unadjusted RR for colon cancer was 1·38 (95% CI 1·31–1·45; appendix); the pooled crude RR was similar (1·37, 95% CI 1·29–1·46).

Lollgen and colleagues13 reported a meta-analysis of RRs for all-cause mortality associated with moderate and high levels of physical activity, qualitatively defi ned. Investigators reported separate estimates for studies in which participants were classifi ed into three, four, or fi ve levels of activity. The adjusted RRs for moderate levels compared with a low level ranged from 0·53 to 0·78; for high levels, from 0·52 to 0·80. We used their primary papers to do a meta-analysis to obtain one pooled RR that compared low with moderate physical activity—ie, a conservative estimate of the eff ect of inactivity. Our pooled adjusted RR was 1·28 (95% CI 1·21–1·36), whereas the pooled unadjusted RR was 1·47 (95% CI 1·38–1·57) and similar to the pooled crude RR of 1·46 (95% CI 1·34–1·60; appendix).

For coronary heart disease, median PAFs associated with physical inactivity, calculated with adjusted RRs, ranged from 3·2% (in southeast Asia) to 7·8% (in the eastern Mediterranean region), with an overall median of 6% (tables 1, 2). These results suggest that 6% of the burden of disease worldwide due to coronary heart disease can be eliminated, if all inactive people become active. The burden of disease was 7% for type 2 diabetes (ranging from 3·9% to 9·6%), 10% (5·6–14·1) for breast cancer, and 10% (5·7–13·8) for colon cancer.

Removal of physical inactivity had the largest eff ect on colon cancer, and the smallest on coronary heart disease, in terms of percentage reduction. However, with respect to the number of cases that can potentially be averted, coronary heart disease would have a far larger eff ect than would colon cancer because of its higher incidence. Although the worldwide incidence of coronary heart disease is not readily available, deaths from coronary heart disease can be viewed against colorectal cancer deaths to provide some perspective; in 2008, 7·25 million people worldwide died from coronary heart disease versus 647 000 from colorectal cancer.18 Applying the median PAFs, we estimated that 15 000 deaths from

Gain in life expectancy (years)

(Continued from previous column)

Ukraine 0·46 (0·00 to 0·97)

UK 1·07 (0·85 to 1·29)

Median for region 0·63

Southeast Asia

Bangladesh 0·10 (0·08 to 0·12)

Bhutan 1·15 (0·42 to 1·95)

Burma 0·27 (0·22 to 0·33)

India 0·34 (0·27 to 0·41)

Indonesia 0·65 (0·51 to 0·80)

Maldives 0·75 (0·18 to 1·37)

Nepal 0·33 (–0·02 to 0·71)

Sri Lanka 0·51 (0·40 to 0·61)

Thailand 0·41 (0·32 to 0·49)

Median for region 0·41

Western Pacifi c

Australia 0·56 (0·15 to 1·00)

Cambodia 0·24 (0·19 to 0·29)

China 0·61 (0·48 to 0·73)

Cook Islands 1·57 (1·24 to 1·91)

Federated States of Micronesia 1·45 (1·14 to 1·77)

Japan 0·91 (0·40 to 1·46)

Kiribati 1·27 (0·99 to 1·55)

Laos 0·43 (–0·01 to 0·90)

Malaysia 1·35 (1·06 to 1·65)

Marshall Islands 1·33 (1·04 to 1·63)

Mongolia 0·24 (0·19 to 0·29)

Nauru 1·21 (0·95 to 1·47)

New Zealand 0·76 (0·61 to 0·93)

Papua New Guinea 0·43 (0·34 to 0·52)

Philippines 0·52 (0·03 to 1·04)

Samoa 1·17 (0·92 to 1·42)

Solomon Islands 0·90 (0·70 to 1·09)

Tonga 1·03 (0·80 to 1·26)

Vietnam 0·31 (–0·01 to 0·64)

Median for region 0·90

Overall

Median 0·68

Data in parentheses are 95% CI. Uncertainty interval calculated on the basis of the lower and upper bounds of the 95% CI of the adjusted population attributable fraction for all-cause mortality.

Table 3: Estimated gains in life expectancy if physical inactivity were eliminated, by WHO region and country

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coronary heart disease in Africa could have been averted in 2008 by removal of physical inactivity. 60 000 could have been avoided in the Americas, 44 000 in the eastern Mediterranean region, 121 000 in Europe, 59 000 in southeast Asia, and 100 000 in the western Pacifi c region. With respect to deaths from breast cancer, 3000 could have been averted in Africa, 11 000 in the Americas, 4000 in the eastern Mediterranean, 14 000 in Europe, 5000 in southeast Asia, and 10 000 in the western Pacifi c; for deaths from colorectal cancer, these numbers were 1000, 14 000, 2000, 24 000, 4000, and 24 000, respectively.

For all-cause mortality, the overall median PAF was 9%. Applying this fi gure to the 57 million deaths worldwide in 2008,18 we estimated that more than 5·3 million deaths (ranging from 525 000 in the eastern Mediterranean to 1·5 million in the western Pacifi c region) could be averted every year if all inactive people become active. Because physical inactivity is unlikely to be completely eliminated, we further estimated poten tial deaths averted when assuming a decrease of inactivity prevalence by 10% or 25% with eff ective public health interventions, instead of 100% (elimin ation). These alternate scenarios resulted in more than 533 000 and 1·3 million deaths potentially avoided worldwide each year.

Using an alternate classifi cation of countries by income (data not shown), we calculated median PAFs for all-cause mortality of 4% for countries with low incomes, 8% for lower-middle incomes, 10% for upper-middle incomes, and 11% for high incomes (with number of deaths averted ranging from 409 000 in countries with low incomes to 2·5 million in those with lower-middle incomes). This analysis yielded estimated numbers of deaths potentially averted in 2008 from coronary heart disease of 15 000, 184 000, 96 000, and 98 000; from breast cancer of 2000, 16 000, 10 000, and 20 000; and from colorectal cancer of 1000, 19 000, 13 000, and 37 000, respectively.

We estimated that the median years of life potentially gained worldwide with elimination of physical inactivity

was 0·68 years (ranging from 0·41 years in southeast Asia to 0·95 years in the eastern Mediterranean region; table 3, fi gure). When we classifi ed countries by income, the median gains were 0·37 years for countries with low incomes, 0·65 for lower-middle incomes, 0·80 for upper-middle incomes, and 0·68 years for high incomes. In a sensitivity analysis that decreased age-specifi c death rates by the PAF for all ages 40 years or older (instead of only ages 40–79 years), the new estimate of years gained worldwide increased to a median of 0·92 years (range 0·49–1·25).

Finally, we used an example to illustrate gains under less stringent assumptions. A recent study of Taiwanese people aged 20 years and older comparing most with least active groups reported an RR for all-cause mortality of 1·35.19 Applying this RR to China for people aged 20 years and older, we calculated a PAF of 9·8% and gain in life expectancy of 1·03 years, versus 8·3% and 0·61 years obtained under the standard assumptions of tables 2 and 3.

DiscussionWorldwide, we estimated that physical inactivity causes 6–10% of the major non-communicable diseases of coronary heart disease, type 2 diabetes, and breast and colon cancers. Furthermore, this unhealthy behaviour causes 9% of premature mortality, or more than 5·3 of the 57 million deaths in 2008.18 With elimination of physical inactivity, life expectancy of the world’s popu-lation might be expected to increase by 0·68 years. These fi ndings make inactivity similar to the established risk factors of smoking and obesity. The added years of life need to be interpreted correctly: they seem low because they represent gains in the whole population (including inactive and active people), rather than in inactive people who become active. Because all the gain accrues to people who move from inactive to active, the increase in life expectancy in the inactive group alone is

Figure: Estimated gains in life expectancy worldwide with elimination of physical inactivity

≥1·000·75–0·990·50–0·740·25–0·49<0·25No data

Years

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228 www.thelancet.com Vol 380 July 21, 2012

greater. For perspective, other research done in the USA estimated that inactive people would gain 1·3–3·7 years from age 50 years by becoming active.20,21 In an east Asian population, life expectancy from age 30 years in active people was 2·6–4·2 years greater than that in inactive people.19

How does physical inactivity compare with other risk factors for poor health? Although risk factors are classifi ed on diff erent scales (thus, the proportion at risk varies across risk factors), it is nonetheless informative to look at two established risk factors targeted for govern-ment action worldwide: smoking and obesity. Smoking was estimated to cause about 5 million deaths world-wide in 2000.22 The proportion of deaths attrib utable to smoking in China, one of the top fi ve cigarette-consuming countries, has been estimated at 3·1% for women and 12·9% for men.23 By elimination of smoking, life expectancy at age 50 years was estimated to increase by 2·3–2·5 years in the US population and 1·1–2·2 years in the populations of nine other high-income countries.24 At an individual level, Beijing never-smokers aged 55 years and older had a life expectancy 4·2–8·8 years longer than that of present smokers.25 As for obesity, if all obese people in the USA were to attain normal weight, life expectancy in the population was estimated to increase by 0·7–1·1 years at birth in one analysis26 and 0·5–0·7 years at age 50 years in another.24 Thus, physical inactivity seems to have an eff ect similar to that of smoking or obesity.

The present analysis updates information from a 2004 WHO report27 and additionally estimates added years of life expectancy in the population. In the WHO report, because of unavailability of data needed for the preferred PAF formula, the incorrect formula (formula 1) was used. Their PAFs ranged from 10% for breast cancer to 22% for coronary heart disease—similar to the present estimate for breast cancer, but larger for coronary heart disease. In part, this diff erence is because the RR of breast cancer for physical inactivity is not confounded by other variables (unadjusted RR 1·34, adjusted RR 1·33), whereas that for coronary heart disease is (unadjusted RR 1·33, adjusted RR 1·16). Further, we conservatively used a pooled RR for coronary heart disease that com-pared physical inactivity with the minimum recom-mended activity level using recently published data,10 whereas WHO used data available at the time of their analysis that compared extreme activity categories, yielding RRs of larger magnitude.

Our estimates are likely to be very conservative. First, the RRs were almost always based on self-reported physical activity levels,28 which are imprecise. In pro-spective studies in which self-reports cannot be biased by the outcomes studied (since they have not yet occurred at the time of reporting), random reporting errors result in underestimation of the RRs. Some studies of physical fi tness—a related measure to physical activity that is more objectively measured—show stronger magnitudes

of association with non-communicable diseases29 (which also might refl ect inherited physiological and metabolic characteristics related to both fi tness and a favourable risk profi le). Second, the pooled RRs were derived from maximally adjusted RRs in the primary studies. Often, these RRs were adjusted for characteristics such as blood pressure, lipid profi le, and glucose or insulin sensitivity. These could be overadjustments, since physical activity reduces risk of coronary heart disease and premature mortality partly through benefi cial eff ects on these variables (a recent analysis suggested an attenuation of about 10% in the RR10). For type 2 diabetes, we used RRs adjusted for BMI—also conservative, since physical activity plays an important part in weight management.3 Third, we used the same RR to calculate PAFs for all countries, based on data mainly from North America and Europe. Whether physical inactivity has similar eff ects in other populations is unclear. For example, we used a pooled adjusted RR for coronary heart disease of 1·16; however, a study in India reported a larger adjusted RR (2·27, 95% CI 1·41–3·70).30 However, our pooled adjusted RR for all-cause mortality, 1·28, is similar to that of 1·25 (95% CI 1·18–1·33) in an east Asian study, comparing inactive people with those meeting minimum physical activity recommendations.19 Fourth, we assumed physical activ ity to reduce all-cause mortality rates only at ages 40–79 years. In a sensitivity analysis that extended the benefi t to age 40 years and older, larger gains in life expectancy were obtained. Fifth, we used one RR instead of a range of RRs to refl ect the dose-response relation between physical inactivity and risks of non-com-municable disease because sparse data are available for the dose-response relation.10 In an illustrative example using China, we showed that applying less stringent assumptions increased PAF by 18% (9·8% vs 8·3%) and life expectancy by 69% (1·03 vs 0·61 years) compared with calculations made under standard assumptions.

Limitations of this study include the use of an adjustment factor to estimate the prevalence of physical inactivity in cases. This adjustment factor was mainly based on populations in North America and Europe, and one study each from China and India; how applicable this factor might be to other countries such as those in Africa or with low incomes is unclear. Also, successful interventions will probably increase activity levels across the board, instead of shifting people across a binary divide of inactive to active assumed in our calculations, potentially yielding greater benefi ts. We examined only the major non-communicable diseases and all-cause mortality, and not other disorders aff ected by physical inactivity (panel 1) or disability resulting from non-communicable diseases. Finally, not all physically in active people choose to be so; some might be physically incapable.

This summer, we will admire the breathtaking feats of athletes competing in the 2012 Olympic Games. Although only the smallest fraction of the population will attain these heights, the overwhelming majority of us are

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able to be physically active at very modest levels— eg, 15–30 min a day of brisk walking—which bring substantial health benefi ts.3–5,19 We must explore all avenues and support all eff orts to reduce physical inactivity worldwide.ContributorsI-ML and PTK designed the study and other authors provided critical input. EJS and PTK undertook data analyses. I-ML, EJS, and FL extracted data from the primary studies used in the meta-analyses. I-ML drafted the report. EJS, FL, PP, SNB, and PTK critically reviewed the report.

Lancet Physical Activity Series Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk, Harold W Kohl 3rd, Estelle Victoria Lambert, I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of interestWe declare that we have no confl icts of interest.

AcknowledgmentsThe fi ndings and conclusions in this report are those of the authors and do not necessarily represent the offi cial position of the US Centers for Disease Control and Prevention. I-ML was supported in part by grant CA154647 from the US National Institutes of Health. EJS was supported in part by grant HL007575 from the US National Institutes of Health. PTK was supported in part by the Louisiana Public Facilities Authority Endowed Chair in Nutrition. We thank Kenneth E Powell, Shane A Norris, and Beverly J Levine for reviewing a previous draft of the report and providing critical input. We thank several people for providing data to calculate the adjustment factor: David Batty, Kennet Harald, Duck-chul Lee, Charles E Matthews, Martin Shipley, Emmanuel Stamatakis, Xuemei Sui, and Nicholas J Wareham. We thank Jacob R Sattelmair and Kathleen Y Wolin for assisting with meta-analyses.

References 1 Rook A. An investigation into the longevity of Cambridge

sportsmen. BMJ 1954; 1: 773–77. 2 Blair SN, Davey Smith G, Lee IM, et al. A tribute to Professor

Jeremiah Morris: the man who invented the fi eld of physical activity epidemiology. Ann Epidemiol 2011; 20: 651–60.

3 US Department of Health and Human Services. 2008 Physical Activity Guidelines Advisory Committee report. http://www.health.gov/paguidelines/ (accessed Sept 1, 2011).

4 Warburton DE, Charlesworth S, Ivey A, Nettlefold L, Bredin SS. A systematic review of the evidence for Canada’s Physical Activity Guidelines for Adults. Int J Behav Nutr Phys Act 2010; 7: 39.

5 WHO. Global recommendations on physical activity for health. Geneva: World Health Organization, 2010.

6 Beaglehole R, Bonita R, Alleyne G, et al. UN High-Level Meeting on Non-Communicable Diseases: addressing four questions. Lancet 2011; 378: 449–55.

7 Powell KE, Blair SN. The public health burdens of sedentary living habits: theoretical but realistic estimates. Med Sci Sports Exerc 1994; 26: 851–56.

8 Rockhill B, Newman B, Weinberg C. Use and misuse of population attributable fractions. Am J Public Health 1998; 88: 15–19.

9 WHO. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization, 2011.

10 Sattelmair JR, Perman J, Ding EL, Hohl HW III, Haskell WL, Lee I-M. Dose-response between physical activity and risk of coronary heart disease: a meta-analysis. Circulation 2011; 124: 789–95.

11 Jeon CY, Lokken RP, Hu FB, van Dam RM. Physical activity of moderate intensity and risk of type 2 diabetes: a systematic review. Diabetes Care 2007; 30: 744–52.

12 Wolin KY, Yan Y, Colditz GA, Lee IM. Physical activity and colon cancer prevention: a meta-analysis. Br J Cancer 2009; 100: 611–16.

13 Lollgen H, Bockenhoff A, Knapp G. Physical activity and all-cause mortality: an updated meta-analysis with diff erent intensity categories. Int J Sports Med 2009; 30: 213–24.

14 Monninkhof EM, Elias SG, Vlems FA, et al. Physical activity and breast cancer: a systematic review. Epidemiology 2007; 18: 137–57.

15 Friedenreich CM. Physical activity and breast cancer: review of the epidemiologic evidence and biologic mechanisms. Recent Results Cancer Res 2011; 188: 125–39.

16 WHO. Life tables for WHO member states. 2011. http://www.who.int/healthinfo/statistics/mortality_life_tables/en/ (accessed Sept 1, 2011).

17 Yusuf S, Hawken S, Ôunpuu S, et al, on behalf of the INTERHEART Study Investigators. Eff ect of potentially modifi able risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004; 364: 937–52.

18 WHO. Global Health Observatory Data Repository. 2011. http://apps.who.int/ghodata/ (accessed Oct 4, 2011).

19 Wen CP, Wai JPM, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet 2011; 378: 1244–53.

20 Franco OH, de Laet C, Peeters A, Jonker J, Mackenbach J, Nusselder W. Eff ects of physical activity on life expectancy with cardiovascular disease. Arch Intern Med 2005; 165: 2355–60.

21 Paff enbarger RS Jr, Hyde RT, Wing AL, Hsieh CC. Physical activity, all-cause mortality, and longevity of college alumni. N Engl J Med 1986; 314: 605–13.

22 Ezzati M, Lopez AD. Estimates of global mortality attributable to smoking in 2000. Lancet 2003; 362: 847–52.

23 Gu D, Kelly TN, Wu X, et al. Mortality attributable to smoking in China. N Engl J Med 2009; 360: 150–59.

24 Crimmins EM, Preston SH, Cohen B. Chapters 3 and 5. Explaining divergent levels of longevity in high-income countries. Washington, DC: National Academies Press, 2011.

25 Tian X, Tang Z, Jiang J, et al. Eff ects of smoking and smoking cessation on life expectancy in an elderly population in Beijing, China, 1992–2000: an 8-year follow-up study. J Epidemiol 2011; 21: 376–84.

26 Olshansky SJ, Passaro DJ, Hershow RC, et al. A potential decline in life expectancy in the United States in the 21st century. N Engl J Med 2005; 352: 1138–45.

27 Ezzati M, Lopez AD, Rodgers A, Murray CJ, eds. Comparative quantifi cation of health risks: global and regional burden of disease attributable to selected major risk factors. Geneva: World Health Organization, 2004.

28 Lee I-M, Paff enbarger RS Jr. Design of present-day epidemiologic studies of physical activity and health. In: Lee I-M, ed. Epidemiologic methods in physical activity studies. New York, NY: Oxford University Press, 2009: 100–23.

29 Kodama S, Saito K, Tanaka S, et al. Cardiorespiratory fi tness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA 2009; 301: 2024–35.

30 Rastogi T, Vaz M, Spiegelman D, et al. Physical activity and risk of coronary heart disease in India. Int J Epidemiol 2004; 33: 759–67.

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Lancet 2012; 380: 247–57

Published OnlineJuly 18, 2012http://dx.doi.org/10.1016/S0140-6736(12)60646-1

This is the fi rst in a Series of fi ve papers about physical activity

*Members listed at end of paper

Universidade Federal de Pelotas, Pelotas, Brazil (P C Hallal PhD); Department of Exercise Epidemiology, Centre for Research in Childhood Health, University of Southern Denmark, Odense, Denmark (Prof L B Andersen PhD); School of Population Health, University of Western Australia, Perth, WA, Australia (Prof F C Bull PhD); Department of Chronic Diseases and Health Promotion, WHO, Geneva,

Physical Activity 1

Global physical activity levels: surveillance progress, pitfalls, and prospectsPedro C Hallal, Lars Bo Andersen, Fiona C Bull, Regina Guthold, William Haskell, Ulf Ekelund, for the Lancet Physical Activity Series Working Group*

To implement eff ective non-communicable disease prevention programmes, policy makers need data for physical activity levels and trends. In this report, we describe physical activity levels worldwide with data for adults (15 years or older) from 122 countries and for adolescents (13–15-years-old) from 105 countries. Worldwide, 31·1% (95% CI 30·9–31·2) of adults are physically inactive, with proportions ranging from 17·0% (16·8–17·2) in southeast Asia to about 43% in the Americas and the eastern Mediterranean. Inactivity rises with age, is higher in women than in men, and is increased in high-income countries. The proportion of 13–15-year-olds doing fewer than 60 min of physical activity of moderate to vigorous intensity per day is 80·3% (80·1–80·5); boys are more active than are girls. Continued improvement in monitoring of physical activity would help to guide development of policies and programmes to increase activity levels and to reduce the burden of non-communicable diseases.

Physical activity in a changing worldSince the industrial revolution, the development of new technologies has enabled people to reduce the amount of physical labour needed to accomplish many tasks in their daily lives. As the availability of new devices has con-tinued to increase, the eff ects on physical labour and human energy expenditure have grown to include many aspects of the lives of more and more people. The eff ects of some of these technologies on physical activity are obvious (eg, steam, gas, and electric engines; trains; cars; and trucks), whereas others are more subtle and complex (eg, televisions, computers, electronic entertainment, the internet, and wireless communication devices).

The use of many of these technologies has been driven by the goal of increased individual worker productivity and reduced physical hardships and disabilities caused by jobs entailing continuous heavy labour. However, the human body has evolved in such a way that most of its systems (eg, skeletal, muscle, metabolic, and cardio-vascular) do not develop and function in an optimum way unless stimulated by frequent physical activity.1 Although the technological revolution has been of great benefi t to many populations throughout the world, it has come at a major cost in terms of the contribution of physical inactivity to the worldwide epidemic of non-communicable diseases.2 In 2009, physical inactivity was identifi ed as the fourth leading risk factor for non-communicable diseases and accounted for more than 3 million preventable deaths.3

Comparisons of patterns of participation in physical activity between countries and regions were unachiev-able until a decade ago,4 largely due to the absence of stand ardised instruments suitable for international use. This barrier caused a so-called collective blind spot, because the evidence for the health benefi ts of physical activity had grown stronger since the 1970s,5 under-pinning the importance of surveillance data to guide national action.6 Without a suitable instrument, early

eff orts to characterise patterns of physical activity frequently used only measures of occupational classifi -cation or only estimations of energy expenditure during leisure-time physical activity as the best available indicators, such as in early epi demiological studies7,8 and subsequent investigations.9

Only in the late 1990s did an international group of academics develop a standardised instrument—the international physical activity questionnaire (IPAQ)10—to

Key messages

• Surveillance of physical activity levels of adult (aged 15 years or older) and adolescent (aged 13–15 years) populations has progressed substantially in the past decade. Available data obtained with standardised self-report instruments now provide estimates of physical activity for 122 countries, or two-thirds of the 194 WHO Member States; these data should be used to inform policy and practice worldwide.

• A third of adults and four-fi fths of adolescents do not reach public health guidelines for recommended levels of physical activity.

• Notable disparities exist in the prevalence of physical inactivity; in most countries inactivity is higher in women than in men, and older adults are less active than are younger adults. These consistent patterns should be used to help policy makers to implement eff ective programmes for the prevention and treatment of non-communicable diseases.

• Trend data from high-income countries suggest that occupational physical activity is decreasing but leisure-time physical activity has increased in adults.

• Gaps in surveillance of physical activity remain. No data are available from about a third of countries, mostly those of low and middle income in Africa and central Asia. Data for trends in physical activity are scarce.

• WHO’s STEPwise approach to chronic disease risk factor surveillance provides a good framework and practical ways to initiate physical activity surveillance, particularly in countries of low and middle income.

• Advances in new technologies and measurement methods, especially accelerometry, show promise for future surveillance of physical activity. These devices have potential widespread practical application if equipment costs continue to fall and suffi cient eff orts are directed towards increasing technical skills and workforce capacity in countries of low and middle income.

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Switzerland (R Guthold PhD); Stanford Prevention Research

Center, Stanford University School of Medicine, Stanford, CA, USA (Prof W Haskell PhD);

Medical Research Council Epidemiology Unit, Cambridge,

UK (Prof U Ekelund PhD); and Department of Sport Medicine,

Norwegian School of Sport Sciences, Oslo, Norway

(Prof L B Andersen, Prof U Ekelund)

Correspondence to:Dr Pedro C Hallal, Rua Marechal

Deodoro 1160, 96020–220, Pelotas, Rio Grande do Sul, Brazil

[email protected]

assess physical activity worldwide, and test its validity and reliability in 12 countries. The development of IPAQ and work leading to the global physical activity questionnaire (GPAQ)11 provided the much needed measurements to support national monitoring and the inclusion of physical inactivity in risk factor surveillance systems. As a result, IPAQ and GPAQ data from about two-thirds of countries worldwide enable a comparative assessment of global patterns of physical activity to be undertaken for the fi rst time.

Our aim is thus to describe worldwide physical activity levels, showing diff erences in participation between regions and populations, and patterns of walking and vigorous-intensity activity. Because of the specifi c and relevant links between health, physical activity, and the environment, we also outline patterns of walking and cycling—ie, so-called active trans-portation. We draw attention to gaps that remain in physical activity surveillance, particularly how scarce trend data are for most countries and the absence of information from many countries of low and middle income. Because new technology might off er scope for surveillance in the future, we assess data obtained with motion sensors in adults and young people. Addition-ally, we present information about the emer ging science of sedentary behaviours, provide an overview of what is known about trends in physical activity, and emphasise the impor tance of surveillance data to drive national and global action.

How inactive is the world’s population?Self-reported physical activity in adultsWe obtained comparable estimates for physical inactivity in adults (aged 15 years or older) from 122 countries with the WHO global health observatory data repository.12 The combined population of these 122 countries represents 88·9% of the world’s population. For our analyses, physical inactivity was defi ned as not meeting any of three criteria: 30 min of moderate-intensity physical activity on at least 5 days every week, 20 min of vigorous-intensity physical activity on at least 3 days every week, or an equivalent combination achieving 600 metabolic equivalent (MET)-min per week.13–15 1 MET is defi ned as the energy spent when an individual sits quietly. With consideration of diff erent intensities of activity components, reported weekly minutes were multiplied by 8 MET for vigorous activity, and by 4 MET for moderate activity or walking.13–15 Inclusion criteria for country data to be used included assessment of physical activity in all domains (ie, leisure-time, occupation, transportation, and housework). The appendix contains further details about methods used to analyse data.

Worldwide, 31·1% (95% CI 30·9–31·2) of adults are physically inactive. This value represents the weighted average of the proportion in the countries studied, taking into account population sizes. The frequency of inactivity varied greatly between WHO regions (fi gure 1):

27·5% (27·3–27·7) of people are inactive in Africa, 43·3% (43·0–43·6) in the Americas, 43·2% (42·8–43·6) in the eastern Mediterranean, 34·8% (34·5–35·1) in Europe, 17·0% (16·8–17·2) in southeast Asia, and 33·7% (33·5–33·9) in the western Pacifi c. Women are more inactive (33·9%) than are men (27·9%). Additionally, large diff erences exist between countries (appendix); for example, the proportion of inactive individuals of both sexes combined ranged from 4·7% (95% CI 4·3–5·1) in Bangladesh to 71·9% (31·0–87·2) in Malta.

Inactivity increases with age in all WHO regions (fi gure 2), which is a pattern known to have a strong biological basis.16 Despite the linear association in all regions, heterogeneity was substantial. Adults aged 60 years or older from southeast Asia are much more active than are individuals of the same age from all other regions, and actually more active than are young adults (aged 15–29 years) from the Americas, the eastern Mediterranean, Europe, and the western Pacifi c.

Physical inactivity is more common in countries of high income than in those of low income (fi gure 3). For years, surveys focusing solely on leisure-time physical activity suggested that, within countries, physical in-activity was more frequent in people with low income than in those with higher socioeconomic status.17,18 Only in the past decade, when standardised instruments could measure total physical activity (ie, leisure-time, occu-pational, housework, and transport-related activity), has a diff erent social pattern of inactivity become apparent.4,19 Whether or not it will persist in the future is unknown, but evidence from Brazil20 suggests that although pre-valence of physical inactivity increased greatly in people with low income between 2002 and 2007, no signifi cant diff erences were reported in those with higher earnings.20 The hypothesis that the social pattern might be shifting is reinforced by falling occupational physical activity (usually higher in people with low income than in those with high income) and increases in leisure-time exercise (more common in people with high income than in those with low income).21

Walking is a common, accessible, inexpensive form of physical activity and is an important component of total physical activity in adult populations.22 It is aerobic and necessitates use of large skeletal muscles, and confers the multifarious health benefi ts of physical activity with few adverse eff ects.23 Interventions have been implemented to increase population levels of walking and have proven this activity’s eff ectiveness.24 64·1% (63·9–64·3) of adults report walking for at least 10 min consecutively on 5 or more days per week. Variation between WHO regions is modest: 57·0% (56·6–57·4) report such walking in Africa, 65·6% (65·3–65·9) in the Americas, 66·9% (66·1–67·7) in the eastern Mediter ranean, 66·8% (66·4–67·2) in Europe, 67·2% (66·7–67·7) in southeast Asia, and 65·0% (64·5–65·5) in the western Pacifi c. Moreover, patterns of walking hardly diff er in men and women and

See Online for appendix

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between age groups (fi gure 4). This fi nding is partly explained by the measurement of all types of walking—ie, recreational, for transport, and occupational.

Participation in vigorous-intensity physical activity is another key indicator of physical activity levels. It has well established health benefi ts,5 which were recognised in the 2010 WHO global recommendations on physical activity for health.14 Vigorous-intensity activity has higher reliability and validity than does moderate-intensity activity with standardised self-report instruments.10 31·4% (31·2–31·4) of adults report vigorous-intensity physical activity on 3 or more days per week. We noted large diff erences between regions: 38·0% (37·6–38·4) of individuals in Africa report such activity, 24·6% (24·3–24·9) in the Americas, 43·2% (42·3–44·1) in the eastern Mediterranean, 25·4% (25·0–25·8) in Europe, 43·2% (42·7–43·7) in southeast Asia, and 35·3% (34·8–35·8) in the western Pacifi c. Within every age group, men are more likely to participate in vigorous-intensity physical activity than are women (fi gure 4). Participation decreases with age (fi gure 4).

Self-reported physical activity in adolescentsThere are substantial short-term and long-term health benefi ts of regular physical activity for adolescents (aged 13–15 years; some overlap with adult age group because systems are independent).25 However, measure-ment of physical activity in this group is complex.26 Although some countries monitor activity in specifi c age groups, repeated measures with time are rare. Worldwide, most progress has been made in the adolescent population. So far, the two most compre-hensive sources of data for adolescent physical activity levels are the global school-based student health survey (GSHS)27 and the health behaviour in school-aged children (HBSC) survey.28

With publicly available data from GSHS,27 we estimated how many 13–15-year-old adolescents in 66 countries of mostly low and middle income reach the public health goal of 60 min per day or more of moderate to vigorous physical activity. We did the same with published HBSC reports and available raw data29,30 for 38 European countries,

Figure 1: Physical inactivity in adults (15 years or older) worldwide in men (A) and women (B)

>50%40–49·9%30–39·9%20–29·9%<19·9%No data

A

B

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the USA, and Canada. By combining information, we were able to obtain estimates for 105 countries (data from Macedonia were available in both data sources, so we used an average).

80·3% (95% CI 80·1–80·5) of 13–15-year-olds do not do 60 min of moderate to vigorous physical activity per day. Girls are less active than are boys (fi gure 5). Estimates were much higher than were those reported in adults. The proportion of adolescents not achieving 60 min per day was equal to or greater than 80% in 56 (53%) of 105 countries in boys, and 100 (95%) of 105 countries for girls. It is important to stress that the cutoff s for adults and adolescents are diff erent.

Active transportationActive transportation has health benefi ts31,32 and can increase physical activity levels of whole populations.24,33–35 Many studies have shown that commuter walking and cycling have benefi cial eff ects on all-cause mortality32,36 and several diseases.36–42 In children, associations be-tween active commuting to school and reduced body-mass index43 and improved cardiovascular risk factor profi les44–47 have been recorded.

Data for active transportation are derived from various sources, such as population studies and transport research. Comparisons of information from diff erent countries are particularly diffi cult because instruments are not standardised and several indicators (eg, people walking or cycling to work, or percentage of trips with diff erent transport modes) are used. Moreover, some investigators combine walking and cycling, whereas others analyse the two modes separately.

We searched PubMed and the Cochrane databases for systematic reviews34,39,48,49 and original research pub lished from 2010 onwards,50–52 and tried to fi nd online national statistics mainly from transport ministries. We identifi ed statistics for the proportion of people walking to work in 12 countries (table).32,39,50–69 Few individuals (<4%) walk to work in Switzerland, the USA, and Australia, but more than 20% do in China, Germany, and Sweden. We obtained data for adults cycling to work for 12 countries.32,39,50,51,57,58,62–65,67,69 The frequency was low (<2%) in Australia, Canada, Ireland, Switzerland, the UK, and the USA, and high (>20%) in China, Denmark, and the Netherlands (table). Finally, data for all active transportation to work (walking or cycling) were available for 12 countries.50,53,56,58–60,62–66,70–74 Overall, fewer than 5% of individuals in Australia, Switzerland, and the USA use active transportation, but many do in China, France, Germany, Sweden, and the Netherlands (table). Data from low-income countries are scarce.

Walking commuters do not travel as far as do cycling commuters and often combine walking with public transport.75 In Stockholm, mean distances are roughly 2 km for walking and 8 km for cycling.75 However, cyclists could be limited by unsafe environments and few bike lanes.75 However, major diff erences exist even between

Figure 4: Proportion of adults (15 years or older) worldwide reporting walking for at least 10 min consecutively on 5 or more days per week (A) and vigorous-intensity physical activity on 3 or more days per week (B) by age group

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Figure 2: Physical inactivity in age groups by WHO region

Africa Americas EasternMediterranean

Europe SoutheastAsia

WesternPacific

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Figure 3: Physical inactivity by sex and World Bank income groups

Both sexes Men Women0

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countries with similar geography, population density, and climate—eg, fewer people in the UK cycle to work than in Denmark and the region of Holland (table)—suggesting that other factors play a part. In Denmark, building of infrastructure to promote cycling has resulted in a 50% increase in cycling in the past two decades.76

Although active transportation is benefi cial for health and the environment, its promotion should take into account unintended eff ects. In several places, pedestrian and cyclist safety are serious concerns, even though the benefi ts from cycling outweigh the risks. If all non-cyclists in Denmark became cyclists, about 12 000 deaths linked to little physical activity would be prevented every year as a result of cycling activity; there, only 30 cyclists are killed in traffi c accidents annually.32 However, the situation is probably diff erent in many large cities in countries of all incomes. The global challenge is to help to improve pedestrian and cyclist safety, and city environments, so that active transportation becomes not only a healthy alternative, but also a safe one.

Objectively measured physical activityNew technologies applied to the measurement of body movement have emerged as an alternative method for assessment of physical activity. Instruments such as accelerometers provide new ways to estimate the frequency, duration, and intensity of physical activity in free-living individuals.77 Importantly, these methods avoid some of the inherent limitations of self-report instruments—ie, recall bias. Accelerometry is widely used in small-scale research studies, and in the past 10 years its application has been tested within population-based surveillance systems in several developed countries (panel 1).

To assess accelerometry data for moderate to vigorous physical activity in adults, we searched Medline and Web of Science for reports in which physical activity was measured with the Actigraph accelerometer. We included population-based studies of healthy adult participants older than 18 years, in which activity was measured for at least 4 days and for at least 600 min per day. All reports

Figure 5: Proportion of 13–15-year-old boys (A) and girls (B) not achieving 60 min per day of moderate to vigorous physical activity

>90% 80–89·9% 70–79·9% 60–69·9% <60% No data

A

B

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used the same defi nition of moderate to vigorous physical activity of 2020 activity counts per min or more. Two studies82,83 were included in separate and combined reports,82–84 and subsequently only results from the com-bined report84 were included. Data from four countries (Norway, Portugal, Sweden, and the USA)84–86 for 9564 individuals were extracted.

For young people, we used data from the international children’s accelerometer database,87 which includes more than 30 000 individuals aged 4–18 years from 21 studies in ten countries. All raw accelerometer data fi les were reanalysed with the same data cleaning and data reduction criteria as for adults. To enable comparison with data for adults, moderate to vigorous physical activity was defi ned as more than 2000 counts per min, adjusted for sex and age.

For adults, the mean accumulated minutes of moderate to vigorous physical activity is roughly 35·5 min per day (95% CI 34·0–37·0) in men and 32·0 min per day (23·5–40·4) in women. Mean time spent doing moderate to vigorous physical activity is similar in men from diff erent countries, ranging between 33·0 min per day in the USA to 37·5 min per day in Portugal. Variation is increased in women, ranging from 19·0 min per day in the USA to 44·6 min per day in Portugal. In young people, the highest amounts of such activity are done in Norway, Switzerland, Estonia, and Australia; values from Belgium, Brazil, and the USA were substantially lower than the pooled adjusted mean of roughly 65 min per day. Highly signifi cant heterogeneity between countries was recorded (appendix).

Caution is warranted in comparisons of accelerometry data and self-report. Most time in moderate to vigorous

physical activity recorded by accelerometry is accumu-lated in periods shorter than 10 min,88 whereas self-report instruments usually prompt the respondent to report activities lasting at least 10 min.10 Additionally, most accelerometer data presented here are derived from high-income countries, in which people are less active than are those from low-income and middle-income countries (fi gure 3).

Sedentary behaviourAnother aspect of the human movement range that has received attention is sedentary behaviour, which is usually defi ned as time spent sitting. Similarly to physical activity, sedentary behaviours occur in diff erent domains (ie, at work, for leisure and entertainment, and while com mut-ing).89 So far, little is known about the patterns of sedentary behaviour in diff erent countries,90 mainly because it has been recognised as a public health issue only in the past 10 years and therefore few standardised instruments are available for its assessment.91 However, with available data from the WHO STEPwise approach to chronic disease risk factor surveillance (STEPS) surveys and the Eurobaro-meter, we could assess and compare time spent sitting in 66 countries both of high and low income.

Overall, the proportion of adults spending 4 or more h per day sitting is 41·5% (41·3–41·7). The value varied greatly in WHO regions: 37·8% (37·4–38·2) of indi viduals sit for 4 or more h per day in Africa, 55·2% (54·3–56·1) in the Americas, 41·4% (40·1–42·7) in the eastern Mediterranean, 64·1% (63·5–64·7) in Europe, 23·8% (23·1–24·5) in southeast Asia, and 39·8% (39·3–40·3) in the western Pacifi c. For adults aged 15–59 years, the pro-portion spending 4 h or more per day sitting does not vary substantially, and both sexes are similar; for individuals aged 60 years or more, the frequency is increased (fi gure 6).

Bauman and colleagues90 presented time spent sitting in 20 countries. They reported a median of 300 min per day (IQR 180–480), wide variation between countries, and longer times in middle-aged adults (40–65 years-old) than in young adults (18–39 years-old)92—a fi nding that was not replicated in our analysis of 66 countries.

With HBSC data from 40 countries in Europe and North America, we estimated that 66% of boys and 68% of girls aged 13–15 years spend 2 h or more per day watching television. In every country studied—with the exception of Switzerland—more than half of the boys and girls spent 2 h or more per day watching television. Guthold and colleagues93 used data for 34 countries from GSHS and reported that, in more than half of the countries, more than a third of students spend 3 h or more per day doing sedentary activities.

Trends in physical activitySeveral behavioural and environmental factors, and megatrends (major forces in societal development that aff ect people’s lives) aff ect population levels of phys-ical activity.94 Rapid urbanisation, mechanisation, and

Walk to work Cycle to work Walk or cycle to work

Australia53,54 3·8% 0·9–1·7%* 4·7%

Austria55 5·0–6·6%* ·· ··

Brazil56 ·· ·· 11·9%

Canada50,51,57 6·6% 1·0–1·2%* ··

China58 22·6% 23·5% 46·1%

Denmark32 ·· 25·0% ··

Finland59 ·· ·· 19·5%

France60 ·· ·· 34·9%

Germany52,61 23·0% 9·0% 32·0%

Ireland62 10·9% 1·9% 12·8%

New Zealand63 7·0% 2·5% ··

Switzerland64 2·2% 0·3% 2·5%

Sweden65 23·5% 9·5% 22·2–33·0%*

Netherlands66,67 12·1% 21·0–25·8%* 37·9%

UK68 12·5% 2·0% 14·5%

USA39,50,51,69 3·1–4·0%* 0·5–3·4%* 4·0–16·7%*

*Interval reported in several studies or data obtained from several regions or states.

Table: Proportion of adults reporting walking to work, cycling to work, or using any type of active transportation (walking or cycling) by country

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increased use of motorised transport could have caused global changes in physical activity.95,96 Examples of national surveillance systems that aim to assess trends in physical activity are scarce, most are fairly recent, and most are in high-income countries.

A systematic review21 showed that adults’ leisure-time physical activity, including sports participation, has increased in the past 20–30 years in fi ve high-income countries. This fi nding seemed to be consistent and was supported by subsequent studies from Canada,97 Spain,98 Sweden,99 and England.100 Re searchers have also reported a simultaneous reduction in occupational physical activ-ity.21,98,100 A comprehensive analysis101 of US data showed that daily energy expend iture in work-related physical activity has fallen by more than 100 calories per day during the past 50 years. Data for time trends in physical activity from countries of low and middle income are extremely sparse and, when available, inconsistent.20,102,103

The magnitude and direction of changes in physical activity with time in young people are less clear than in adults. A systematic review21 of studies from fi ve high-income countries established that physical activity during physical education classes has decreased since the early 1990s. Additionally, use of active transportation has fallen in the USA,104 Switzerland,105 and Canada106 in the past 40 years. A review focusing on diff erent domains of activity107 showed that available evidence does not support the notion that overall physical activity levels and sport participation have fallen in young people. As with adults, the paucity of data for changes in physical activity with time from countries of low and middle income is worrying.

Very few studies from a small number of high-income countries have examined time trends in physical activity by objective methods. In Japan, the proportion of adults achieving 10 000 steps per day fell by 5% from 2000 to 2007.108 Reductions in physical activity have been recorded in Czech boys aged 14–18 years between 1998 and 2000, and between 2008 and 2010,109 and in Canadian boys and girls aged 8–16 years from 2001 to 2006.110 Conversely, a study in Sweden111 showed that the number of accumu-lated steps per day increased between 2000 and 2006 in boys and girls aged 7–9 years.

Surveillance progress and gapsMuch progress has been made in the availability of national population-level data for physical activity in the past decade, particularly in adults. About two-thirds of all WHO Member States have at least some data for population levels of physical activity, which is a great surveillance achievement. Collectively, data now available for adult and adolescent populations provide a global picture of the pattern of participation and exposure to the risk of inactivity, and form the basis for national policy development as called for by the global strategy for diet, physical activity, and health112 and for guidance of practice at the national and local community levels.

However, notable gaps remain. One is the absence of continuous surveillance systems implemented at the national level, preventing most countries from analysing trends data. Well established surveillance systems for physical activity are a luxury available in only very few countries, most of which are highly developed (panel 1). Additionally, the distribution of countries with no data is not random. Data gaps are concentrated in Africa, and the poorest parts of Latin America and central Asia. A good example of how physical activity surveillance can be

Panel 1: Physical activity surveillance in the USA

Physical activity surveillance in the USA has included national and state-based surveys. The national health and nutrition examination survey (NHANES)78 is a population-based survey providing information about health and nutrition. Health examination surveys were done throughout the 1960s and were followed by NHANES from 1971 onwards. NHANES has two parts: home interviews and health examinations. Physical activity questions were introduced in 1999, allowing analyses of secular trends in the proportion of physical inactivity and its correlates. NHANES provides data for adults (leisure-time, transportation, and household activities) and children (leisure-time activities). In 2003, accelerometry data were obtained in addition to self-report.

Other surveys began in the 1980s to monitor the prevalence of the major behavioural risks associated with premature morbidity and mortality. Data collection was systematised as the behavioural risk factor surveillance system (BRFSS) in 1984.79,80 Data are obtained monthly in all 50 states, the District of Columbia, Puerto Rico, the US Virgin Islands, and Guam. More than 350 000 people are interviewed every year, making BRFSS the largest telephone health survey in the world. Data from BRFSS have been widely used for research. Between 1984 and 2000, physical activity questions focused on only leisure-time activities. However, domestic and transport-related physical activity were added to the survey from 2001. Although occupational activities are included in the questionnaire, they are not part of the total physical activity score. In the 2011 version of BRFSS, eight core physical activity questions were incorporated. 15 000 young people in grades 9–12 (usually aged 15–18 years) are assessed every year in a separate part of the surveillance system (youth risk behaviour factor surveillance).81 Leisure-time, transport-related, and domestic physical activity are assessed, as well as participation in physical education classes.

Figure 6: Proportion of individuals reporting 4 h or more of sitting per day by age category

Both sexes Men Women0

10

20

30

40

50

60

70

80

Prop

ortio

n (%

)

15–29 years 30–44 years 45–59 years ≥60 years

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initiated and sustained in countries of low and middle income is the WHO STEPwise approach (panel 2).

Translation of knowledge into actionOur fi ndings are troubling. Roughly three of every ten individuals aged 15 years or older—about 1·5 billion people—do not reach present physical activity recom-mendations.5,14 The situation in adolescents is even more worrying, with a worldwide estimate that four of every fi ve adolescents aged 13–15 years do not meet present guidelines. As summarised by Lee and colleagues,115 these individuals are at increased risk of coronary heart disease, diabetes, some types of cancer, several other diseases, and premature death.

Some methodological issues with available surveillance data should be raised. Our estimates were corrected for the well known over-reporting of physical activity with IPAQ (appendix),116–119 and we adjusted values for age and region (urban vs rural), which are two factors known to aff ect physical activity behaviours. With these strategies, the well known limitations of self-reporting in adult populations were minimised. However, self-reports are unreliable, especially for housework and occupational physical activity, and in countries of low and middle income,120 where transport, occupational, and housework activities are often mixed in daily life.

Additionally, perceptions about the meaning of physical activity might vary between countries, sexes, and age groups, particularly because people tend to com pare themselves with peers when replying to physical activity questions.99 Fortunately, ways to overcome this issue

have been proposed and implemented, such as the use of show cards and culturally relevant examples (panel 2). Another diffi culty is that not all samples are representative of a whole country’s population. These limitations of available self-reported data could partly explain the large diff erences in prevalence of physical inactivity between countries. Finally, the limitations of data presently available for sedentary behaviour should be acknow-ledged, because surveillance information is typically restricted to single items instead of standardised and validated instruments.121 Furthermore, available infor-mation about active transportation comes from diff erent sources and few countries.

As public health eff orts to increase physical activity and decrease sedentary time proceed, standardised physical activity surveillance procedures need to be implemented broadly and repeatedly. These measures are necessary to understand which intervention strat-egies work for which populations, and to identify target populations at greatest risk. Two validated questionnaires have been successfully implemented across countries and cultures, but many existing systems would have to be expanded to assess specifi c domains of physical activity, especially active transportation and sedentary behav iours. Existing sur veillance systems would have to be expanded to include these specifi c aspects. Advances in new technologies and measurement methods, especially accelerometry, show promise for future sur-veillance of physical activity. These devices could have widespread practical application if equipment costs continue to fall and suffi cient eff orts are directed towards increasing technical skills and workforce capacity in countries of low and middle income.

Alteration of population levels of physical activity through improved use of existing surveillance data is a major challenge for the 21st century, because societal trends are leading to less not more activity than previously. The traditional public health approach based on evidence and exhortation has—to some extent—been unsuccessful so far. With few exceptions, health pro-fessionals have been unable to mobilise governments and populations to take physical inactivity suffi ciently ser iously as a public health issue. Our results show clear progress in surveillance, partly because the growing burden of non-communicable diseases has prompted governments and international agencies to monitor physical activity worldwide. These achievements were only made possible because thousands of individuals from various parts of the world kindly provided infor-mation about their behaviour. In return, governments, policy makers, and the research community should help to build societies in which the choice of being physically active is not only healthy, but also convenient, enjoyable, safe, aff ordable, and valued.ContributorsAll authors wrote sections of this report, provided feedback on drafts, and approved the fi nal version.

Panel 2: The WHO STEPwise approach to chronic disease risk factor surveillance

The WHO STEPwise approach to chronic disease risk factor surveillance (STEPS) was initiated in 2000, to assist countries of low and middle income to obtain information about risk factors for major non-communicable diseases. The overall goal is to build and strengthen country capacity to undertake surveillance within an integrated, systematic, sustainable framework.113 With the same standardised questions and protocols, all countries can use STEPS information not only for monitoring within-country trends, but also for making comparisons between countries. The global physical activity questionnaire was developed for STEPS. This instrument measures physical activity at work and in the household, for transport, and for leisure separately.11 The use of show cards and culturally specifi c examples for each activity type contained in the questionnaire ensures complete understanding of the questions and cultural adaptation.

In 2000, physical activity data were available for only two countries in the WHO African region.4 2 years later, professionals working in Ministries of Health, and other health professionals and statisticians in ten of the 46 African countries had received training about implementation of the STEPS approach; this number had increased to 35 by early 2006. By then, the remaining 11 countries had already successfully undertaken a STEPS survey. Since 2006, all African countries have received STEPS training, and physical activity data are now available for the 35 countries that have completed surveys, including fi ve countries that have done two surveys. 26 countries have published the results in country reports or journal articles, or both.114 In ten countries that have completed a STEPS survey, eSTEPS— ie, hand-held computers to input data introduced in 2009—has been implemented.

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Lancet Physical Activity Series Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk, Harold W Kohl 3rd, Estelle Victoria Lambert, I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of interestWe declare that we have no confl icts of interest.

AcknowledgmentsWe alone are responsible for the views expressed in this report and they do not necessarily represent the decisions, policy, or views of WHO. We thank Valerie Lyn Clark, Ken Hardman, Lisa Micklesfi eld, and Andrea Torres for their help with data gathering.

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84 Hagströmer M, Troiano RP, Sjöström M, Berrigan D. Levels and patterns of objectively assessed physical activity—a comparison between Sweden and the United States. Am J Epidemiol 2010; 171: 1055–64.

85 Hansen BH, Kolle E, Dyrstad SM, Holme I, Anderssen SA. Accelerometer-determined physical activity in adults and older people. Med Sci Sports Exerc 2012; 44: 266–72.

86 Baptista F, Santos DA, Silva AM, et al. Prevalence of the Portuguese population attaining suffi cient physical activity. Med Sci Sports Exerc 2012; 44: 466–73.

87 Sherar LB, Griew P, Esliger DW, et al. International children’s accelerometry database (ICAD): design and methods. BMC Public Health 2011; 11: 485.

88 Hagstromer M, Troiano RP, Sjostrom M, Berrigan D. Levels and patterns of objectively assessed physical activity—a comparison between Sweden and the United States. Am J Epidemiol 2010; 171: 1055–64.

89 Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev 2010; 38: 105–13.

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90 Bauman A, Ainsworth BE, Sallis JF, et al. The descriptive epidemiology of sitting a 20-country comparison using the international physical activity questionnaire (IPAQ). Am J Prev Med 2011; 41: 228–35.

91 Levine JA, Lanningham-Foster LM, McCrady SK, et al. Interindividual variation in posture allocation: possible role in human obesity. Science 2005; 307: 584–86.

92 Lee PH, Yu YY, McDowell I, et al. Performance of the international physical activity questionnaire (short form) in subgroups of the Hong Kong Chinese population. Int J Behav Nutr Phys Act 2011; 8: 81.

93 Guthold R, Cowan MJ, Autenrieth CS, Kann L, Riley LM. Physical activity and sedentary behavior among schoolchildren: a 34-country comparison. J Pediatr 2010; 157: 43–49.

94 Pratt M, Sarmiento OL, Montes F, et al, for the Lancet Physical Activity Working Group. The implications of megatrends in information and communication technology and transportation for changes in global physical activity. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)60736-3.

95 Assah FK, Ekelund U, Brage S, Mbanya JC, Wareham NJ. Urbanization, physical activity, and metabolic health in sub-Saharan Africa. Diabetes Care 2011; 34: 491–96.

96 Sullivan R, Kinra S, Ekelund U, et al. Socio-demographic patterning of physical activity across migrant groups in India: results from the Indian Migration Study. PLoS One 2011; 6: e24898.

97 Juneau CE, Potvin L. Trends in leisure-, transport-, and work-related physical activity in Canada 1994–2005. Prev Med 2010; 51: 384–86.

98 Palacios-Cena D, Alonso-Blanco C, Jimenez-Garcia R, et al. Time trends in leisure time physical activity and physical fi tness in elderly people: 20 year follow-up of the spanish population national health survey (1987–2006). BMC Public Health 2011; 11: 799.

99 Sjol A, Thomsen KK, Schroll M, Andersen LB. Secular trends in acute myocardial infarction in relation to physical activity in the general Danish population. Scand J Med Sci Sports 2003; 13: 224–30.

100 Stamatakis E, Chaudhury M. Temporal trends in adults’ sports participation patterns in England between 1997 and 2006: the Health Survey for England. Br J Sports Med 2008; 42: 901–08.

101 Brownson RC, Boehmer TK, Luke DA. Declining rates of physical activity in the United States: what are the contributors? Annu Rev Public Health 2005; 26: 421–43.

102 Matsudo VK, Matsudo SM, Araujo TL, Andrade DR, Oliveira LC, Hallal PC. Time trends in physical activity in the state of Sao Paulo, Brazil: 2002–2008. Med Sci Sports Exerc 2010; 42: 2231–36.

103 Hallal PC, Knuth AG, Rombaldi AJ, et al. Time trends of physical activity in Brazil (2006–2009). Rev Bras Epidemiol 2011; 14 (suppl 1): 53–60.

104 McDonald NC. Active transportation to school: trends among US schoolchildren, 1969–2001. Am J Prev Med 2007; 32: 509–16.

105 Grize L, Bringolf-Isler B, Martin E, Braun-Fahrlander C. Trend in active transportation to school among Swiss school children and its associated factors: three cross-sectional surveys 1994, 2000 and 2005. Int J Behav Nutr Phys Act 2010; 7: 28.

106 Buliung RN, Mitra R, Faulkner G. Active school transportation in the Greater Toronto Area, Canada: an exploration of trends in space and time (1986–2006). Prev Med 2009; 48: 507–12.

107 Ekelund U, Tomkinson G, Armstrong N. What proportion of youth are physically active? Measurement issues, levels and recent time trends. Br J Sports Med 2011; 45: 859–65.

108 Inoue S, Ohya Y, Tudor-Locke C, Tanaka S, Yoshiike N, Shimomitsu T. Time trends for step-determined physical activity among Japanese adults. Med Sci Sports Exerc 2011; 43: 1913–19.

109 Sigmundova D, El Ansari W, Sigmund E, Fromel K. Secular trends: a ten-year comparison of the amount and type of physical activity and inactivity of random samples of adolescents in the Czech Republic. BMC Public Health 2011; 11: 731.

110 Thompson AM, McHugh TL, Blanchard CM, et al. Physical activity of children and youth in Nova Scotia from 2001/02 and 2005/06. Prev Med 2009; 49: 407–09.

111 Raustorp A, Ludvigsson J. Secular trends of pedometer-determined physical activity in Swedish school children. Acta Paediatr 2007; 96: 1824–28.

112 WHO. Global strategy on diet, physical activity and health. Geneva: World Health Organization, 2004.

113 Armstrong T, Bonita R. Capacity building for an integrated noncommunicable disease risk factor surveillance system in developing countries. Ethn Dis 2003; 13 (suppl 2): S13–18.

114 Guthold R, Louazani SA, Riley LM, et al. Physical activity in 22 African countries: results from the World Health Organization STEPwise approach to chronic disease risk factor surveillance. Am J Prev Med 2011; 41: 52–60.

115 Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, for the Lancet Physical Activity Series Working Group. Eff ect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)61031-9.

116 Ekelund U, Sepp H, Brage S, et al. Criterion-related validity of the last 7-day, short form of the International Physical Activity Questionnaire in Swedish adults. Public Health Nutr 2006; 9: 258–65.

117 Ainsworth BE, Macera CA, Jones DA, et al. Comparison of the 2001 BRFSS and the IPAQ Physical Activity Questionnaires. Med Sci Sports Exerc 2006; 38: 1584–92.

118 Rzewnicki R, Vanden Auweele Y, De Bourdeaudhuij I. Addressing overreporting on the international physical activity questionnaire (IPAQ) telephone survey with a population sample. Public Health Nutr 2003; 6: 299–305.

119 Lee PH, Macfarlane DJ, Lam TH, Stewart SM. Validity of the international physical activity questionnaire short form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act 2011; 8: 115.

120 Hallal PC, Gomez LF, Parra DC, et al. Lessons learned after 10 years of IPAQ use in Brazil and Colombia. J Phys Act Health 2010; 7 (suppl 2): S259–64.

121 Bauman A, Ainsworth BE, Bull F, et al. Progress and pitfalls in the use of the international physical activity questionnaire (IPAQ) for adult physical activity surveillance. J Phys Act Health 2009; 6 (suppl 1): S5–8.

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Lancet 2012; 380: 258–71

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)60735-1

This is the second in a Series of fi ve papers about physical activity

*Members listed at end of paper

Prevention Research Collaboration, School of Public

Health, Sydney University, Sydney, NSW, Australia

(Prof A E Bauman PhD); School of Health and Biosciences,

Pontifícia Universidade Católica do Paraná, Curitiba,

Brazil (Prof R S Reis PhD); Federal University of Parana, Curitiba, Brazil (Prof R S Reis);

Family and Preventive Medicine, University of

California San Diego, San Diego, CA, USA

(Prof J F Sallis PhD); UCL Institute of Child Health,

University College London, London, UK

(Prof J C Wells PhD); MRC Epidemiology Unit, Institute

of Metabolic Science, Addenbrooke’s Hospital,

Cambridge, UK

Physical Activity 2

Correlates of physical activity: why are some people physically active and others not?Adrian E Bauman, Rodrigo S Reis, James F Sallis, Jonathan C Wells, Ruth J F Loos, Brian W Martin, for the Lancet Physical Activity Series Working Group*

Physical inactivity is an important contributor to non-communicable diseases in countries of high income, and increasingly so in those of low and middle income. Understanding why people are physically active or inactive contributes to evidence-based planning of public health interventions, because eff ective programmes will target factors known to cause inactivity. Research into correlates (factors associated with activity) or determinants (those with a causal relationship) has burgeoned in the past two decades, but has mostly focused on individual-level factors in high-income countries. It has shown that age, sex, health status, self-effi cacy, and motivation are associated with physical activity. Ecological models take a broad view of health behaviour causation, with the social and physical environment included as contributors to physical inactivity, particularly those outside the health sector, such as urban planning, transportation systems, and parks and trails. New areas of determinants research have identifi ed genetic factors contributing to the propensity to be physically active, and evolutionary factors and obesity that might predispose to inactivity, and have explored the longitudinal tracking of physical activity throughout life. An understanding of correlates and determinants, especially in countries of low and middle income, could reduce the eff ect of future epidemics of inactivity and contribute to eff ective global prevention of non-communicable diseases.

IntroductionGlobally, many adults and children do insuffi cient physical activity to maintain good health.1 Furthermore, the population burden of inactivity is unacceptably high.2 Although strategies to increase physical activity are being developed,3,4 eff ect sizes are usually small to moderate, and eff ective interventions are not widely applied. The prevalence of physical activity is slow to improve and is worsening in some countries.5 As the global burden of non-communicable diseases increases, risk factors such as physical inactivity become relevant in low-income and middle-income countries, not just in the most developed nations.6 Understanding the causes of physical activity

behaviour is essential for development and improvement of public health interventions,7 much as aetiological studies of disease provide information about treatments. Of particular interest is how aetiological factors diff er between physical activity domains—ie, areas of life in which activity is done (at home, at work, in transport, and in leisure time)—and with country, age, sex, ethnic origin, and socioeconomic status.

One challenge in the interpretation of evidence is that most studies have used cross-sectional designs. This so-called correlates research assesses only statistical association, rather than providing evidence of a causal relationship between factors and physical activity.8,9 Longi tudinal observational studies and experimental data could identify factors that have strong causal associations with physical activity.9 When such factors are identifi ed in studies of aetiological design, they are described as determinants.8

Because physical activity is aff ected by diverse factors, behavioural theories and models are used to guide the selection of variables for study.8 Integration of ideas from several theories into an ecological model (includ-ing inter-relations between individuals and their social and physical environments) is now common.10 This approach uses a comprehensive framework to explain physical activity, proposing that determinants at all levels—individual, social, environmental, and policy—are contri butors. A key principle is that know ledge about all types of infl uence can inform develop ment of multilevel inter ventions to off er the best chance of success.10 Figure 1 shows a multilevel model of physical activity infl uences, which guided our classifi cation of variables in this report. The model is ecological because inter-relations between individuals and their social and

Key messages

• Population levels of physical activity participation are low, and improved understanding of why some people are active and others are not is needed

• Some consistent correlates of physical activity are individual-level factors such as age, sex, health status, self-effi cacy, and previous physical activity

• Ecological models posit that the physical and social environments—ie, economic conditions, societal norms, urbanisation, industrialisation—are important determinants of physical activity

• Correlates have been less studied in low-income and middle-income countries than in other nations, and although broadly similar to those in high-income countries, they are more focused on the prevalent domains of physical activity in developing countries—ie, correlates of transport and occupational activity

• New research has identified genetics, evolutionary biology, and variation in physical activity behaviour throughout life as important determinants

• Improvement of the research base, with a stronger focus on determinants research (with improved causal inference rather than repetition of cross-sectional correlates studies) will further an understanding of physical activity in populations and interventions designed to increase activity levels

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(Prof R J F Loos PhD); Genetics of Obesity and Related Metabolic Traits Program, Mount Sinai School of Medicine, New York, NY, USA (Prof R J F Loos); and Physical Activity and Health Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland (B W Martin MD)

Correspondence to:Prof Adrian E Bauman, Prevention Research Collaboration, School of Public Health, Building K25, University of Sydney, Sydney, 2006 NSW, [email protected]

physical environments are inclu ded. A key principle is that understanding of all levels of infl uence can inform development of multi level interventions that off er the best chance for success.10 Variables within individuals, such as psycho logical and biological factors, are widely studied, as are inter personal variables. Environmental, policy, and global variables are less studied, but are thought to have widespread eff ects. The combination and interaction of factors and at these levels are expected to infl uence physical activity.

Physical activity is done for various reasons, and the SLOTH (sleep, leisure-time, occupation, transportation, and home-based activities) model11 delineates the domains of physical activity. Ecological models of physical activity have been developed that suggest correlates are specifi c to domains.12 All domains are important for understanding of worldwide physical activity, because frequency of activity in each domain varies greatly between countries.13,14 For example, occu-pational, household, and transport domains are the most common types of physical activity in low-income and middle-income countries, whereas leisure-time activities contribute more to total physical activity in high-income countries than elsewhere.14

We have three objectives. First, we aim to summarise present knowledge about correlates and determinants of physical activity in adults and children, on the basis of evidence from systematic reviews of physical activity correlates.15,16 We provide an outline of new research into physical activity domains, particularly exploring corre-lates of active leisure and recreation, and active trans-portation. Additionally, we describe the rapidly evolving fi eld of environmental correlates of physical activity. Second, we examine correlates and determinants

research in countries of low and middle income, where physical inactivity is rapidly becoming a major risk factor for non-communicable disease.17 Third, we analyse correlates and determinants of physical activity that are least studied, such as genetic factors, lifecourse trajec-tories, evolutionary and societal factors, and obesity (fi gure 1).

Studies of correlates and determinants We identifi ed individual, social, and environmental correlates of physical activity in studies with adults (aged ≥18 years) and children (aged 5–13 years depending on the study) or adolescents (aged 12–18 depending on the study), with variables categorised with our eco logical model. Reviews published after Jan 1, 1999, were obtained with a systematic search of Academic Search Premier, Medline, PsycInfo, SportDiscus, and Web of Science (appendix). We used the search terms “physical activity”, “physically active”, “exercise”, “exercising”, “motor behavior”, “active living”, “active transport”, “inactivity”, “inactive”, “walk”, “walking”, “cycling or cycle or bike or biking or bicycle or bicycling”, “deter minants”, “correlates”, “demograph*”, “biologic*”, “psycho social”, “environ ment*”, “genetic”, and “review”. We did the fi nal search in April, 2012. We used no language restrictions. Additional papers were retrieved from our individual databases and from references within the reports identifi ed.

The outcomes in the reports identifi ed by the initial search were mostly leisure-time or recreational physical activity. Some reviews reported on total physical activ-ity,18 often measured objectively with acceler ometers, especially in children,16,19 and a few provided correlates of other domains of activity,20 particularly active trans-portation.21 For each report, we coded variables on the

Individual EnvironmentInterpersonal

Psychological

Biological

Geneticfactors

Early life exposures Middle aged Older adultChildhood Adolescent Young adult

Lifecourse

Evolutionaryphysiology

• Social support• from family• from friends• at work

• Cultural norms andpractices

• Social environment• Seeing others active

(behavioural modelling)• Crime, traffic, incivilities• Organisational practices

• Built environment• Community design• Neighbourhood walkability• Public transport• Parks and recreation facilities• Aesthetics and pleasantness• Walking and cycling facilities• Building location and design• Pedestrian safety; crossings

• Natural environment• Vegetation, topography,

weather• National parks, trails,

walking routes

Regional or national policy

• Transport systems

• Urban planning andarchitecture

• Parks and recreation sector

• Health sector

• Education and schools sector

• Organised sport sector

• National physicalactivity plans

• National physical activityadvocacy

• Corporate sector

Global

• Economic development

• Global media

• Global product marketing

• Urbanisation

• Global advocacy

• Social and culutural norms

Intrapersonal• cognition• beliefs• motivation

Figure 1: Adapted ecological model of the determinants of physical activity

See Online for appendix

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basis of clear evidence that the factor was a correlate or determinant, evidence of no relation ship (not a correlate or determinant), or no evidence (not reported). A limitation of this approach was that we obtained narra-tive reviews describing the consis tency—not the magni-tude—of associations, so formal pooling of data or meta-analyses was seldom under taken. We sought correlates for all ages, and used a fi ve-category classi—fi cation system:15 demographic or biological, psycho-social, behavioural (including previous activity par tici pation and other health-related behaviours), social and cultural, and environmental factors.

Studies of physical activity correlates in low-income and middle-income countries have not been previously summarised. We searched Medline and Web of Science with the term “‘physical activity’ or ‘exercise’ and ‘correlates’ or ‘determinants’” as title, topic words, key-words (appendix). We included studies published in English, Spanish, Portuguese, French, and German. We identifi ed original reports and separated results by type of physical activity, because leisure-time activity made only a small contribution to overall activity in many nations.22 We used the World Bank defi nitions of countries of low and middle income. We categorised variables into broad groupings as for high-income countries, because we had insuffi cient studies to undertake a detailed review of individual correlates.

Finally, we investigated correlates that are studied less than are others, on the basis of our conceptual framework (fi gure 1). We chose to investigate variation with time (tracking), heritability, the role of evolutionary biology, and obesity as determinants. Finally, we examined poten tial policy, macrosocial, and global determinants, because they might be important at the population level.

Correlates and determinants of physical activity Demographic, psychosocial, behavioural, and social factorsWe initially identifi ed 32 reviews of demographic, psycho social, behavioural, and social factors in adults, adolescents, and children, of which 16 systematic reviews were used (appendix). Of those, seven reviews of children and adolescents met our inclusion criteria (appendix) and were used for the fi nal synthesis. Reports varied from comprehensive reviews16,23 to those that focused on only longitudinal studies.20,24 Other reviews were of adolescent girls,25 pre-school children (aged 2–5 years),26 and parental correlates of physical activity.16,20,23,24,26 In those published since 2000, consis-tent evidence has emerged for 39 separate correlates and 11 separate determinants (identifi ed in longitudinal studies only) in children, and 51 cor relates including seven determinants in adolescents (appendix).

Male sex is a consistent positive determinant in children aged 4–9 years; for other age groups of children and adolescents, sex is a correlate but not a consistent determinant (table 1). In children, parental marital status, including single-parent status, was identifi ed as a

non-determinant (table 1). No relationship was noted for body-mass index and other anthropometric measures in children or adolescents (table 1). A white ethnic origin was a consistent positive determinant in one systematic review of adolescents,24 but not in another (table 1).20

Of psychosocial factors, self-effi cacy (confi dence in the ability to be physically active in specifi c situations) was a consistent positive correlate and determinant of physical activity in children and adolescents (table 1). Perceived behavioural control (general perceptions of ability to be physically active) is a determinant in adolescents, but evidence is inconclusive in children (table 1). The fi ndings for valuing physical activity for health status (appearance or achievement), and barriers to physical activity in children are inconsistent (table 1). Perceived competence and attitude are not determinants in adolescents (table 1). Findings for behavioural factors in children and adolescents vary: smoking seems to be unrelated to physical activity, but previous physical activity does seem to be a predictor (table 1).

Of social and cultural factors, parental activity was not a determinant in children or a correlate in adolescents. Family support was identifi ed as a correlate in children and adolescents, but it was not a determinant in children. Children’s perception of their parents’ behaviour was not a determinant of their own activity, and in adolescents it was not a correlate. In adolescents, general social support for physical activity was confi rmed as a determinant in one review (table 1).

In adults, research into correlates started with theoretical approaches to understanding individual behaviour. This fi eld expanded to subsequently consider environmental correlates within an ecological frame-work.27 In this review of non-environmental adult physical activity correlates, we identifi ed nine reviews meeting the inclusion criteria (table 2). Chronologically, reviews were initially generic,15 or focused on older adults,28 women,18 special issues (eg, personality),29 life events,31 and occupational correlates of physical activity.30,33 The most recent reviews identifi ed determinants and used longi-tudinal designs.29,32,34 Consistent evidence has emerged for 36 separate correlates since 1999, including 20 separate determinants in adults (appendix).

Health status and self-effi cacy are the clearest correlates in adults, with consistent evidence for a direct role in four of seven reviews (table 2). Consistent evidence from one of two reviews shows that both are determinants (table 2). The next clearest are personal history of physical activity during adulthood and intention to exercise, both with consistent evidence for a direct role from two correlate reviews and one determinant review. The stages of behavioural change according to the transtheoretical model were direct correlates in one review and direct determinants in another.

Additionally, we noted that age (inversely), male sex, education level, ethnic origin, overweight (inversely), perceived eff ort (inversely), and social supports are

For more on World Bank defi nitions see http://data.

worldbank.org

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reported correlates of activity, but were not determinants. Marital status and social norms were not determinants. In Kirk and Rhodes’s review of determinants in the work setting,33 occupational category was directly associated with leisure-time physical activity, but inversely related to total activity.

Other factors (job strain, working hours, and overtime) had inverse associations with leisure-time physical activity.33 Finally, the most recent reviews32,34 (with data from only longitudinal studies) showed that stress is an inverse determinant and that physical and psycho-logical outcome realisations are direct determinants of

Children Adolescents

Sallis (2000)16

Van Der Horst (2007)23

Hinkley (2008)26

Edwardson (2010)19

Craggs (2011)20

Craggs (2011)20

Uijtdewilligen (2011)24

Sallis (2000)16

Biddle (2005)25

Van Der Horst (2007)23

Edwardson (2010)19

Craggs (2011)20

Uijtdewilligen (2011)24

Study characteristics

Ages 3–12 years 4–12 years

2–5 years 6–11 years 4–9 years 10–13 years 4–12 years 13–18 years 10–18 years*

13–18 years

12–18 years

14–18 years 13–18 years

Publication period of studies included

1970–98 1999–2005

1980–2007

To 2009 To 2010 To 2010 2004–10 1970–98 1999–2003

1999–2005

To 2009 To 2010 2004–10

Number of quantitative studies included

54 57† 24 41 46† 46† 30† 54 51 57† 60 46† 30†

Endpoints Overall Sitting; overall

Overall Leisure; overall

Leisure; occupation; transport; home

Leisure; occupation; transport; home

Sitting; overall

Overall Leisure; overall

Sitting; overall

Leisure; overall

Leisure; occupation; transport; home

Sitting; overall

Proportion of longitudinal studies included

13 (24)% 6 (11%)† 3 (13%) 8 (20%) 46 (100%) 46 (100%) 30 (100%) 7 (13%) 10 (20%) 6 (11%)† 7 (12%) 46 (100%) 30 (100%)

Accumulated number of review citations for consistent evidence‡

Correlates and determinants

24 38 47 53 54 64 64 35 49 68 76 82 84

Determinants only

0 0 0 0 1 11 11 0 0 0 0 6 8

Demographic and biological variables

Male sex Correlate Correlate Correlate NR Determinant Inconclusive Inconclusive Correlate Correlate Correlate NR Inconclusive Inconclusive

Ethnic origin (white)

Inconclusive Not correlate

Not correlate

NR Inconclusive Inconclusive NR Correlate Correlate Not correlate

NR Not determinant

Determinant

Marital status of parent

Not correlate

Not correlate

NR NR Inconclusive Not determinant

NR NR NR NR NR NR NR

Body-mass index or anthro-pometry

Inconclusive Not correlate

Not correlate

NR Inconclusive Not determinant

NR Not correlate

NR Not correlate

NR Inconclusive Inconclusive

Psychosocial variables

Perceived competence

Inconclusive NR NR NR Inconclusive Inconclusive NR Correlate Correlate NR NR Not determinant

NR

Self-effi cacy Inconclusive Correlate NR NR NR Determinant NR Inconclusive Correlate Correlate NR Determinant NR

Attitude Not correlate

NR NR NR Inconclusive Inconclusive NR NR NR Correlate NR Not determinant

Inconclusive

Perceived behavioural control

NR NR NR NR NR Inconclusive Inconclusive NR NR NR NR Determinant Inconclusive

Value of health and status

NR NR NR NR NR Not determinant

NR Correlate NR NR NR NR NR

Barriers to physical activity

Inverse association

Not correlate

NR NR NR Not determinant

NR Not correlate

Inverse association

NR NR Inconclusive NR

(Continues on next page)

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maintenance of physical activity, but action planning is a determinant of initiation of physical activity.

Environmental correlates Although research into environmental correlates of physical activity began only slightly more than a decade ago, many reports are already available (table 3, appen-dix). A 2011 review of 103 papers42 showed results for children and adolescents. Generally, fi ndings were inconsistent across studies. For both children and adolescents, the most consistent associations were derived from objectively measured environmental vari-ables and reported domain-specifi c physical activity. Objectively measured environ ments might be more accurate, and reported physical activity allowed investi-gators to match environmental attributes with activity domain. The most robust correlates for children were walkability, traffi c speed, and volume (inversely), land-use mix (proximity of homes and destin ations such as shops), residential density, and access or proximity to recreation facilities.42 Land-use mix and residential density were the most robust correlates for adolescents.42

Most information comes from cross-sectional studies in adults, although Van Stralen and colleagues32 confi ned their analysis to longitudinal research designs. In adults, only two of nine reviews identifi ed neighbourhood design aspects, such as walkability (designed so that residents can walk from home to nearby destinations)

and street connectivity (grid-like pattern of streets), as correlates of transport-related activity, with no other consistent correlates of this outcome. Leisure activity was consistently related to transportation environment (eg, pavement and safety of crossings) in two reviews, to aesthetic variables (eg, greenness and rated attractive-ness) in another two, and to proximity to recreation facilities and locations in one review (table 3). Total physical activity was related to environmental variables in all fi ve categories, most convincingly with recreation facilities and locations, transportation environment, and aesthetics (table 3). Essentially no consistent environ-mental correlates of physical activity among older adults were identifi ed (table 3).

Low-income and middle-income countriesWe identifi ed 68 original investigations into correlates from low-income and middle-income countries (appendix). Half the studies are from the past 2 years. Nearly all were done in countries of upper-middle income rather than in those of low income. Many studies were from Brazil (n=39) and China (n=7), together accounting for two-thirds of studies identifi ed.

The most frequently reported categories of correlates are demographic and biological (fi gure 2), of which sex, age, and socioeconomic status are the most consis-tent. As reported in high-income countries, male, young, and wealthy groups are more active than are others.

Children Adolescents

Sallis (2000)16

Van Der Horst (2007)23

Hinkley (2008)26

Edwardson (2010)19

Craggs (2011)20

Craggs (2011)20

Uijtdewilligen (2011)24

Sallis (2000)16

Biddle (2005)25

Van Der Horst (2007)23

Edwardson (2010)19

Craggs (2011)20

Uijtdewilligen (2011)24

(Continued from previous page)

Behavioural variables

Previous physical activity

Correlate NR NR NR NR Determinant Inconclusive Correlate NR NR NR Inconclusive Determinant

Smoking Not correlate

NR NR NR NR Not determinant

NR Inconclusive Inverse association

Not correlate

NR NR NR

Social and cultural variables

Perceived parental role models

NR NR NR NR NR Not determinant

NR NR NR NR Not correlate

NR NR

Parental activity

Inconclusive NR Correlate Not correlate

Inconclusive Not determinant

Inconclusive Not correlate

NR Not correlate

Not correlate

Inconclusive Inconclusive

Support for physical activity

NR NR NR NR NR NR NR NR NR NR NR Determinant NR

Support for physical activity from parents and family

NR Correlate NR NR Inconclusive Not determinant

NR Correlate Correlate Correlate Correlate Inconclusive NR

Only variables with consistent evidence16 for their role as a determinant of physical activity in longitudinal studies are shown. NR=not reported. *Girls only. †Studies of children and adolescents. ‡Three or more original reports cited in review; at least 60% of them show the same association (after Sallis et al16).

Table 1: Systematic reviews of correlates and determinants of physical activity in children and adolescents

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Rhodes (1999)28

Trost (2002)15

Plonczynski (2003)18

Rhodes (2006)29

Kaewthummanukul (2006)30

Allender (2008)31

Van Stralen (2009)32*

Kirk (2011)33

Koeneman (2011)34

Study characteristics

Ages ≥65 years† ≥18 years ≥65 years‡ ≥18 years NR NR ≥40 years; >50 years† 18–64 years ≥55 years

Publication period of studies To 1999 1998–2000 1994–2001 1969–2006 1990–2002 1977–2007 1990–2008 1984–2010 1990–2010

Number of quantitative studies

41 38 16 32 11 19 59 62 30

Endpoints Exercise Leisure; overall

Leisure; overall

Leisure; overall

Leisure; overall Leisure; overall

Initiation; maintenance Leisure Exercise; overall

Proportion of longitudinal studies included

14 (34%) 7 (18%) 1 (6%) 16 (50%) 0 9 (47%) 59 (100%) 11 (18%) 30 (100%)

Accumulated number of review citations for consistent evidence§

Correlates and determinants 13 41 47 53 58 60 80 84 87

Determinants only 0 0 0 0 0 0 20 20 23

Demographic and biological variables

Age Inverse correlate

Inverse correlate

Inconclusive NR Inverse correlate NR Not determinant NR Not determinant

Education Inconclusive Correlate NR NR Inconclusive NR Not determinant NR NR

Male sex Correlate Correlate NR NR Inconclusive NR Not determinant Inconclusive Inconclusive

Income and socioeconomic status

Inconclusive Correlate Correlate NR Inconclusive NR Not determinant NR NR

Marital status NR Inconclusive Inconclusive NR Inconclusive Inconclusive Initiation not determinant; maintenance inconclusive

NR NR

Ethnic origin (white) NR Correlate Inconclusive NR Inconclusive NR Not determinant NR Not determinant

Health status or perceived fi tness

Correlate Correlate Correlate NR Inconclusive Correlate Initiation inconclusive; maintenance determinant

NR Not determinant

Overweight or obesity NR Inverse correlate

NR NR NR NR Initiation inconclusive; maintenance not determinant

NR Inconclusive

Psychosocial variables

Attitudes Correlate Not correlate NR NR Inconclusive NR Initiation inconclusive; maintenance not determinant

NR NR

Intention to exercise Correlate Correlate NR NR Inconclusive NR Initiation determinant; maintenance inconclusive

NR NR

Action planning NR NR NR NR NR NR Initiation determinant; maintenance NR

NR NR

Self-effi cacy Correlate Correlate Correlate NR Correlate NR Initiation determinant; maintenance inconclusive

NR Inconclusive

Stage of change¶ Inconclusive Correlate NR NR Inconclusive NR Determinant NR NR

Stress NR Inconclusive Inconclusive NR Inconclusive NR Initiation NR; maintenance inverse determinant

NR NR

Physical activity characteristics and perceived eff ort

NR Inverse correlate

NR Inverse correlate

NR NR Initiation NR; maintenance not determinant

NR NR

Physical outcome realisations

NR NR NR NR NR NR Initiation NR; maintenance determinant

NR NR

Psychological outcome realisations

NR NR NR NR NR NR Initiation NR; maintenance determinant

NR NR

Behavioural variables

Activity history during adulthood

Inconclusive Correlate NR NR NR NR Determinant NR Inconclusive

Social and cultural variables

Social support from friends and peers

Correlate NR Inconclusive NR NR NR Initiation inconclusive; maintenance not determinant

NR NR

Social norms Not correlate NR NR NR Inconclusive NR Initiation NR; maintenance not determinant

NR NR

Only variables with consistent evidence16 for their role as a determinant of physical activity in longitudinal studies are shown. NR=not reported. *Van Stralen and colleagues consistently reported the endpoints separately and they are mutually exclusive. †Study mean. ‡Women only. §Three or more original reports cited in review; at least 60% of them show the same association (after Sallis et al16). ¶As per the transtheoretical model.

Table 2: Systematic reviews of correlates and determinants of physical activity in adults

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Diff erences exist between cultures—eg, physical activ ity increases with age as people retire in China and some east Asian nations,43 indicating possible country-level patterns in leisure-time and other domains of physical activity. We note a positive association between socio-economic status and physical activity in coun tries of low and middle income, by contrast with the inconsistent or inverse results from high-income countries.

Behavioural variables are the second most studied correlate in countries of low and middle income, mostly in adults and adolescents. The little evidence available shows that previous participation and present physical activity are positively associated. One study established that risk behaviour (eg, drug misuse) and other risk factors (eg, hypertension) had inverse associations with physical activity (appendix).

Very few studies in low-income and middle-income countries have addressed psychological, cognitive, and aff ective variables. Of six that have, only barriers to exercise and depression were consistently inversely associated with physical activity in adults (appendix).

That measures adapted to diff erent cultures and contexts are unavailable could explain why such little research into psychological, cognitive, and aff ective correlates has been done in these countries.

Additionally, social and cultural factors have been infrequently studied. Social support has consistent asso-ci ations with activity, and in adults, family support is positively associated (appendix). The fi nding from high-income countries that parental social support is important for physical activity in young people is not supported by studies in low-income and middle-income countries (appendix).

Environmental correlates of physical activity have been reported in 11 studies in countries of low income and middle income (appendix). None were in children, and only one was in adolescents (appendix). Most reports show associations with perceptions of environ ment rather than with objective measures (appendix). Perceived access to recreation facilities is the most consistent environmental correlate; a positive associ ation with leisure-time, trans-port, and total physical activity was reported in nearly all

Humpel (2002)35

Cunningham (2003)36

Owen (2004)37

Duncan (2005)38*

Wendel-Vos (2007)39

Saelens (2008)40

Van Stralen (2009)32

Panter (2010)21

Van Cauwenberg (2011)41

Study characteristics

Ages Adults Adults Adults NR ≥18 years Adults ≥40 years† 18–65 years Mean >65 years

Publication period of studies included

NR 1966–2002 To 2004 1989–2005 1980–2004 2005–06 1990–2007 1990–2009 2000–2010

Number of quantitative studies included

19 27 18 16 47 29 59 36 31

Proportion of longitudinal studies included

1 (5%) NR 2 (11%) 0 3 (6%) NR 59 (100%)‡ NR 3 (10%)

Report type Systematic review

Systematic review

Systematic review

Meta-analysis

Systematic review

Systematic review and review of reviews

Systematic review

Systematic review

Systematic review

Transport activity outcome

Neighbourhood design Inconclusive NR Inconclusive NR Not correlate Correlate NR Correlate Inconclusive

Transport environment Inconclusive NR Inconclusive NR Inconclusive Inconclusive NR Inconclusive Inconclusive

Social environment NR NR NR NR Not correlate Inconclusive NR NR Inconclusive

Aesthetics NR NR Inconclusive NR Not correlate Inconclusive NR Inconclusive Not correlate

Leisure activity outcome

Recreation facilities and locations

Correlate Inconclusive Inconclusive NR Not correlate Inconclusive NR NR Inconclusive

Transport environment Correlate Inconclusive Inconclusive NR Not correlate Correlate NR NR Inconclusive

Social environment Inconclusive NR NR NR Not correlate Inconclusive NR NR Not correlate

Aesthetics Correlate NR Correlate NR Not correlate Inconclusive NR NR Not correlate

Total physical activity outcome

Neighbourhood design Inconclusive NR Inconclusive Correlate Not correlate Inconclusive Inconclusive NR Inconclusive

Recreation facilities and locations

Correlate Inconclusive Correlate Correlate Correlate Inconclusive Determinant NR Inconclusive

Transport environment Correlate Inconclusive Correlate Correlate Inconclusive Inconclusive Determinant NR Inconclusive

Social environment Inconclusive Inconclusive Inconclusive Not correlate Inconclusive Inconclusive Determinant NR Inconclusive

Aesthetics Correlate Correlate Correlate NR Inconclusive Inconclusive Inconclusive NR Not correlate

Correlate categories with consistent evidence from at least one of the reviews or with a signifi cant association in Duncan et al38 are listed. Categories are adapted from Ding.42 Reviews were included when they had at least one variable with consistent evidence. NR=not reported. *Distinction between inconclusive and not correlate impossible because of the way in which results were presented. †Study mean >50 years. ‡All determinants studies.

Table 3: Systematic reviews of environmental correlates of physical activity in adults

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studies (appendix). Safety from crime and traffi c is not associated with physical activity, although one study did show an inverse association in adults (appendix). Few built-environment and walkability variables have been investigated and results are not consistent (appendix). However, density of exercise facilities and urbanisation (ie, urban versus rural residences) are positively associated with physical activity (appendix).

A broader investigation: from genes to policyGenes, evolution, and obesity as determinantsBesides published reviews of well studied correlates of physical activity, additional correlates and determinants have been investigated (fi gure 1, panels 1–3, appendix). Genetics and genetic profi les could aff ect physical activity in populations (panel 1). Additionally, ideas and data from investigations of evolutionary biology can help to explain the mismatch between the human need for physical activity and an environment that generally discourages such activity (panel 2). Whether physical activity level persists within individuals with time is another area of research. Tracking coeffi cients are high in short periods but lower with time, and attenuates through the lifecourse (appen dix).87 Further research is necessary to establish whether persistence in physical activity behaviour within indiv iduals is a function of the individual (eg, personality or physiology) or environ-mental stability.88

A new idea is that obesity might be a driver of physical inactivity (panel 3). This notion is quite diff erent to the expected causal direction, in which low total physical activity is assumed to lead to obesity through reduced energy expenditure.89 The relation might be bidirectional, and high rates of obesity might be a contributing factor to low total physical activity (panel 3).

Policy correlatesFigure 1 shows high-level factors that aff ect physical activity. Policy is now described in many ecological models.10 Policy interventions can aff ect whole popu-lations for long periods. For the physical activity fi eld, policy provides guidance for collective and individual behaviour and can be informal or formal legislative or regulatory actions taken by governmental or non-governmental organisations.90,91 Policies can aff ect phys-ical activity at local (school or workplace), regional government, or national levels.91,92 They usually require partnerships and actions outside the health sector to improve conditions, support services, and environments that enable physical activity, and are an integral part of national physical activity planning.93 Policies can mandate investments in resources (eg, bike paths, parks, and sports programmes) or develop relevant public health regulations (eg, pavement specifi cations, stair design standards, and payment for physical activity counselling in health care).94

Cross-sectional analyses show that policy is a correlate of physical activity.95–98 For example, Pucher and Buehler95

Panel 1: Genetic determinants of physical activity

Genetics is a possible determinant of physical activity—ie, a heritable component aff ects activity behaviours, not just measures of fi tness. Similar to other behaviours, such as eating (appetite), evidence from human and animal studies44–48 indicates that physical activity is regulated by intrinsic biological processes. Animal studies44,45 suggest that CNS mechanisms might regulate daily physical activity. Twin and family studies have shown that genetic factors contribute to variation in reported daily physical activity levels, with heritability estimates ranging from small (h² <30%)49–52 to moderate (h²=30–65%),53–58 and even high (h²=78%; appendix).59 The large heterogeneity might be due to the large ranges in age within and between studies, the accuracy with which daily physical activity is assessed, and study design.

Substantial individual diff erences have been noted in the acute averse and rewarding eff ects of physical activity, implicating genetic factors.60 Specifi cally, reward systems will be activated in individuals with above-average abilities, those who crave activity, and those who feel rewarded by accomplishing an activity; adverse eff ects will be reported in those who feel pain, fatigue, or even exertion. As such, candidate genes might be part of the reward systems and pain sensation.60 Candidate gene studies have mainly focused on genes that constitute the dopaminergic61–63 and melanocortinergic64,65 pathways. So far, associations between genetic variants in the melanocortin 4 receptor (MC4R),66 the leptin receptor,67–69 the dopamine receptor D2,70 and daily physical activity have been most consistent. Two genome-wide linkage studies56,71 have showed promising linkage with chr2p22-p16 on chr18q,71 a locus harbouring MC4R.56 The most recent and successful gene-discovery framework is genome-wide association studies, but no such investigation into daily physical activity has been done. A fairly small study of exercise participation did not identify any signifi cant genome-wide associations.72

Overall, despite evidence for a genetic contribution, candidate gene and genome-wide studies have not yet identifi ed genetic loci that have robust associations with daily physical activity. Large-scale genome-wide association studies that comprehensively survey the genome will identify new loci, which in turn may point towards new insights into the biology that underlies variation in physical activity.

ChildrenAdolescentAdultOlder

70

60

Num

ber o

f cor

rela

tes 50

40

30

20

10

03

24

40

8

1

6

14

22 2

1

8111

114

Demographicaland biological

Psychologicaland cognitive

Behavioural Social Environmental

Figure 2: Correlates of physical activity identifi ed in countries of low and middle incomeTotal number of correlates divided into fi ve broad categories. More than one correlate could be reported in one study.

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identifi ed policies and environmental supports in Germany, Denmark, and the Netherlands that explain high levels of cycling in those countries. Investigators of a 2011 review96 identifi ed 13 quasiexperimental studies of built-environment changes, and reported that cycling infrastructure, trails, and park upgrades lead to increased physical activity. However, the fi ndings were inconsis-tent, and improved study designs might lead to null results. The eff ect of policy and legislation on physical activity participation in schools is mixed.97,98

Societal-level factors and social norms also aff ect physical activity. Some are acute societal events, such as economic crises, civil unrest, or natural disasters.99 Societal trends probably have diff erent eff ects on physical activity domains. Responses to economic crises might reduce leisure-time activity participation and increase transport-related activity.100 The opposite cir cum stance—ie, economic growth—could be noted in many develop ing countries, with a corresponding change in trends. Additionally, long-term social mores and cultural values could aff ect physical activity patterns in communities and regions. The social value attached to physical activity can vary widely between cultures and change with time. For example, cycling can either be perceived as tiresome and socially undesirable or can become normative and even fashionable.95 There is some evidence for the interaction between social values and other determinants of physical activity, but

interventions to change social norms could be an eff ective way to change physical activity.101 International sporting competition and large events are often advocated to enhance physical activity, but the evidence for any measurable eff ects on population physical activity is scarce.102

To show that global factors are correlates is diffi cult, but the pervasive forces of urbanisation, mechanisation, and changes in transportation patterns probably aff ect total physical activity. Both increased affl uence and geographical shifts to megacities reduce so-called active living in countries of low and middle income.103,104 Changes to work patterns, with an increase in sedentary occupations in most countries, have also contributed to total physical activity reductions.80

DiscussionResearch into physical activity correlates is an evolving fi eld showing that the aetiology of physical activity is complex and varies by domains, such as leisure time and transport. In the past two decades, an expansion has occurred in the number and type of factors examined as correlates and determinants, moving beyond individual factors and adopting multilevel ecological models.10 These approaches draw attention to the fact that there are several levels of infl uence across a wide range of age and geographical groups, including those in countries of low

Panel 2: From evolutionary biology to societal determinants

An evolutionary perspective assumes that many components of our physiology are adapted to a range of expected behaviour. Is there evidence that people became physically active out of necessity and biological adaptation, and then had to reduce activity because of mechanisation and culturally and technologically induced decreases in the need for energy expenditure?

Physical activity level can be calculated as the ratio of total energy expenditure to basal metabolic rate. Ancestral foragers—of larger body size on average than are contemporary foragers—had estimated mean physical activity levels of roughly 1·7 (range 1·5–2·1),73 which is little diff erent from those in industrialised populations with moderate activity levels.74 Non-human primates do less activity than do human beings (1·2–1·5),75 suggesting that our species adapted to increased physical activity for foraging. Subsistence farmers have variable levels of activity, with a mean of about 1·9 in men and 1·8 in women, but ranging up to roughly 2·5.76 However, in urban populations, the most sedentary individuals do little activity (about 1·5).77 Overall, people could be encouraged to achieve levels of about 1·75, as was recommended by WHO and the Food and Agriculture Organisation for health in 2004,78 but this value is much higher than is that of sedentary populations.77

Panel 3: Is obesity a determinant of physical activity?

The notion that physical activity is a key determinant of body fat in individuals and populations is common, seemingly supported by the logic of the energy-balance equation and empirical reports of cross-sectional associations between adiposity and activity.79 On this basis, clinicians assume that physical activity will induce weight loss in overweight individuals, but secular declines are also judged a key driving factor in the worldwide obesity epidemic.80,81 However, in the past decade, studies have begun to challenge both these assumptions, suggesting instead that adiposity could be a determinant of physical activity. In several longitudinal studies,82,83 baseline activity did not predict follow-up adiposity, whereas baseline adiposity predicted follow-up activity. Promotion of physical activity has little eff ect on prevention of obesity in children, adolescents, or adults.84 Although long-term trends in mechanisation and transport, and equivalent behaviours such as rural–urban migration, could reduce activity and hence cause weight gain,85 whether substantial reductions in physical activity in industrialised populations have occurred since the 1980s is a matter of debate.86 Conversely, some believe that real decreases in total physical activity have occurred,80 which indicates a possible role of physical activity in obesity prevention. Clearly, further work is needed, but evidence does suggest that increasing obesity could be a contributor to high levels of inactivity in human populations.

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and middle income. Evidence for demographic and genetic correlates could identify subgroups that need intensive intervention. Research into psychological, inter personal, and environmental correlates can identify new potential mediators for use in interventions8—ie, programmes aff ecting these correlates would be expected to lead to changes in physical activity behaviour. Targeting evidence-based mediators in interventions is a crucial step in improvement of the eff ectiveness of physical activity interventions.

Thus, the purpose of the study of correlates is linked to improvement in intervention development.7 This linkage is infrequently made explicit, and correlates studies remain as stand-alone hypothesis-generating research, typically in small, non-representative samples, with sub-optimal measures of both exposures and physical activity. Furthermore, fairly few consistent correlates of physical activity have been identifi ed, suggesting that intervention approaches targeting unsupported media-tors (ie, know ledge or attitudes) could be ineff ective. Our review has identifi ed a small number of variables as consistent correlates. They include: reported health and intention to exercise in adults; male sex, self-effi cacy and previous physical activity at all ages; and family social support in adolescents.

The new area of environmental correlates research shows that few consistent correlates have been identifi ed for specifi c domains of transport and leisure activity. However, reviews of adults have identifi ed consistent correlates with total physical activity in four of fi ve categories of environmental attributes. The strongest fi ndings were with recreation facilities and locations, transportation environments, and aesthetics. A compre-hensive review of young people supported neighbourhood design, recreation facilities and locations, and trans-portation environment as consistent correlates. Environ-ment correlates have not been extensively studied in older adults. Environ mental changes can be achieved through population-wide changes to policy. Because these policy decisions are made outside the health sector, cross-sectoral partnerships are needed to infl uence physical environments in countries at all levels of dev-elop ment to make them more supportive of physical activity behaviours.91,92

A limitation of the correlates literature is that most studies have used a cross-sectional design.8 Nonetheless, these studies have some advantages. They provide evi-dence about potential mediators for planning of inter-ventions and help to prioritise population target groups. Cross-sectional studies allow several variables to be

Panel 4: The next steps

Future research needs improved measures of exposure (correlates), objective physical activity measures, prospective designs, and advanced data modelling to assess causal determinants rather than just associations between variables. For this fi eld to become more useful in designing interventions than it is presently, we draw attention to a few areas of potential improvement.

Standardised comparisons of correlates are needed, with similar measures in high-income and low-income countries, that take into account strengths of diff erent correlates and an investigation of cultural and country-level factors. Increased research emphasis is suggested for physical activity correlates research in countries of low and middle income, and in special populations, socially disadvantaged groups, and obese individuals. Building research capacity might be needed to achieve these goals.

An understanding of environmental correlates of transport and leisure-time activity in low-income and middle-income countries is urgently needed to support the development of interventions to reverse the rapidly changing determinants of inactivity occurring through urbanisation, passive entertainment, and motorised transport. Multilevel models to explain all domains of physical activity (transport, leisure, occupation, home) will lead to improved, contextually tailored interventions.

The potential of ecological approaches in correlates research has not been fully realised, although there is good evidence that variables at all ecological levels are signifi cantly related to

physical activity.8 Interactions across levels are a principle of ecological models—eg, the combination of favourable psychosocial and environmental variables should improve prediction of high physical activity, but they are infrequently assessed. Such fi ndings are becoming available,107,108 supporting multilevel interventions.

New methods to analyse mediators of physical activity interventions are accumulating. Possible mechanisms of change are measured repeatedly to establish whether they account for recorded intervention eff ects on outcomes.108 A review of early studies of mediators109 had inconsistent results, so improved measures and studies are needed.105,106 New areas, such as behavioural economics can also provide conceptual foundations for experimental studies of physical activity determinants.110

In addition to the ecological model previously described, new and innovative categories of correlates should be sought (panels 1–3). A growing area of study is brain mechanisms of physical activity.111 Reductions in dopamine receptors contribute to the age-related fall in physical activity,112 and strong evidence has been reported that the brain continually adjusts power output of muscles during exercise to limit exertion to safe levels.113 Finally, further cross-sectional studies in high-income countries are unlikely to be informative. A change in research could lead to scientifi c progress and increased relevance for design of physical activity interventions.

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assessed at low cost, providing an evidence base for improvement of intervention design.7 A limitation is that most research has reported leisure-time activity, which could provide a small window on total physical activity. Self-report of correlates is a methodological concern, and consistency of data across measures and settings is needed to strengthen evidence for a specifi c correlate. Reporting biases might diff er between cul-tures, so creative investi gations are needed to under-stand these variables.

A next step to verify the causal role of consistent correlates is to examine them in intervention trials and in generalisable samples. For more defi nitive under-standing of why people are active, longitudinal deter-minants research is needed into what predicts changes in physical activity.32,34 This research will need improved methods, including use of multilevel theories of change, tests of causal pathways of mediator variables, and more robust statistical assessment of the several levels of infl uence on physical activity. This work has started to accumulate, with summary reviews of mediators of physical activity now reported for adults and children.105,106

One new area in this review is the study of corre lates and determinants in countries of low and middle income. This evidence is increasing rapidly and strength ens the call for correlates research across domains of physical activity and with time. Inter nation ally, researchers need to investigate why residents of some countries are more physically active than are those residing in demographically similar countries. The study of developing countries emphasises potential diff erences in correlates between domains of physical activity. For example, active trans-portation could be normal for poor people in low-income and middle-income countries, and as affl uence increases, active transportation decreases. A diff erent socio economic gradient might be apparent in high-income countries, where leisure-time activity pre dominates and social class and physical activity are directly related.

In summary, the study of correlates is well advanced and can provide an evidence base for the improvement of inter ventions, but the fi eld has room for improvement. This con tradiction comes about because many corre-lates re ports are published each year, but many identify similar—usually psychosocial and environmental—corre lates in cross-sectional samples. Furthermore, true multi level studies are needed, as are studies targeting subgroups at risk of low activity levels. Innovative frameworks for cor relates research—eg, consideration of genetic, evolution ary, societal, and macroeconomic factors, and improved designs and statistical methods—could contribute to the next generation of correlates research (panel 4). Addition ally, correlates should be included in public health surveillance systems, such as in the Physical Activity Monitor in Canada.114 The greatest challenge for this fi eld will be translation of research into public health action.

ContributorsAll authors devised and developed the approach, with detailed discussions and meetings at all phases, and read and commented on every version of the report. AEB is guarantor, and did searches and reviews, synthesised data, and led the writing of the report. RSR and BWM did detailed searches and syntheses of systematic reviews, and edited drafts. JFS reviewed all content and all drafts, and worked especially on fi gure 1 and the ecological model. JCW wrote the obesity and evolution panels, and commented on and edited drafts. RJFL wrote the genetics section, and commented on and edited drafts.

Lancet Physical Activity Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk, Harold W Kohl 3rd, Estelle Victoria Lambert, I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of interest We declare that we have no confl icts of interest.

AcknowledgmentsWe thank Ding Ding, Rona Macniven, Klaus Gebel, Adriano Akira Hino, Cassiano Ricardo Rech, Miriam Wanner, Claudia Frick, and Michèle Geissbühler for research assistance.

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57 Carlsson S, Andersson T, Lichtenstein P, Michaelsson K, Ahlbom A. Genetic eff ects on physical activity: results from the Swedish Twin Registry. Med Sci Sports Exerc 2006; 38: 1396–401.

58 Aaltonen S, Ortega-Alonso A, Kujala UM, Kaprio J. A longitudinal study on genetic and environmental infl uences on leisure time physical activity in the Finnish Twin Cohort. Twin Res Hum Genet 2010; 13: 475–81.

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59 Joosen AM, Gielen M, Vlietinck R, Westerterp KR. Genetic analysis of physical activity in twins. Am J Clin Nutr 2005; 82: 1253–59.

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63 Baik JH, Picetti R, Saiardi A, et al. Parkinsonian-like locomotor impairment in mice lacking dopamine D2 receptors. Nature 1995; 377: 424–28.

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65 Marie L, Miura GI, Marsh DJ, Yagaloff K, Palmiter RD. A metabolic defect promotes obesity in mice lacking melanocortin-4 receptors. Proc Natl Acad USA 2000; 97: 12339–44.

66 Loos RJF, Rankinen T, Tremblay A, Perusse L, Chagnon Y, Bouchard C. Melanocortin-4 receptor gene and physical activity in the Quebec Family Study. Int J Obes (Lond) 2004; 29: 420–28.

67 Farooqi IS, Jebb SA, Langmack G, et al. Eff ects of recombinant leptin therapy in a child with congenital leptin defi ciency. N Engl J Med 1999; 341: 879–84.

68 Licinio J, Caglayan S, Ozata M, et al. Phenotypic eff ects of leptin replacement on morbid obesity, diabetes mellitus, hypogonadism, and behavior in leptin-defi cient adults. Proc Natl Acad USA 2004; 101: 4531–36.

69 Stefan N, Vozarova B, Del Parigi A, et al. The Gln223Arg polymorphism of the leptin receptor in Pima Indians: infl uence on energy expenditure, physical activity and lipid metabolism. Int J Obes Relat Metab Disord 2002; 26: 1629–32.

70 Simonen RL, Rankinen T, Perusse L, et al. A dopamine D2 receptor gene polymorphism and physical activity in two family studies. Physiol Behav 2003; 78: 751–57.

71 Simonen RL, Rankinen T, Perusse L, et al. Genome-wide linkage scan for physical activity levels in the Quebec Family study. Med Sci Sports Exerc 2003; 35: 1355–59.

72 De Moor MH, Liu YJ, Boomsma DI, et al. Genome-wide association study of exercise behavior in Dutch and American adults. Med Sci Sports Exerc 2009; 41: 1887–95.

73 Malina RM, Little BB. Physical activity: the present in the context of the past. Am J Hum Biol 2008; 20: 373–91.

74 Black AE, Coward WA, Cole TJ, Prentice AM. Human energy expenditure in affl uent societies: an analysis of 574 doubly-labelled water measurements. Eur J Clin Nutr 1996; 50: 72–92.

75 Leonard WR, Roberston ML. Nutritional requirements and human evolution: a bioenergetics model. Am J Hum Biol 1992; 4: 179–95.

76 Dufour DL, Piperata BA. Energy expenditure among farmers in developing countries: what do we know? Am J Hum Biol 2008; 20: 249–58.

77 Erlichman J, Kerbey A, James P. Are current physical activity guidelines adequate to prevent unhealthy weight gain? A scientifi c appraisal for consideration by an Expert Panel of the International Obesity Task Force (IOTF). London: International Obesity Task Force, 2001.

78 Food and Agricultural Organization, WHO, UN University Expert consultation. Report on human energy requirements. Rome: FAO, 2004.

79 Ness AR, Leary SD, Mattocks C, et al. Objectively measured physical activity and fat mass in a large cohort of children. PLoS Med 2007; 4: e97.

80 Church TS, Thomas DM, Tudor-Locke C, et al. Trends over 5 decades in US occupation-related physical activity and their associations with obesity. PLoS One 2011; 6: e19657.

81 Prentice AM, Jebb SA. Obesity in Britain: gluttony or sloth? BMJ 1995; 311: 437–39.

82 Ekelund U, Brage S, Besson H, Sharp S, Wareham NJ. Time spent being sedentary and weight gain in healthy adults: reverse or bidirectional causality? Am J Clin Nutr 2008; 88: 612–17.

83 Metcalf BS, Hosking J, Jeff ery AN, Voss LD, Henley W, Wilkin TJ. Fatness leads to inactivity, but inactivity does not lead to fatness: a longitudinal study in children. Arch Dis Child 2011; 96: 942–47.

84 Wilks DC, Besson H, Lindroos AK, Ekelund U. Objectively measured physical activity and obesity prevention in children, adolescents and adults: a systematic review of prospective studies. Obes Rev 2011; 12: e119–29.

85 Cook I, Alberts M, Lambert EV. Relationship between adiposity and pedometer-assessed ambulatory activity in adult, rural African women. Int J Obes (Lond) 2008; 32: 1327–30.

86 Westerterp KR, Speakman JR. Physical activity energy expenditure has not declined since the 1980s and matches energy expenditures of wild mammals. Int J Obes (Lond) 2008; 32: 1256–63.

87 Telama R. Tracking of physical activity from childhood to adulthood: a review. Obes Facts 2009; 2: 187–95.

88 Fortier MD, Katzmarzyk PT, Malina RM, Bouchard C. Seven-year stability of physical activity and musculoskeletal fi tness in the Canadian population. Med Sci Sports Exerc 2001; 33: 1905–11.

89 Bauman A, Allman-Farinelli M, Huxley R, James WPT. Leisure-time physical activity alone may not be a suffi cient public health approach to prevent obesity—a focus on China. Obes Rev 2008; 9 (suppl 1): 119–26.

90 Brownson RC, Baker EA, Houseman RA, Brennan LK, Bacak SJ. Environmental and policy determinants of physical activity in the United States. Am J Public Health 2001; 91: 1995–2003.

91 Bellew B, Bauman A, Martin B, Bull F, Matsudo V. Public policy actions needed to promote physical activity. Curr Cardiovasc Risk Rep 2011; 5: 340–49.

92 WHO Global strategy on diet, physical activity and health. May, 2004. http://www.who.int/dietphysicalactivity/en/ (accessed June 28, 2012).

93 Daugbjerg S, Kahlmeier S, Racioppi F, et al. Promotion of physical activity in the European region: content analysis of 27 national policy documents. J Phys Act Health 2009; 6: 905–17.

94 Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. An ecological approach to creating more physically active communities. Annu Rev Public Health 2006; 27: 297–322.

95 Pucher J, Buehler R. Making cycling irresistible: lessons from the Netherlands, Denmark and Germany. Transport Rev 2008; 28: 495–528.

96 McCormack GR, Shiell A. In search of causality: a systematic review of the relationship between the built environment and physical activity among adults. Int J Behav Nutr Phys Act 2011; 8: 125.

97 Kelder SH, Springer AS, Barroso CS, et al. Implementation of Texas Senate Bill 19 to increase physical activity in elementary schools. J Public Health Policy 2009; 30 (suppl 1): S221–47.

98 Belansky ES, Cutforth N, Delong E, et al. Early impact of the federally mandated local wellness policy on physical activity in rural, low-income elementary schools in Colorado. J Public Health Policy 2009; 30 (suppl 1): S141–60.

99 Franco M, Orduñez P, Caballero B, et al. Impact of energy intake, physical activity, and population-wide weight loss on cardiovascular disease and diabetes mortality in Cuba, 1980–2005. Am J Epidemiol 2007; 166: 1374–80.

100 Hou N, Popkin BM, Jacobs DR Jr, et al. Longitudinal trends in gasoline price and physical activity: the CARDIA study. Prev Med 2011; 52: 365–69.

101 Bauman A, Chau J. The role of media in promoting physical activity. J Phys Act Health 2009; 6 (suppl 2): S196–210.

102 Murphy N, Bauman A. Mass sporting and physical activity events—are they “bread and circuses” or public health interventions to increase population levels of physical activity. J Phys Act Health 2007; 4: 193–202.

103 Yadav K, Krishnan A. Changing patterns of diet, physical activity and obesity among urban, rural and slum populations in north India. Obes Rev 2008; 9: 400–08.

104 Dans A, Ng N, Varghese C, et al. The rise of chronic non-communicable diseases in southeast Asia: time for action. Lancet 2011; 377: 680–89.

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105 Rhodes RE, Pfaeffl i LA. Mediators of physical activity behaviour change among adult non-clinical populations: a review update. Int J Behav Nutr Phys Act 2010; 7: 37.

106 Lubans DR, Foster C, Biddle SJH. A review of mediators of behavior in interventions to promote physical activity among children and adolescents. Prev Med 2008; 47: 463–70.

107 Saelens BE, Sallis JF, Frank LD, et al. Neighborhood environmental and psychosocial correlates of adults’ physical activity. Med Sci Sports Exerc 2012; 44: 637–46.

108 Carlson JA, Sallis JF, Conway TL, et al. Interactions between psychosocial and built environment factors in explaining older adults’ physical activity. Prev Med 2012; 54: 68–73.

109 Lewis BA, Marcus BH, Pate RR, Dunn AL. Psychosocial mediators of physical activity behavior among adults and children. Am J Prev Med 2002; 23 (suppl 1): 26–35.

110 Epstein LH, Saelens BE. Behavioral economics of obesity: food intake and energy expenditure. In: Bickel WK, Vuchinich RE, Vuchinich RE, eds. Reframing health behavior change with behavioral economics. Mahwah, NJ: Erlbaum: 2000: 295–314.

111 Dishman RK. Introduction: exercise, brain, and behavior. Med Sci Sports Exerc 1997; 29: 37–38.

112 Ingram DK. Age-related decline in physical activity: generalization to nonhumans. Med Sci Sports Exerc 2000; 32: 1623–29.

113 Noakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: a novel model of integrative central neural regulation of eff ort and fatigue during exercise in humans: summary and conclusions. Br J Sports Med 2005; 39: 120–24.

114 Kohl HW 3rd, Craig CL, Lambert EV, et al, for the Lancet Physical Activity Series Working Group. The pandemic of physical inactivity: global action for public health. Lancet 2012; published online July 18. DOI:10.1016/S0140-6736(12)60898-8.

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Lancet 2012; 380: 272–81

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)60816-2

This is the third in a Series of fi ve papers about physical activity

*Members listed at end of paper

University of Tennessee at Chattanooga and University of Tennessee College of Medicine,

Chattanooga, TN, USA (Prof G W Heath DHSc);

Prevention Research Center in St Louis, Brown School of Social Work and School of

Medicine Division of Public Health Sciences, Washington

University in St Louis, St Louis, MO, USA (D C Parra MPH,

Prof R C Brownson PhD); School of Medicine (O L Sarmiento MD)

and Department of Industrial Engineering (F Montes MSc),

Universidad de los Andes,

Physical Activity 3

Evidence-based intervention in physical activity: lessons from around the worldGregory W Heath, Diana C Parra, Olga L Sarmiento, Lars Bo Andersen, Neville Owen, Shifalika Goenka, Felipe Montes, Ross C Brownson, for the Lancet Physical Activity Series Working Group*

Promotion of physical activity is a priority for health agencies. We searched for reviews of physical activity interventions, published between 2000 and 2011, and identifi ed eff ective, promising, or emerging interventions from around the world. The informational approaches of community-wide and mass media campaigns, and short physical activity messages targeting key community sites are recommended. Behavioural and social approaches are eff ective, introducing social support for physical activity within communities and worksites, and school-based strategies that encompass physical education, classroom activities, after-school sports, and active transport. Recommended environmental and policy approaches include creation and improvement of access to places for physical activity with informational outreach activities, community-scale and street-scale urban design and land use, active transport policy and practices, and community-wide policies and planning. Thus, many approaches lead to acceptable increases in physical activity among people of various ages, and from diff erent social groups, countries, and communities.

Importance of physical activity promotionScientifi c guidelines issued by various international bodies, national centres and institutes, and professional organisations have documented that regular physical activity protects against coronary heart disease, type 2 diabetes, some cancers, hypertension, obesity, clinical depression, and other chronic disorders.1–5 These fi ndings have been reiterated in Lee and colleagues’ systematic review of the evidence.6 Therefore, the substantial potential benefi ts of promotion of physical

activity for whole populations and at-risk individuals have become a well established agenda for public health agencies and all types of health-care delivery systems worldwide.7

Historically, the primary roles for public health agencies and non-governmental organisations at the international, national, state, and local levels have been to monitor, protect, and promote the public’s health.8 These functions have been intended to complement contributions of health-care delivery systems and other community sectors to establish eff ective prevention, control, and manage -ment of diseases and chronic disorders.9 In the past three decades, the focus of public health has expanded to include initiatives to introduce inter ventions for injury prevention and control, chronic disease prevention and management, health-promoting public policies, environ-mental supports for behavioural change, and broad-reach interventions through health communication and media.10 Interventions to increase physical activity in whole populations are now promin ent in initiatives, with community-based infor mational, behavioural, social, policy, and environmental ap proaches.11,12

Physical activity behaviours are aff ected by factors operating at several levels, which are broadly perceived as personal (such as biological and psychological attributes), social (family, affi liation group, and work factors), and environmental (contexts for diff erent forms of physical activity and policy factors that could determine availability of relevant settings and opportunities).13,14 Thus, inter-sectoral approaches that operate at various levels seem to be the most successful ways to increase physical activity.15

Community-based health promotion—ie, encourage-ment of physical activity at national, state or regional, and local levels—can be successful and has greatest reach only through intersectoral collaboration.16–18 To plan, promote, and coordinate eff orts to increase

Key messages

• Initiatives to promote physical activity can have increased eff ectiveness when health agencies form partnerships and coordinate eff orts with several other organisations: schools; businesses; policy, advocacy, nutrition, recreation, planning, and transport agencies; and health-care organisations

• Eff ective public communication and informational approaches promoting physical activity include community-wide campaigns, mass media campaigns, and decision prompts encouraging the use of stairs versus lifts and escalators

• Initiatives to increase social support for physical activity within communities, specifi c neighbourhoods, and worksites can eff ectively promote physical activity

• Comprehensive school-based strategies encompassing physical education, classroom activities, after-school sports, and active transport can increase physical activity in young people

• Environmental and policy approaches can create or enhance access to places for physical activity with outreach activities; infrastructural initiatives through urban design of land use and planning at community and street scales and active transport policy and practices are eff ective

• To properly support initiatives for the promotion of physical activity, workforces need to be trained in physical activity and health, core public health disciplines, and methods of intersectoral collaboration

• Although individuals need to be informed and motivated to adopt physical activity, the public health priority should be to ensure that environments are safe and supportive of health and wellbeing

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CEIBA Complex Systems Research Center, Bogotá, Colombia; Centre for Research in Childhood Health, Institute of Sports Science and Clinical Biomechanics, University of Southern Denmark Odense, Denmark (Prof L B Andersen Dr Med Sci); Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway (Prof L B Andersen); Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia (Prof N Owen PhD); The University of Queensland, Cancer Prevention Research Centre, School of Population Health, Brisbane, QLD, Australia (Prof N Owen); and Indian Institute of Public Health, Public Health Foundation of India, New Delhi, Delhi, India (S Goenka PhD)

Correspondence to:Prof Gregory W Heath, 928 Oak Street, Chattanooga, TN 37403, [email protected]

physical activity,19 public health agencies especially need to form partnerships with several community organisations: schools; businesses; policy, advocacy, nutrition, recreation, planning, and transport agencies; and health-care organisations.20 In these eff orts, public health agencies should ensure that strategies to reduce health inequities in physical activity are implemented, should monitor the eff ectiveness and reach of inter-ventions, and need to report routine assessments of the programmes to relevant stakeholders and partners.21

Search strategy and selection criteriaHere, we summarise representative evidence-based phys-ical activity interventions from throughout the world that are linked to a broad understanding of health promotion and disease prevention at the national, state and regional, and local levels. We did a systematic review of reviews to assess the present evidence. We searched the Database of Abstracts of Reviews of Eff ects (DARE), the Cochrane library, TRIP, PubMed (Medline), the American Psycho-logical Association, National Guidelines Clearing house, and the System for Information on Grey Literature in Europe (SIGLE; OpenGrey) for systematic reviews of physical activity interventions in any language. The search was limited to reviews published between Jan 1, 2001, and July 31, 2011 (PubMed search was between Jan 1, 2000, and Dec 31, 2011). Search keywords were “physical activity”, “interventions”, “systematic review”, “meta analysis”, and “adults”. The total number of merged records in all datasets was 1547, of which 100 reviews met the criteria for inclusion. These reviews were abstracted and summarised. We under took further examination of internationally represented evidence-based programmes to supplement the search. The table shows characteristics of reviewed studies.

Additionally, the eff ect-size estimates (mean net per-centage change calculated with data from our review of

reviews) provided the opportunity to separate out estimates for several diff erent settings (eg, workplaces), populations (eg, older adults ), or intervention types (eg, behavioural ap proaches; fi gure). Although some esti-mates of eff ect size are small (0·16 for computer-tailored interventions), others are moderate (eg, after-school programmes; fi gure). Overall, these data show that specifi c interventions consistently have modest to sub-stantial eff ects on physical activity behaviour.

We used previous work34,35 to divide evidence-based intervention strategies into categories of varying eff ective-ness with the criteria from the systematic reviews. The fi rst is interventions to promote physical activity; they have been collectively and systematically reviewed to assess their eff ectiveness. Second, promising practices from recommended interventions were iden tifi ed that either singly or collectively have shown some eff ective-ness but do not adhere completely to the evidence-based criteria used in reviews. Third, emerging intervention strategies have been assessed, peer-reviewed, and reported, but are so new that they have not yet been incorporated into systematic evidence reviews.

We classifi ed intervention strategies according to domains established by the guide to community pre-ventive services.36 These domains are used because they conveniently capture most physical activity intervention strategies delivered throughout the world and consist of descriptors that are also in other international recom-mendation documents.1,2,5 Campaigns and informational approaches—ie, strategies to change knowledge, attitudes, and behaviour within a com munity—to promotion of physical activity form one domain. Another is that behavioural and social approaches aim to teach people behavioural management skills that are necessary for successful adoption and maintenance of behaviour change, and to create organisational and social environ-ments that enable and enhance change. A third is that

Number of reviews

Type of reviews Median year of publication (range)

Countries in which included studies were done Number of studies of minorities and populations of low socioeconomic status

School 5 3 narrative; 1 review of reviews; 1 meta-analysis

2011 (2009–11) USA, France, Norway, Belgium, Germany, Greece, Australia, Russia, England, Canada, Brazil, Iran, Denmark, Sweden, and Spain

2

Workplace 5 4 narrative; 1 meta-analysis 2005 (2002–10) USA, Australia, New Zealand, Finland, Spain, England, Belgium, Norway, and Canada

Not specifi ed

Community 14 12 narrative; 1 review of reviews; 1 meta-analysis

2008 (2002–11) England, Scotland, Wales, USA, Australia, Switzerland, Finland, Germany, Canada, Belgium, Brazil, Netherlands, Russia, China, Denmark, Chile, Colombia, Cyprus, Philippines, Iran, Pakistan, and Norway

8

Clinical or primary care

18 17 narrative; 1 meta-analysis 2005 (2000–10) USA, Australia, New Zealand, England, Canada, Sweden, Finland, South Korea, Spain, Austria, China, Croatia, Italy, France, Netherlands, Norway, Japan, and Belgium

5

Several settings

58 40 narrative; 3 reviews of reviews; 15 meta-analyses

2008 (2001–11) USA, England, Scotland, Wales, Sweden, Australia, Belgium, Canada, Denmark, Netherlands, Germany, Norway, Finland, Ireland, Switzerland, Greece, France, Spain, South Korea, New Zealand, North Korea, Japan, and Colombia

27

Total 100 76 narrative; 5 reviews of reviews; 19 meta-analyses

·· ·· 42

Table: Characteristics of reviewed studies by setting and target group

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environmental and policy approaches are designed to structure physical and organisational environments so that people have accessible, safe, attractive, and convenient places to be physically active.

With Roux and colleagues’ criteria,37 we selected strat-egies for inclusion here on the basis of several criteria: recommended by the original review; repre sented at least one of the three intervention domains; studied in children, adolescents, or adults without established disease; intervention lasted 3 months or longer; had a detailed study protocol; and had a measure for physical activity outcomes.

Campaigns and informational approachesA recommended strategy within this domain is use of community-wide campaigns (appendix),36 such as the Stanford heart disease prevention pro gramme38 and the Wheeling Walks intervention.39 These campaigns repre-sent large-scale, high-intensity, high-visibility pro gram-ming and often use television, radio, newspapers, and other media to raise awareness, disseminate targeted health messages to specifi c segments of the population (ie, segmented messages), and reinforce behaviour change. This strategy often uses multicomponent, multi sector, and multisite inter ventions. These interventions are directed mainly to specifi c populations in com munities in countries of middle to high income.36 By contrast, reviews that have not included observational studies or investigations with insuffi cient evidence (not necessarily ineff ective) have shown that evidence in support of community-wide

interventions is inconsistent, especially in communities in countries of low to middle income.40,41

Mass media campaigns can lead to change, especially when they are linked to specifi c community programmes. Although initially categorised as having insuffi cient evidence,36 this type of intervention has emerged as a promising public health practice.42,43 The VERB cam-paign44 targeted so-called tweens (ie, young people aged 9–13 years) in communities throughout the USA with mass media eff orts, internet links, and community events and programmes designed to increase and maintain physical activity. It was characterised by the use of several media, segmented messages, and links to community programming, and eff ectively increased physical activity of young adolescents.45

One emerging practice is delivery of short infor-mational, instructional, and motivational messages about physical activity at key community sites. This approach has been used mainly in communities in Latin America,41 and is based on short educational and motivational messages related to physical activity that are delivered regularly (from daily to three times per week) to the target population. It was developed in Brazil and focuses on key community sites, such as workplaces, centres for senior citizens, and community centres.46 It is distinct from mass media campaigns because the messaging is site-specifi c and is often delivered by a health educator or communicator.46

Point-of-decision prompts are single-component inter-ventions designed to remind and motivate people to use

Effec

t size

Computer tailo

red22

Self-efficacy (a

dults)23

Healthy adults

25

Workplace26

Older adults

27 *

Behavioural change

(adults)28

Website deliv

ered

(adults)29

After sc

hool (child

ren

and adolescents)

30

Obese population3

1

Pedometers32

Distance in

terventions

(adults)33 †

1·0

0

0·16 0·16 0·16

0·19

0·21 0·260·32

0·440·44 0·44

0·68

0·2

–0·2

–0·4

0·4

0·6

0·8

Physical acti

tivty

counsellin

g (health

care)2

4

Figure: Mean eff ect-size estimates from original systematic reviewsAll are mean eff ect size and 95% CIs, unless otherwise indicated. *Index. †Range.

See Online for appendix

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stairs in buildings instead of the lift or escalator to ascend or descend to another fl oor.36 This strategy is supported by suffi cient evidence and has been successful when population-specifi c signage has been used in various settings (eg, transport stations, worksites, hospitals, universities, and shopping centres) and access to stairs has been improved.36,47–49

Behavioural and social approachesIndividually adapted programmes to change health behaviour are characterised by a multicomponent intervention approach, and aim to have participants incorporate physical activity into their daily routines.36 Goal setting, social support, and behavioural rein-forcement through self-reward, structured problem solving, and relapse prevention are examples of this type of intervention.36 Such programmes can be delivered in group settings or by email, internet, mail, or telephone, or by all four means. Interventions that are focused on the individual usually consist of an assessment of a participant’s physical activity and readiness to change, a tailored activity plan, and identifi cation of community interventions through a centralised health provider or promoter.50 This approach, which focuses on lifestyle physical activity, is cost-eff ective when compared with supervised physical activity programmes.51

Social support in community settings is an example of a strategy that capitalises on social networks to rein-force physical activity behaviour. Behavioural and social approaches include creation of buddy systems, behavioural contracts between the participant and programme leaders, and formation of walking or other physical activity support groups.24 For example, Kriska and colleagues52 organised women in Pittsburgh, PA, USA, into walking clubs within their neighbourhoods and sent communi cations (eg, newsletters and phone prompts) designed to reinforce and sustain the walking networks. Similarly, Lombard and co-workers53 organised walking partners and small groups in communities in the state of Virginia, USA. They provided initial training about walking and behavioural principles, neighbour hood maps, and other supports. Phone networks and regular prompts and updates were used to reinforce behaviours and provide opportunities for participants to ask questions.

Community settings can be worksites, community centres, health facilities, and parks and recreational facilities. Jeff rey and colleagues54 used personal trainers in a community centre in Minneapolis, MN, USA, behaviour-based sessions, phone follow-up, and fi nancial incentives to reinforce physical activity behaviours. With so-called community coaches such as personal trainers for assessment of and counselling for physical activity, these interventions are most often classifi ed as clinical. However, this approach is relevant to the public health sector, because many public health agencies continue to deliver primary health care.55

Provider-based physical activity counselling has under-gone systematic review, and suffi cient evidence is still not available to allow its recommendation as a single-component intervention.56 However, this approach has promising results when integrated into existing com-munity eff orts.57 Patrick and colleagues’ review57 cited sources such as evidence reviews from the US Preventive Services Task Force, the Cochrane Collaboration, and the UK National Institute for Health and Clinical Excellence (NICE), as well as published medical and psychological reports and other relevant sources. Others have recorded that evidence for health-care provider assessment and counselling of patients for promotion of physical activity is mixed; brief stand-alone counselling by providers is not eff ective, but offi ce-based screening and advice followed by telephone or community support for physical activity does sustain long-term improvements in physical activity behaviour in patients.58 Thus, models of health-care-provider delivery that emphasise coordin ation with clinical and community resources could be the best possible way to promote physical activity in patients.59

Community physical activity classes are promising.41 These programmes off er fi tness instruction and aerobics classes at no charge to participants and often take place in public places (eg, parks, school yards, community centres, worksites, and common sports facilities). Programmes such as these ones provide social support, are of particular importance in places with few recre-ational public parks, and are relevant for underserved populations (women, older adults, and individuals of low socioeconomic status) who are less likely to achieve recommended levels of physical activity. Because payment is not usually needed to participate in such programmes, these strategies could also contribute to a reduction in social and health disparities.41

This type of intervention has been introduced in communities in Latin America: São Paulo,60 Recife,61 and other cities in Brazil;62 and Bogotà, Colombia.63 It can take several forms: instructor-led physical activity classes (eg, aerobics, stretching, yoga, and dancing) in parks or plazas, and in community centres in neigh-bourhoods of low to high income; use of readily available environ mental resources within communities that support physical activity behaviours; and educational and pro motional materials provided to participants to achieve further behavioural and social reinforcement and con nectedness to the classes within each of the inter vention communities.64,65

A recommended strategy within the behavioural and social domain is school-based physical education. School-based interventions could increase levels of phys-ical activity in children (appendix) because physical education is mandatory in many countries and the least active children—who are otherwise diffi cult to target—have to participate.66 Programmes can be delivered during and after school.67 Some core components for eff ective school-based interventions have been reported: increased

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number (fi ve sessions of at least 45 min per week) or improved quality of classes,36 increased physical activity during break and at other times, capacity building and staff training, changes in the curricula, provision of equipment and materials, and adjustment of interventions to target specifi c populations.66,68–70 Many studies have been based on several components, such as diet and family-based interventions, and reduction of sedentary time.70 Eff ects of school-based interventions have been assessed with various outcomes, such as physical activity level, fi tness, obesity, other cardiovascular risk factors, and wellbeing.70–72 Various studies in high-income and middle-income countries41,69 and other reviews66–68 have shown that participation in school-based interventions increases children’s physical activity, improves fi tness outcomes and motor skills, and reduces cardiovascular disease risk factors.

Policy and environmental approachesWalking and biking trails and exercise facilities can be created or enhanced to promote physical activity, and access to existing facilities can be increased with a reduction in structural and environmental barriers (eg, increased safety, improved aff ordability; appendix).36 Environmental and policy initiatives are often supported by training of personnel or participants, or both, pro-vision of social support, and further integration of these structures, facilities, and programmes into communities. In Linenger and co-workers’ 1991 report,73 new infra-structure (ie, bike paths), increased access to facilities (ie, expanded hours of operation, and lighted and integrated paths), and improved programming were provided in a residential naval base. A 2012 study74 reinforced these fi ndings73 by showing that installation of clusters of fi tness equipment in parks along with eff orts to promote the equipment increases physical activity of children, young people, and adults in these places. Provision of such infrastructure is reasonable from a cost perspective.74,75

Urban design and land-use regulations, policies, and practices commonly strive to create communities that are pleasant places to live. These types of interventions use policy instruments such as zoning regulations and building codes and environmental changes imple-mented by government policies or developers’ practices. Policies can encourage transit-oriented development and address street layouts, density of development, location of stores, jobs, and schools within walking distance of areas in which people live.76 Heath and colleagues77 reviewed 12 studies undertaken in the USA and one from Canada. Four of these studies compared communities with grid or rectilinear street design with those with cul-de-sac street design.77 Three studies compared pedestrian friendly environments (eg, ease of street crossing, topography, and continuity of pavements) with environments that were not friendly to pedestrians. The intervention and comparison communities were

similar in terms of socioeconomic status and racial or ethnic variables. The NICE review of promotion of physical activity through built or natural environments76 provided further evidence for this intervention strategy outside North America.

In view of the diversity between countries and popu-lations in published work, results should be applicable to various settings and communities, provided that appro priate attention is paid to adaptation of the inter-vention to target populations. The studies reviewed77 were under taken in fairly dense, urban environments, so whether the same components of design and land use apply to rural settings is unclear, although many of the design features are relevant in small towns and cities in rural regions.77 Potential barriers need to be addressed if public health and intersectoral initiatives are to be eff ective in community urban design and land-use regu-lations, policies, and practices. Diffi culties could be caused by the way in which cities are built because urban landscapes change slowly, by zoning regulations that preclude mixed-use neighbour hoods, by the cost of remodelling or retro fi tting exist ing communities, by ineff ective communi cation between diff er ent profes-sional groups (ie, urban planners, archi tects, engineers, and public health pro fessionals), and by changing of behavioural norms of urban design, lifestyle, and phys-ical activity patterns.76,77

Changes in policy of street-scale urban design and land use to support physical activity in small geographical areas that are generally restricted to a few blocks are eff ective in promoting physical activity. These policies and practices can be improved street lighting or infra-structure projects that increase the ease and safety of street crossing, ensure pavement continuity, introduce or enhance traffi c calming such as centre islands or raised crosswalks, or improve the aesthetics of the street area such as landscaping.76,77 These interventions are designed to enhance the urban environment and to increase physical activity by redesigning of streets and pavements, creation of bike lanes and paths, and improvements in the perceived environment.76,77 Most of the interventions reviewed focused on issues related to access, aesthetics, and safety.76,77

We reviewed representative studies from several countries and included one study each from the USA, Australia, Belgium, Canada, England, and Germany.77 We identifi ed relighting of streets (installing of new lights or improvements in present lighting), redesigning of streets, and improvements in street aesthetics as inter-vention strategies.77 Measures of eff ectiveness for street-scale strategies showed that the median net percentage change (eff ect size) from baseline to follow-up was 48·5% (IQR 10·0–180·0).77 This type of intervention is probably applicable across diverse settings and popu-lation groups, provided that appro priate attention is paid to adaption of the intervention to specifi c settings and target populations.7,77

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Transportation or travel interventions of interest to promotion of physical activity include those that aim to: enhance pedestrian, transit, and light rail (ie, commuter trains and subways) access; increase pedestrian and cyclist activity and safety; reduce car use; and improve air quality. In a 2006 review,77 researchers mainly identifi ed intervention strategies to increase walking and bicycling transport. These strategies used policy and environmental changes such as creation or enhancement of bike lanes or both, building of pave ments, subsidy of transit passes, incentives to share use of cars or vans, increases in the cost of parking, and use of bicycle racks on buses.77

We identifi ed three studies of more than 90 overall from 1990 to 1998 that assessed the eff ectiveness of trans portation and travel policies and practices. Since we did our search, the number of studies of active transport has increased substantially. In a review of the role of policies to increase and promote active travel, de Nazelle and colleagues78 examined published work associated with the health eff ects of policies that encourage active travel. The aim of their study was to identify active transport measures in the context of the development of models of health-eff ect assessment to help decision makers to create eff ective policies in support of healthy environ ments. They identifi ed substantial modal shifts in active travel in several international studies that were in direct response to specifi c transport policies and interventions.78 de Nazelle and co-workers78 concluded that well designed policies might enhance health benefi ts through indirect outcomes such as improved social capital (ie, expected collective or economic benefi ts derived from cooperation between individuals and groups) and diet, but these synergies are not suffi ciently well understood to allow present quantifi cation. They also reported that assessment of the eff ects of active transport policies is highly complex, although many associations can still be quantifi ed.78

Another potentially eff ective intervention strategy has been used in Latin American communities, such as Curitiba and São Paulo in Brazil,79,80 Bogotà in Colombia,63 and a similar national programme in Chile.41 It uses community-wide policies and planning combined with multicomponent eff orts in communities to promote physical activity.41 The plans and policies are designed to reduce environmental and structural barriers that directly aff ect physical activity behaviours.41 They are promoted through media campaigns and incentives at various levels (eg, individual, corporate, local, and regional). This type of strategy not only provides information that is intended to motivate individual behaviour change, but also focuses on the provision of institutional and environmental support to sustain changes in physical activity behaviour with time.41 An example of these interventions are the programmes known as Ciclovía,81 which have been rapidly disseminating throughout regions of the Americas (appendix). Ciclovía now exist in nearly 50% (17 of 35) of countries in the Americas.81,82

Translation, adaptation, capacity building, and keys to successOn the basis of existing evidence, an interesting pattern seems to be emerging, which emphasises important regional and cultural diff erences in how physical activity promotion is being approached around the world. The best options for interventions aimed at communities and individuals are probably dictated by local region and culture for some populations and settings. For example, previous reviews of work from Latin America41 have identifi ed a high prevalence of community-based interventions whereas those of high-income countries tend to identify interventions focus-ing on indi viduals.2,20,21,36,37

Such diff erences in approaches between countries of diff erent income status could be partly explained by sociocultural and geopolitical variability in how public health issues are addressed, which is potentially a result of a paternalistic governmental approach in some areas in Latin America, compared with the cultural importance of individual choice in regions of high income. Never-theless, interventions such as Ciclovía and the physical activity classes in community settings are being rapidly disseminated in communities within Canada, the USA, and Europe.82 Documentation (and ideally systematic assessments) of other locally relevant forms of physical activity and initiatives from large, culturally diverse, economically developing countries (including other parts of Asia and Africa) would be highly informative, providing a complete global view of interventions that work. Pratt and colleagues83 have drawn attention to the mismatch that exists on examination of a population’s exposure to evidence-based physical activity interven tions, expressed by population density, in countries of low and middle income compared with those of high income.

An adequately trained public health workforce is a core component of an eff ective global strategy for various issues, such as promotion of physical activity.84 A well known established training programme for capacity building is the physical activity and public health practitioner’s course on community interventions, spon-sored by the University of South Carolina Prevention Research Center.85,86 Through the US Centers for Disease Control and Prevention’s WHO Collaborating Center for Physical Activity and Health Promotion, this course has been replicated in many countries of low and middle income, such as Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, India, Kuwait, Malaysia, Mexico, Peru, South Africa, Thailand, and Venezuela (appendix).87,88 The Agita São Paulo programme in the Centre for Laboratory Studies on Physical Fitness of São Caetano do Sul, Brazil, has been promoting empowerment related to physical activity at various levels and in several stakeholders across Latin America for more than a decade.87 Kohl and co-workers88 provide greater detail about the need, content, and reach of physical activity and public health courses throughout the world than we discuss here.

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Alteration of population-wide levels of physical activity has proven to be complex and is driven by factors associ ated with intra-individual, sociocultural, environ mental, political, and fi nancial variables.89 Promotion of physical activity participation as a public health objective can be a basis for broad social and environmental challenges to be addressed.90 For example, the public priority to promote physical activity through active transport (particularly walking and bicycle use) provides many mutual points of interest that are in common with the transportation, injury-reduction, sustainability, energy-use, urban-planning, and environmental-pro tection agendas.91,92

In our review, some important themes emerged from around the world. Irrespective of diff erences in income status between countries, we identifi ed several promising and successful physical activity interventions when communities undertake specifi c tasks (panel).

Limitations and next stepsSeveral limitations are associated with our review of reviews. Although we attempted to identify reports from around the world irrespective of language, we have mainly drawn information from reports in English, Spanish, and Portuguese. Additionally, we did not attempt to complete a thorough search of the grey literature. Much of the published work did not include measures of external validity and hence restricted the generalisability of the fi ndings to other settings and countries. Despite these limitations, our systematic

organisation of these fi ndings should be valuable to practitioners and to physical activity and health scientists.

Overall, many evidence-based approaches increase physical activity of people of diff erent ages, and from various social groups and countries to an acceptable level of eff ectiveness. Similarly, several promising and emer ging interventions from middle-income countries deserve attention and rigorous assessment, and could potentially be both cost-eff ective and replicable in other communities. From such an international, evidence-based perspective—although there is a place for in-forming and motivating individuals to adopt physical activity—the traditional roles of public health through health protection and health promotion should be pursued by countries, cities, and communities as part of an intervention agenda for physical activity.7 Therefore, an increase in the likelihood of positive results will ensure that environments are safe and supportive of good health, that risk factors are controlled, and that disease and injury are avoided.93

In children and adolescents, physical activity could be greatly increased through school-focused initiatives. For the whole population, and particularly for adults, development of policies and environmental supports (especially through partnerships with other sectors, specifi cally transport and urban planning) that increase opportunities for physical activity within communities would allow great progress.94 Interventions would probably have increased eff ectiveness, to the extent that they could address the determinants of physical activity at several levels. Ideally, physical activity initiatives should apply the relevant models and address the factors at individual, behavioural, social, environmental, and policy levels.13,14 However, within the realities of public health practice, this ideal is diffi cult to achieve. Because disparities exist in amount of physical activity in subgroups of the popu-lations, public health professionals need to tailor policy and environmental eff orts and programmes to promote increased physical activity opportunities everywhere, with specifi c attention to initiatives that address the needs of disadvantaged subgroups.ContributorsGWH drafted the report outline, and wrote and organised subsequent drafts. All other authors provided crucial input and approved the fi nal version. DCP, OLS, and FM did the systematic search and developed the table and the fi gure, with input from the other authors. LBA provided invaluable insight and wrote the initial narrative addressing school-based interventions. NO provided guidance in writing of the sections associated with behavioural and social determinants of physical activity and their contributions to the interventions reviewed and discussed. SG contributed substantially to sections of the narrative addressing international comparisons and the importance of capacity building and training. RCB wrote substantial portions of the report addressing the principles of evidence-based public health practice and systematic review methods.

Lancet Physical Activity Series Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk,

Panel: Community tasks that lead to successful interventions

• Set aside suffi cient resources to eff ectively inform, educate, and empower their residents to achieve recommended levels of physical activity where they live, work, and learn

• Mobilise intersectoral partnerships to develop eff ective strategies through informational, social, and behavioural, and policy and environmental approaches to physical activity promotion

• Develop policies and plans for policy implementation and assessment that support individual and community eff orts to promote physical activity and active living

• Use evidence-based and promising practice methods for planning and implementation of community-based physical activity interventions and communication of physical activity messages

• Implement innovative new interventions and ensure they are assessed to add to the evidence base

• Understand and promote active living principles through national, regional or state, and community partnerships to organise and support active transport, active sport, and active recreation

• Understand and apply key components of evidence-based approaches to assessment of physical activity promotion

• Form partnerships with public health agencies to undertake routine surveillance of physical activity and inactivity behaviours in community-specifi c residents, such as specifi c health, environmental, and policy correlates

• Provide training and capacity building in partnership with other community organisations in use and adaptation of evidence-based physical activity interventions

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17 Israel BA, Eng E, Schultz AJ, Parker EA, eds. Methods in community-based participatory research for health. San Francisco, CA: Jossey-Bass, 2005.

18 Cargo M, Mercer SL. The value and challenges of participatory research: strengthening its practice. Ann Rev Public Health 2008; 29: 325–50.

19 WHO. A guide for population-based approaches to increasing levels of physical activity: implementation of the WHO global strategy on diet, physical activity, and health. Geneva: World Health Organization, 2007.

20 Heath GW. The role of the public health sector in promoting physical activity: national, state, and local applications. J Phys Act Health 2009; 6 (suppl 2): S159–67.

21 Kahn EB, Ramsey LT, Brownson RC, et al. Physical activity. In: Zaza S, Briss PA, Harris KW, eds. The guide to community preventive services: what works to promote health. Oxford: Oxford University Press, 2005: 80–113.

22 Krebs P, Prochaska JO, Rossi JS. A meta-analysis of computer-tailored interventions for health behavior change. Prev Med 2010; 51: 214–21.

23 Williams SL, French DP. What are the most eff ective intervention techniques for changing physical activity self-efficacy and physical activity behavior—and are they the same? Health Educ Res 2011; 26: 308–22.

24 Lin JS. O’Connor E, Whitlock EP, Beil TL. Behavioral counseling to promote physical activity and a healthful diet to prevent cardiovascular disease in adults: update of the evidence for the US Preventive Services Task Force. December, 2010. http://www.uspreventiveservicestaskforce.org/uspstf11/physactivity/physart.htm (accessed March 20, 2012).

25 Conn VS, Hafdahl AR, Mehr DR. Interventions to increase physical activity among healthy adults: meta-analysis of outcomes. Am J Public Health 2011; 101: 751–58.

26 Conn VS, Hafdahl AR, Cooper PS, Brown LM, Lusk SL. Meta-analysis of workplace physical activity interventions. Am J Prev Med 2009; 37: 330–39.

27 Conn VS, Valentine JC, Cooper HM. Interventions to increase physical activity among aging adults: a meta-analysis. Ann Behav Med 2002; 24: 190–200.

28 Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Eff ective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol 2009; 28: 690–701.

29 Vandelanotte C, Spathonis KM, Eakin EG, Owen N. Website-delivered physical activity interventions: a review of the literature. Am J Prev Med 2007; 33: 54–64.

30 Beets MW, Beighle A, Erwin HE, Huberty JL. After-school program impact on physical activity and fi tness: a meta-analysis. Am J Prev Med 2009; 36: 527–37.

31 Gourlan MJ, Trouilloud DO, Sarrazin PG. Interventions promoting physical activity among obese populations: a meta-analysis considering global eff ect, long-term maintenance, physical activity indicators and dose characteristics. Obes Rev 2011; 12: e633–45.

32 Kang M, Marshall SJ, Barriera TV, Lee JO. Eff ect of pedometer-based physical activity interventions: a meta-analysis. Res Q Exerc Sport 2009; 80: 648–55.

33 Jenkins A, Christensen H, Walker JG, Dear K. The eff ectiveness of distance interventions for increasing physical activity: a review. Am J Health Promot 2009; 24: 102–17.

34 Brownson RC, Fielding JE, Maylahn CM. Evidence-based public health: a fundamental concept for public health practice. Ann Rev Public Health 2009; 30: 175–201.

35 Brennan L, Castro S, Brownson RC, Claus J, Orleans CT. Accelerating evidence reviews and broadening evidence standards to identify eff ective, promising, and emerging policy and environmental strategies for prevention of childhood obesity. Annu Rev Public Health 2011; 32: 199–223.

36 Kahn EB, Ramsey LT, Brownson RC, et al. The eff ectiveness of interventions to increase physical activity: a systematic review. Am J Prev Med 2002; 22: 73–107.

37 Roux L, Pratt M, Tengs TO, et al. Cost eff ectiveness of community-based physical activity interventions. Am J Prev Med 2008; 35: 578–88.

Harold W Kohl 3rd, Estelle Victoria Lambert, I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of interestWe declare that we have no confl icts of interest. The fi ndings and conclusions in this report are those of the authors and do not necessarily represent the offi cial position of any of the organisations, institutions, or agencies to which they are affi liated.

AcknowledgmentsWe thank Baley Whary for technical support in the preparation of portions of the report for submission for publication and Ken Powell for his initial review and critique of the outline proposal.

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66 Kriemler S, Meyer U, Martin E, et al. Eff ect of school-based interventions on physical activity and fi tness in children and adolescents: a review of reviews and systematic update. Br J Sports Med 2011; 45: 923–30.

67 Atkin AJ, Gorely T, Biddle SJ, et al. Interventions to promote physical activity in young people conducted in the hours immediately after school: a systematic review. Int J Behav Med 2011; 18: 176–87.

68 van Sluijs EM, McMinn AM, Griffi n SJ. Eff ectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ 2007; 335: 703–07.

69 Ribeiro I, Parra DC , Hoehner CM, et al. School-based physical education programs: evidence-based physical activity interventions for youth in Latin America. Glob Health Promot 2010; 17: 5–15.

70 Resaland GK, Andersen LB, Holme IM, Mamen A, Andersen LB. Eff ects of a 2-year school-based daily physical activity intervention on cardiorespiratory fi tness: the Sogndal school-intervention study. Scand J Med Sci Sports 2011; 21: 302–09.

71 Yildirim M, van Stralen MM, Chinapaw MJ, et al. For whom and under what circumstances do school-based energy balance behavior interventions work? Systematic review on moderators. Int J Pediatr Obes 2011; 6: e46–57.

72 Waters E, de Silva-Sanigorski A, Hall BJ, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev 2011; 12: CD001871.

73 Linenger JM, Chesson CV, Nice DS. Physical fi tness gains following simple environmental change. Am J Prev Med 1991; 7: 298–310.

74 Cohen A, Marsh T, Williamson S, Golinelli D, McKenzie TL. Impact and cost-eff ectiveness of family Fitness Zones: a natural experiment in urban public parks. Health Place 2012; 18: 39–45.

75 Wang Guijing, Macera CA, Scudder-Soucie B, et al. Cost analysis of the built environment: the case of bike and pedestrian trails in Lincoln, Neb. Am J Public Health 2004; 94: 549–53.

76 National Institute for Health and Clinical Excellence. Promoting and creating built or natural environments that encourage and support physical activity. London: National Institute for Health and Clinical Excellence, 2008.

77 Heath GW, Brownson RC, Kruger J, Miles R, Powell KE, Ramsey LT. The eff ectiveness of urban design and land use and transport policies and practices to increase physical activity: a systematic review. J Phys Act Health 2006; 1: S55–71.

78 de Nazelle A, Nieuwenhuijsen MJ, Antó JM, et al. Improving health through policies that promote active travel: a review of evidence to support integrated health impact assessment. Environ Int 2011; 37: 766–77.

79 Reis RS, Hallal PC, Parra DC, et al. Promoting physical activity through community-wide policies and planning: fi ndings from Curitiba, Brazil. J Phys Act Health 2010; 7 (suppl 2): S137–45.

80 Matsudo V, Matsudo S, Araújo T, Andrade D, Oliveira L, Hallal P. Time trends in physical activity in the state of São Paulo, Brazil: 2002–2008. Med Sci Sports Exerc 2010; 42: 2231–36.

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81 Montes F, Sarmiento OL, Zarama R, et al. Do health benefi ts outweigh the costs of mass recreational programs? an economic analysis of four Ciclovía programs. J Urban Health 2011; 89: 153–70.

82 Sarmiento O, Torres A, Jacoby E, Pratt M, Schmid TL, Stierling G. The Ciclovía-Recreativa: a mass-recreational program with public health potential. J Phys Act Health 2010; 7 (suppl 2): S163–80.

83 Pratt M, Sarmiento OL, Montes F, et al, for the Lancet Physical Activity Series Working Group. The implications of megatrends in information and communication technology and transportation for changes in global physical activity. Lancet 2012; published online July 18. http://dx.doi.org/10.1016/S0140-6736(12)60736-3.

84 Koplan JP, Puska P, Jousilahti P, et al. Improving the world’s health through national public health institutes. Bull World Health Organ 2005; 83: 154–57.

85 Brown DR, Pate RR, Pratt M, et al. Physical activity and public health: training courses for researchers and practitioners. Public Health Rep 2001; 116: 197–202.

86 Franks AL, Brownson RC, Bryant C, et al. Prevention research centers: contributions to updating the public health workforce through training. Prev Chronic Dis 2005; 2: A26.

87 Matsudo SM, Matsudo VR. Coalitions and networks: facilitating global physical activity promotion. Promot Educ 2006; 13: 133–38, 158–63.

88 Kohl HW 3rd, Armstrong T, Craig CL, et al. The pandemic of physical inactivity: global action for public health. Lancet 2012; http://dx.doi.org/10.1016/S0140-6736(12)60898-8.

89 Brownson RC, Parra DC, Dauti M, et al. Assembling the puzzle for promoting physical activity in Brazil: a social network analysis. J Phys Act Health 2010; 7 (suppl 2): S242–52.

90 Sallis JF, Cervero RB, Ascher W, et al. An ecological approach to creating active living communities. Annu Rev Public Health 2006; 27: 297–322.

91 Woodcock J, Edwards P, Tonne C, et al. Public health benefi ts of strategies to reduce greenhouse-gas emissions: urban land transport. Lancet 2009; 374: 1930–43.

92 Kahlmeier S, Racioppi F, Cavill F, Rutter H, Oja P. “Health in all policies” in practice: guidance and tools to quantifying the health eff ects of cycling and walking. J Phys Act Health 2010; 7 (suppl 1): S120–25.

93 Heath GW. The role of the public health sector in promoting physical activity: national, state, and local applications. J Phys Act Health 2009; 6 (suppl 2): S159–67.

94 Sallis JF, Kraft K, Linton LS. How the environment shapes physical activity: a transdisciplinary research agenda. Am J Prev Med 2002; 22: 208–10.

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Lancet 2012; 380: 282–93

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)60736-3

This is the fourth in a Series of fi ve papers about physical activity

*Members listed at end of paper

National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease

Control and Prevention, Atlanta, GA, USA (M Pratt MD,

L G Perez MPH); School of Medicine (O L Sarmiento MD, M Pratt), and Department of

Industrial Engineering (F Montes MSc), Universidad de

Physical Activity 4

The implications of megatrends in information and communication technology and transportation for changes in global physical activityMichael Pratt, Olga L Sarmiento, Felipe Montes, David Ogilvie, Bess H Marcus, Lilian G Perez, Ross C Brownson, for the Lancet Physical Activity Series Working Group*

Physical inactivity accounts for more than 3 million deaths per year, most from non-communicable diseases in low-income and middle-income countries. We used reviews of physical activity interventions and a simulation model to examine how megatrends in information and communication technology and transportation directly and indirectly aff ect levels of physical activity across countries of low, middle, and high income. The model suggested that the direct and potentiating eff ects of information and communication technology, especially mobile phones, are nearly equal in magnitude to the mean eff ects of planned physical activity interventions. The greatest potential to increase population physical activity might thus be in creation of synergistic policies in sectors outside health including communication and transportation. However, there remains a glaring mismatch between where studies on physical activity interventions are undertaken and where the potential lies in low-income and middle-income countries for population-level eff ects that will truly aff ect global health.

IntroductionNon-communicable diseases account for 60% of all deaths globally, and 80% of these deaths occur in low-income and middle-income countries.1 An epidemio logical transition from a burden of disease dominated by communicable

diseases to one dominated by non-communicable diseases2 is now occurring in countries with low and middle incomes as it has previously in those with high incomes.3 Physical inactivity is a major risk factor for non-communicable diseases, accounting for an estimated 3·2 million deaths per year.4 Most of these deaths, as well as the huge burden of morbidity and disability attributable to physical inactivity, take place in countries with low and middle incomes. Public health attention to physical inactivity has evolved rapidly in the past decade, as shown by the 2004 WHO global strategy on diet, physical activity, and health,5 the 2010 WHO global recommendations on physical activity for health,6 and the central role of physical activity in the 2009 WHO action plan for the global strategy for the prevention and control of non-communicable diseases7 and the UN General Assembly summit on non-communicable diseases.8

A major goal for public health is to identify evidence-based interventions to promote physical activity in populations. To do so, several types of evidence are needed.9–11 Type 1 evidence defi nes the causes of disease due to physical inactivity and the magnitude, severity, and preventability of inactivity. Type 2 evidence describes the eff ectiveness of specifi c interventions that address physical inactivity. Type 2 evidence (summarised in the Cochrane Library, Community Guide reviews, or UK National Institute for Health and Clinical Excellence [NICE] guidance) identifi es eff ective interventions for promotion of physical activity.12,13 Type 3 evidence shows in what contexts interventions are implemented and how they can be adapted from one population to another (eg, from a high-income country to those with low and middle incomes).9,11 Most intervention studies have not been done in countries with low and middle incomes

Key messages

• Non-communicable diseases account for 60% of deaths globally, and 80% of these deaths occur in low-income or middle-income countries

• Physical inactivity is one of the major risk factors for non-communicable diseases, accounting for an estimated 3·2 million deaths per year

• The challenges and opportunities in prevention of non-communicable diseases show several important megatrends—major forces in societal development that are likely to shape people’s lives in the next 10–15 years

• Information and communication technologies in the form of internet and mobile phone access have grown enormously during the past decade; these technologies have the potential to aff ect physical activity

• Trends in transportation, including the growth in ownership and use of private cars and improved and well integrated public transit systems, have the potential to both negatively and positively aff ect participation in physical activity, especially walking

• On the basis of a review of publications about physical activity interventions, we modelled the eff ects of megatrends in internet access, mobile phone access, and car ownership on physical activity

• The direct and potentiating eff ects of mobile phone technology on physical activity in middle-income and upper-income countries are similar in size to the mean eff ects of planned physical activity interventions in community and clinical settings

• The greatest potential for increasing population physical activity might be in the creation of supportive policies in sectors outside health (transportation, urban planning, and communication)

• There is a glaring mismatch between where the studies of physical activity interventions have been done and where the potential lies for population-level eff ects that will truly aff ect global health (low-income and middle-income countries)

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los Andes, CEIBA Complex Systems Research Centre, Bogotá, Colombia; MRC Epidemiology Unit and UKCRC Centre for Diet and Activity Research, Institute of Public Health, Cambridge, UK (D Ogilvie FFPH); Department of Family and Preventive Medicine, University of California in San Diego, La Jolla, CA, USA (Prof B H Marcus PhD); Prevention Research Center in St Louis, Brown School and School of Medicine, Division of Public Health Sciences, Washington University in St Louis, St Louis, MO, USA (Prof R C Brownson PhD)

Correspondence to:Dr Michael Pratt, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA 30341-3717, [email protected]

and have not addressed the question of how eff ective interventions can be adapted from one country to another.14 The scarcity of type 3 evidence suggests a need for increased attention on the external validity of studies (the extent to which fi ndings can be applied to other populations, settings, and times)15,16 to complement the emphasis so far on the internal validity of well controlled eff ectiveness trials.

During consideration of which interventions are appropriate and eff ective, the usual evidence hierarchies might not apply. The randomised controlled trial is typically regarded as the most robust study design to test hypotheses about the eff ects of interventions.17 As such, randomised controlled trials are often more likely to be funded, published, and included in systematic reviews. However, well designed observational studies (including studies of so-called natural experiments)18 can also be powerful aids to estimation of risk, understanding of disease, and evaluation of interventions,19 particularly in the policy arena, in which random assignment of exposure might be politically or practically infeasible. In these situations, alternative research designs20 are often best to address policy-relevant questions.

The challenges and opportunities in prevention of non-communicable diseases indicate several important megatrends—defi ned as major forces in societal develop-ment that are likely to shape people’s lives during the next 10–15 years. Many of the actions that aff ect population levels of physical activity might occur outside the health sector and potentially be shaped by mega trends. Factors such as environmental justice and social equity, economic and technological development, trans port, urbanisation, pedestrian-oriented urban develop ment, and global com-munication could have much greater eff ect on physical activity than do strategies derived from a traditional medical or public health perspective. Environmental justice refers to the need to improve environmental conditions for populations challenged by poverty, poor education, and scarcity of resources.21 These conditions are closely related to social inequity, which implies an unfair distribution of social, cultural, and environmental re-sources between advan taged and disadvantaged groups.22,23 Environmental conditions include the built environment, public space, and other structural factors that aff ect health behaviours such as physical activity.24–26 Addressing of inequalities in access to facilities, safe public spaces, and other supports for active lifestyles is often the fi rst step in promotion of physical activity. The growth of information and com munication technologies such as the worldwide web and mobile phones provides new opportunities for delivery of physical activity interventions, but also poses challenges for upholding of principles of social equity across the digital divide. Similarly, the potential physical activity benefi ts of new public transport and pedestrian and bicycle route networks might be threatened by increasing ownership and use of private cars, particularly in countries with low and middle incomes.

We aimed to improve understanding of the eff ect-iveness and potential eff ect of interventions to address the global burden of physical inactivity. We had fi ve objectives: (1) to assess the potential eff ect of megatrends in information and communication technologies and transport on physical activity; (2) to use the fi ndings of a targeted review of physical activity interventions to guide development of a simulation model; (3) to model the changes in population physical activity that are potentially attributable to and aff ected by these mega-trends within the clinical, public health, and intersectoral domains; (4) to illustrate key issues through case studies; and (5) to provide policy-related recommendations related to the fi ndings of the analyses.

Megatrends in information and communication technologies and transportBackgroundPhysical activity promotion has developed in recent decades from a focus on individual behaviour change to the wider societal and environmental determinants of health-rel ated behav iour.27,28 Two major themes of con-tem porary societal change are the development of information and com munication technologies and the growth in use of motor vehicles. Both these megatrends could have a bearing on the promotion or maintenance of physical activity in populations, especially because diff erential access to these technologies, across and within countries, could aff ect existing health inequalities. They should therefore be considered through the per-spective of social equity in assessments of their potential to reach and infl uence individuals, particularly those in greatest need of low-cost interventions.29

Information and communication technologiesInformation and communication technologies are ex-panding very rapidly worldwide. Access to the internet, for example, increased enormously from 1997 to 2009 (from 0·01% to 4·3% of the population in low-income countries; from 0·21% to 23·8% in middle-income countries; and from 11·2% to 51·9% in high-income countries). Mobile phone access increased similarly from 1997 to 2009 (from 0·05% to 28·9% in low-income countries; from 1% to 71% in middle-income countries; and from 17·9% to 96·3% in high-income countries). These large increases present a challenge for identifi cation and testing of eff ective technologies to change health behaviours. Physical activity is one of many health behaviours that have the potential to change substantially as a result of increasing availability of information and communication technologies and of technology-based interventions.

The internet is identifi ed as an important source of health information by more than half its users30 and could, therefore, be a useful medium for physical activity interventions. Most research into use of the internet for physical activity health promotion has been done in

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the USA31–38 (with additional studies in Canada,39 Australia,40,41 Switzerland,42 and the Netherlands43) and mainly on healthy but overweight and fairly sedentary white adults, especially women.38,40,43–46 Overall, web-based interventions show small positive eff ects. How ever, on the basis of our review, few internet-based physical activity trials have used programme features specifi cally matched to theoretical constructs known to result in changes in physical activity behaviour and likely to increase eff ectiveness.

Around 95% of countries have mobile telephone networks, about 70% of people worldwide use mobile phones,47 and most countries have more mobile phone subscribers than fi xed landlines.48 Much of the recent

proliferation of mobile phone use has occurred in low-income and middle-income countries.47,48 Mobile phones have attracted less attention than the internet for research on physical activity promotion.49 Although mobile phone calls can be taken on the go, delivery of interventions over the telephone still needs scheduling, staffi ng, and other resources. However, the more direct, personal interaction from phone calls creates a greater sense of personal and social support than do traditional face-to-face interventions, which is associated with improved health outcomes.50

Mobile phone short-message service (SMS) presents a promising application for delivery of interventions because of its widespread use in less affl uent and less healthy populations. SMS is pervasive across cultures,

Country income level

Upper-middle incomeHigh income

A

B

C

Low incomeLower-middle income

Figure 1: Internet users (A), mobile phone users (B), and car ownership (C), by country incomeEach country in this density-equalising map is resized according to the number of internet or mobile-phone users or car owners with the Gastner and Newman algorithm.62

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socioeconomic backgrounds, and country economic development levels, with an estimated 4 billion users worldwide.51 This service allows instantaneous delivery of short messages (maximum 160 characters) that can be accessed at a time that suits recipients, including when they are in situations or environments that are conducive to physical activity or involve making choices between active and sedentary options. SMS can also be more cost-eff ective than telephone calls and allows for two-way communication, in which participants can send infor-mation to elicit feedback and interact asynchronously and fl exibly.52

The gap between people with eff ective access to digital and information technology and those without has been referred to as the digital divide.53 The idea was originally popularised with respect to the disparity in internet access between rural and urban areas of the USA,54,55 but it also refers to wider inequalities in access by sex, income, race, and location.55 People who are overweight, of low socio-economic position, and who might, there fore, stand to gain the most from an intervention to promote physical activity might be less likely to have access to internet technology. The global digital divide refers to the uneven development of the internet throughout the world and the associated disparities in access to information, education, and business oppor tunities between wealthy countries and those with low and middle incomes.56–59 Interestingly, however, poor populations globally have been early adopters of mobile phones, emphasising that costs are not a substantial barrier to mobile phone service.60 The highest mobile phone use in the USA occurs in adolescents, young adults, socioeconomically disadvantaged populations, and people who rent their homes or frequently change addresses.61 Whether considered within a country or globally, the digital divide that has been noted for internet access does not seem to be present for mobile phones (fi gure 1). Therefore, mobile phones have great potential to reach populations that previously had restricted access to interventions or health-care information.

TransportThe potential to promote physical activity through transport exemplifi es the importance of intersectoral approaches to policy and assessment;63–65 walking and cycling are forms of recreational activity as well as modes of daily transport that can replace trips previously made by motor vehicle. Reduction of journeys made in vehicles should be a complementary policy goal to that of promotion of physical activity because reduction of sedentary time, such as that spent in cars, might also be important for chronic disease prevention, and use of motor vehicles is associated with various wider population health consequences including injuries, noise, local air pollution, and carbon emissions.66 A modelling study67 based on London and Delhi showed that although reduction of carbon emissions through technical modifi cation of the vehicle fl eet would have

some health benefi ts, much greater population health benefi ts would be realised by active travel substitution, in which a large proportion of urban trips are shifted to walking and cycling, even after any increase in injuries was taken into account.68 Investigators applying alter-native model assumptions to diff erent datasets have reached much the same conclusions.67,69

The growth in ownership and use of private cars—particularly in high-income countries such as the UK, where annual kilometres travelled by car or van have increased more than ten times since the 1950s70 (fi gure 1)—has made it possible for people to live, work, shop, and pursue leisure activities in widely dispersed locations. In such contexts, car ownership might be important to enable access to opportunities and ameni-ties, and is associated with reduced morbidity and mortality even after adjustment for other markers of socioeconomic status.71–73 However, Illich74 argued in the 1970s that the mobile car-based society had created universal enslavement, and Adams’ more recent notion of hypermobility encapsulates the idea that ever-increasing mobility imposes unacceptable social costs

Panel 1: Case study: urban transformation in Bogotá, Colombia

Bogotá has implemented broad policy and infrastructure changes to improve public space and transport. These urban and social changes have enhanced the environment for walking and cycling, improved public transport, and increased public safety. Bogotá is now widely known for the TransMilenio bus rapid transit (BRT) system and weekly street closures for recreation (Ciclovía). The TransMilenio and Ciclovía are associated with increased physical activity82,86 and are promising models for intersectoral promotion of physical activity.85,87 TransMilenio buses operate in exclusive lanes, have fi xed stations, serve 1·4 million people daily, and are generally the fastest means of moving around Bogotá. Cross-sectional studies show that neighbourhood access to BRT is positively associated with walking for transport87 and walking during leisure time.85 These associations might also be attributable to parallel improvements in infrastructure, including pavements, pedestrian crossings and bridges, connecting cycle routes, and signage.

The Ciclovía is a free community programme in which 97 km of streets are closed for 7 h on Sundays and holidays allowing access to pedestrians, runners, rollerbladers, and cyclists. Participation in the Ciclovía ranges from 600 000 to 1 400 000 users per event, and annual costs are about $1·7 million. The Ciclovía engages nine sectors: education, environment, health, police, sports, culture and recreation, transport, urban planning, and local government. In a country with substantial social inequity, the Ciclovía is notable in that 90% of the participants are from low and middle socioeconomic strata. Adults who report participating in the Ciclovía are more likely to meet weekly physical activity recommendations and to use bikes for transportation than are those who do not participate.85 A 2009 survey suggested that 15% of Ciclovía participants would otherwise be spending their time on sedentary behaviours if the Ciclovía was not available.88 The Ciclovía is estimated to provide 13·6% of the recommended population requirement for weekly minutes of physical activity for Bogotá, while needing minimum investment in infrastructure. A cost-benefi t analysis of the Ciclovía in Bogotá yielded benefi t-to-cost ratios of 3·23–4·26.89 Implementation of government-supported programmes such as the Ciclovía in existing public spaces seems to be a cost-eff ective means to increase physical activity. Ciclovías are now in more than 100 cities in the Americas and seem to have the right combination of eff ectiveness, feasibility, and political appeal to become a mainstay of global physical activity promotion.

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and that it is, therefore, possible for a society to have too much of a good thing.75 This opinion is especially important since in countries such as the UK, car ownership,76 carbon emissions from private motor vehicles,77 and child pedestrian mortality78 are all strongly socially patterned: people who benefi t most from the hypermobile society are usually not those who bear the brunt of the adverse eff ects. These costs of widespread motorisation are also not limited to high-income countries, as shown by the increase in body-mass index associated with a transition from cycling to car use in adults in China,79 where the total motor vehicle fl eet increased ten times between 1990 and 2005.80

By contrast with private motor vehicles, improvement of public transport such as bus or rail services might allow participation in physical activity, particularly in the form of walking at either end of the journey. Evidence from cross-sectional studies in the USA, Australia, Europe, and Colombia suggests that people who use, or have access to, public transport are more likely to walk and tend to be more physically active than are those who do not.81–85 Promotion of physical activity is unlikely to be the primary concern of transit systems, but if the needs of pedestrians and cyclists are properly addressed in the design of vehicles, stations, and their surroundings, schemes such as the TransMilenio bus rapid transit (BRT) in Bogotá could help to increase the use of active travel while providing high-quality public transport at a lower cost than traditional rail services (see case study on urban transformation in Bogotá, panel 1).90 Evidence from robust intervention studies is scarce at present, but favourable trends in travel patterns have been reported in many cities that have introduced integrated urban transport policies.91 Further implemen tation and assess ment of these inter-ventions are important because controlled studies of interventions to promote cycling suggest that their eff ects are small.92 Interventions to promote walking have a stronger evidence base, although their eff ective-ness to increase physical activity might depend on targeting of specifi c groups or settings.93 The evidence shows an evaluative bias whereby interventions applied to whole populations have tended to be assessed by less rigorous methods than those applied to small groups of motivated volunteers.94

Megatrends related to information and com munication technologies and transport might have sub stantial poten-tial eff ects on physical activity promotion, even though so far fairly few studies have focused on these areas.

Physical activity intervention reviewsWe did a systematic search to identify the latest reviews of published work about interventions to increase physical activity to provide input for a simulation model of physical activity interventions and megatrends. We used several electronic databases, websites, and published sources for our search: Clinical Evidence,

Cochrane Library, Centre for Reviews and Dissemination (DARE admin database, HTA, NCCHTA), Embase, National Guidelines Clearinghouse, Medline, PubMed, NICE, PsycINFO, SIGLE, Sociological Abstracts, and TRIP. We searched the databases for systematic reviews or meta-analyses related to inter ventions and physical activity in human beings, published from Jan 1, 2001, to July 31, 2011, and PubMed from Jan 1, 2000, to Dec 20, 2011 (for methods see appendix pp 9–10). Reviews were classifi ed according to setting and type of intervention (clinical, community, schools, workplace, or other) and, for technology-based interventions, whether they were delivered by mobile phone or over the internet. When a systematic review or meta-analysis did not provide pooled eff ect estimates, but did provide standardised mean diff erences, we estimated pooled mean eff ect sizes using a random eff ects model or reported a range of eff ect estimates. The standardised mean eff ect corresponds to the eff ect size of an intervention for promotion of physical activity standardised to a uniform scale. To obtain the stand ardised mean eff ect, we used the standardised mean diff erences method. This method expresses the size of the treatment eff ect in each trial relative to the variability in that trial (appendix p 2).

We analysed 100 reviews of physical activity inter-ventions (appendix p 9). Five systematic reviews were reviews-of-reviews, 19 were meta-analyses, and 76 were narrative reviews that did not provide quantitative eff ect estimates results from pooled eff ects or meta-regressions. 18 reviews covered interventions in clinical settings, 14 described community settings, fi ve covered school settings, fi ve described workplace settings, and the remainder consisted of several settings or reported not having a setting restriction for the search and synthesis. 60 reviews included studies done in high-income countries, whereas only eight included studies done in low-income and middle-income countries; 32 reviews did not include country-specifi c information. Seven reviews examined internet-based or web-based interventions; three dealt with mobile phone inter-ventions; and four addressed interventions in the transportation sector. 50 reviews were of studies of adults; 19 of children and adolescents; 11 of adults and children; three of older adults; 13 of any age group; and four did not specify the age group.

Taken as a whole, the evidence in our review showed consistent, signifi cant eff ects of the interventions on physical activity behaviours. Full results of the review of physical interventions are reported elsewhere in The Lancet.95 In view of the large reach of some of these interventions (eg, mobile phones), the prevented fraction is potentially large, and thus we developed the model that follows. We chose the results from the systematic reviews (appendix p 6) as inputs for the model because they included the megatrends of interest in this study.

See Online for appendix

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Simulation model for megatrends and physical activity interventionsWe designed scenarios to assess the potential eff ect of interventions taking into consideration the eff ects of megatrends by country income. The megatrends used in the models were internet access, mobile phone access, and car ownership, including the eff ect of fuel price on car ownership. The model for information and communication technology interventions included those delivered directly via these technologies and the facilitating eff ects of the technologies on other physical activity interventions (appendix pp 4–5). The model for car ownership included the relation between active travel time (as a proxy for physical activity) and private car ownership (appendix pp 7–8). Megatrends and country classifi cation by income are based on the 2011 world development indicators from the World Bank database.96 The World Bank’s main criterion for classifying econ omies is gross national income per head (appendix p 2). We selected the eff ect estimates for physical activity interventions from the most recent systematic reviews, and based the eff ect estimate for car ownership on the one available study, a cross-sectional study from the UK.75

Our model showed that the potential eff ect of web-based interventions on physical activity, at the population level, is positive and varies by country income. The estimates by country income showed a dose-response relation (fi gure 2), showing that the potential eff ect increases as country income increases (0·65 min per week for countries with low income; 1·71 min per week for lower-middle income; 4·78 min per week for upper-middle income; and 8·88 min per week for high-income). Because the total population of middle-income countries is much greater than that of high-income countries, the weighted potential eff ect size (appendix p 4; the potential population reached weighted by the potential eff ect size) for middle-income countries (3·44) is double that of high-income countries (1·46) for the internet access contribution to the expected population min of physical activity per week (table 1).

As for our fi ndings for web-based interventions, we identifi ed a positive potential eff ect of mobile phone inter ventions on physical activity at the population level. The estimates by country income, however, showed a dose-response relation diff erent from that of internet-based interventions (fi gure 2); specifi cally, increasing linearly from low income to upper-middle income (4·37 min per week for countries with low income; 8·22 min per week for lower-middle income; 13·52 min per week for upper-middle income; and 14·03 min per week for high-income countries) and then reaching a plateau. As with internet-based interventions, the greater proportion of the global population in middle-income countries is important for projection of the population-weighted potential eff ect sizes (appendix p 4) for mobile-phone-based interventions. The population-weighted

contribution to the expected min of physical activity in middle-income countries (7·91) exceeds that of high-income countries (2·27; table 1).

Whereas our fi ndings for mobile-phone-based and web-based interventions show a positive potential eff ect on physical activity at the population level, we identifi ed a negative potential eff ect of car ownership on population-level active travel. The estimates by country income showed a dose-response relation, indicating a larger negative eff ect as country income increased (–0·12 min per day for low income; –0·48 min per day for lower-middle income; –0·80 min per day for upper-middle income; and –3·11 min per day for high income; table 2). In view of the population distribution across countries by income, we did not expect to fi nd a diff erence in the negative contribution to the expected min of active travel per day in middle-income countries versus high-income countries. When we adjusted the estimates by fuel pricing increment, the negative eff ect decreased slightly. The weighted decrement was 0 for low-income countries and 0·01 for middle-income and high-income countries. The SD for each potential eff ect estimate was high, possibly relating to the uncertainty of the results from use of one study (table 2). For the

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t

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0

0·1

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0·3

0·5

0·6

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Telephone (mobile phone)Clinical, unadjusted (mobile phone)Community (mobile phone)Overall (mobile phone)Clinical, 40% (mobile phone)

A

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Figure 2: Potential eff ect estimate for information and communication technologies(A) Internet. (B) Mobile phone. Clinical=interventions in a health-care setting.

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sensitivity analysis, we estimated the error of the Monte Carlo approximation accounting for the point estimate and its 95% CI (–6 min, 95% CI –12·04 to –0·32; table 2).

Discussion and conclusionsType 1 evidence from 100 reviews of community-based and clinic-based physical activity interventions, including rigorous evidence-based reviews, consistently showed small improvements of physical activity in the short and medium terms. Eff ect sizes were small for individuals (pooled overall eff ect size in healthy adults of 14·7 min of physical activity per week97), but large enough to promise real population-level benefi ts if these interventions can be applied on a large scale. Geoff rey Rose’s classic observation that small mean changes at the individual level often lead to substantially greater eff ects at the population level seems likely to apply for physical activity.98 A glaring mismatch exists, however, between where the studies on physical activity interventions have been done and where the potential lies for population-level eff ects that can truly aff ect global health (fi gure 3), suggesting a scarcity of type 3 (contextual) evidence. Of the 95 primary reviews of interventions that we identifi ed, only eight included studies done in middle-income and low-income countries. This disparity would be of little importance if country and cultural context did

Low income Middle income Lower-middle income Upper-middle income High income

Internet

Overall

SME 0·01 (0·17) 0·06 (0·09) 0·02 (0·03) 0·06 (0·07) 0·12 (0·12)

Mean eff ect (min per week) 0·61 (1·20) 4·76 (5·99) 1·71 (2·32) 4·68 (4·50) 8·88 (7·42)

WPE (min per week) 0·07 3·44 0·62 1·68 1·46

Website interventions

SME 0·02 (0·03) 0·13 (0·13) 0·05 (0·05) 0·13 (0·08) 0·25 (0·11)

Community interventions

SME 0·01 (0·02) 0·11 (0·10) 0·04 (0·04) 0·11 (0·06) 0·20 (0·07)

Clinical interventions

SME, population-wide eff ect 2·6% 0·00 (0·00) 0·00 (0·00) 0·00 (0·00) 0·00 (0·00) 0·01 (0·00)

SME, population-wide eff ect 40% 0·01 (0·01) 0·04 (0·04) 0·02 (0·01) 0·04 (0·02) 0·08 (0·03)

SME, unadjusted 0·01 (0·02) 0·11 (0·09) 0·04 (0·04) 0·10 (0·06) 0·20 (0·07)

Mobile phones

Overall

SME 0·06 (0·07) 0·14 (0·14) 0·11 (0·14) 0·18 (0·16) 0·18 (0·17)

Mean eff ect (min per week) 4·37 (5·72) 10·96 (10·91) 8·22 (10·91) 13·52 (12·45) 14·03 (12·67)

WPE (min per week) 0·51 7·91 2·98 4·87 2·27

Telephone interventions

SME 0·19 (0·15) 0·48 (0·22) 0·36 (0·22) 0·60 (0·21) 0·62 (0·20)

Community interventions

SME 0·10 (0·07) 0·25 (0·09) 0·19 (0·09) 0·31 (0·06) 0·33 (0·04)

Clinical interventions

SME, population-wide eff ect 2·6% 0·00 (0·00) 0·01 (0·00) 0·00 (0·00) 0·01 (0·00) 0·01 (0·00)

SME, population-wide eff ect 40% 0·04 (0·03) 0·10 (0·03) 0·07 (0·04) 0·12 (0·02) 0·13 (0·02)

SME, unadjusted 0·10 (0·07) 0·25 (0·109) 0·18 (0·09) 0·30 (0·05) 0·32 (0·04)

Data in parentheses are SD. SME=standardised mean eff ect. WPE=potential eff ect weighted by population distribution.

Table 1: Potential eff ect of the internet on physical activity interventions (based on eff ect estimates from web-based physical activity interventions and other physical activity interventions) and the potential eff ect of mobile phones on physical activity interventions (based on eff ect estimates from telephone-based physical activity interventions and from other physical activity interventions), by country income

Low income Middle income Lower-middle income

Upper-middle income

High income

PET –0·123 –0·786 –0·477 –0·798 –3·114

SD 0·137 0·816 0·383 0·816 2·084

WPE –0·016 –0·555 –0·271 –0·110 –0·500

Fuel increase, short term

PEF 0·001 0·008 0·005 0·008 0·031

WPEF 0·000 0·014 0·007 0·003 0·013

Fuel increase, long term

PEF 0·003 0·020 0·012 0·020 0·078

WPEF 0·000 0·014 0·007 0·003 0·013

PET=potential eff ect of car ownership on active travel time (min per day). WPE=weighted potential eff ect, by population distribution. PEF=potential eff ect of 10% fuel price rise on daily min of physical activity. WPEF=weighted potential eff ect, by population distribution, of 10% fuel price rise on daily min of physical activity.

Table 2: Potential eff ect of car ownership on active travel min per day, by country income

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not matter in the selection and eff ectiveness of inter-ventions. The results of an evidence-based review of physical activity interventions in Latin America, however, suggest that there are major diff erences between the types of physical activity interventions used in North and South America.86

Countries with low and middle incomes account for 84% of the global population, 80% of mortality from non-communicable diseases, and—as shown in the simulation model—most of the potential increase in population physical activity. The potential eff ect of information and communication technologies and transport megatrends is also more important in countries with low and middle incomes than in those with high incomes, even though penetration of the technologies is greatest in high-income countries. An especially interesting contrast was noted between the distributions and trends for internet access and mobile phone ownership by country income. Internet access is much higher in high-income countries, whereas access to mobile phone and SMS technology is already almost equal in countries with upper-middle and high incomes; by 2020, this pattern is also likely to be true for countries with lower-middle incomes.

This type of contextual evidence has important rami-fi cations for delivery of public health interventions to

address physical inactivity. The direct and potentiating eff ects of information and communication technologies are impressive compared with the pooled overall eff ect sizes of planned physical activity interventions. For example, our model predicts an eff ect of web technology on physical activity interventions in high-income coun tries of 9 min per week, and eff ect sizes of 14 min per week for mobile phone technology in countries with upper-middle and high incomes. In other words, the potentiating eff ects of these widespread technologies are roughly the same size as the mean eff ect size of targeted physical activity interventions. During the next decade, the relative reach and importance of SMS technology in low-income and middle-income countries will further increase. Just as for research in these countries, however, little research exists on mobile-phone-based and SMS-based physical activity interventions. Only three of the 95 primary reviews that we identifi ed focused on mobile phones, of which none included studies done in low-income and middle-income countries. We therefore have little knowledge of the eff ectiveness of the types of interventions that might be potentiated by these infl uential global megatrends.

Social equity is an important modifi er of the potential eff ectiveness of physical activity interventions. Increased access to information and communication technologies and motor vehicles has been associated with sedentary

A

B

Low incomeLower-middle income

Country income level

Upper-middle incomeHigh income

Figure 3: Mismatch between world population and evidence for physical activity interventions as measured by scientifi c publicationsCountries in this density-equalising map are resized according to country population (A) and number of times a country is reported to be included in a review (B).

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lifestyles, as well as with wealth, within and between countries. The digital divide, however, might not apply to all technologies. The case study of an SMS-based physical activity intervention (panel 2) shows that this intervention strategy can be eff ective in a low-income population at high risk of inactivity. The results of our simulation model show that because access to SMS diff ers little between middle-income and high-income countries, the modelled eff ect of SMS on physical activity is actually increased in middle-income countries, which account for 71% of the global population; this conclusion suggests that mobile phones might be a less inequitable way of delivering interventions to promote physical activity than would be the internet in countries of all incomes.

Similarly, within the transport sector, there might be positive eff ects from trends in development and tech-nology in addition to the well documented negative health eff ects of motor vehicle use. The case study of congestion charging in London, UK, presented in the appendix p 12, is a good example of a transport-sector policy already used in high-income countries and dependent on automatic

number plate recognition, mobile communications, and related tech nologies for its successful operation, which has the potential to increase the use of physically active modes of transport (walking and cycling). Of even greater relevance is the case of Bogotá, Colombia, where a series of urban policies, infrastructure changes, and pro-grammes are associated with increased physical activity. The best studied programme in Bogotá, the Ciclovía, attracts about a million users every week, most from low and middle socioeconomic strata. The case studies that we present suggest that not all trends in transport, development, and technology will inevitably have undesir-able eff ects on physical activity, and that some types of interventions might actually narrow gaps in physical activity and health associated with social inequity.

Our model has several limitations. As noted, very few studies of physical activity interventions have been done in low-income and middle-income countries. Eff ect size estimates are, therefore, disproportionately aff ected by studies from high-income countries and might not accu-rately refl ect interventions applied worldwide. Although megatrends for information and commu nication tech-nologies and car ownership are clear, few data are available for the association between these factors and physical activity. Modelling of the complex bidirectional associations that potentially exist between information and communication technologies, car owner ship and use, and overall transport choices is especially diffi cult. For example, car ownership might be associated with inactivity and obesity, but also with improved overall health status. Increased access to infor mation and com-munication technologies can increase sedentary time, but might also allow delivery of physical activity inter-ventions. We could not include the potential positive eff ect of urban planning and transport inter ventions, such as BRT and the Ciclovía, in the model because eff ect sizes on physical activity for these strategies have not yet been reported.

There are also limitations inherent in the structure of the model that we developed. We fi tted the potential eff ects of physical activity interventions as random distributed variables, independent of megatrend ex-posure. We assumed independence between the inter-vention eff ect estimates and megatrend exposure, but actual global data for the relation between exposure to megatrends and interventions are not available. Future studies might consider a Bayesian approach, including the conditional probability of exposure to an intervention given megatrend exposure. For example, studies of internet-based inter ventions could take into account varying exposure to the megatrend by tracking of webpage traffi c. For car owner ship, studies need to assess the potential for activity substitution (eg, use of car versus walking, cycling, or use of another type of motor vehicle) with specifi c physical activity inter ventions. Unlike the models for the internet and mobile phone megatrends, the model for car ownership depended on

Panel 2: Case study: texting to promote physical activity

The use of short-messaging services (SMS or text messaging) has risen as a low-cost way to deliver reminders and information to large numbers of individuals wishing to change their health-related behaviours, including physical activity. Although the reliance on some technologies might exclude people from low socioeconomic backgrounds, the use of mobile phones has substantially increased in recent years in low-income populations in most parts of the world, making SMS a channel with potential broad reach to underserved populations.51 A study in Australia used an SMS-based intervention to increase physical activity in postnatal women, a population at high risk of inactivity, and specifi cally recruited women from communities with high representations of single-parent families and low education, and low-income households.49 Participants received 42 text messages during the 13-week intervention that contained personally tailored behavioural and cognitive tips for increasing activity, ranging across themes from social support to physical activity opportunities in their neighbourhoods. Across the 13 weeks, those who received text messaging signifi cantly increased their frequency of moderate-to-vigorous physical activity and frequency of walking for exercise. These participants also reported signifi cantly greater min per week of walking for exercise than those who did not receive the SMS reminders.

Mobile phone use is also increasing in low-income and middle-income countries, drawing attention to text messaging as a channel with large potential global reach.47,48 Harnessing the growing reach of mobile phones in countries with low and middle incomes, the Kenyan WelTelKenya project implemented an SMS-based intervention to increase adherence to antiretroviral treatment (ART) in new HIV-infected patients.99 Although most participants (76%) lived on less than US$5 per day, 87% owned their own mobile phone and the remaining 13% had access to a phone. For a year, participants in the intervention group were sent one text message per week inquiring about their status, if they had any problems, and asking them to respond within 48 h. Adequate adherence (taking >95% of pills) was reported in 62% of the intervention group compared with 50% of the standard care group, and was accompanied by a signifi cant decrease in disease outcomes. In view of the high cost of ART drugs, the inclusion of SMS seems to be an especially cost-eff ective way to improve adherence and to potentially improve public health. With the high prevalence of both physical inactivity and mobile phone access in low-income and middle-income countries, SMS-based interventions to initiate and maintain physical activity in these countries seem quite promising.

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one estimate of the exposure-outcome relation between car ownership and active travel time from a cross-sectional observational study in the UK.75

Even with these limitations, the results of our review of physical activity interventions and the simulation model incorporating these reviews and megatrends have important implications for research and policy. A much more global perspective is clearly needed for both physical activity research and practice. Physical activity interventions and policies are unlikely to be optimised when more than 90% of the evidence and experience comes from high-income countries, while 84% of the world lives in the very diff erent context of low-income and middle-income countries. This issue also suggests a major need to develop research capacity for physical activity within countries with low and middle incomes to build a contextually appropriate base of type 3 evidence.

Megatrends and policies in sectors beyond health seem to have major potential eff ects on population-level physical activity. To improve understanding of these complex eff ects, multisectoral research teams incorp-orating behavioural, economic, and social sciences using a combination of qualitative and quantitative methods, including modelling and policy analysis, will be needed. The challenge of focusing research in countries with low and middle incomes, at the same time that the overall complexity of methods and research teams is mounting, could be partly addressed by an increased emphasis on international collaboration in research and training.

Although technology-based physical activity inter-ventions seem promising, they certainly need additional insight and improvement. Global access to these tech-nologies, as well as the eff ects that they might have on activity and inactivity, need to be considered. Our model suggests that policies focused on enhanced access to mobile phones and delivery of interventions by this medium could be especially important. New technolo gies, such as smartphones, interactive voice response, and interactive video games, are increasingly prevalent in high-income countries, but are more expensive than traditional mobile phones. These technologies might become impor-tant mediums for promotion of physical activity globally, if prices drop suffi ciently for them to become as ubiquitous as standard mobile phones are today.

Policy changes in transportation and planning will also be important. Intersectoral approaches with the potential to promote physical activity as a cobenefi t already exist, including carbon pricing, integrated transit systems, traffi c restriction, and increasing green space and bike-pedestrian networks. Enhancement of these strategies, especially in the context of countries with low and middle incomes, and consideration of social justice and equity seem to be logical steps towards improved promotion of global physical activity. As important as it might be to improve placement of physical activity

within health-care systems and public health, the greatest potential to increase population-level physical activity might be through creation of supportive policies in other sectors. Global megatrends in information and communication technologies and transportation seem to have important eff ects on physical activity directly and by potentiating inter vention strategies.ContributorsMP designed the study and other authors provided critical input. OLS and FM did the systematic search and modelling procedures, and developed the tables and fi gures with input from the other authors. All authors drafted sections of the report and provided critical review of the draft.

Lancet Physical Activity Series Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk, Harold W Kohl 3rd, Estelle Victoria Lambert, I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of InterestWe declare that we have no confl icts of interest.

AcknowledgmentsThe fi ndings and conclusions in this report are those of the authors and do not necessarily represent the offi cial position of the US Centers for Disease Control and Prevention (CDC). We thank Andrés Medaglia González and Roberto Zarama for their mentoring support and Carlos Grijalba, Carlos Pedraza, and Andrea Ramirez for their contributions to the systematic search (Universidad de los Andes, Bogotá, Colombia), and Britta Larsen (University of California San Diego, San Diego, CA, USA) and Madalena Soares (CDC) for their assistance with the report; several organisations that have provided grant support to one or more of the authors and their research teams: the Coca Cola Company (unrestricted training grant to the CDC Foundation in support of the work of MP, LGP, and Madalena Soares); the International Union for Health Promotion and Education (partial support of in-person writing meetings in Atlanta, GA, USA, and Rio de Janeiro, Brazil); the Centre for Diet and Activity Research, a UKCRC Public Health Research Centre of Excellence funded by the British Heart Foundation, Economic and Social Research Council, Medical Research Council, National Institute for Health Research, and the Wellcome Trust under the auspices of the UK Clinical Research Collaboration (support of DO); the Center for Interdisciplinary Studies in Basic and Applied Complexity, CeiBA (Bogotá, Colombia; Colciencias grant 519 2010, support of FM); and the CDC Prevention Research Center’s programme contract U48/DP001903 (Applying Evidence–Physical Activity Recommendations in Brazil) for support of RCB.

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79 Bell AC, Ge K, Popkin BM. The road to obesity or the path to prevention: motorized transportation and obesity in China. Obes Res 2002; 10: 277–83.

80 Pucher J, Peng Z-R, Mittal N, Zhu Y, Korattyswaroopam N. Urban transport trends and policies in China and India: impacts of rapid economic growth. Transport Reviews 2007; 27: 379–410.

81 Besser LM, Dannenberg AL. Walking to public transit: steps to help meet physical activity recommendations. Am J Prev Med 2005; 29: 273–80.

82 MacDonald JM, Stokes RJ, Cohen DA, Kofner A, Ridgeway GK. The eff ect of light rail transit on body mass index and physical activity. Am J Prev Med 2010; 39: 105–12.

83 Villanueva K, Giles-Corti B, McCormack G. Achieving 10 000 steps: a comparison of public transport users and drivers in a university setting. Prev Med 2008; 47: 338–41.

84 Wener R, Evans G. A morning stroll: levels of physical activity in car and mass transit commuting. Env Behav 2007; 39: 62–74.

85 Gomez LF, Sarmiento OL, Parra DC, et al. Characteristics of the built environment associated with leisure-time physical activity among adults in Bogota, Colombia: a multilevel study. J Phys Act Health 2010; 7 (suppl 2): S196–203.

86 Hoehner CM, Soares J, Parra Perez D, et al. Physical activity interventions in Latin America: a systematic review. Am J Prev Med 2008; 34: 224–33.

87 Cervero R, Sarmiento OL, Jacoby E, Gomez LF, Neiman A. Infl uences of built environment on walking and cycling: lessons from Bogota. Int J Sust Transp 2009; 3: 203–26.

88 Zarama R, Sarmiento OL. Ciclovías y ciclorutas: sistemas complejos promotores de modos de transporte sostenible. Unpublished.

89 Montes F, Sarmiento OL, Zarama R, et al. Do health benefi ts outweigh the costs of mass recreational programs? An economic analysis of four Ciclovía programs. J Urban Health 2012; 89: 153–70.

90 Ogilvie D, Griffi n S, Jones A, et al. Commuting and health in Cambridge: a study of a ‘natural experiment’ in the provision of new transport infrastructure. BMC Public Health 2010; 10: 703.

91 Pucher J, Dill J, Handy S. Infrastructure, programs, and policies to increase bicycling: an international review. Prev Med 2010; 48: S106–25.

92 Yang L, Sahlqvist S, McMinn A, Griffi n SJ, Ogilvie D. Interventions to promote cycling: systematic review. BMJ 2010; 341: c5293.

93 Ogilvie D, Foster CE, Rothnie H, et al. Interventions to promote walking: systematic review. BMJ 2007; 334: 1204.

94 Ogilvie D, Egan M, Hamilton V, Petticrew M. Systematic reviews of health eff ects of social interventions: 2. Best available evidence: how low should you go? J Epidemiol Community Health 2005; 59: 886–92.

95 Heath GW, Parra DC, Sarmiento OL, et al, for the Lancet Physical Activity Series Working Group. Evidence-based physical activity interventions: lessons from around the world. Lancet 2012; published online July 18. http:/dx.doi.org/10.1016/S0140-6736(12)60816-2.

96 The World Bank. World development indicators. 2011.97 Conn VS, Hafdahl AR, Mehr DR. Interventions to increase physical

activity among healthy adults: meta-analysis of outcomes. Am J Public Health 2011; 101: 751–58.

98 Rose G. Sick individuals and sick populations. Int J Epidemiol 1985; 14: 32–38.

99 Lester RT, Ritvo P, Mills EJ, et al. Eff ects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial. Lancet 2010; 376: 1838–45.

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Lancet 2012; 380: 294–305

Published OnlineJuly 18, 2012

http://dx.doi.org/10.1016/S0140-6736(12)60898-8

This is the fi fth in a Series of fi ve papers about physical activity

*Members listed at end of paper

University of Texas Health Science Center, Houston School of Public Health, and University

of Texas at Austin Department of Kinesiology and Health

Education, Austin, TX, USA (Prof H W Kohl 3rd PhD);

Canadian Fitness and Lifestyle Research Institute, Ottawa, ON,

Canada, and School of Public Health, University of Sydney,

Sydney, NSW, Australia (C L Craig MSc); UCT/MRC

Research Unit for Exercise Science and Sports Medicine,

Department of Human Biology, Faculty of Health Sciences,

University of Cape Town, Cape Town, South Africa

(Prof E V Lambert PhD); Tokyo Medical University, Department

of Preventive Medicine and

Physical Activity 5

The pandemic of physical inactivity: global action for public healthHarold W Kohl 3rd, Cora Lynn Craig, Estelle Victoria Lambert, Shigeru Inoue, Jasem Ramadan Alkandari, Grit Leetongin, Sonja Kahlmeier, for the Lancet Physical Activity Series Working Group*

Physical inactivity is the fourth leading cause of death worldwide. We summarise present global eff orts to counteract this problem and point the way forward to address the pandemic of physical inactivity. Although evidence for the benefi ts of physical activity for health has been available since the 1950s, promotion to improve the health of populations has lagged in relation to the available evidence and has only recently developed an identifi able infrastructure, including eff orts in planning, policy, leadership and advocacy, workforce training and development, and monitoring and surveillance. The reasons for this late start are myriad, multifactorial, and complex. This infrastructure should continue to be formed, intersectoral approaches are essential to advance, and advocacy remains a key pillar. Although there is a need to build global capacity based on the present foundations, a systems approach that focuses on populations and the complex interactions among the correlates of physical inactivity, rather than solely a behavioural science approach focusing on individuals, is the way forward to increase physical activity worldwide.

The pandemic of physical inactivity should be a public health priorityTheoretically, prioritisation for public health action is informed largely by three factors: the prevalence and trends of a health disorder; the magnitude of the risk associated with exposure to that disorder; and evidence for eff ective prevention and control. A practice or behaviour that is clearly related to a health disorder, is prevalent, and is static or increasing in its prevalence should be a primary target for public health policy for disease prevention and health promotion. Too often, however, the inertia of tradition, pressure from special interest groups, media attention, and other external forces can overcome this approach.

Available data suggest that 31% of the world’s popu-lation is not meeting the minimum recommendations for physical activity1 and, in 2009, the global prevalence of inactivity was 17%.2 Despite promising positive trends in leisure-time (discretionary) physical activity in some countries, incidental, transportation-related, and occu-pational physical activity prevalences are falling.3–6 The global challenge of physical inactivity is further amplifi ed by the risk it conveys. Lee and colleagues7 presented persuasive evidence that 6–10% of all deaths from non-communicable diseases worldwide can be attributed to physical inactivity, and this percentage is even higher for specifi c diseases (eg, 30% for ischaemic heart disease).8 In 2007, 5·3–5·7 million deaths globally from non-communicable diseases could have theoretically been prevented if people who were inactive had instead been suffi ciently active. Most of these eff ects of physical inactivity are not mediated through body composition. Finally, several approaches have acceptable eff ectiveness for increasing physical activity across diff erent ages, social groups, and countries worldwide.9 In view of the prevalence, global reach, and health eff ect of physical inactivity, the issue should be appropriately described as pandemic, with far-reaching health, economic, environ-mental, and social consequences.

Moreover, the associated morbidity of health disorders related to inactivity, including health-related quality of life as well as direct and indirect economic costs, exerts a substantial burden on societies and health systems. For example, annual direct health-care costs range from US$28·4 to $334·4 per head in Australia,10 UK,11 and Switzerland12 and, including indirect costs, from $154·7 to $418·9 per head in Canada13 and the USA.14 The magnitude of economic implications of physical inactivity is diffi cult to compare at present, and a more in-depth global analysis is needed.

Key messages

• The high prevalence of physical inactivity, its harmful health and environmental consequences, and the evidence of eff ective physical activity promotion strategies, make this problem a global public health priority

• Physical activity and public health is a new discipline, merging several areas of specialisation including epidemiology, exercise and sport science, behaviour science, and environmental health science, among others; these diff erent areas are needed to tackle the global pandemic of physical inactivity because multidisciplinary work is essential

• Early development of the discipline has been largely opportunistic and, as a result, physical activity has usually been coupled with other public health agendas and is often not a fully recognised, standalone, public health priority

• Capacity building, workforce training, and intersectoral approaches are needed in all regions for physical activity research, practice, policy, and advocacy and education

• A systems approach to physical activity beyond a reliance on behavioural science needs coordinated changes at the individual, social and cultural, environmental, and policy levels; building of intersectoral action is particularly needed in countries with low-to-middle incomes, where the unintended consequences of development might negatively aff ect transport-related, household, and occupational physical activity

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Public Health, Tokyo, Japan (Prof S Inoue MD); Department of Physiology, Faculty of Medicine, The Health Sciences Center—Kuwait University, Kuwait City, Kuwait (J R Alkandari PhD); National Health Security Offi ce, Bangkok, Thailand (G Leetongin MD); and Physical Activity and Health Unit, Institute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland (S Kahlmeier PhD)

Correspondence to:Dr Harold W Kohl 3rd, University of Texas Health Science Center, Houston—School of Public Health, Austin Regional Campus, Michael and Susan Dell Center for Healthy Living, Austin, TX 78701, [email protected]

Social and economic transitions that aff ect popula-tions can have a profound eff ect on health and health behaviour. For example, the rapid economic development and drastic social changes in many Latin American countries in recent years have been mirrored by a rapid trend away from undernutrition and micronutrient defi ciencies to overnutrition and obesity, along with an ageing population and an increase in the prevalence of non-communicable diseases.15 That physical activity is also related to development is particularly evident and of concern in low-income and middle-income countries, where occupational, domestic, and transport-related physical activities might contribute more to overall energy expenditure than does leisure time or recreational activity.16 Moreover, in the fourth paper in this Series, Pratt and colleagues17 presented compelling models showing the potential eff ect of developing global information and communications technologies on physical activity.

Increasing urbanisation and rapid economic devel-opment in China have been linked to reductions in overall and occupational physical activity in adults16,18 as well as increased television viewing in children.19 Simi-larly, in Africa, rural-to-urban migration is associated with reductions in prevalence of physical activity.20,21 In some cases, the urban-to-rural gradient for inactivity more than doubles. The challenge is magnifi ed in view of the fact that, in 20 years, 60% of west Africans will live in urban areas and two-thirds of people moving into urban areas in Africa do so into poverty. Such large shifts in physical activity demand scrutiny with a public health lens to assess the population-level causes, rather than a solely clinical view, to understand the causes of inactivity among individuals.22

Important global progress has been made in organ-isation and mobilisation of eff orts for tobacco and alcohol control23,24 and promotion of a healthy diet.25,26 Physical inactivity has begun to be recognised as the fourth type of exposure that needs to be addressed for control of non-communicable diseases.27 However, and despite robust research on how to address physical inactivity,9 there has been an evidence-policy gap for action. As a relative newcomer to the area, physical activity has yet to garner equal global organisation and advocacy power to receive the appropriate political recognition and investments. The eff ect of this tardiness has been to put physical activity in reverse gear compared with population trends and advances in tobacco and alcohol control and diet. This unacceptable situation needs to be addressed with haste if the world is to reach its goals for control of non-communicable diseases.27 In the next sections, we summarise existing global physical activity eff orts and emphasise challenges that point the way forward to address the global pandemic of physical inactivity. We argue that lasting progress needs to be built on early eff orts, but that a full systems approach should be taken to fully integrate physical activity into public health.

Advancement of physical activity and public health: building on existing progressOverviewPhysical activity promotion to improve the health of populations, rather than individual behaviours, has only had an identifi able infrastructure since 2000. The reasons for this late start are myriad and complex. First, there is a perception, albeit incorrect, that the science base for physical activity and health has lagged behind other important issues such as tobacco use and diet. Second, as a result of a grafting of exercise science to public health science, the specialty of physical activity and public health has its roots in several areas. Exercise science, epidemiology, behavioural science, environmental health science, and others have each contributed to the emergence of the discipline of physical activity and public health and the absence of centralisation has resulted in diff use and uncoordinated development. As such, early action in training and growth of infrastructure has often been opportunistic rather than systematic. Finally, physical activity has frequently been coupled with diet28,29 to address obesity, rather than defi ned as a standalone public health issue, despite evidence for many independent health eff ects of physical activity and physical inactivity.30 Such opportunistic approaches by coupling or integration with other health determinants might have merit for the physical activity policy agenda for some health outcomes, but they unavoidably restrict the scope of action and impede a full approach to address all aspects of physical activity and inactivity. Further, such partnering for convenience should not to be confused with building of equally footed partnerships for action.

What resources and strategies are needed to move physical activity and public health to the mainstream?31 To harness the science for public health action, creative thinking coupled with development of partnerships for action are needed to help physical activity to become a public health priority. Global capacity building in physical activity is crucial. A systematic approach to capacity building involves an assessment of existing capacity and resources, planning and target setting, intersectoral collaboration built on a strong foundation of leadership and advocacy, workforce development in teaching, research and practice, and monitoring of progress. Global capacity building should be advanced by evolving and expanding existing assets. Figure 1 shows a timeline of major international benchmarks as the specialty has emerged in four broad areas. For each area, progress is detailed to provide direction for further development of global capacity.

Policy and planningTwo major global eff orts have occurred since 2000 in policy and planning. First, in 2004, the World Health Assembly adopted the WHO global strategy on diet, physical activity, and health28 and WHO subsequently published implementation aids in support of the

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strategy.42–44 Second, a UN high-level meeting on non-communicable diseases was convened in September, 2011,32 specifi cally to address prevention and control eff orts of diseases that claimed 63% of global deaths in 2008. At the UN meeting, physical inactivity was identifi ed as an important determinant of non-communicable diseases globally, but received less emphasis than tobacco, alcohol, and diet. These two eff orts are obviously important in their contexts and have certainly been seminal in raising international awareness of the issues of physical inactivity. However, the absence of focus specifi cally on inactivity in these two initiatives in favour of coupling with diet serves to weaken eff orts for broad, focused approaches to tackle physical inactivity. For example, the fi rst version of the currently proposed global monitoring framework for the prevention and control of non-communicable diseases45 did not contain a target or indicators for physical inactivity, although such indicators were present for tobacco, diet, and alcohol. Targets and indicators for physical inactivity were subsequently included in the second draft version of the document only after substantial advocacy eff orts by many interested parties including the global and regional networks. If physical activity is not retained, the four factors that are meant to support non-communicable disease prevention (physical activity, tobacco control, diet, and alcohol) will be eff ectively reduced unacceptably to only three. Member states will then not have a mandate for action to address physical activity as a matter of public health urgency.

Another topic for consideration is that physical activity promotion is not only important for the prevention of

non-communicable diseases, but it might also play a key part in eff orts against global warming through the pro-motion of active transportation, improvement of social relationships, reduction of social inequities, and stimu-lation of the use of public spaces. Global eff orts in the policy and planning area urgently need to place health promotion, in this case through physical activity practice, as much more than a risk factor for non-communicable diseases, but actually a basic human right.

One crucial approach to build capacity and infra-structure in physical activity and public health is the development and implementation of national policies and action plans.46 A recent WHO report suggests47 that, although 73% of member states reported having an identifi able plan, strategy, or policy to address physical inactivity, only 55% of these plans, strategies, or policies were reported to be operational. Further, only 42% were operational as well as funded. Sub stantial global variation exists, with reported plans, strategies, or policies less prevalent (46%) in the African WHO region, but uni-versal (100%) in the southeast Asia WHO region. There was also a substantial diff erence between income groups, with 82% of countries with upper-middle incomes reporting plans relative to 68% of those with lower-middle incomes. These data provide the fi rst global overview, but validation of these self-reported data is needed because items could have been interpreted and reported diff erently by diff erent countries.

What constitutes good policy for physical activity promotion? The mere existence of a national physical activity policy or action plan does not secure its func-tionality or implementation. Plans are not imple men-tation, implementation is not strategy, and strategies are not evidence of population change. Nor does the existence of a national policy necessarily produce success. Ideally, national policies and action plans are designed not for implementation solely by governments, but rather for mobilisation of both governmental and non-governmental collaboration towards advancement of physical activity and reduction of physical inactivity. The recent Brazilian experience is one from which many such lessons can be learned.48 Similar action is needed worldwide.

A policy audit tool was developed49 on the basis of a literature review of previous work on cross-country comparisons on physical activity policy,46,50–53 identifying a set of 17 key attributes identifi ed as essential for successful implementation of a population-wide ap-proach to promote physical activity across the lifecourse. These attributes include an evidence-based, consultative approach and integration across sectors and policies, national recommendations on physical activity levels, national goals and targets, an implementation plan including several strategies and evaluation based on a national surveillance system. Successful implementation also depends on political commitment and sustainable funding, leadership and coordination, working in part-ner ship, a network supporting professionals as well as

Figure 1: Emergence of global infrastructure for physical activity and public healthWHO DPAS=WHO global strategy on diet, physical activity and health.28 UN NCD=UN high-level meeting on non-communicable disease.32 HEPA=Health Enhancing Physical Activity.33 RAFA/PANA=Red Actividad Fisica de las Americas/Physical Activity Network of the Americas.34 AP-PAN=Asia Pacifi c Physical Activity Network.35 GAPA=Global Advocacy for Physical Activity.36 AFRO-PAN=Africa Physical Activity Network.37 CDC/IUHPE=Centers for Disease Control and Prevention/International Union for Health Promotion and Education. JPAH=Journal of Physical Activity and Health.38 ISPAH=International Society for Physical Activity and Health.39 IPAQ=international physical activity questionnaire.40 GPAQ=global physical activity questionnaire.41

Policy and planning

WHO DPAS(2004)

UN NCD(2011)

HEPA Europe(2005)Leadership and advocacy

RAFA/PANA(2000)

Agita Mundo(2002)

AP-PAN(2005)

GAPA(2007)

AFRO - PAN(2010)

Professional development and training CDC/IUHPE(2004)

JPAH(2004)

ISPAH(2009)

Surveillance

IPAQ(2001)

1995 2000 2005 2010

GPAQ(2005)

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ensuring links between policy and practice, and a communication strategy and a clear programme brand-ing. The policy audit tool can act as a catalyst for increased communication and joint strategic planning by identi fying synergies and discrepancies among policy areas (appendix).

Leadership and advocacyThe tardy emergence of physical activity and public health as a distinct discipline can partly be attributed to disparate leadership and the fact that, to date, physical activity has not been fi rmly rooted in public health. As shown in fi gure 1, regional networks have been the foundation in this area. The fi rst regional network in the world was Red Actividad Fisica de las Americas (Physical Activity Network of the Americas; RAFA/PANA).34 RAFA/PANA seeks to harness substantial resources and interest in physical activity from Canada to Chile. RAFA/PANA was followed by similar eff orts to coalesce several interests in Europe,33 Asia-Pacifi c,35 and most recently Africa.37 A global physical activity network initiative, Agita Mundo,54 has evolved simultaneously from early beginnings in Brazil.55

These networks all have the common goal to provide a platform for exchange of experiences, to strengthen existing initiatives, and to identify and disseminate good practice. Other goals include advocacy, dissemination of knowledge, workforce training, and the development of national networks or research collaborations. The described poor support for physical activity is also illustrated by the fact that none of these networks receives sustainable institutional support of any kind, so they all depend almost entirely on voluntary contributions of central steering bodies and member institutions. Despite scarce resources, the networks represent mem bers from more than half the countries in each region and have produced tangible results and products. For example, through the leadership of the RAFA/PANA network, nine national networks have been formed (Colombia, Peru, Argentina, Chile, Costa Rica, Mexico, Uruguay, El Salvador, Venezuela) and, together with Agita Mundo, mass events are organised regularly, which engage millions of partici-pants in physical activity. The European network has established working groups on national approaches, youth and elderly people, and settings such as health care, sport clubs, and working environments and on surveillance and injury prevention, which collect and analyse approaches and case studies and develop guidelines and practical tools for imple mentation. The Asia-Pacifi c network delivers a biweekly newsletter to more than 4000 readers, which has both an advocacy and scientifi c communication function. The most recently formed African network produces a quarterly newsletter, and provides a platform for regional collaborative research and advocacy in various African countries. Early evaluation eff orts for the regional and global networks need to be formalised and expanded.

Regional networks help to support communication and common interest events. Active promotion to advance a

cause needs advocacy. Encouragingly, formal advocacy eff orts have more recently emerged in the fi eld. In 2007, Global Advocacy on Physical Activity36 (GAPA) was launched. GAPA works to strengthen advocacy, dissem-ination, and capacity around physical activity promotion and policy.

While these eff orts proceed, additional approaches are needed to build global capacity in physical activity and public health. Although physical activity has to further establish itself as fully recognised standalone specialty on an equal footing with those of diet, tobacco control, and others, working across diff erent silos and estab-lishing partnerships for action specifi c to physical activity could be the most important advance to be made. For example, many non-governmental organisations have long been involved in sport promotion; however, only recently have networks of these organisations involved in Sports for All and Sports for Development identifi ed health as a key outcome objective, particularly in countries with low and middle incomes.56–58 The Health in All Policies approach59 has emerged to integrate health concerns into policy decisions taken in other sectors. This approach needs increased health system capacity to engage other sectors eff ectively in adopting policies that maximise possible health gains. Success not only needs eff ective advocacy skills, but, more importantly, the ability to identify mutually benefi cial actions that allow the target sectors to achieve their own goals while protecting and promoting health.

A successful example of this approach is an inter national project that was coordinated by WHO. The project developed guidance and practical tools for economic assessments of the health eff ects of cycling and walking.60–62 The products were developed through a systematic review of relevant research followed by a comprehensive con-sensus building process61 involving experts specifi cally selected to represent an inter disciplinary range of profes-sional backgrounds and expertise (health and epidemiology, health and transport economics, a practice or advocacy perspective, policy development and implementation). The project pro duced aids that were transparent and easy to use. Health economic assessment tools for cycling have already been adopted by several countries for their offi cial toolbox for economic assessment of cycling infrastructure and are applicable in countries with high, middle, and low incomes.62,63 These projects show that use of economic arguments to advocate investments into policies that have clear sector-specifi c benefi ts is a promising strategy to win the support of these sectors and could have great potential to result in health benefi ts.

Training and professional developmentDespite seemingly incomplete development of a global physical activity and public health infrastructure, some coordinated workforce training eff orts have emerged. Although certifi cation programmes for exercise pro-fessionals have existed for many years,64,65 the emphasis

See Online for appendix

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on population health has only been recent. The US Centers for Disease Control and Prevention and the International Union for Health Promotion and Education have been drivers of international training eff orts, to educate public health professionals regarding the fundamentals of physical activity, its role in public health, and eff ective strategies for successful physical activity promotion.9 Up to mid-2012, 25 of these international courses have been held in most WHO regions with more than 1400 participants.

In 2004, a professional journal, the Journal of Physical Activity and Health, was launched to help to build scientifi c evidence on physical activity and health38 and the International Society for Physical Activity and Health was organised in 2009 to provide international leadership in the advancement of physical activity for health.39 The crucial need to move physical activity into the public health mainstream involves leadership from these inter-national organisations to further emphasise professional development of practitioners and academic training of researchers and teachers. This need is especially strong in countries with low and middle incomes facing a wave

of economic and social changes that will probably reduce the physical activity demands of daily life.

This training should focus (among other things) on planning, intersectoral collaboration (including sport, health, transportation, and other key areas), imple-mentation of evidence-based physical activity strategies and how to increase demand for access to safe places for physical activity. Social mobilisation is a crucial aspect of this training and has been successfully used in Brazil.36 Public health should lead this eff ort, but other disciplines such as medicine, physical therapy, nutrition, education, psychology and behavioural science, and urban planning and design need to affi liate. Although the needed numbers of practitioners in this area is unknown, it is certainly more than are presently working. If practi-tioners in each of these areas were reoriented to make physical activity a priority in their work, the workforce addressing these needs would be greatly expanded.

Beyond the existing practitioner workforce, academic training should be oriented for preparation of the future generations at all levels. Graduate training specialisations in physical activity and public health should emerge and with them a broad range of core competencies that set a minimum standard of knowledge. The development of the Physical Activity and Public Health Specialist certifi cation by the US National Society for Practitioners of Physical Activity and Public Health66 and the American College of Sports Medicine is a major step forward. Competencies for this certifi cation (and associated sets of knowledge, skills, and abilities) have been developed in six crucial areas: partnership development; use of data and scientifi c information; planning and evaluation; inter-vention; organisational structure; and exercise science in public health. This model can probably be adapted and implemented in other countries.

Formal academic training programmes and graduate training should also be created to guide the next gen-eration of researchers in this area. Global capacity in exercise science, physical education, physical therapy, public health, architecture and planning, and envir-onmental health should not only be increased, but be oriented towards integration and comprehensive approaches to physical activity and public health.

Finally, more research into eff ective programmes that increase physical activity and reduce physical inactivity, particularly in countries with low and middle incomes, is needed to help to further build the evidence base for their national policies and action plans.42 To expedite this process, journals could ideally consider adopting editorial policies to support and perhaps even fast-track articles on inter-ventions in low-income and middle-income countries.

Monitoring and surveillancePhysical activity and public health was advanced sub-stantially by the development and implementation of standardised surveillance tools for physical activity. The

Panel 1: Physical activity surveillance: if it is important, it must be measured

Comprehensive surveillance systems are crucial to advance physical activity and public health. The development and introduction of such a comprehensive system poses challenges and is dependent on the capacities and resources available. Yet having such physical activity information will serve to improve investment of scarce resources, increase accountability, and help to make effi cient and eff ective investments. Canada’s experience provides one example of how comprehensive physical activity surveillance can be implemented. In the mid-1990s, a needs assessment was done with scholars, representatives of federal and provincial or territorial (state) governments, and national-level non-governmental organisations. Key indicators were identifi ed at the individual, social, and physical environment levels across schools, workplaces, and municipalities (land-use, transportation, recreation systems). Results have been used for advocacy, setting targets, tracking of progress (related to capacity, policies, programmes, and services), shaping of policy and strategies, market segmentation, and evaluation of health education campaigns. Canada’s system evolved over time to include many data sources including objective as well as self-report measures. Data sources have included regular specifi c population-based and setting-based (eg, schools, workplaces, municipalities) surveys, supplemented by population health surveys and transportation surveys. As data became available, its value in guiding policy and practice was recognised and demand for data increased. Therefore, it was important to have a long-term vision for surveillance and to implement components of the system as capacity and commitment to measurement grew. As new measures were included, existing measures were retained at least on a periodic basis. Otherwise, if methods or questions or measures had changed, trends over time could not have been assessed.

Other countries can learn from these lessons by creating their own vision of what population and sector-related data would be needed to assess changes in the conditions that aff ect physical activity in their country and what policies and interventions they might adopt to increase physical activity and decrease sedentary behaviour. A core set of indicators could then be identifi ed within this framework and measured over time as commitment to surveillance strengthens. The key to implementation of a policy-relevant system is to begin with a comprehensive vision of what data are needed to inform policy and practice and then to implement the various elements of that system as feasible.

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international physical activity questionnaire40 and the global physical activity questionnaire41 have provided ways for specifi c countries on a regional and global scale to gather data for the prevalence of people meeting physical activity recommendations, the prevalence of physical inactivity, and (for the global questionnaire) domain-specifi c behaviour estimates. However, as dis cussed in the fi rst paper of this Series,1 persistent gaps are noted in physical activity surveillance including the scarcity of continuous surveillance systems implemented at the national level (resulting in an absence of trend data), any data in a third of countries, and standardised data for active transportation, sedentary behaviours, and school physical education class attendance among indicators.

Optimum physical activity surveillance focuses on levels and behaviours, their determinants and outcomes, and indicators of proven and promising solutions to address low physical activity in various segments of the population. As such, the focus is not the traditional epidemiological disease-case fi nding approach to sur-veillance, but rather the monitoring of trends in people’s physical activity behaviour and assessment of progress in changing the underlying determinants that aff ect physical activity. Physical activity surveillance should provide information for policies and interventions that reside in many sectors (health, education, recreation, transportation, land-use planning, etc).

Health-related measures focus on meeting physical activity recommendations and domain-specifi c meas-ures—for example, walking and bicycling for transport, occupational physical activity, attendance of physical education classes at school, physical demands of chores, and participation in physically active recreation and sport. To inform the many levels and sectors needed for intervention, ecological frameworks67 spanning deter-minants and correlates at the individual, social, physical environment, and societal levels are needed to organise the vast array of factors aff ecting physical activity. Assessment of only individual physical activity is not enough to inform policy and planning. Panel 1 describes Canada’s experience with comprehensive physical ac-tivity surveillance.

Beyond behavioural science to public healthThe key question is why progress in physical activity promotion as a public health issue has been less developed than that in other public health areas? The pandemic of inactivity spans the world and economic development and social transitions portend a likely increase in the prevalence of inactivity and the incidence of non-communicable diseases for years to come, par-ticularly in countries with low and middle incomes. The response to physical inactivity has been incomplete, unfocused, and most certainly understaff ed and under-funded, particularly compared with other risk factors for non-communicable diseases. The relative infancy of the specialty and absence of infrastructure might be part of

the reason for slow progress. Noticeably under-repre-sented has been leadership by global, regional, and national health-focused foundations with the means to advance this issue. Further, international leadership provided by the US Centers for Disease Control in physical activity and public health is now on the wane.

A major part of the answer could also lie in the initial approaches to solving the issue. Instead of a population-based public health emphasis, eff orts have focused on individual health. A foundation of public health is the realisation that health and illness have causes that go beyond biology and behaviour.68 For physical activity, a strong case can be made that the science of how to change individual behaviours has overshadowed eff orts to understand true population change. Because of this unbalanced focus, the structural and systemic changes necessary to promote physical activity in populations (with commensurate changes in prevalence) across various sectors have not yet been addressed system-atically. Although much has been learned about how individuals can change their physical activity behaviour and the determinants of those behaviours,69 little pro-gress in population-level changes has been documented. A similar experience occurred in global tobacco control, where initially the burden of responsibility was put solely

Figure 2: Behavioural and environmental (A) and systems (B) approaches to physical inactivityA shows a traditional behavioural or environmental intervention strategy for physical inactivity. Various behavioural theories or environmental models are applied to address individual predisposing factors, an intervention is developed and delivered, and behaviour change (increased physical activity) is expected. B shows a complex systems perspective for physical activity, whereby there is an acknowledgment of issues, such as delay functions, adaptation, unintended consequences, competing interests, and feedback that could negatively aff ect an approach to increase physical activity. Various characteristics might also accelerate or inhibit the speed of the eff ectiveness of the strategies.

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on individuals. Once that view expanded to include recognition of societal responsibility as well, population-level action and changes in smoking prevalence followed. Physical activity has to learn from these examples.

Only recently has research and promotion regarding the environmental eff ects that impede or support individual-level physical activity begun to blossom.70,71 These eff orts defi ne, measure, and interpret the funda-mental aspects of the physical environment in which an individual or sets of individuals live, work, and recreate and how these aspects aff ect physical activity. However, changing the focus of action on environmental infl u-ences would only shift the attention from one type of strategy (behavioural) to another (environmental) with-out full consideration of how individuals behave in given environments and how changes in the environments can aff ect changes in physical activity patterns.

For true change in the global action on physical activity, we have to embrace the complexity of the entire

system in conceiving solutions rather than focusing only on parts of the puzzle such as an individual or an environ mental approach alone.72 A systems approach (fi gure 2) acknowledges the complex non-linearity of health behaviours, including the many interactions, delays in adoption, adaptations, competing actions, and unin tended consequences that can occur within a system. A systems approach acknowledges such com-plexities and allows for planning to counteract the unintended consequences.

A key feature of such complex systems is that many inputs and levels of infl uence are considered to be interdependent. An attempt is made to understand the pathway towards a specifi c health behaviour and not only the simple, univariable or linear determinants at an individual or environmental level. Rather, systems ap proaches identify enablers, accelerants, synergies, and interconnectedness of multiple infl uences and thus have the highest potential to aff ect population physical activity.

As a hypothetical example, a behavioural programme to increase school-based physical activity during phys-ical education could be very successful; however, an unin tended consequence might be that physical activity elsewhere during a day for those children could decrease. Similarly, a transportation policy designed to reduce automobile congestion, improve air quality, and increase access and social equity in a population by increasing eff ective mass transportation options could result in increased incidental and transportation-related physical activity behaviours for one segment of that population, but could actually reduce transportation-related physical activity for other segments, resulting in a net zero gain. Improvements in the mass transit system might not immediately result in adoption (and increased transport-related physical activity) by the target population (delay). Adaptations could occur such that once the novelty of the new transport system wears off , adopters could return to their usual methods of (sedentary) trans portation. Specifi c accelerants and inhibitors (subsidised rider fares, for example) could interact with these and other infl uences and ultimately aff ect physical activity associated with transportation choice. Traditional linear health behaviour models and theories are not designed to take these kinds of inter-actions into consideration. Such work is in its infancy, but wide-scale diff usion of such approaches would accelerate the eff ect of physical activity and public health eff orts throughout the world.

Multiple levels of infl uence in physical activity behav iour is clearly one key aspect of a complex system. As discussed by Bauman and colleagues69 in the second paper in this Series, there is a vast array of determinants of physical activity behaviour initiation, maintenance, and relapse. Public and organisational policy, the phys ical environment, the family and social environment, occupation, individual self-effi cacy, and genetics among others have all been

Panel 2: Call to action: guiding principles

The freedom and opportunity for individuals to participate in physical activity should be viewed as a basic human right. To improve global health by increasing population levels of physical activity, we urge all organisations from the governmental (including national, regional, and local), non-governmental, and private sectors to take action in developing and supporting eff ective physical activity promotion strategies that embrace a systems approach and adhere to the guiding principles of the Toronto Charter, including:• Adopt evidence-based strategies that target the whole

population as well as specifi c vulnerable subgroups• Address the environmental, social, and individual

determinants of physical inactivity• In addressing determinants of physical activity behaviour,

embrace an equity approach to reduce the disparity in access to opportunities for physical activity

• Implement sustainable actions in partnership at national, regional, and local levels and across many sectors to achieve greatest eff ect

• Build capacity and support training in research, practice, policy, evaluation, and surveillance

• Use a lifecourse approach by addressing the needs of children, families, adults, elderly people, and people with disabilities as well as specifi c settings such as worksites and schools

• Advocate to decision makers and the general community for an increase in political commitment to and resources for physical activity

• Ensure tailoring to cultural sensitivities and adapt strategies to accommodate varying local realities, cultures, contexts, and resources

• Allow healthy personal choices by making the physically active choice the easy choice

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studied with respect to their relation to physical activity. Each of these types of determinants probably has diff erent mechanisms of action in diverse sectors. Moreover, the methods of each area diff er and are quite possibly distinct in their approaches of study. It is important to study these infl uencers in relation to understanding of the system in which they operate. Moreover, the relative contributions of the determinants could change and become less or more prominent as systems change.

Additionally, physical activity is not solely a health sector responsibility, nor should it be. City and com-munity planners, transportation engineers, school au th-orities, recreation and parks offi cials, private employ ers and the media, along with health-care workers and public health practitioners all are instrumental in promoting (or inhibiting) population levels of physical activity. Each of these stakeholders has diff erent motiv-ations and goals, interactions with other infl uencers,

Specifi cally, we urge the UN and WHO to:• Provide strong global leadership in promoting a systems

approach to the development, implementation, and monitoring of national physical activity policies, strategies, and action plans

• Ensure targets and indicators for monitoring physical activity, physical inactivity, and sedentary behaviour are adopted and maintained as an integral part of global eff orts aimed at prevention and control of non-communicable diseases

• Partner with others, including other UN organisations, to continue to provide and expand professional training on the fundamentals of physical activity, its role in public health, and public policy and eff ective strategies for action

We urge the World Bank, international development agencies, foundations, and other international agencies to:• Support the work of, and coordination among, global

and regional networks for physical activity promotion, particularly those consisting mainly of countries with low-to-middle incomes, to engage in regional planning, translation of research, exchange of experience, and expertise, and implement regional and national action plans

• Recognise the key role that physical activity has in the prevention of non-communicable diseases and in enhancing the health of populations, particularly in low-income and middle-income countries

• Support the development and implementation of national plans to promote physical activity, particularly in countries with low-to-middle incomes

We urge countries to:• Develop and implement multisectoral strategies and action

plans focused specifi cally on physical activity that are framed within a systems approach

• Assign a clear stewardship role for physical activity to a relevant government body to form a multisectoral infrastructure building on existing structures

• Adopt evidence-based national recommendations and policy guidance on physical activity for health and quantifi ed population targets

• Allocate suffi cient sustainable resources for implementation, as well as evaluation and comprehensive surveillance for accountability

We urge ministries of health to:• Reorient services and funding at national, regional, and local

levels to prioritise physical activity as a standalone area of work

• Foster partnerships including through cross-governmental implementation at all levels and gain input and engagement from all stakeholders that form a broad multisectoral constituency both within and outside government

• Make physical activity an integral part of an overall disease prevention and health promotion model, including screening for physical inactivity, counselling about physical activity in prevention and disease treatment and management strategies as well as increased investment in comprehensive physical activity promotion policies, action plans, and implementation programmes

We urge ministries of education and other education authorities to:• Implement policies that support high-quality, compulsory

physical education• Promote and implement policies that encourage and

support active travel to school• Provide opportunities for physical activity during and after

the school day as well as healthy school environments

We urge ministries of sport and other recreation sector authorities to:• Develop and implement sport and recreation policy and

funding systems that prioritise increased community access to aff ordable physical activity opportunities

• Develop programmes adapted to the needs of particular segments of the community that are less active than others

We urge ministries of planning to:• Support and implement urban and rural planning policies,

design guidelines and building codes that support walking, cycling, public transport, sport, and recreation with a particular focus on equitable access and safety

We urge ministries of transport to:• Prioritise transport policies and services that promote active

forms of non-motorised transport, with an emphasis on equitable access and safety

• Fund infrastructure support for walking, cycling, and public transit

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Panel 3: Call to action: key actions necessary to advance global health through physical activity

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and measures of success and priorities. If systems are not changed in a more coordinated manner, any successful programme of one single stakeholder could be off set by unexpected consequences to another stake-holder or by equal and opposite eff ects of diff erent programmes. Complete understanding of all stake-holders, their interactions, and how their interactions make up the whole is crucial to understanding of the systems that impede progress on physical activity. Such a task again will necessitate coordination, communi-cation, and partnership devel opment across the myriad of stakeholders who can aff ect change.

Many previous public health solutions have been the primary responsibility of the health sector (eg, tobacco control, infection control), but meaningful progress was only made possible when inputs from several areas were taken into account. Physical inactivity is an issue that crosses many sectors and has to be addressed as such. Although the health sector, from counselling of indi-vidual patients in a medical care setting, all the way to community-based programmes for physical activity promotion, can and should play a major part, other sectors are equally, if not more, important in the systems dynamics of physical activity and public health.

Thus, many parties (governments, international organ-isations, the private sector, and civil society) need to contribute complementary actions in a coordinated approach. Priority actions include policies to improve the built environments, cross-cutting actions (such as leadership, healthy public policies, and monitoring), and much greater funding for prevention programmes. Increased investment in population monitoring systems would improve the accuracy of forecasts and evaluations. Based on a strong independent identity and increased evidence base, the integration of actions within existing systems into both health and non-health sectors can

greatly increase the eff ect and sustainability of policies. Such a consideration has been recently off ered for the prevention of obesity73 and should be considered as a model to guide future work to promote physical activity globally. A systems approach might also include physical activity within a non-communicable disease programme or obesity prevention agenda (which might be very important for countries with low and middle incomes), or other opportunistic means to leverage action. Al-though an important launching point, actions should always be conceptualised within a larger systems approach so that additional opportunities can be identifi ed and harmoniously implemented.

Finally, there is a heterogeneity of infl uences that is acknowledged in systems thinking. Given the same family environment, the same physical environment, and other physical activity determinants, why are some people very active, others intermittently active, and still others inactive? Clearly, diff erent determinants exist and they manifest diff erently, resulting in a variable, incomplete, and unsatisfactory model to predict physical activity. This variability in infl uence, coupled with the multiple levels of infl uence and the multiple stake-holders, argues strongly that public health eff orts for physical activity promotion cannot be expected to increase the prevalence of health-enhancing physical activity throughout the world without a complete sys-tems approach. Behavioural science and environmental science have contributed to our understanding and defi nition of the issue at the individual level. By its very nature, systems thinking needs transcendence of traditional silos and boundaries to address large-scale issues. If public health is to be improved by population shifts in physical activity prevalence, those changes have to be aff ected by a change in thinking to embrace a systems approach. Although diffi cult to implement and

(Continued from previous page)

We urge employers, the private sector, and media to:• Develop and implement programmes, facilities, and

incentives that encourage and support employees and their families to be physically active

• Orient marketing, advertising, and promotional messages to encourage physical activity and discourage physical inactivity and sedentary behaviours

• Collaborate with government and non-governmental organisations in the creation and promotion of opportunities to promote and engage in physical activity

We urge academics and academia to:• Undertake research to further clarify the open questions on

physical activity and health, in particular on eff ective promotion strategies in all life settings and complete systems approaches

• Invest in translation of research into practice

• Create graduate training programmes that integrate and take a comprehensive approach to physical activity and public health

• Further build the evidence base for eff ective programmes, national plans, and on cost-eff ectiveness, particularly in countries with low and middle incomes

Finally, we urge individuals and organisations in civil society to:• Advocate to decision makers and the general community

for an increase in political commitment and resources to increase population levels of physical activity

• Commit to and implement plans for the development and capacity building of the physical activity and public health infrastructure that is commensurate with the magnitude, reach, and eff ect of the issue

• Seek ways to become and remain physically active at levels recommended for the preservation and promotion of health and wellbeing

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communicate, such an approach is necessary to address physical activity as a public health issue.

Call to actionAs part of the International Society for Physical Activity and Health, GAPA36 works to strengthen advocacy, dis-sem in ation, and capacity around physical activity promo-tion and policy. GAPA was instrumental in developing the 2009 Toronto Charter, a ten-point action plan for global promotion of physical activity74 and resource materials to guide action.75 The Charter has been trans-lated into 17 languages with seven more forthcoming. Such products are intended to guide national agendas, to strengthen advocacy, and to incorporate lessons learned from other risk factor success stories, in particular from tobacco control.76 In this call to action, we urge widespread adoption of the principles outlined in panel 2, which are based on and expanded from the Toronto Charter, and key actions detailed in panel 3.

ConclusionsPhysical inactivity is pandemic, a leading cause of death in the world, and clearly one of the top four pillars of a non-communicable disease strategy. However, the role of physical activity continues to be undervalued despite evidence of its protective eff ects and the cost burden posed by present levels of physical inactivity globally. There is an urgent need to build global capacity. Although progress has been made in policy and planning, leadership and advocacy, workforce training, and surveillance, much needs to be done to fully address this global issue. Advancement of global capacity needs intersectoral collaboration, improved understanding of what works, particularly in countries with low and middle incomes, comprehensive monitoring to assess progress in im ple-mentation of policies and action plans, and momentum in development of a highly skilled workforce in physical activity and public health. New partners, an expanded leadership base, resources at the country and local level, and expanded infrastructure are crucially needed to advance physical activity as a public health issue. Further-more, a systems-based approach is needed to address the complex interactions between the various conditions that promote or impede population levels of physical activity. Understanding and application of complex systems to aff ect physical activity will allow infrastructure changes that will give individuals and populations the freedom to be more physically active and healthy.

This Series in The Lancet is a crucial step for physical activity and public health. The physical activity research community, governments, and civil society, among others, can take advantage of the summary of knowledge presented in this report to drive action for physical activity. But our share of responsibility does not end with pub lication of the Series. Setting of goals and meas-urement of progress is crucial if the specialty is to continue to grow and evolve. As a tangible means to move

forward, the Lancet Physical Activity Observatory is being launched (panel 4).ContributorsHWK was responsible for conceptualisation, drafting, writing, editing, revising, fi gure design, communicating with the Lancet editorial offi ce, and leadership of author group meetings. CLC, EVL, and SK contributed to conceptualisation, drafting, writing, editing, and intellectual contributions through participation in author group meetings. SI contributed to conceptualisation, editing, and intellectual contributions through participation in author group meetings. JRA contributed to writing, editing, and intellectual contributions through participation in author group meetings. GL contributed to conceptualisation and intellectual contributions through participation in author group meetings.

Lancet Physical Activity Series Working GroupJasem R Alkandari, Lars Bo Andersen, Adrian E Bauman, Steven N Blair, Ross C Brownson, Fiona C Bull, Cora L Craig, Ulf Ekelund, Shifalika Goenka, Regina Guthold, Pedro C Hallal, William L Haskell, Gregory W Heath, Shigeru Inoue, Sonja Kahlmeier, Peter T Katzmarzyk, Harold W Kohl 3rd, Estelle Victoria Lambert,

Panel 4: Lancet Physical Activity Observatory

How will we measure progress? The Working Group has prepared a list of primary goals to be monitored over time so that progress can be measured. These goals should serve as a unifying set of achievable actions that, when met, will result in a healthier world population. By 2016, the following four key goals in physical activity and public health are proposed:

1 Reduce the global prevalence of physical inactivity among adults from 31% to 28%

2 Increase the proportion of adolescents engaging in at least 1 h per day of vigorous and moderate-intensity physical activity from 21% to 24%

3 Reduce the proportions of coronary heart disease, type 2 diabetes, breast cancer, colon cancer, and premature deaths worldwide that are attributable to physical inactivity by 10%

4 Increase the proportion of peer-reviewed scientifi c publications on physical activity (levels, trends, correlates, consequences, interventions, and policy) that come from low-income and middle-income countries over the total number of publications by 10%

In addition to the four primary goals, an additional series of secondary goals to be tracked over time and that will need data systems for assessment are proposed. To achieve these goals, the Lancet Physical Activity Observatory will be created. In addition to keeping track of the progress, reporting on that progress through publications and meetings, the observatory will work with other entities (Global Advocacy for Physical Activity and International Society for Physical Activity and Health, Agita Mundo and regional networks) on advocacy for physical activity promotion, in particular working with governments worldwide, to help countries to achieve the physical activity goals established here. Further details about the mission, purpose, primary and secondary goals, and objectives of the Lancet Physical Activity Observatory will be made available online.

For more on the Lancet Physical Activity Observatory see http://www.lancetphysicalactivityobservatory.com

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I-Min Lee, Grit Leetongin, Felipe Lobelo, Ruth J F Loos, Bess Marcus, Brian W Martin, Neville Owen, Diana C Parra, Michael Pratt, Pekka Puska, David Ogilvie, Rodrigo S Reis, James F Sallis, Olga Lucia Sarmiento, Jonathan C Wells.

Confl icts of interestWe declare that we have no confl icts of interest.

AcknowledgmentsInput to draft versions of this report were provided by Reynaldo Martorell, Gregory W Heath, Kenneth E Powell, Fiona C Bull, Lise Gauvin, Art Salmon, Adrian E Bauman, Francesca Racioppi, Harry Rutter, Nick Cavill, and Trevor Shilton.

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