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Prevalence and potential risk factors of self-reported diabetes among elderly people in China: A national cross-sectional study of 224,142 adults

Xing Hu, Ling‐bing Meng, Zhimin Wei, Hongxuan Xu, Jianyi Li, Yingying Li, Na Jia, Hui Li, Qi Xin, Xuezhai Zeng, Qiuxia Zhang, Juan Li, Deping Liu

2022Frontiers in Public Health15 citationsDOIOpen Access PDF

Abstract

Aim To evaluated the prevalence and potential risk factors of self-reported diabetes among the elderly in China, by demographic data, socioeconomic factors, and psychological factors. Methods Descriptive analysis and Chi-square analysis were used to assess the prevalence and variation between self-reported diabetes and non-diabetes by demographic data, living habits, socioeconomic factors and comorbidities. Univariate and multivariate logistic regression were used to describe the odds ratios (OR) of diabetes prevalence in different groups, while stratification analysis was performed to describe prevalence based on gender, age, and urban/rural areas. Results 215,041 elderly adults (102,692 males and 112,349 females) were eventually included in the analysis. The prevalence of self-reported diabetes among the elderly in China is about 8.7%, with the highest prevalence in Beijing (20.8%) and the lowest prevalence in Xizang (0.9%). Logistic regression analysis showed that urban area ( P < 0.001), older age (65–84 years old, P < 0.001), female ( P < 0.001), higher income( P < 0.001), poor sleep quality ( P = 0.01) and some other factors were potential risk factors for diabetes. Conclusions This study illustrates the prevalence and potential risk factors of diabetes among the elderly in China Meanwhile, these results provide information to assist the government in controlling non-communicable diseases in the elderly.

Topics & Concepts

MedicineDiabetes mellitusSocioeconomic statusCross-sectional studyLogistic regressionDemographyEnvironmental healthGerontologyMultivariate analysisOdds ratioPopulationInternal medicineEndocrinologyPathologySociologyDiabetes, Cardiovascular Risks, and LipoproteinsChronic Disease Management StrategiesDiabetes Management and Education
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