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Sex-specific associations between skeletal muscle mass and incident diabetes: A population-based cohort study.
- Source :
-
Diabetes, obesity & metabolism [Diabetes Obes Metab] 2024 Mar; Vol. 26 (3), pp. 820-828. Date of Electronic Publication: 2023 Nov 23. - Publication Year :
- 2024
-
Abstract
- Aims: To investigate the sex-specific associations between predicted skeletal muscle mass index (pSMI) and incident type 2 diabetes in a retrospective longitudinal cohort of Chinese men and women.<br />Materials and Methods: We enrolled Chinese adults without diabetes at baseline from WATCH (West chinA adulT health CoHort), a large health check-up-based database. We calculated pSMI to estimate skeletal muscular mass, and measured blood glucose variables and assessed self-reported history to identify new-onset diabetes. The nonlinear association between pSMI and incident type 2 diabetes was modelled using the penalized spline method. The piecewise association was estimated using segmented linear splines in weighted Cox proportional hazards regression models.<br />Results: Of 47 885 adults (53.2% women) with a median age of 40 years, 1836 developed type 2 diabetes after a 5-year median follow-up. In women, higher pSMI was associated with a lower risk of incident type 2 diabetes (P <subscript>nonlinearity</subscript> = 0.09, hazard ratio [HR] per standard deviation increment in pSMI: 0.79 [95% confidence interval {CI} 0.68, 0.91]). A nonlinear association of pSMI with incident type 2 diabetes was detected in men (P <subscript>nonlinearity</subscript> < 0.001). In men with pSMI lower than 8.1, higher pSMI was associated with a lower risk of incident type 2 diabetes (HR 0.58 [95% CI 0.40, 0.84]), whereas pSMI was not significantly associated with incident diabetes in men with pSMI equal to or greater than 8.1 (HR 1.08 [95% CI 0.93, 1.25]).<br />Conclusions: In females, a larger muscular mass is associated with a lower risk of type 2 diabetes. For males, this association is significant only among those with diminished muscle mass.<br /> (© 2023 John Wiley & Sons Ltd.)
Details
- Language :
- English
- ISSN :
- 1463-1326
- Volume :
- 26
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Diabetes, obesity & metabolism
- Publication Type :
- Academic Journal
- Accession number :
- 37997500
- Full Text :
- https://doi.org/10.1111/dom.15373