Introduction: The Rose hypothesis predicts that since genetic variation is greater within than between populations, genetic risk factors will be associated with individuals' risk of disease but not population disparities, and since socioenvironmental variation is greater between than within populations, socioenvironmental risk factors will be associated with population disparities but not individuals' disease risk.
Methods: We used the UK Biobank to test the Rose hypothesis for type 2 diabetes (T2D) ethnic disparities in the UK. Our cohort consists of 26 912 participants from Asian, black and white ethnic groups. Participants were characterised as T2D cases or controls based on the presence or absence of T2D diagnosis codes in electronic health records. T2D genetic risk was measured using a polygenic risk score (PRS), and socioeconomic deprivation was measured with the Townsend Index (TI). The variation of genetic (PRS) and socioeconomic (TI) risk factors within and between ethnic groups was calculated using analysis of variance. Multivariable logistic regression was used to associate PRS and TI with T2D cases, and mediation analysis was used to analyse the effect of PRS and TI on T2D ethnic group disparities.
Results: T2D prevalence differs for Asian 23.34% (OR=5.14, CI=4.68 to 5.65), black 16.64% (OR=3.81, CI=3.44 to 4.22) and white 7.35% (reference) ethnic groups in the UK. Both genetic and socioenvironmental T2D risk factors show greater within (w) than between (b) ethnic group variation: PRS w=64.60%, b=35.40%; TI w=71.18%, b=28.19%. Nevertheless, both genetic risk (PRS OR=1.96, CI=1.87 to 2.07) and socioeconomic deprivation (TI OR=1.09, CI=1.08 to 1.10) are associated with T2D individual risk and mediate T2D ethnic disparities (Asian PRS=22.5%, TI=9.8%; black PRS=32.0%, TI=25.3%).
Conclusion: A relative excess of within-group versus between-group variation does not preclude T2D risk factors from contributing to T2D ethnic disparities. Our results support an integrative approach to health disparities research that includes both genetic and socioenvironmental risk factors.
Objective: To examine associations between myocardial infarction (MI) and multiple physical function metrics.
Methods: Among participants aged ≥45 years in the REasons for Geographic And Racial Differences in Stroke prospective cohort study, instrumental activities of daily living (IADL), activities of daily living (ADL), gait speed, chair stands, and Short Form-12 physical component summary (PCS) were assessed after approximately 10 years of follow-up. We examined associations between MI and physical function (no MI [n = 9,472], adjudicated MI during follow-up [n = 288, median 4.7 years prior to function assessment], history of MI at baseline [n = 745], history of MI at baseline and adjudicated MI during follow-up [n = 70, median of 6.7 years prior to function assessment]). Models were adjusted for sociodemographic characteristics, health behaviours, depressive symptoms, cognitive impairment, body mass index, diabetes, hypertension, and urinary albumin to creatinine ratio. We examined subgroups defined by age, gender, and race.
Results: The average age at baseline was 62 years old, 56% were women, and 35% Black. MI was significantly associated with worse IADL and ADL scores, IADL dependency, chair stands, and PCS, but not ADL dependency or gait speed. For example, compared to participants without MI, IADL scores (possible range 0-14, higher score represents worse function) were greater for participants with MI during follow-up (difference: 0.37 [95% CI 0.16, 0.59]), MI at baseline (0.26 [95% CI 0.12, 0.41]), and MI at baseline and follow-up (0.71 [95% CI 0.15, 1.26]), p < 0.001. Associations tended to be greater in magnitude among participants who were women and particularly Black women.
Conclusion: MI was associated with various measures of physical function. These decrements in function associated with MI may be preventable or treatable.