文章摘要
陈一佳,苏健,覃玉,沈冲,潘恩春,俞浩,陆艳,张宁,周金意,武鸣.基于潜在类别分析的社会经济地位与2型糖尿病患者死亡风险的前瞻性研究[J].中华流行病学杂志,2022,43(10):1619-1625
基于潜在类别分析的社会经济地位与2型糖尿病患者死亡风险的前瞻性研究
A prospective cohort study on socioeconomic status and risk of all-cause mortality among patients with type 2 diabetes based on latent class analysis
收稿日期:2022-01-07  出版日期:2022-10-18
DOI:10.3760/cma.j.cn112338-20220107-00010
中文关键词: 糖尿病  2型  社会经济地位  死亡风险  潜在类别分析  前瞻性研究
英文关键词: Diabetes  type 2  Socioeconomic status  Mortality  Latent class analysis  Prospective study
基金项目:江苏省领军人才与创新团队计划(K201105);江苏省第五届“333工程”(BRA2020090);江苏省卫生健康委员会2020年度医学科研项目(M2020085)
作者单位E-mail
陈一佳 南京市疾病预防控制中心慢性非传染病防制科, 南京 210003  
苏健 江苏省疾病预防控制中心慢性非传染病防制所, 南京 210009  
覃玉 江苏省疾病预防控制中心慢性非传染病防制所, 南京 210009  
沈冲 南京医科大学公共卫生学院流行病与卫生统计学系, 南京 211166  
潘恩春 淮安市疾病预防控制中心, 淮安 223001  
俞浩 江苏省疾病预防控制中心慢性非传染病防制所, 南京 210009  
陆艳 苏州市疾病预防控制中心慢性非传染病防制科, 苏州 215004  
张宁 常熟市疾病预防控制中心, 常熟 215500  
周金意 江苏省疾病预防控制中心慢性非传染病防制所, 南京 210009  
武鸣 江苏省疾病预防控制中心慢性非传染病防制所, 南京 210009 jswuming@vip.sina.com 
摘要点击次数: 1999
全文下载次数: 510
中文摘要:
      目的 探讨2型糖尿病患者中社会经济地位(SES)和全死因死亡风险的关联。方法 以江苏省常熟市、淮安市清江浦区和淮安区纳入国家基本公共卫生服务管理的17 553名2型糖尿病患者作为观察队列。首先通过潜在类别分析,根据5项社会经济指标对患者的SES进行分类。然后利用Cox比例风险回归模型分性别计算不同SES人群随访期间的全死因死亡风险比(HR)及其95%CI,并按照年龄、城乡进行分层分析。结果 研究人群累计随访100 529.08人年,平均随访5.7年,随访期间糖尿病患者死亡1 829人。根据潜在类别模型拟合结果提示含3个潜在类别的模型最佳,故将人群SES分为低(8 256人,47.0%)、中(4 427人,25.2%)、高(4 870人,27.8%)3组。以高SES组为参照,调整混杂因素后,男、女性低SES组发生死亡的HR值(95%CI)分别为1.84(1.53~2.21)和1.41(1.51~1.72)。分层分析发现,男、女性低SES组在 < 60岁患者中发生死亡的HR值(95%CI)分别为1.99(1.12~2.95)和2.01(1.20~3.23),在≥60岁患者中为1.90(1.57~2.31)和1.40(1.13~1.73);男、女性低SES组在城市患者中发生死亡的HR值(95%CI)分别为1.54(1.17~2.04)和1.27(1.02~1.59),在农村患者中为2.11(1.55~2.85)和2.64(1.17~3.35)。结论 低SES可增加2型糖尿病患者死亡风险,且这种负向关联在年轻人和农村人群中更显著。
英文摘要:
      Objective To investigate the relationship between socioeconomic status (SES) and all-cause mortality in patients with type 2 diabetes.Methods 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.Results 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%CI) 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%CI) 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 HR values (95%CI) 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.Conclusions Lower SES increased the risk of all-cause mortality in type 2 diabetic patients, which is more significant in younger and rural populations.
查看全文   Html全文     查看/发表评论  下载PDF阅读器
关闭