Association between fat-to-muscle mass ratio and depressive symptoms in U.S. adults: evidence from a nationally...

Emerging evidence suggests that body composition, particularly the balance between fat and muscle mass, may influence mental health. However, the relationship between fat‑to‑muscle mass ratio (FMR) and depressive symptoms in adults remains unclear. This study explored associations between regional and total FMR and depressive symptoms in a nationally representative sample of US adults.

This cross-sectional study included 8767 adults from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Multivariable logistic regression was used to examine associations between arm, leg, trunk, and total FMR and depressive symptoms. Receiver operating characteristic (ROC) analysis, restricted cubic splines (RCS), subgroup analyses, and multiple imputation were performed to assess predictive performance, the shape of the association, and robustness.

Among 8767 US adults, 697 exhibited depressive symptoms. After comprehensive adjustment, multivariable logistic regression analysis revealed that higher leg, trunk, and total FMR were independently associated with greater odds of depressive symptoms (all P < 0.05), while arm FMR was not (P > 0.05). Compared to the lowest quartile, individuals in the highest quartile of leg, trunk, and total FMR had 76% (OR: 1.76, 95% CI 1.06-2.92), 47% (OR: 1.47, 95% CI 1.06-2.04), and 66% (OR: 1.66, 95% CI 1.08-2.56) higher odds, respectively. ROC analysis revealed modest discriminatory accuracy, with AUCs ranging from 0.729 to 0.731. RCS models indicated a linear positive association (P for non-linearity > 0.05). The findings were consistent across subgroups and robust to sensitivity analyses (all P-interaction > 0.05).

Elevated leg, trunk, and total FMR are associated with an increased likelihood of depressive symptoms, positioning FMR as a comprehensive risk indicator that links body composition to mental health. Although useful for risk stratification, its modest predictive performance limits its utility as a standalone screening tool.