Influence of Socioeconomic Gender Inequality on Sex Disparities in Prevention and Outcome of Cardiovascular Disease: Data From a Nationwide Population Cohort in China

Abstract

Background Knowledge gaps remain in how gender‐related socioeconomic inequality affects sex disparities in cardiovascular diseases (CVD) prevention and outcome. Methods and Results Based on a nationwide population cohort, we enrolled 3 737 036 residents aged 35 to 75 years (2014–2021). Age‐standardized sex differences and the effect of gender‐related socioeconomic inequality (Gender Inequality Index) on sex disparities were explored in 9 CVD prevention indicators. Compared with men, women had seemingly better primary prevention (aspirin usage: relative risk [RR], 1.24 [95% CI, 1.18–1.31] and statin usage: RR, 1.48 [95% CI, 1.39–1.57]); however, women's status became insignificant or even worse when adjusted for metabolic factors. In secondary prevention, the sex disparities in usage of aspirin (RR, 0.65 [95% CI, 0.63–0.68]) and statin (RR, 0.63 [95% CI, 0.61–0.66]) were explicitly larger than disparities in usage of angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers (RR, 0.88 [95% CI, 0.84–0.91]) or β blockers (RR, 0.67 [95% CI, 0.63–0.71]). Nevertheless, women had better hypertension awareness (RR, 1.09 [95% CI, 1.09–1.10]), similar hypertension control (RR, 1.01 [95% CI, 1.00–1.02]), and lower CVD mortality (hazard ratio, 0.46 [95% CI, 0.45–0.47]). Heterogeneities of sex disparities existed across all subgroups. Significant correlations existed between regional Gender Inequality Index values and sex disparities in usage of angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers (Spearman correlation coefficient, r =−0.57, P =0.0013), hypertension control ( r =−0.62, P =0.0007), and CVD mortality ( r =0.45, P =0.014), which remained significant after adjusting for economic factors. Conclusions Notable sex disparities remain in CVD prevention and outcomes, with large subgroup heterogeneities. Gendered socioeconomic factors could reinforce such disparities. A sex‐specific perspective factoring in socioeconomic disadvantages could facilitate more targeted prevention policy making.