| Title: | Fat-muscle balance and incident diabetes: evidence from Chinese and UK cohorts |
| Journal: | Diabetes Research and Clinical Practice |
| Published: | 1 Jun 2026 |
| DOI: | https://doi.org/10.1016/j.diabres.2026.113363 |
Publication 19817
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Abstract
Background Excess adiposity is a major risk factor for diabetes, but conventional anthropometric indices such as body mass index do not distinguish between fat and lean mass. How body composition, particularly fat-free mass (FFM) and fat mass (FM) balance, relates to incident diabetes remains unclear. Methods We analyzed a Chinese health examination cohort (n = 2,252) and the UK Biobank (UKB; n = 472,158). Incident diabetes was identified through chronic disease registry (Chinese cohort) and from hospital/primary care records plus medication data (UKB). Cox models estimated the associations of fat mass index (FMI), fat-free mass index (FFMI), FFM/FM, and appendicular skeletal muscle mass index (ASMI) with incident diabetes. Results During a median follow-up of 4.3 and 14.3 years, 115 (5.1%) and 22,563 (4.8%) participants developed diabetes in the Chinese cohort and UKB, respectively. Higher FMI and FFMI were associated with higher diabetes risk in both cohorts. In contrast, FFM/FM was inversely associated with incident diabetes in the Chinese cohort (HR [95% CI] = 0.45 [0.28-0.71], P = 0.001) and UKB (HR [95% CI] = 0.50 [0.48-0.51], P < 0.001). ASMI was null in the Chinese cohort but was positively associated with diabetes in UKB. Conclusion FFM/FM was a more consistent and informative indicator of diabetes risk than absolute lean mass indices</p>
7 Authors
- Yuanyuan Wu
- Min Yang
- Yang Gao
- Ying Mei
- Dongfang Liu
- Xianbin Ding
- Feifei Cheng
1 Application
| Application ID | Title |
|---|---|
| 91850 | Using phenome-wide mendelian randomization and machine leaning to identify novel drug targets for aging and aging-related disease |
Enabling scientific discoveries that improve human health