Ethnic differences, obesity and cancer,stages of the obesity epidemic and cancer prevention

Professor TH Lam, JP, BBSMD, FFPH, FFOM, Hon FHKCCM, FHKAM, FRCP

Sir Robert Kotewall Professor in Public HealthSchool of Public Health

The University of Hong Kong

UICC World Cancer CongressMelbourne, Australia

3-6 December 2014

Outline

Obesity and ethnic differences

Obesity and cancer: the evidence

Stages of the obesity epidemic

Conclusions

What is Obesity? Simple yet complex Epidemiologically: general (total, global) versus central -

simplistic definitions and classification Body weight, body fat and body fat percent Body Mass Index most commonly used for general

obesity: only data available in most studies Waist circumference (and Waist Hip Ratio): central

obesity: data available only in more recent studies Cannot distinguish between lean mass and fat mass Different methods to measure body fat: all with limitations

Racial/Ethnic Differences: Body Fat %/Body Mass Index

Indonesians (Malays, Chinese); Singaporean Chinese, Malays and Indians; Hong Kong Chinese

All Asians studied: higher Body Fat % at a lower Body Mass Index compared to Caucasians:

Same Body Mass Index, Asian Body Fat % 3-5% points higher Same Body Fat %, Asian Body Mass Index 3-4% points lower Different Body Fat%/Body Mass Index ratio: body build, i.e. trunk-to-leg

length ratio and slenderness, muscularity

(Deurenberg et al 2002)

Body Fat%/Body Mass Index Ethnic Specific

Relationships between Body Fat % and Body Mass Index differ between ethnic groups

Not all “Asians” are equal: Chinese, Indonesians of Malays ancestry and Thais

Not all “Chinese” are equal: New York, Beijing and Hong Kong

(Deurenberg et al 2002)

Problems and Challenges

Data limited and most reports had small sample size, uncertain representativeness, different methods/assumptions/equations for body fat assessment

Studies with different ethnic groups measured in the same laboratory using the same methodologies are needed

Universal Body Mass Index cut-off points are not appropriate

(Deurenberg et al 2002)

Linear, non-linear, dichotomous

Obesity, adiposity, Body Fat%, Body Mass Index, Waist Circumference, etc are all continuous variables

Linear or nonlinear relationship with disease outcomes

Using cut-off points for obesity (general or central) are needed but would it add to our understanding of the causes and effects of obesity and its mechanisms?

Or would it generate more confusion?

Meta-analysis/systematic reviews on ethnic differences are based on studies with different methods at different time periods in different places with different socio-economic developments

Many studies were not specifically designed to compare ethnic/racial differences

Meta-analysis - heterogeneity

Ethnic/racial differences could be explained by extraneous factors: regional, socioeconomic developments (high, middle and low income countries, or regions within the same countries): gradual developments in many decades versus recent rapid developments; immigration, inter-generational differences

Life course differences (e.g. early life events, weight gain from birth to middle age)

Extraneous and life course factors

Obesity increases risk of many diseases Cardiovascular, type 2 diabetes, some cancers and all-cause

mortality (prospective evidence)

Obesity is associated with many risk factors: dyslipidemia, high blood pressure (cross-sectional associations)

Obesity has many determinants: e.g. diet, sedentary living, physical inactivity, energy balance, socio-economic and obesity control

Longer latency and smaller Risk Ratio for cancer

Obesity and other risk factors

Evidence predominantly from Western populations, and mainly from Body Mass Index

Difficulties in separating the effect of obesity from its associated risk factors

Adjustment of risk factors, treating them as “confounders” may not clarify the effects of obesity and its interaction with (effect modification by) other risk factors

Over-adjustment?

Obesity and cancerEvidence from World Cancer Research Fund International

1997 2007 2010-14First Expert report Second Expert Report Continuous Update Project

Oesophagus C -Pancreas C CGallbladder ? P -Liver ? -Colorectum ? C CBreast pre-M P (↓) P (↓)Breast post-M P(breast) C CEndometrium C C CKidney P C -Ovary - - PProstate (advanced) - - PC = ConvincingP = Probable? Possible 1997; Limited 2007

Body Mass Index and cancerEvidence from World Cancer Research Fund International

Cancer Body Mass Index Risk Ratio of increased bodyIncrement fatness (95% CI) Report date

Prostate(advanced) 5 kg/m2 1.08(1.04-1.12) 2014Ovarian 5 kg/m2 1.06(1.02-1.11) 2014Endometrial 5 kg/m2 1.50(1.42-1.59) 2013Pancreatic 5 kg/m2 1.10(1.07-1.14) 2012Colorectal 1 kg/m2 1.02(1.02-1.03) 2011Postmenopausal breast 2 kg/m2 1.05(1.03-1.07) 2010Premenopausal breast 2 kg/m2 0.97(0.95-0.99) 2010Kidney 5 kg/m2 1.31(1.24-1.39) 2007Gallbladder 5 kg/m2 1.23(1.15-1.32) 2007Oesophageal no analysis 2007

Body fatness (Body Mass Index): More cancer with convincing

Abdominal fatness: Only colorectum convincing

Probable: pancreas, breast postmenopausal and endometrium)

Adult weight gain: None convincing

World Cancer Research Fund InternationalSecond Expert Report 2007

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Foods containing dietary fibreAflatoxinsNon-starchy vegetables1

Allium vegetablesGarlicFruits2

Foods containing lycopeneFood containing selenium3

Red meatProcessed meatCantonese-style salted fishDiets high in calcium4

Salt, salted and salty foodsGlycaemic loadArsenic in drinking waterMaté

CoffeeBeta-carotene6

Physical activityBody fatnessAdult attained heightGreater birth weightLactation

Alcoholic drinks5

Convincing decreased risk

Probable decreased risk

Probable increased risk

Convincing increased riskSubstantial effect on risk unlikely

Continuous Update Project matrix of strong evidence

Obesity and cancer: ethnic differences?Asia-Pacific Cohort Studies Collaboration 2010

Body Mass Index and cancer mortality

39 cohorts, 424,519 people (77% Asian)

4,872 cancer deaths from 401,215 (excluding follow up<3y)

(Parr 2010)

Obesity and cancer: ethnic differences ?Asia-Pacific Cohort Studies Collaboration 2010

Increased risk (Hazard Ratio (95% Confidence Interval)) in Body Mass Index ≥30 vs Body Mass Index 18.5-24.9– all-causes (excluding lung and

upper aerodigestive) 1.21(1.09-1.36)– colon 1.50(1.13-1.99)– rectum 1.68(1.06-2.67)– breast(≥60y) 1.63(1.13-2.35)– ovary 2.62(1.57-4.37)– cervix 4.21(1.89-9.39)– prostate 1.45(0.97-2.19)– leukaemia 1.66(1.03-2.68)(Parr et al 2010)

No regional differences in Hazard Ratio for cancer and Body Mass Index except oropharynx and larynx: inverse in Australia and New Zealand, absent in Asia

Asian data: mainly Japan

Insufficient data on Waist Circumference, Waist Hip Ratio

Test of regional interaction (heterogeneity): low stat. power

(Parr et al 2010)

Obesity and cancer: ethnic differences ?Asia-Pacific Cohort Studies Collaboration 2010

Body Mass Index and 22 cancers

Largest cohort study, 5.24 million UK adults, 166,955 incident cancers

Primary care data (Big data)

BMI associated with 17 of 22 cancers, effects varied substantially

5 kg/m2, roughly linearly: uterus (1.62), gallbladder (1.31), kidney (1.25), cervix (1.10), thyroid (1.09), leukaemia (1.09)

(Bhaskaran 2014)

Liver (1.19), colon (1.10), ovarian (1.09), postmenopausal breast (1.05) overall, but effects varied by underlying Body Mass Index or individual characteristics

Lung and oral cavity: no association in never smokers

10 of 22 cancers: non-linearity or effect modification

• Different mechanisms(Bhaskaran 2014)

Body Mass Index and 22 cancers

(Bhaskaran 2014)

(Bhaskaran 2014)

Association between body-mass index (BMI) and specific cancers, allowing for non-linear effects, with 99% CIs

The reference BMI for these plots (with HR fixed as 1·0) was 22 kg/m2. Separate models were fitted for each cancer type, each with a restricted cubic spline for BMI (knots placed at equal percentiles of BMI), adjusted for age, calendar year, diabetes status, alcohol use, smoking (all at time of BMI recording), socioeconomic status (index of multiple deprivation), and stratified by sex. HR=hazard ratio.

Systemic review Body Mass Index 2014 Update

28 studies* to supplement Renehan 2008

Associations differ widely by cancer site in both size and character

Very few data for possible non-linearity

Effect modification by sex in a few, most showed larger effect on colon in men than women

Information scarce on effect modification by smoking, menopausal status and age

(Bhaskaran 2014)

* Including Bhaskaran, 8 on colon, 5 on rectum, breast, uterus, 4 on ovaries, non-Hodgkin Lymphoma; mostly from the West, Korea and Japan; consistent results

Data from Parkin et al, Pisani et al, Globocan 2012, IARC

Cancer is increasing

Prevalence of overweight and obesity

1769 studies, 188 countries, 21 regions and development status (developed or developing) as defined in Global Burden of Disease

Overweight Body Mass Index ≥ 25 to <30 kg/m2

Obesity: Body Mass Index ≥ 30 kg/m2

Adults ≥ 20y, children & adolescents 2-19y; 17 age groups(Ng 2014)

Age-standardised prevalence of overweight and obesityand obesity alone, ages ≥20 years, by sex, 1980-2013

Overweight + obese

Obesity

(Ng 2014)

Adults (≥20), 1980-2013 Body Mass Index ≥ 25 kg/m2 (overweight /obese) Prevalence:

Men: 28.8% to 36.9% (by 28.1%; 0.62 percentage point/y) Women: 29.8% to 38.0% (by 27.5%; 0.63 percentage point/y)

No. of overweight /obese people: 875 to 2100 million; increased by 240%

Prevalence of overweight and obese increasing in both developed and developing countries

2013: higher in women in developed and developing countries Rate of increase of overweight /obese greatest 1992-2002;

slowed down in the past decade, esp developed countries(Ng 2014)

Age-standardised prevalence of overweight and obesity, and obesity alone (based on International Obesity Task Force cutoffs), ages 2-19 years, by sex, 1980-2013

Overweight + Obese

Obesity

(Ng 2014)

Prevalence of overweight/Obese:DevelopedBoys 16.9% to 23.8% (by 40.8%; 0.53 percentage point/y)Girls 16.2% to 22.6% (by 39.5%; 0.49 percentage point/y)DevelopingBoys 8.1% to 12.9% (by 59.3%; by 0.37 percentage point/y)Girls 8.4% to 13.4% (by 59.5%; by 0.38 percentage point/y)

In both developed & developing, small sex differences in levels and trends

(Ng 2014)

Children & adolescents (2-19), 1980-2013

Obesity is increasing

Obesity is increasing

Adults Children & AdolescentsHighest in the worldMale 52.4%(Tonga) 23.7%(Samoa)Female 69.1%(Samoa) 36.0%(Kiribati)USA/UKMale 31.7%/24.5% 12.4%/7.4%Female 33.9%/25.4% 29.7%/8.1%China/BrazilMale 3.8%/11.7% 6.9%/6.8%Female 5.0%/20.6% 2.8%/7.6%

Prevalence of obesity (Body Mass Index ≥30kg/m2) 2013

Global health challenge

Obesity is increasing

No national success stories in 33 years (no significant decreases)

Wide variation in rates of increase from the same initial level

Epidemic might have peaked in developed countries

Others might not reach 40+% as in some developing countries

(Ng 2014)

Can we learn from the Stages of the

Epidemic of Tobacco?

Four Stages Tobacco Epidemic Model

Stages of Tobacco Epidemic

Stage 1 to 4 for different regions/ countries, by sex

A large gap of several decades between peak of tobacco consumption and the peak of tobacco-induced deaths

Full impact of adverse outcomes only observed recently in the West (US/UK); not yet in low-middle income countries (Asia)

Effective tobacco control declining consumption, diseases (e.g. lung cancer) and mortality in the West

Four Stages Obesity Epidemic Model

Hypotheses for obesity epidemicStage 1: Prevalence of obesity up to 20%; 5% death; >30 years.

Stage 2: Rapid increase in obesity to a peak of 60%; 10% death.; 30 years.Stage 3: Downturn in obesity to 30%; deaths peak at 30% death; 40 years.

Stage 4: Prevalence and death slowly decreasing to ≤10%; >60 years.

We are here

The epidemic curves same for men and women

The West and some C: Early stage, Stage 2 Rising, high obesity level; Rising mortality

Low-middle income countries: Early stage 1 Early rise of obesity Low, or early rise of mortality

? A gap of 40 years between peak of obesity (60%) and peak of death (30%)

Stages of Obesity Epidemic

Need to interpret geographic and ethnic differences taking into account the stages

Caution when pooling results from different stages in meta-analysis

Like tobacco, epidemiological studies at early stages would underestimate the risks and disease burden

What we are seeing is only the beginning and the worse is yet to come. Results observed in the past and now: under-estimate the full impacts in the west; grossly under-estimate in low-middle income countries

The health consequences causally linked to smoking

Source: USDHHS 2004, 2006, 2012.Note: The condition in red is a new disease that has been causally linked to smoking in this report

More than 50 years for smoking

50 years of USSG Report

List of cancer causally related increasing

Colorectal and liver newly added in 2014

How many years for obesity and cancer?

Measurements of obesity: Body Mass Index, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percentage and others: more complex than tobacco

Different definitions of obesity using Body Mass Index and other indices. Health effects: Smoking is a very strong cause (almost exclusively) for lung

cancer. Obesity does not have a single disease predominantly caused by obesity

Benefits of quitting smoking: great and quick; benefits of obesity reduction not clear

Duration of obesity, especially since early childhood, is more important than “baseline” obesity

Early stage of obesity research Further research will reveal more harms from obesity, especially long term

obesity since early life

Obesity is more complex than tobacco

Life Course Studies of Obesity Obesity/overweight can start from early childhood (or earlier) to late

adulthood

Trajectory of obesity/overweight; extent and duration of obesity

Factors affecting changes in obesity/overweight (such as illnesses, efforts to reduce weight in healthy people)

Reverse causation, confounding and effect modification

Inter-generational effect: parental obesity, pregnancy weight status on offspring

Different effects on different diseases

Risk reversal of weight/obesity reduction

Lack of results; studies needed:

Trajectory of obesity reduction, relapse

Population trends of reducing obesity

Benefits from weight/obesity reduction (observational)

Effects of interventions to reduce weight/reduction

Interventions: individual and public health

Benefits: general and specific diseases; individual and disease burden

is needed for the

Stages of Epidemic Life Course Obesity Research (SELCOR)

Growing andComplex Global Epidemic of Obesity

and for

Different populations, regions,races and ethnicity

Prevention and Obesity controlA greater and more complex challenge than tobacco control

1. We advocate for a Framework Convention on Obesity Control (FCOC)

2. The MPOWER strategies against tobacco are immediately applicable by replacing the word “tobacco” with “obesity”

2. We need results on health benefits (risk reversal) from obesity reduction

World Cancer Research Fund International Estimates of preventable fraction of specific cancer sites from body fatness

Source: www.wcrf.org/int/cancer-facts-figures/preventability-estimates/cancer-preventability-estimates-body-fatness

F C T C

F C O C

Framework Convention on Tobacco Control

Monitor smoking and prevention policies Protect people from smoking Offer help to “quit” smoking Warn about the dangers of smoking Enforce bans on smoking advertising, promotion

and sponsorship Raise taxes against smoking

F C T C - MPOWER

Monitor obesity and prevention policies Protect people from obesity Offer help to “quit” obesity Warn about the dangers of obesity Enforce bans on obesity advertising, promotion and

sponsorship Raise taxes against obesity

F C O C - MPOWER

Conclusions

Ethnic differences on Body Fat%/Body Mass Index; but not clear on the association between obesity and cancer

Obesity, cancer and evidence that obesity causes cancer increasing

Now at early stages of obesity epidemic: risks and disease burden under-estimated

Life-course research needed Much can be prevented: MPOWER and FCOC Health benefits from obesity reduction: decades later

For further information

@wcrfint

facebook.com/wcrfint

www.wcrf.org

Professor TH LamThe School of Public Health University of Hong Kong

hrmrlth@hku.hk

Acknowledgements: Many thanks to World Cancer Research Fund International