Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China.
Age Ageing. 2022 Jul 1;51(7). doi: 10.1093/ageing/afac167.
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.
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.
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.
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.
在中低收入国家，社会经济地位不平等与死亡率和预期寿命之间的关系仍不确定，生活方式在多大程度上起到中介或调节作用仍存在争议。
我们纳入了中国健康与营养调查（1991-2011 年）中的 21133 名成年人，构建了三个参数来反映参与者的个体总体社会经济地位（综合收入、教育和职业）和地区水平（城市化指数）以及生活方式（计算吸烟、身体活动不足和不健康饮食和体重的数量）。死亡率和预期寿命的 HR 通过时间依赖性 Cox 模型和寿命表法分别估计。
在中位数为 15.2 年的随访期间，记录了 1352 例死亡。与低个体和地区社会经济地位相比，高个体和地区社会经济地位的死亡率 HR（95%CI）分别为 2.38（1.75-3.24）和 1.84（1.51-2.24），相当于 50 岁时损失 5.7（2.7-8.6）和 5.0（3.6-6.3）个生命年。生活方式仅解释了死亡率中社会经济差异的≤11.5%。在所有社会经济群体中，较高的生活方式风险评分与较高的死亡率相关。与具有高 SES 和 0-1 种生活方式危险因素的成年人相比，具有低个体 SES 和 3-4 种生活方式危险因素的成年人的死亡率 HR（95%CI）为 7.06（3.47-14.36），相当于 50 岁时损失 19.1（2.6-35.7）个生命年。
这是第一项全国性队列研究报告称，在中国，不利的 SES 与死亡率升高和预期寿命缩短相关，而生活方式对此略有介导。危险的生活方式与所有社会经济群体的死亡率升高相关，而具有危险生活方式和不利 SES 的人则具有更高的死亡率风险。
