Abstract

Body mass index cannot distinguish between fat-mass and muscle-mass, which may result in obesity misclassification. A dual-energy x-ray absorptiometry (DXA)-derived phenotype classification based on fat-mass and muscle-mass has been proposed for adults (>18 yo). We extend this research by developing children’s fat-mass and muscle-mass reference curves and determining their utility in identifying cardiometabolic risk. Children’s (≤17 yo) DXA data in NHANES, a US national health survey (n=6,120) were used to generate sex- and age-specific deciles of appendicular skeletal muscle index and fat mass index (kg/m2) with the Lambda Mu Sigma (LMS) method. The final curves were selected through goodness of fit (AIC, Q-tests, detrended Q-Q plot). Four phenotypes (high [H] or low [L], adiposity [A] and muscle mass [M]: HA-HM, HA-LM, LA-HM, LA-LM) were identified using the literature’s guidelines above/below the median compared to same-sex and same-age peers. The curves and their corresponding phenotypes were applied to QUALITY data, a longitudinal cohort (n=630, 8-10 yo in 2005) to assess whether the phenotypes correctly identified cardiometabolic risk using multiple linear regression at baseline, follow-up one (2008-2010), or follow-up two (2015-2017). Models were adjusted for age, sex, and Tanner’s stage. Chained equation was used to impute missing values in QUALITY. Compared to LA-HM, LA-LM was associated with lower glucose at baseline; HA-HM was associated with lower HDL-c and higher LDL-c, triglycerides, and HOMA-IR; HA-LM was associated with elevated triglycerides and HOMA-IR at all timepoints (all p<0.05). These phenotypes allowed for discrimination of cross-sectional cardiometabolic risks, but further longitudinal exploration is recommended.