PD550 - OBJECTIVE GENDER-RELATED TRAIT ASSESSMENT BY BIOELECTRICAL IMPEDANCE ANALYSIS

PD550

OBJECTIVE GENDER-RELATED TRAIT ASSESSMENT BY BIOELECTRICAL IMPEDANCE ANALYSIS

M. Nishizawa^1,*, Y. Oshima¹, T. Nagahama¹, T. Shiota¹, T. Miyama¹, M. Ishikawa¹, Y. Yamada², A. Pietrobelli³, S. B. Heymsfield⁴

¹R&D Dept, TANITA, Tokyo, ²Department of Medicine and Science in Sports and Exercise, Tohoku University, Sendai, Japan, ³Gynaecology and Pediatrics, University of Verona, Verona, Italy, ⁴Metabolism & Body Composition, Pennington Biomedical Research Center, Louisiana, United States

Rationale: Binary gender input in body composition devices may create psychological burden and may not fully reflect individual diversity; however, using a single common prediction equation without considering gender-related skeletal and tissue characteristics may increase estimation error. We investigated whether BIA-derived traits could be used to classify individuals and assign appropriate prediction equations without requiring gender input.

Methods: Multi-frequency BIA was performed in 901 adults (M: 413, F: 488) aged 18–86 years using the MC-980 (TANITA, Japan). Resistance distribution maps by gender and age were constructed, and trait scores were derived from each individual’s position on these maps. Using these scores, prediction equations were selected and weighted without gender input to estimate %fat and muscle mass. Results were compared with DXA and with conventional assessment using self-selected gender input.

Results: Objective evaluation based on combinations of multiple resistance distribution maps showed >80% concordance with genetic classification as male or female and was generally consistent with self-identified gender. When prediction equations were weighted according to these trait scores, estimated %fat and muscle mass showed extremely strong correlations with values obtained using self-selected gender input (R > 0.99, p < 0.0001) and also correlated strongly with DXA measurements (R > 0.93, p < 0.0001).

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Conclusion: Gender-related physical traits relevant to body composition assessment may be captured objectively from multi-frequency BIA resistance patterns and may be distributed along a continuum rather than a simple binary classification. This approach may support more individualized body composition assessment without requiring gender input.

Disclosure of Interest: None declared