AIMS/HYPOTHESIS: We determined the degree to which metabolic syndrome components, inflammation and health behaviours account for the social gradient in CHD. METHODS: A total of 5312 men, initially aged 39 to 63 years, were followed for 13.1 years for incident coronary death or non-fatal myocardial infarction according to socioeconomic position (employment grade). The contribution of explanatory factors to socioeconomic differences in CHD was assessed by the reduction in hazard ratios computed using Cox models. The effects of measurement error were taken into account. RESULTS: Coronary events were more common in lower employment grades than in higher, with a hazard ratio (relative index of inequality) of 2.2 (95% CI 1.3-3.7), after adjustment for age and ethnic group. Behavioural risk factors (mainly smoking and diet) explained a third of the socioeconomic gradient in CHD incidence. Components of the metabolic syndrome and inflammatory markers predicted CHD incidence and also explained a third of the gradient. Combined, these two groups of predictors, i.e. behavioural and biological, accounted for over half of the socioeconomic gradient in incident CHD. Adding body height as a marker of the effects of early life increased this figure to about 60%. CONCLUSIONS/ INTERPRETATION: A major question has been how someone's socioeconomic position can lead to increased risk of CHD. Socioeconomic differences in components of the metabolic syndrome (and inflammatory markers) provide part of the answer. This was, to an important degree, independent of the contribution of health behaviours to the socioeconomic differentials in CHD.
AIMS/HYPOTHESIS: We determined the degree to which metabolic syndrome components, inflammation and health behaviours account for the social gradient in CHD. METHODS: A total of 5312 men, initially aged 39 to 63 years, were followed for 13.1 years for incident coronary death or non-fatal myocardial infarction according to socioeconomic position (employment grade). The contribution of explanatory factors to socioeconomic differences in CHD was assessed by the reduction in hazard ratios computed using Cox models. The effects of measurement error were taken into account. RESULTS: Coronary events were more common in lower employment grades than in higher, with a hazard ratio (relative index of inequality) of 2.2 (95% CI 1.3-3.7), after adjustment for age and ethnic group. Behavioural risk factors (mainly smoking and diet) explained a third of the socioeconomic gradient in CHD incidence. Components of the metabolic syndrome and inflammatory markers predicted CHD incidence and also explained a third of the gradient. Combined, these two groups of predictors, i.e. behavioural and biological, accounted for over half of the socioeconomic gradient in incident CHD. Adding body height as a marker of the effects of early life increased this figure to about 60%. CONCLUSIONS/ INTERPRETATION: A major question has been how someone's socioeconomic position can lead to increased risk of CHD. Socioeconomic differences in components of the metabolic syndrome (and inflammatory markers) provide part of the answer. This was, to an important degree, independent of the contribution of health behaviours to the socioeconomic differentials in CHD.
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