In 13.1 years follow-up we documented 201 cases of coronary death or non-fatal myocardial infarction. The overall event rate was 3.3 per 1000 person-years. shows the hazard ratios for CHD across the employment grades, which are well described by a strong linear trend (p<0.001). Using the relative index of inequality method, the hazard ratio (95% CI) for being of low employment grade was 2.43 (1.48 – 4.00).
Fig. 1 Age-adjusted HR (95% CI) for coronary death/non-fatal myocardial infarction by employment grade, Whitehall II men. The number of CHD events is shown above error bars for each grade. p<0.001 for linear trend; p=0.63 for departures from linear trend (more ...)
Adverse health behaviours and a majority of biological risk factors were inversely associated with employment grade at baseline in 1991 to 1993 (). Hypotensive medication was related to low employment grade (high 4.9, medium 5.4, low 8.8%, p=0.02 for trend), whereas use of lipid-lowering drugs was weakly related to high employment grade (high 0.8, medium 0.6, low 0.0%, p=0.10 for trend). shows the age-adjusted relation of risk factors to 13 year incidence of major CHD events. For continuous variables, standardised effects (hazard ratio for 1 SD risk factor difference) are presented. Considered singly, all risk factors except factor VIIc showed the expected association with CHD. The contribution of each variable to the social gradient in CHD incidence was calculated using the RII for employment grade, adjusted for age and ethnicity. Although the majority of this population, even in the lowest grade, were non-smokers, current smoking accounted for 19% of the social gradient in incident CHD. Traditional risk factors (smoking, blood pressure, serum cholesterol) explained, statistically, 30% of the CHD gradient – a finding similar to that observed in the first Whitehall study (3
). Based on a logistic model, additional correction for measurement error increased the explanation by a further 8 percentage points.
Prevalence and means of demographic factors, health-related behaviours and risk factors in 5,312 men at phase 3 by employment grade
Association between phase 3 risk factors and incident CHD, and the effect of adjustment for single risk factors on the relative index of inequality for grade
Diet and physical activity accounted for 15 and 8% of the social gradient in CHD respectively (6 and 6% after adjustment for smoking). A complete case analysis of the effect of diet on the social gradient in CHD gave estimates and standard errors similar to those derived using imputed values. Components of the metabolic syndrome and inflammatory markers contributed substantially to the social gradient in CHD. BMI, which highly correlated with waist circumference, contributed to the gradient (12%). WHR accounted for more of the gradient (24%) than did waist circumference, but we retained waist, following ATPIII. Height contributed 9% to the social gradient in CHD incidence.
Reductions of the social gradient in CHD incidence by adjustments for metabolic syndrome risk factors in logistic models without (and with) adjustment for measurement error were similar: waist −14% (−14%), systolic blood pressure −8% (−10%), diastolic blood pressure −8% (−12%), HDL-cholesterol −13% (−15%), triacylglycerol −18% (−22%) and fasting glucose 0% (0%). Adjustment for measurement error increased the explanatory effect of fibrinogen (24 versus 15%), CRP (27 versus 22%), IL-6 (29 versus 17%), smoking (25 versus 20%) and diet (24 versus 16%). Adjustment for antihypertensive medication, for which no measurement error estimate was available, explained approximately a further 2% of the RII for employment grade in all models. Adjustment for lipid-lowering medication did not change the RII for employment grade in any of the models.
Health behaviours together explained 30% of the employment grade gradient (). Metabolic syndrome variables explained 27% (model B). Metabolic syndrome and behavioural variables together reduced the social gradient in CHD by 51% (model C), indicating a degree of overlap of the two sets of explanatory effects. Comparison of attenuating effects in models A, B and C showed that about one quarter of the contribution of metabolic syndrome to the disease gradient arises through social differences in health behaviours. If inflammatory markers are treated as components of the metabolic syndrome cluster, the attenuation of the disease gradient is higher (42%, model B1). Based on models A, B1 and C1, where inflammatory mechanisms are assumed to play a causal role in CHD development, the estimate for the overlap in the explanatory effects of health behaviours and metabolic syndrome on the disease gradient was higher.
The two groups of variables, behavioural and biological, together with height as a marker of early life influences, both genetic and environmental, increased the explanation of the social gradient in CHD to about 60%. Using WHR rather than waist circumference, attenuation in the full explanatory model including height was the same.
The contribution to the social gradient in CHD of combinations of risk factors was estimated in analyses based on logistic regression models without (and with) adjustment for measurement error. Compared with the corresponding estimates from Cox models, those derived from logistic models were similar for behavioural factors (−31% [−41%]) and metabolic syndrome variables (−27% [−29%]). The contribution to the gradient increased to −44% (−48%) when inflammatory markers were added to the metabolic variables and to −59% (−61%) when health behaviours were also added. In the final model with health behaviours, biological variables and height, allowance for measurement error added 3% (72 versus 69%) to the explanation.