Social Inequality in Health – Causation and Selection: A Twin Approach
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Transcript of Social Inequality in Health – Causation and Selection: A Twin Approach
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Why do we age so differently?
VELUX FONDEN
Funded by:
Social Inequality in Health – Causation and Selection: A Twin Approach
Ph.D. Student Mia Madsen DARC: Odense & Copenhagen, Project start June 2008
Supervisors
Kaare Christensen, Merete Osler, Anne-Marie Nybo Andersen
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Research question
A strong and consistent association between socioeconomic position and health is well-established, but is this association a true causal relationship or a spurious one, produced by underlying background factors?
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Matched on genotype (partly or fully) and childhood environment
Do they differ significantly with respect to health outcomes?
Discordant on adult SEP
Analytical approachCausation or selection?
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The principal of twin studies: Three comparisons
Cohort DZ MZ
Early environmental confounding
↑↑ - -
Genetic confounding ↑↑ ↑ -
No confounding by genes or common environment
↑↑ ↑↑ ↑↑
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The evidence so far… Contradictory findings
Generally, no association between SEP and health when genetic constitution and rearing environment are controlled for. Osler et al. 2007, Osler et al. 2009 & Behrman et al. (work in progress) (Danish data)
Persisting association between SEP and health in intra-pair analyses (Krieger et al. 2005 & Lundborg 2008) (American data)
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Social Science and Medicine, 2009
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Evidence continued…
Societal context seems to play a role Results seem to depend on the social indicators
used Results seem to vary according to health outcomes
studied
Power limitations? Chance findings?
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Editorial IJE ”...These are important findings that now require
replication in larger twin data sets using a wider range of health outcomes…”
(Ebrahim, S)
Aim: In nation-wide registers to investigate the effect of different social indicators during the life course on survival and a wide range of different health outcomes in a twin population matched on early life experiences and genetic make-up (partly or fully)
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Data sources & information
Danish Twin Registry (1870 and onwards, N=75,000+)
Statistics Denmark (Information on all twins + 5% sample of all birth cohorts from the general population)
Health Causes of death (1973-2006) Hospitalizations (incl. diagnoses,
operations, and accidents causing admission to hospital (1977-2004))
Cancer registry (soon)
Social data Income (1980-2004) Occupation (1980-2004) Socio-economic position (1980-
2004) Civil status (1980-2004) Education (1980-2004)
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1st paper – initial analyses
Educational status and all cause and cause-specific mortality Follow-up: 1980-2006 Education: 1980, International Standard of Classification
(ISCED) (Primary/Secondary, Upper secondary/Post-secondary non-tertiary, Tertiary)
Mortality: All cause, CVD (+ischemic and stroke), Cancer, Smoking-related cancer, Respiratory causes, External causes, Abnormal findings/insufficiently defined symptoms
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Study population
TWIN POPULATION Born 1921-1950 N=32,594 Alive per 1.1.1980 N=31,934 Living in DK per 1.1.1980 N=31,342 Part of Intact Pair N=27,866 Complete information N=27,334
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Descriptives, education
Educational status (ISCED) N %
Primary/secondary 13,585 48.8
Post-secondary 9,760 35.0
Tertiary 3,989 14.3
Missing 532 1.9
Total cohort 27,866 100
Discordant twin pairs Primary/secondary & Post-secondary: N=6000 (900 MZ) Primary/secondary & Tertiary: N=3060 (402 MZ) Post-secondary & Tertiary: N=1456 (198 MZ)
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Cause of death
ISCED Cohort
HR CI 95% HR CI 95% HR CI 95%
MALES
All causes
Post secondary 0.87 0.84-0.91 0.88 0.72-1.08 0.76 0.52-1.12
Tertiary 0.64 0.60-0-67 0.67 0.47-0.94 0.77 0.43-1.42
CVD
Post secondary 0.84 0.79-0.89 1.09 0.77-1.54 0.56 0.28-1.12
Tertiary 0.58 0.53-0.64 0.54 0.28-1.05 0.58 0.21-1.61
Cancer
Post secondary 0.98 0.93-1.05 1.03 0.71-1.50 1.10 0.55-2.21
Tertiary 0.78 0.72-0.86 0.84 0.46-1.53 1.69 0.52-5.50
5% RS N=96,639
Intra-pair
DZSS N=11,556 MZ N=5426
Intra-pair
Educational status and selected causes of death
Cox regression analysis
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Summary of results
The effect of education seems to persist in the intrapair analyses for all cause mortality and CVD. For cancer the pattern is less clear.
Results are compatible with an independent effect of educational status in adulthood above and beyond genetic constitution and other background factors.