Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach

Abstract

Background: Socio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors.

Methods: Data were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education.

Results: Lower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest.

Conclusions: These observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities.

Keywords: Socio-economic inequalities; all-cause mortality; causal inference; health behaviours; intervention; mediation; multiple mediators.

Figure 1.

Causal structures of mediators considered: representing two potential causal structures of socio economic position (SEP), mediating lifestyle behaviours (ML), an intermediate phenotype (MP) of body mass index (BMI) and co-morbidities (MM), and the causal structure of all mediators (M) assessed jointly (C) in the present study. (A) displays a Directed Acyclic Graph (DAG) where SEP leads to changes in ML, MP and MM, whereas (B) displays an alternative causal structure where SEP influences ML and ML influences MP, but MM influences MP. Based on these two potential directions (among others not represented) between mediators, we assess all mediators ‘en bloc’ as displayed in (C).

Figure 2.

Survival curves for women and men by two socio-economic indicators of socio-economic position (SEP) and education, adjusted for age, marital status and cohort. Higher socioeconomic indicators are represented by the dotted lines and lower socioeconomic indicators are represented by solid lines.