Muscle-to-fat ratio identifies functional impairments and cardiometabolic risk and predicts outcomes: biomarkers of sarcopenic obesity

Background Sarcopenic obesity aims to capture the risk of functional decline and cardiometabolic diseases, but its operational definition and associated clinical outcomes remain unclear. Using data from the Longitudinal Aging Study of Taipei, this study explored the roles of the muscle-to-fat ratio (MFR) with different definitions and its associations with clinical characteristics, functional performance, cardiometabolic risk and outcomes. Methods (1) Appendicular muscle mass divided by total body fat mass (aMFR), (2) total body muscle mass divided by total body fat mass (tMFR) and (3) relative appendicular skeletal muscle mass (RASM) were measured. Each measurement was categorized by the sex-specific lowest quintiles for all study participants. Clinical outcomes included all-cause mortality and fracture. Results Data from 1060 community-dwelling older adults (mean age: 71.0 +/- 4.8 years) were retrieved for the study. Overall, 196 (34.2% male participants) participants had low RASM, but none was sarcopenic. Compared with those with high aMFR, participants with low aMFR were older (72 +/- 5.6 vs. 70.7 +/- 4.6 years, P = 0.005); used more medications (2.9 +/- 3.3 vs. 2.1 +/- 2.5, P = 0.002); had a higher body fat percentage (38 +/- 4.8% vs. 28 +/- 6.4%, P < 0.001), RASM (6.7 +/- 1.0 vs. 6.5 +/- 1.1 kg/m(2), P = 0.001), and cardiometabolic risk [fasting glucose: 105 +/- 27.5 vs. 96.8 +/- 18.7 mg/dL, P < 0.001; glycated haemoglobin (HbA1c): 6.0 +/- 0.8 vs. 5.8 +/- 0.6%, P < 0.001; triglyceride: 122.5 +/- 56.9 vs. 108.6 +/- 67.5 mg/dL, P < 0.001; high-density lipoprotein cholesterol (HDL-C): 56.2 +/- 14.6 vs. 59.8 +/- 16 mg/dL, P = 0.010]; and had worse functional performance [Montreal Cognitive Assessment (MoCA): 25.7 +/- 4.2 vs. 26.4 +/- 3.0, P = 0.143, handgrip strength: 24.7 +/- 6.7 vs. 26.1 +/- 7.9 kg, P = 0.047; gait speed: 1.8 +/- 0.6 vs. 1.9 +/- 0.6 m/s, P < 0.001]. Multivariate linear regression showed that age (beta = 0.093, P = 0.001), body mass index (beta = 0.151, P = 0.046), total percentage of body fat (beta = 0.579, P < 0001) and RASM (beta = 0.181, P = 0.016) were associated with low aMFR. Compared with those with high tMFR, participants with low tMFR were older (71.7 +/- 5.5 vs. 70.8 +/- 4.7 years, P = 0.075); used more medications (2.8 +/- 3.3 vs. 2.1 +/- 2.5, P = 0.006); had a higher body fat percentage (38.1 +/- 4.7 vs. 28 +/- 6.3%, P < 0.001), RASM (6.8 +/- 1.0 vs. 6.5 +/- 1.1 kg/m(2), P < 0.001), and cardiometabolic risk (fasting glucose: 104.8 +/- 27.6 vs. 96.9 +/- 18.7 mg/dL, P < 0.001; HbA1c: 6.1 +/- 0.9 vs. 5.8 +/- 0.6%, P < 0.001; triglyceride: 121.4 +/- 55.5 vs. 108.8 +/- 67.8 mg/dL, P < 0.001; HDL-C: 56.4 +/- 14.9 vs. 59.7 +/- 15.9 mg/dL, P = 0. 021); and had worse functional performance (MoCA: 25.6 +/- 4.2 vs. 26.5 +/- 3.0, P = 0.056; handgrip strength: 24.6 +/- 6.7 vs. 26.2 +/- 7.9 kg, P = 0.017; gait speed: 1.8 +/- 0.6 vs. 1.9 +/- 0.6 m/s, P < 0.001). Low tMFR was associated with body fat percentage (beta = 0.766, P < 0.001), RASM (beta = 0.476, P < 0.001) and Mini-Nutritional Assessment (beta = -0.119, P < 0.001). Gait speed, MoCA score, fasting glucose, HbA1c and tMFR were significantly associated with adverse outcomes, and the effects of aMFR were marginal (P = 0.074). Conclusions Older adults identified with low MFR had unfavourable body composition, poor functional performance, high cardiometabolic risk and a high risk for the clinical outcome.