Educational inequalities in cardiovascular diseases and their mediating factors across different generations: a prospective cohort study

医学 生命银行 前瞻性队列研究 人口学 队列 比例危险模型 调解 冲程(发动机) 老年学 队列研究 疾病 鹿特丹研究 入射(几何) 不平等 内科学 生物信息学 法学 物理 社会学 数学分析 工程类 政治学 光学 生物 机械工程 数学
作者
Nana Wang,Xiaocan Jia,Zhixing Fan,Chaojun Yang,Yuping Wang,Jingwen Fan,Chenyu Zhao,Yongli Yang,Xuezhong Shi
出处
期刊:European Heart Journal - Quality of Care and Clinical Outcomes [Oxford University Press]
卷期号:11 (5): 622-630 被引量:4
标识
DOI:10.1093/ehjqcco/qcaf010
摘要

Abstract Aims This study aimed to assess the educational inequalities in cardiovascular disease (CVD), coronary heart disease (CHD), and stroke among four generations, and to analyse the mediating role of healthy lifestyles and metabolic factors. Methods and results This prospective cohort study included 447 227 participants from UK Biobank, with a mean age of 56.10 (8.08) years, divided into four generations born in 1930s, 1940s, 1950s, and 1960s. Cox regression models and the relative index of inequality (RII) were employed to estimate educational inequality on CVD, CHD, and stroke. Counterfactual mediation analysis was utilized to estimate the mediating effects of healthy lifestyles and metabolic factors. After a median of 13.39 years follow-up, 81 470 cases of CVD were documented. In the fully adjusted model, compared to participants with college education, participants with primary school or below had hazard ratios [95% confidence interval (CI)] for CVD of 1.03 (0.96, 1.11), 1.05 (1.03, 1.08), 1.15 (1.10, 1.20), and 1.37 (1.25, 1.51) in 1930s, 1940s, 1950s, and 1960s, respectively. RII (95% Cl) in CVD increased from 1.04 (0.94,1.14) in the 1930s to 1.35(1.22,1.49) in the 1960s. Across all generations, the proportion mediated by healthy lifestyles and metabolic factors on CVD was 13.36–21.72% and 30.65–40.70%, respectively. Similar results were observed for CHD and stroke. Conclusion Educational inequalities in CVD incidence persisted across generations, with potentially greater disparities in 1960s. Implementing effective interventions for healthy lifestyle and metabolic factors that target the less educated population may help reduce these health disparities.
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