Abstract

Lower neighborhood-level socioeconomic status (SES) is associated with an increased risk of vascular disease in developed countries. This study aims to identify village- and individual-level determinants of stroke and coronary heart disease (CHD) in a rural Chinese population. We analyzed data from a population-based survey of 14,424 rural Chinese adults aged over 40 years from 54 villages. Primary outcomes were stroke and coronary heart disease (CHD) prevalence. Village-level SES was determined from the Chinese government's official statistical yearbook. Individual-level characteristics were obtained by in-person interviews. Prevalence rate ratios (RRs) and 95% confidence intervals (95% CIs) were calculated using generalized linear mixed models with log-link function to explore associations of village-level SES and individual social, demographic, and cardiovascular risk factors with stroke or CHD. Variance was expressed using the median rate ratio (MRR) and interval rate ratio (IRR). Village accounted for significant variability in the prevalence of stroke (MRR = 1.70; 95% CI: 1.42-1.94; P < 0.05) and CHD (MRR = 1.59; 95% CI: 1.35-1.78, P < 0.05), with village-level income alone accounting for 10% and 13.5% of between-village variation in stroke and CHD, respectively. High-income villages were at higher risk of both stroke (RR = 1.69, 95% CI: 1.09-2.62) and CHD (RR = 1.63, 95% CI: 1.13-2.34) than lower-income villages. Among individual-level risk factors, hypertension was associated with a higher prevalence of stroke (RR = 2.33, 95% CI: 1.93-2.80) than CHD (RR = 1.58, 95% CI: 1.38-1.82), whereas obesity was only associated with CHD (RR = 1.43, 95% CI: 1.23-1.66). In addition, there was an interaction between age and income; residents of higher-income villages below age 60 had a higher prevalence of CHD (RR = 1.58, 95% CI: 1.15-2.18) but not stroke. There were differences in vascular risk across rural villages in China, with higher lifetime stroke and CHD prevalence in higher-income villages. For CHD, neighborhood effects were stronger among younger residents of high-income villages. The results may have implications for public health interventions targeting populations at risk.

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