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transcript
The association between early life socioeconomic position and adult
health, from mortality to preclinical disease. What do we know?
Bruna GalobardesDepartment of Social Medicine
University of Bristol, UK
National Poverty Center, March 2009
A life course approach in epidemiology investigates the long term effects on health and chronic disease risk of physical and social hazards during gestation, childhood, adolescence, young adulthood and later adult life (and across generations).
It studies the biological, behavioural and social pathways that operate across the life course and influence the development of chronic diseases.
What is a life course approach?
“It is insufficient to glibly state that all health and social outcomes are due to life course influences. This is analogous to stating that all health is a function of genetic and environmental exposures. Whilst factually correct it does not further our understanding of aetiology or help policy formulation.”
Ben-Shlomo & Kuh (Lifecourse approach to chronic disease epidemiology, 2nd edition)
Life course epidemiology – stating the obvious?
“The ringing in your ears – I think I can help!”
Early life socioeconomic position (SEP) and cause-specific mortality:
is the association established?
The importance of looking at specific causes of death:helps establishing causal associations and describing the pathways that link early socioeconomic circumstances with later disease.
Systematic review of individual-level studies Ecological studiesMigration and place of birth studiesLong-term disease trends
Evidence from :
Bruna Galobardes, George Davey Smith and John W. Lynch
Epidemiologic Reviews 2004;26:7-21J Epidemiol Community Health 2008;62:387-90 Ann Epidemiol 2006;16:91-104
The systematic reviews on mortality are based on at least 125,961 deaths (66 558 deaths in a Swedish study and 20 887 deaths in a study from Norway) from 40 studies (some reported in more than one publication): 38 prospective, 2 case-control, 1 cross-sectional.
Evidence from individual-level studies:
Inclusion criteria: individual-level studies, adult mortality (studies reporting grouped fatal and non-fatal events were excluded or inclusion of hypertension in the outcome definition)
Countries: United Kingdom, Sweden, Finland, Norway, Denmark, Netherlands, United States, Russia, France, Belgium and South Korea.
Birth cohorts: The majority included people born during or before the 1940s and 1950s, and the youngest birth cohorts dated from the late-1950s to the 1960s.
In the initial review 19 of the 29 studies measured the participants’ SEP during childhood or young adulthood. The remainder obtained data by participant recall during adulthood.
The father’s occupation was the most common indicator.
Main conclusions:
Most studies support an association between childhood socioeconomic position and overall mortality.
Not all causes of death are equally related to childhood socioeconomic conditions.
• Childhood SEP is particularly important for mortality from stomach cancer.
• Childhood SEP was particularly important for haemorrhagic stroke but there was not consistency across studies.
• Childhood circumstances contribute, together with socioeconomic conditions in adult life, in determining mortality from coronary heart disease, liver and lung cancer, respiratory-related deaths and diabetes. The relative contribution of child-versus-adult circumstances varied in different contexts.
• Childhood circumstances may contribute to external (including unintentional injuries and homicide) and alcohol-related causes of death, especially in northern European countries.
• There is no evidence for an association with overall non-smoking-related cancers.
Main conclusions:
Stomach cancer mortality
Davey Smith, Hart, Blane et al. BMJ 1998;316;1631-1635
Leon & Davey Smith BMJ 2000;320:1705-6
Infant mortality in 1921-3 and stomach cancer rates in 1991-3 for men aged 65-74
Hemminki & Li Int J Cancer 2002;99:229-37
Risk of stomach cancer in first and second generation migrants in Sweden
Migration studies:
Stroke mortality
Lawlor et al. Lancet 2002;360:1818-23
Evidence from disease trends …
Lawlor et al. Lancet 2002;360:1818-23
Evidence from disease trends …
Lawlor et al. Lancet 2002;360:1818-23
Childhood social class and stroke subtype:
Manual vs. Manual vs.+
non-manual non-manual
Haemorrhagic 2.84 (1.12-7.20) 3.22 (1.15-9.03)
Ischaemic 1.25 (0.77-2.03) 0.92 (0.53-1.61)+risk factor adjusted
Hart and Davey Smith; J Epidemiol Community Health 2003
Evidence from individual level studies …
Evidence from individual level studies …
Hart et al. JECH 2003;57:385-91
“studies from Sweden and Norway, and the mothers of the 1958 cohort found both types of stroke, ischemic and hemorrhagic, had a similar social patterning thus not supporting earlier reports where worse childhood SEP was a stronger predictor for hemorrhagic stroke “
Galobardes, Davey Smith, Lynch. J Epidemiol Community Health 2008;62:387-90
Cardiovascular disease mortality and morbidity
Those who experienced worse socioeconomic conditions in their childhood, independently of their circumstances during adult life, generally were at greater risk for developing and dying of CVD:
Davey Smith, Hart, Blane et al. BMJ 1998;316;1631-1635
Sinhg-Manoux, Ferrie, Chandola et al. Int J Epidemiol 2004;33:1072-1079
The relative contribution of child-versus-adult socioeconomic conditions varied in different contexts:
Smoking: Different life course exposure to tobacco smoking may explain the relative different contributions of child versus adult SEP on CHD in different countries.
In US: Childhood SEP more important. Alameda County study in the United States, those from poorer backgrounds during childhood were less likely to quit and therefore had smoked more throughout their lives, despite the socioeconomic reversals in smoking pattern in the adult population.
Netherlands: Conversely, a cross-sectional study of a younger population showed that smoking was influenced more by adult SEP.
• Pre-clinical CVD – atherosclerosis:
At the time of publication of the systematic review there were 2 studies measuring carotid intima media thickness (a measure of the width of the artery wall) or carotid stenosis. Both studies reported higher levels of atherosclerosis among women but not among men.
More recent studies (“not systematic”) :
Multi-Ethnic Study of Atherosclerosis (MESA): Childhood SEP was independently associated with subclinical IMT in both men and women.
Young Finns study, parental occupation in childhood or young adulthood of the participant was not associated with IMT or flow mediated vasodilation.
Atherosclerosis Risk in Communities Study (ARIC, US): “Lower cumulative life course SEP was associated with higher burden of subclinical atherosclerosis”
Issues to consider:
Confounding by adult SEP
Does the association persist among younger cohorts?
Effects across generations
Confounding by adult SEP Glasgow Alumni Cohort study: >90% class I and II in adulthood
Galobardes et al. JECH 2006;60:527-9
Does the association persist among younger cohorts?
Younger birth cohorts have not experienced the level of socioeconomic strain previous birth cohorts had, however, the association between childhood SEP and mortality can still be found
Younger cohort Older cohort
All cause 1.27(1.24, 1.30) 1
1.41 (1.34, 1.48) 2
1.44 (1.27, 1.63) 3
CVD 1.54 (1.45, 1.64) 1
2.17 (1.89, 2.49) 2
1.52 (1.24, 1.87) 3
Stomach cancer
1.32 (1.10, 1.59) 1
2.34 (1.54, 3.54) 2 2.06 (0.93, 4.57) 3
1 Swedish cohort (Lawlor et al, 2007); 2 Norwegian cohort (Naess et al, in
press; 3 Collaborative study (Davey Smith et al. 1998)
Effects across generations:
Osler et al. JECH 2005;59:38-41
Effects across generations:
Osler et al. JECH 2005;59:38-41
Models / pathways can explain life course inequalities in health:
Cumulative vs. interaction
Importance of education
Genetic/in-utero vs. environment
Theoretical life course models
• Critical period model with or with out later effect modifier with later life effect modifier
Ben-Shlomo & Kuh IJE 2002
• Accumulation of risk with independent and uncorrelated insults with correlated insults
“risk clustering” “chains of risk” with additive or trigger pathways
Critical and sensitive periods
• Critical period – a time period only during which an exposure has an effect.– Thalidomide and limb abnormalities
– Imprinting of parental characteristics (Lorenz)
• Sensitive period - a time period during which an exposure has a greater effect than outside this period– Learning a second language in childhood
– Clinical disease associated with infectious disease exposure
Theoretical life course models
• Critical period model with or with out later effect modifier with later life effect modifier
Ben-Shlomo & Kuh IJE 2002
• Accumulation of risk with independent and uncorrelated insults with correlated insults
“risk clustering” “chains of risk” with additive or trigger pathways
TIME
Accumulation model – independent risks
A
C
B
OUTCOME
MEASURE
Kuh et al (JECH 2003:57:778-783)
TIME
Accumulation model – risk clustering
A CB
OUTCOME
MEASURE
D
Kuh et al (JECH 2003:57:778-783)
TIME
Chains of risk model – trigger
A CB
OUTCOME
MEASURE
Kuh et al (JECH 2003:57:778-783)
TIME
Chains of risk model – additive
A CB
OUTCOME
MEASURE
Kuh et al (JECH 2003:57:778-783)
Relative death rates (95% CI) by cumulative social class, adjusted for age and risk factors, for men in West of Scotland
Collaborative Study (Davey Smith et al 1997)
Cumulative Social Class
All 3 non-manual
2 non-manual
2 manual All 3 manual
P value for trend
All cause
Age adjusted
1 1.29(1.08, 1.56)
1.45(1.21, 1.73)
1.71(1.46, 2.01)
< 0.0001
Age & risk factor
1 1.30(1.08, 1.57)
1.33(1.11, 1.60)
1.57(1.33, 1.85)
< 0.0001
CVD
Age adjusted
1 1.51(1.16, 1.98)
1.90(1.47, 2.45)
1.94(1.53, 2.45)
< 0.0001
Age & risk factor
1 1.57(1.20, 2.05)
1.78(1.37, 2.31)
1.92(1.51, 2.45)
< 0.0001
Lawlor et al AJE 2006;164:907-15
Importance of education
Genetic/in-utero vs. environment
Osler et al. IJE 2006;35:1272-77
* **
* 1.69, ** 1.76
Genetic/in-utero vs. environment
Explanations for these findings …
Genetic/in-utero vs. environment
Underlying genetic mechanism
• Genetic factor poor health low SEP
•Inherited personality traits SEP
health-related behaviours
• IQ
Prenatal programming effect the mother’s lifestyle and health during pregnancy child’s foetal development
Assortative mating: father/partner will have similar SEP and health
Genetic/in-utero vs. environment
Chance finding
Selection bias
Osler et al. IJE 2006;35:1272-77
Barker & Osmond BMJ 2000;293:1271-75.
Mortality rates per 10,000 person years 1990-94 by indices of housing conditions in 1960 and household
income in 1990, Oslo
Men Women
1960 1990 1960 1990
Index values
1 (poor) 48 59 27 32
2 49 55 20 25
3 38 37 18 20
4 30 26 15 16
5 29 27 13 15
6 26 23 19 13
7 (well off) 20 18 17 9
From: Claussen et al. J Epidemiol Community Health 2003;57:40-45.
All cause mortality by cumulative social class and car driving
0
0.5
1
1.5
2
2.5
3 NM 2 NM 1M 1 NM 2 M 3 M
Cumulative social class
Haz
ard
rati
os
Yes No
Davey Smith et al, BMJ 1997
Cardiovascular mortality according to cumulative risk indicator (father’s social class, adulthood social class, smoking,
alcohol use)
4 favourable (0 unfavourable)
517 47 1 3 favourable (1 unfavourable)
1299 227 1.99 (1.45 - 2.73)
2 favourable (2 unfavourable)
1606 354 2.60 (1.92 - 3.52)
1 favourable (3 unfavourable)
1448 339 2.98 (2.20 - 4.05)
0 favourable (4 unfavourable)
758 220 4.55 (3.32 - 6.24)
N CVD deaths Relative risk
Davey Smith and Hart AJPH 2002
Poor health at age 33 & cumulative SES (birth - 33yrs)
0
5
10
15
20
25
4 5 6 7 8 9 10 11 12 13 14 15 16
lifetime SES score
% fair/
poo
r he
alth
men
women
Source: Power et al, 1999
Lifetime SEP score
WorstBest
Age adjusted relative rates of CVD mortality by father’s social class and adulthood social class
Screening social class
Father’s social class Non manual Manual
Non manual 1 1.45 (1.04-2.01)
Manual 1.56 (1.29-1.88) 1.86 (1.56-2.22)
Davey Smith and Hart, AJPH 2002
Relative index of inequality according to 1960 and 1990 socio-economic position: all-cause mortality
1960 RII 1990 RII 1960 RII adjusted for 1990 SEP
1990 RII adjusted for 1960 SEP
Men 2.63 (2.06 to 3.35)
3.14 (2.44 to 4.04)
2.48 (1.94 to 3.16) 3.00 (2.33 to 3.86)
Women 1.55 (1.12 to 3.13)
2.50 (1.77 to 3.53)
1.47 (1.06 to 2.04) 2.45 (1.73 to 3.47)
From: Claussen et al. J Epidemiol Community Health 2003;57:40-45.
Leon & Davey Smith BMJ 2000;320:1705-6
Evidence from ecological studies …
Chains of risk
“The impact of some factor in childhood may lie less in the immediate behavioural change it brings about than in the fact it sets into motion a chain reaction in which one ‘bad’ thing leads to another, or, conversely, that a good experience makes it more likely that another one will be encountered.” Rutter 1988
Rosvall et al. BMC Public Health 2006;6:203-