Income variability and incident cardiovascular disease in diabetes: a population-based cohort study

Abstract

Abstract Background and Aims Longitudinal change in income is crucial in explaining cardiovascular health inequalities. However, there is limited evidence for cardiovascular disease (CVD) risk associated with income dynamics over time among individuals with type 2 diabetes (T2D). Methods Using a nationally representative sample from the Korean National Health Insurance Service database, 1 528 108 adults aged 30–64 with T2D and no history of CVD were included from 2009 to 2012 (mean follow-up of 7.3 years). Using monthly health insurance premium information, income levels were assessed annually for the baseline year and the four preceding years. Income variability was defined as the intraindividual standard deviation of the percent change in income over 5 years. The primary outcome was a composite event of incident fatal and nonfatal CVD (myocardial infarction, heart failure, and stroke) using insurance claims. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated after adjusting for potential confounders. Results High-income variability was associated with increased CVD risk (HRhighest vs. lowest quartile 1.25, 95% CI 1.22–1.27; Ptrend < .001). Individuals who experienced an income decline (4 years ago vs. baseline) had increased CVD risk, which was particularly notable when the income decreased to the lowest level (i.e. Medical Aid beneficiaries), regardless of their initial income status. Sustained low income (i.e. lowest income quartile) over 5 years was associated with increased CVD risk (HRn = 5 years vs. n = 0 years 1.38, 95% CI 1.35–1.41; Ptrend < .0001), whereas sustained high income (i.e. highest income quartile) was associated with decreased CVD risk (HRn = 5 years vs. n = 0 years 0.71, 95% CI 0.70–0.72; Ptrend < .0001). Sensitivity analyses, exploring potential mediators, such as lifestyle-related factors and obesity, supported the main results. Conclusions Higher income variability, income declines, and sustained low income were associated with increased CVD risk. Our findings highlight the need to better understand the mechanisms by which income dynamics impact CVD risk among individuals with T2D.