Association between fat-to-muscle ratio and diabetic kidney disease: a nationwide NHANES analysis with real-world validation - Zhang, Xiaohong; Lin, Jiaqun; Wang, Wenfeng; Lin, Zishan; Fang, Yuan; Xu, Yanfang; Wan, Jianxin (Frontiers in Nutrition, 2025)
BackgroundObesity and abnormal body composition are recognized contributors to diabetic kidney disease (DKD) development. The fat-to-muscle mass ratio (FMR), an indicator of body composition, remains insufficiently studied in relation to DKD risk.MethodsThis study was a nationwide cohort analysis utilizing data from eight National Health and Nutrition Examination Survey (NHANES) cycles. FMR was derived using dual-energy X-ray absorptiometry (DXA) and evaluated in both categorical and continuous forms. Given the cross-sectional design of NHANES for DKD status assessment, the association between FMR and DKD was analyzed as a prevalence association. Mortality outcomes were further evaluated via retrospective linkage to the National Death Index, forming a retrospective mortality cohort among prevalent DKD cases. To validate the association between FMR and DKD prevalence, we additionally analyzed an independent hospital-based clinical cohort, in which FMR indices were also measured by DXA, and a logistic regression analysis was performed.ResultsAfter applying the exclusion criteria, 680 DKD patients were included in the analysis. Over a median follow-up of 97 months, 267 deaths (37.58%) were recorded. DKD patients exhibited significantly higher arm-FMR, trunk-FMR, and total-FMR values. A logistic regression analysis revealed that arm-FMR, trunk-FMR, and total-FMR were independently associated with an increased DKD risk (all p < 0.0001). Stratified subgroup analyses further confirmed significant associations between FMR and DKD, with notable interactions observed in arm-FMR and trunk-FMR when stratified by age and sex. The receiver operating characteristic curve analysis demonstrated that trunk-FMR exhibited the strongest predictive value for DKD (AUC = 0.812, sensitivity = 85.9%, specificity = 63.8%). The Kaplan–Meier survival curves revealed that lower FMR quartiles were associated with better survival outcomes for both all-cause and CVD mortality among DKD patients (all log-rank p < 0.001). Moreover, non-linear associations were detected between FMR and DKD prevalence, as well as between FMR and mortality outcomes. In the real-world validation cohort consisting of 94 patients, a univariate logistic analysis revealed that all FMRs were identified as risk factors for the development of DKD. Another multivariate logistic analysis revealed that trunk-FMR exhibited the highest predictive model value (OR = 12.029, 95% CI 1.431–121.317, p = 0.026, AUC = 0.735).ConclusionThis NHANES-based study identified a robust association between FMR and DKD prevalence, along with all-cause and CVD mortality. Importantly, these associations were further supported by an independent real-world clinical cohort, underscoring the robustness and generalizability of our findings. Optimizing FMR may play a pivotal role in improving the prognosis of DKD patients.