Multiple regression model for ascertaining the skeletal muscle mass index using grip strength and lifestyle factors in older outpatients.

[Purpose] Skeletal muscle mass index, an essential parameter for diagnosing sarcopenia, necessitates special measurement. Using clinical data that can be easily evaluated through nutrition counselling, we aimed to develop a formula to derive the skeletal muscle mass index. [Participants and Methods] This retrospective study enrolled older outpatients who visited an acute-care hospital for the periodical consultation of comorbidities. The skeletal muscle mass index was measured using the bioimpedance method. Stepwise multiple linear regression was used to clarify the relationship between the skeletal muscle mass index and various factors, including age, sex, height, body weight, the Charlson Comorbidity Index, grip strength, the Barthel Index, and lifestyle factors. [Results] Among the 142 participants of this study, we applied a prediction model that was derived as follows: skeletal muscle mass index (kg/m²)=0.361 × sex (0: female, 1: male) + 0.068 × body weight (kg) -0.065 × Charlson Comorbidity Index (score) + 0.022 × grip strength (kg) + 0.089 × balanced meals per day (3: three meals, 2: two meals, 1: one meal, or 0: no meals) + 0.101 × working activity (1: unemployed at home, 2: housework, 3: desk work, 4: desk/non-desk work, or 5: non-desk work) + 1.549 (R²=0.847). [Conclusion] Dietary habits and working activities correlated with the skeletal muscle mass index. This model may facilitate the calculation of the skeletal muscle mass index in patients whose bioimpedance data are unavailable.