Identification of risk factors for diabetes in Chinese middle-aged and elderly adults
Rattachement africain : my, cn, au. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
This study aimed to identify and analyze the factors associated with the prevalence of diabetes among Chinese adults, using data from the China Health and Retirement Longitudinal Study (CHARLS). Data from the CHARLS cohort, with a mean age of 63.3 years, were analyzed using SPSS software. Descriptive statistics were performed for the overall population, as well as urban and rural subgroups. Logistic regression models were employed to assess the association between diabetes and variables such as age, gender, smoking, alcohol consumption, hypertension, and mental health disorders. Paired-sample t-tests were conducted to evaluate changes in diabetes prevalence across 2015, 2018, and 2020. The average of diabetes increased from 1.08 in 2015 to 1.15 in 2020, with a statistically significant difference (P < 0.001). Paired-sample t-tests showed significant differences between 2020 and 2018, as well as between 2018 and 2015 (P < 0.001). Logistic regression analysis identified hypertension (aOR = 0.447, 95% CI: 0.410-0.488, P < 0.001) and chronic disease (aOR = 0.024, 95% CI: 0.013-0.042, P < 0.001) as key risk factors for diabetes. Mild physical exercise was a protective factor (aOR = 0.813, 95% CI: 0.708-0.935, P < 0.01), while smoking (aOR = 1.220, 95% CI: 1.088-1.369, P < 0.001) and alcohol consumption (aOR = 1.125, 95% CI: 1.020-1.242, P < 0.05) increased the risk. Smoking and alcohol had a greater impact in urban areas, while hypertension and mental health disorders were more influential in rural areas. This study demonstrates that age, gender, smoking, alcohol consumption, hypertension, and mental disorders significantly influence the risk of diabetes among Chinese adults aged 45 and above. Distinct risk factors were identified between urban and rural populations, highlighting the necessity for tailored intervention strategies. The longitudinal analysis from 2015 to 2020 revealed a substantial increase in diabetes prevalence, underscoring the critical need for sustained and targeted public health efforts.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Identification of risk factors for diabetes in Chinese middle-aged and elderly adults
- Date Crossref
- 12/04/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
-
Universiti Putra Malaysia pays non établi dans la noticeUniversité ou école supérieure
-
Guilin University of Aerospace Technology pays non établi dans la noticeUniversité ou école supérieure
-
Guilin University of Technology pays non établi dans la noticeUniversité ou école supérieure
-
Guilin University of Electronic Technology pays non établi dans la noticeUniversité ou école supérieure
-
Binzhou Medical University pays non établi dans la noticeUniversité ou école supérieure
-
Shandong University of Aeronautics pays non établi dans la noticeUniversité ou école supérieure
-
The University of Sydney pays non établi dans la noticeUniversité ou école supérieure
-
Guangxi Normal University pays non établi dans la noticeUniversité ou école supérieure
-
College of Public Administration pays non établi dans la noticeUniversité ou école supérieure
-
Faculty of Educational Studies Department of Sports Studies pays non établi dans la noticeUniversité ou école supérieure
-
College of Materials Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
-
Faculty of Medicine and Health pays non établi dans la noticeUniversité ou école supérieure
Universiti Putra Malaysia, Guilin University of Aerospace Technology et Guilin University of Technology, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.