Comparing the educational gradients in three cardiovascular disease-specific health measures

Less-educated persons have worse cardiovascular health. We compare the educational gradients in three disease-specific health measures (biomarkers, self-reported doctors’ diagnoses and cause-specific mortality) in order to compare their relevance in different stages of the disease process. We study 14,102 people aged 50–89 from the US Health Retirement Study (HRS) in the period 2006–17. We use six CVD biomarkers (systolic/ diastolic blood pressure, ratio total/HDL cholesterol, C-reactive protein, body mass index, HbA1c) and two self-reported doctors’ diagnoses (stroke, heart attack). We estimate the gradient in biomarkers using log-binomial regression and the hazard of diagnoses and CVD mortality with Cox survival models.Among those without pre-diagnosed CVD conditions, the educational gradient in mortality is highest (RR 1.97), the gradient for those who receive a CVD diagnosis is in the middle (RR 1.46), and the gradient in biomarkers is lowest (RR 1.32). Among those with recent/ older diagnoses, the biomarker gradient is comparable to levels among the non-diagnosed, while the mortality gradient is much lower (RR 1.35). The gradients in diagnoses and mortality are only slightly explained by differences in biomarkers.The comparison of the three gradients and the mediation analysis suggest that in each of the steps to diagnosis and death there are social factors involved that increase the gradient and go beyond what biomarkers can predict. Having a CVD diagnosis leads to smaller mortality gradients, presumably because of the convergence of educational differences in behaviour and during treatment and monitoring. Our findings support prevention as a strategy against social inequalities in CVD.Key messagesThe educational gradient is highest for mortality; next highest is diagnoses; lowest is biomarkers.The gradients in diagnoses and mortality are only slightly explained by differences in biomarkers.CVD progression is subject to social factors that widen the gradient beyond biomarkers’ predictivity.Among diagnosed people, changes in behaviour and treatment seem to lower the mortality gradient.