O080
A NOVEL BODY PHENOTYPE SCORING SYSTEM: A COMPREHENSIVE METHOD FOR ASSESSING THE QUANTITY AND FUNCTION OF MUSCLE AND FAT
W. Ji1,*, H. He1, X. Liu1, J. Cui1
1Jilin University First Hospital, Changchun, China
Rationale: Skeletal muscle and adipose tissue are key indicators of nutritional status, exhibiting substantial crosstalk and context-dependent contributions to health; thus, an integrated framework incorporating both is needed to assess overall health status.
Methods: UK Biobank participants with complete data (n = 485,821) were randomly split into derivation (70%) and validation (30%) sets. Key variables (anthropometric, body composition, physical function) and outcomes [falls, metabolic syndrome (MetS), cancer, all-cause mortality] were collected. Predictors were selected using LASSO logistic regression, and continuous variables were optimally binned. A point-based score for falls was developed via grid search, with risk strata defined by dynamic programming. Associations with outcomes were assessed using logistic regression and log-rank tests. Subgroup analyses validated robustness.
Results: Derivation and validation sets were well balanced (all P > 0.05). The rs-MFSS (0–22 points), based on fat mass, waist-to-height ratio, handgrip strength, and walking pace, showed a monotonic increase in fall risk. Three strata (low:0–9, intermediate:10–17, high:18–22 points) demonstrated good discrimination. Across both sets, falls, MetS, and cancer increased stepwise (all P < 0.001), while survival declined (log-rank P < 0.001). Subgroup analyses showed higher mortality risk in the high-risk group, with consistent gradients.
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Conclusion: The rs-MFSS, integrating skeletal muscle and adipose tissue across quantity, function, and distribution, showed robust predictive performance for multiple outcomes, including MetS, cancer, and mortality. Developed using a data-driven approach, it offers a concise yet comprehensive tool that outperforms single indicators, with consistent validation supporting its utility as a simple, generalizable approach for risk stratification and future research.
Disclosure of Interest: None declared