PD032
DEFINING THE HEALTHY BENCHMARK: USING PEAK BODY COMPOSITION ASSESSED BY DUAL-ENERGY X-RAY ABSORPTIOMETRY IN YOUNG ADULTS TO IDENTIFY MUSCULAR AND OBESE PHENOTYPES ACROSS THE LIFESPAN OF INDIANS
N. Sanwalka1,2, B. Samant3,*, N. Kajale1, A. Khadilkar1
1Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, 2 Department of Nutrition and Biostatistics, NutriCanvas, 3Clinical Nutrition Therapy, Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute, Mumbai, India
Rationale: Body mass index (BMI) is insufficient for accurately reflecting changes in body fat and muscle mass, especially among Indian populations who tend to have higher body fat percentages at lower BMI levels. Our aim was to develop sex-specific reference values and diagnostic thresholds for body composition indices using DXA, and to assess how these indices change with age and vary in phenotype.
Methods: Cross-sectional study was conducted in 420 healthy adults (215 males) (20–84 years). Body composition was measured using dual-energy X-ray absorptiometry (GE-Lunar iDXA). Reference sub-cohort of healthy, non-obese individuals aged 20–30 years (n=106) was utilized to establish reference values. Diagnostic thresholds were determined through receiver operating characteristic analysis in young cohort aged 20–30 years (n=205) and were validated in adults aged ≥31 years (n=215).
Results: Pronounced sexual dimorphism and age-related variations were noted in all body composition metrics. Females showed higher levels of adiposity, while males had greater muscularity (p<0.05). As age increased, adiposity indices rose, and relative muscularity indices decreased, with the most significant changes occurring after age of 30. Optimal thresholds for elevated obesity risk in males (females) for fat mass index were ≥5.9 kg/m² (≥8.6 kg/m²) while indicators of reduced muscularity relative to adiposity for ASM-to-fat mass ratio was ≤3.07 (≤1.46). These indices, showed high diagnostic accuracy and outperformed BMI in identifying adiposity as defined by body fat percentage.
Conclusion: Results emphasize notable age-related changes in phenotype and reveal that BMI tends to underestimate metabolic risk. The indices developed provide more precise tools for detecting adiposity and could enhance early risk assessment in this demographic.
Disclosure of Interest: None declared
