广西壮族自治区少数民族29~80岁自然人群睡眠状况与2型糖尿病的关联性研究  

Relationship between sleep status and type 2 diabetes among the natural populations of ethnic minorities aged 29-80 in Guangxi Zhuang autonomous region

作　　者：姚美 袁观斗[1,2,3] 陈世连 韦载娲 廖丽娟 何松青 曾小云[4] Yao Mei;Yuan Guandou;Chen Shilian;Wei Zaiwa;Liao Lijuan;He Songqing;Zeng Xiaoyun(Division of Hepatobiliary Surgery,the First Affiliated Hospital of Guangxi Medical University,Nanning 530021,China;Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor(Guangxi Medical University),Ministry of Education,Nanning 530021,China;Guangxi Key Laboratory of Immunology and Metabolism for Liver Diseases,Nanning 530021,China;School of Public Health of Guangxi Medical University,Nanning 530021,China)

机构地区：[1]广西医科大学第一附属医院肝胆外科,南宁530021 [2]区域性高发肿瘤早期防治研究教育部重点实验室(广西医科大学),南宁530021 [3]广西肝脏疾病免疫与代谢研究重点实验室,南宁530021 [4]广西医科大学公共卫生学院,南宁530021

出　　处：《中华实验外科杂志》2025年第1期117-121,共5页Chinese Journal of Experimental Surgery

基　　金：国家重点研发计划(2022YFE0131600);广西自然科学基金(2022GXNSFAA035642);111计划(D17011);广西医科大学高水平创新团队及杏湖学者计划。

摘　　要：目的探讨睡眠状况与2型糖尿病患病风险间的关系。方法选取广西南宁市良庆区2018年1月至2019年12月"广西少数民族慢性病前瞻性队列研究"项目的调查对象5860人作为研究对象。该项目采用横断面研究设计,抽样方法为方便抽样。单因素Logistic回归筛出年龄、体重指数(BMI)、剧烈运动、中等体力活动、散步5个协变量。Lasso回归筛出睡眠质量、入睡时间、睡眠效率、睡眠障碍4个变量。最后,利用5个协变量的3种模型,使用多因素Logistic回归分析4个睡眠变量与2型糖尿病的关系。结果本次调查5860人,有效问卷5856份(有效率为99.9%)。在调查的5856人中,2型糖尿病患病率为3.07%,睡眠不良发生率为21.16%。单因素Logistic回归表明睡眠质量(β=0.50,P<0.01)、睡眠效率(β=0.31,P<0.01)、睡眠障碍(β=0.53,P<0.01)、入睡难易程度(β=0.29,P<0.01)、睡眠总分匹兹堡睡眠质量指数(β=0.12,P<0.01)和2型糖尿病有关联。在14个协变量中,年龄(β=1.34,P<0.01)、体重指数(β=0.49,P<0.01)、剧烈运动(β=-0.39,P<0.05)、中等体力运动(β=-0.58,P<0.05)和散步(β=0.45,P<0.05)5个变量为主要协变量。Lasso回归表明睡眠质量(β=0.23)、入睡难易程度(β=0.09)、睡眠效率(β=0.16)、睡眠障碍(β=0.35)为主要影响因素。3种模型的多因素Logistic回归分析显示睡眠质量[比值比(OR)值=1.26,95%可信区间(CI):0.97~1.63]、睡眠效率(OR=1.17,95%CI:0.98~1.39)、睡眠障碍(OR=1.42,95%CI:1.06~1.91)与2型糖尿病有关联。结论广西少数民族自然人群29~80岁人群中,睡眠不良的发生率较高,睡眠质量差、睡眠效率低和存在睡眠障碍是2型糖尿病的危险因素。Objective To investigate the relationship between sleep status and the risk of Type 2 Diabetes Mellitus(T2DM).Methods A total of 5860 people were selected as the research objects from the"Guangxi Minority Chronic Diseases Prospective Cohort Study"project from January 2018 to December 2019 in Liangqing District,Nanning City,Guangxi Province.This study employed a cross-sectional design with convenience sampling.Univariate logistic regression identified five covariates:age,BMI,vigorous exercise,moderate physical activity,and walking.Lasso regression selected four variables:sleep quality,sleep latency,sleep efficiency,and sleep disorders.Finally,three models using these five covariates were analyzed with multivariate logistic regression to explore the relationship between the four sleep variables and type 2 diabetes.Results A total of 5860 individuals were surveyed,with 5856 valid questionnaires(a validity rate of 99.9%).Among the surveyed individuals,the prevalence of type 2 diabetes was 3.07%,and the incidence of poor sleep was 21.16%.Univariate logistic regression indicated that sleep quality(β=0.50,P<0.01),sleep efficiency(β=0.31,P<0.01),sleep disorders(β=0.53,P<0.01),difficulty falling asleep(β=0.29,P<0.01),and the total score of the Pittsburgh Sleep Quality Index(β=0.12,P<0.01)were associated with type 2 diabetes.Among the 14 covariates,age(β=1.34,P<0.01),body mass index(β=0.49,P<0.01),vigorous exercise(β=-0.39,P<0.05),moderate physical activity(β=-0.58,P<0.05),and walking(β=0.45,P<0.05)were identified as the main covariates.Lasso regression indicated that sleep quality(β=0.23),difficulty falling asleep(β=0.09),sleep efficiency(β=0.16),and sleep disorders(β=0.35)were the main influencing factors.The results of Lasso regression only providedβvalues without P values.Multivariate logistic regression analysis of the three models showed that sleep quality[odds ratio(OR)=1.26,95%confidence interval(CI):0.97-1.63],sleep efficiency(OR=1.17,95%CI:0.98-1.39),and sleep disorders(OR=1.42,95%CI:1.06-1.91)were

关 键 词：睡眠 2型糖尿病 LOGISTIC回归 

分 类 号：R587.1[医药卫生—内分泌]