Chen Y J, Su J, Qin Y, Shen C, Pan E C, Yu H, Lu Y, Zhang N, Zhou J Y, Wu M
Department of Non-communicable Chronic Disease Control, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China.
Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2022 Oct 10;43(10):1619-1625. doi: 10.3760/cma.j.cn112338-20220107-00010.
To investigate the relationship between socioeconomic status (SES) and all-cause mortality in patients with type 2 diabetes. A total of 17 553 patients with type 2 diabetes were recruited under the National Basic Public Health Service Project in Changshu county, Qingjiangpu district, and Huai'an district in Huai'an city of Jiangsu province as participants. Latent class analysis was applied to classify the individuals based on five socioeconomic indicators. Then, Cox proportional hazards regression models were used to estimate the associations of different levels of SES with all-cause mortality, and stratified analysis was performed according to age and area. Among 100 529.08 person-years of the fo1low-up, the median follow-up time was 5.7 years, and 1 829 deaths occurred during the follow-up period. According to the relevant results of the latent class model, the model of the "three classes" was the best. The related population was then divided into low SES (8 256 people, 47.0%), medium SES (4 427 people, 25.2%), and high SES groups (4 870 people, 27.8%). Compared to patients with high SES, the multivariate-adjusted hazard ratio (95%) of all-cause mortality associated with low SES for males and females were 1.84 (1.53-2.21) and 1.41 (1.51-1.72), respectively. Stratified analysis showed that the hazard ration (95%) of all-cause mortality associated with low SES for males and females were 1.99 (1.12-2.95) and 2.01 (1.20-3.23), respectively, in people younger than 60 years old, and were 1.90 (1.57-2.31) and 1.40 (1.13-1.73) in people over 60 years old. The values (95%) for all-cause mortality associated with low SES for the male and females were 1.54 (1.17-2.04) and 1.27 (1.02-1.59) in the urban population with 2.11 (1.55-2.85) and 2.64 (1.17-3.35) in rural population, respectively. Lower SES increased the risk of all-cause mortality in type 2 diabetic patients, which is more significant in younger and rural populations.
探讨2型糖尿病患者社会经济地位（SES）与全因死亡率之间的关系。在江苏省淮安市清江浦区、淮安区以及常熟县的国家基本公共卫生服务项目中，共招募了17553例2型糖尿病患者作为研究对象。应用潜在类别分析，根据五个社会经济指标对个体进行分类。然后，使用Cox比例风险回归模型估计不同SES水平与全因死亡率之间的关联，并根据年龄和地区进行分层分析。在100529.08人年的随访中，中位随访时间为5.7年，随访期间有1829例死亡。根据潜在类别模型的相关结果，“三类”模型最佳。随后将相关人群分为低SES组（8256人，47.0%）、中SES组（4427人，25.2%）和高SES组（4870人，27.8%）。与高SES患者相比，低SES男性和女性全因死亡率的多变量调整风险比（95%）分别为1.84（1.53 - 2.21）和1.41（1.51 - 1.72）。分层分析显示，在60岁以下人群中，低SES男性和女性全因死亡率的风险比（95%）分别为1.99（1.12 - 2.95）和2.01（1.20 - 3.23），在60岁以上人群中分别为1.90（1.57 - 2.31）和1.40（1.13 - 1.73）。在城市人群中，低SES男性和女性全因死亡率的风险比（95%）分别为1.54（1.17 - 2.04）和1.27（1.02 - 1.59），在农村人群中分别为2.11（1.55 - 2.85）和2.64（1.17 - 3.35）。较低的SES增加了2型糖尿病患者全因死亡的风险，在年轻人群和农村人群中更为显著。
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