Skeletal muscle mass and all‐cause mortality: Findings from the CRONICAS cohort study. Issue 2 (2nd January 2023)

• Record Type: Journal Article
• Authors: Bernabe‐Ortiz, Antonio; Carrillo‐Larco, Rodrigo M.; Gilman, Robert H.; Smeeth, Liam; Checkley, William; Miranda, J. Jaime
• Is Part Of: Tropical medicine & international health. Volume 28:Issue 2(2023)
• Page Start: 107
• Page End: 115
• Publication Date: 2023-01-02
• Subjects: all‐cause mortality -- bio‐impedance analysis -- cohort study -- skeletal muscle mass; Tropical medicine -- Periodicals; Public health -- Periodicals; 616.988
• DOI: 10.1111/tmi.13844
• Languages: English
• ISSNs: 1360-2276

Abstract

Abstract: Objective: We aimed (1) to evaluate the agreement between two methods (equation and bio‐impedance analysis [BIA]) to estimate skeletal muscle mass (SMM), and (2) to assess if SMM was associated with all‐cause mortality risk in individuals across different geographical sites in Peru. Methods: We used data from the CRONICAS Cohort Study (2010–2018), a population‐based longitudinal study in Peru to assess cardiopulmonary risk factors from different geographical settings. SMM was computed as a function of weight, height, sex and age (Lee equation) and by BIA. All‐cause mortality was retrieved from national vital records. Cox proportional‐hazard models were developed and results presented as hazard ratios (HRs) with 95% confidence intervals (95% CIs). Results: At baseline, 3216 subjects, 51.5% women, mean age 55.7 years, were analysed. The mean SMM was 23.1 kg (standard deviation [SD]: 6.0) by Lee equation, and 22.7 (SD: 5.6) by BIA. Correlation between SMM estimations was strong (Pearson's ρ coefficient = 0.89, p < 0.001); whereas Bland–Altman analysis showed a small mean difference. Mean follow‐up was 7.0 (SD: 1.0) years, and there were 172 deaths. In the multivariable model, each additional kg in SMM was associated with a 19% reduction in mortality risk (HR = 0.81; 95% CI: 0.75–0.88) using the Lee equation, but such estimate was not significant when using BIA (HR = 0.98; 95% CI: 0.94–1.03). Compared to the lowest tertile, subjects at the highest SMM tertile had a 56% reduction in risk of mortality using the Lee equation, but there was no such association when using BIA estimations. Conclusion: There is a strong correlation and agreement between SMM estimates obtained by the Lee equation and BIA. However, an association between SMM and all‐cause mortality exists only when the Lee equation is used. Our findings call for appropriate use of approaches to estimate SMM, and there should be a focus on muscle mass in promoting healthier ageing.