| Title: | Risk Factors for Sarcopenia in Women with Type 2 Diabetes and the Effects of Metformin: A Cross-Sectional Study of 7,731 Patients from the UK Biobank |
| Journal: | International Journal of Women's Health |
| Published: | 1 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41268386/ |
| DOI: | https://doi.org/10.2147/ijwh.s556435 |
| URL: | https://www.dovepress.com/article/download/108932 |
Publication 19076
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Objective: To examine the sarcopenia risk factors and the association between metformin use and sarcopenia in female patients with Type 2 diabetes mellitus (T2DM) through a cross-sectional analysis of data from the UK Biobank.</p>
Methods: In a cross-sectional analysis of 7,731 women with T2DM from the UK Biobank, participants were categorized into nonsarcopenia, probable sarcopenia, and sarcopenia groups based on the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Logistic regression models were employed to investigate the association between metformin use and sarcopenia, adjusting for age, education, physical activity, and comorbidities.</p>
Results: The prevalence of probable sarcopenia and sarcopenia was 16.2% and 3.4%, respectively, with rates increasing with age. Metformin use was significantly associated with a higher risk of sarcopenia (adjusted OR 1.13; 95% CI 1.01-1.26). This association remained consistent across various subgroups, including different age ranges and levels of physical activity.</p>
Conclusion: Metformin use was cross-sectionally associated with higher odds of sarcopenia, particularly in older women with low physical activity and comorbidities. These findings highlight the need for further longitudinal and mechanistic studies to confirm the relationship and explore potential underlying mechanisms.</p>
12 Authors
- Nianchun Liao
- Jianan Chen
- Wenjun Hu
- Huihong Shi
- Song Liu
- Zaoqiang Zhang
- Youxi Lin
- Xianjian Qiu
- Yanbo Chen
- Tongzhou Liang
- Peijie Shi
- Wenjie Gao
1 Application
| Application ID | Title |
|---|---|
| 117320 | Identifying potential interactions and crosstalk between brain and bone during in degenerative or rheumatic bone disease using UK Biobank |
Enabling scientific discoveries that improve human health