社会经济地位
预期寿命
医学
人口学
老年学
中国
队列
弱势群体
环境卫生
人口
地理
政治学
内科学
社会学
考古
法学
作者
Yanbo Zhang,Yue Li,Tingting Geng,Xiong‐Fei Pan,Yanfeng Zhou,Gang Liu,An Pan
出处
期刊:Age and Ageing
[Oxford University Press]
日期:2022-07-01
卷期号:51 (7)
被引量:12
标识
DOI:10.1093/ageing/afac167
摘要
Abstract Background socioeconomic inequity in mortality and life expectancy remains inconclusive in low- and middle-income countries, and to what extent the associations are mediated or modified by lifestyles remains debatable. Methods we included 21,133 adults from China Health and Nutrition Survey (1991–2011) and constructed three parameters to reflect participants’ overall individual- (synthesising income, education and occupation) and area-level (urbanisation index) socioeconomic status (SES) and lifestyles (counting the number of smoking, physical inactivity and unhealthy diet and bodyweight). HRs for mortality and life expectancy were estimated by time-dependent Cox model and life table method, respectively. Results during a median follow-up of 15.2 years, 1,352 deaths were recorded. HRs (95% CIs) for mortality comparing low versus high individual- and area-level SES were 2.38 (1.75–3.24) and 1.84 (1.51–2.24), respectively, corresponding to 5.7 (2.7–8.6) and 5.0 (3.6–6.3) life-year lost at age 50. Lifestyles explained ≤11.5% of socioeconomic disparity in mortality. Higher lifestyle risk scores were associated with higher mortality across all socioeconomic groups. HR (95% CI) for mortality comparing adults with low individual-level SES and 3–4 lifestyle risk factors versus those with high SES and 0–1 lifestyle risk factors was 7.06 (3.47–14.36), corresponding to 19.1 (2.6–35.7) life-year lost at age 50. Conclusion this is the first nationwide cohort study reporting that disadvantaged SES was associated with higher mortality and shorter life expectancy in China, which was slightly mediated by lifestyles. Risk lifestyles were related to higher mortality across all socioeconomic groups, and those with risk lifestyles and disadvantaged SES had much higher mortality risks.
科研通智能强力驱动
Strongly Powered by AbleSci AI