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Comparison of the associations between appendicular lean mass adjustment methods and cardiometabolic factors
1Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Background And Aims:
To compare the cross-sectional and longitudinal associations between appendicular lean mass (ALM) and cardiometabolic risk factors according to body-size adjustment methods and the contributions of genetic and/or environmental factors to the correlations between those traits.
Methods And Results:
Regression coefficients per sex-specific 1 standard deviation in bodyweight (wt), body mass index (BMI), or height-squared (ht2) adjusted ALM (assessed using a dual-energy X-ray absorptiometer (DXA) and a bioelectrical impedance analyzer (BIA) at baseline)/changes in these indices (assessed using BIA) were compared in terms of their associations with blood pressure (BP), lipid profiles, and insulin resistance profiles in 2655 participants for cross-sectional analysis and 332 participants for longitudinal analysis (follow-up time, 32.2 ± 7.9 months). A bivariate genetic analysis of the genetic/environmental cross-trait correlations was conducted to determine their cross-sectional relationships. After adjusting for sociodemographic factors, health behaviors, and BMI in the analysis for ALM/ht2, ALM/wt and ALM/BMI had favorable associations with all cardiometabolic risk factors, while ALM/ht2 had favorable associations with some risk factors. In longitudinal associations, changes in ALM/wt and ALM/BMI had inverse associations with increments of lipid profiles, insulin, and homeostasis model assessment of insulin resistance (HOMA), while change in ALM/ht2 did not have associations with increments of cardiometabolic risk factors. ALM/ht2 had genetic correlations with seven of nine risk factors; ALM/wt and ALM/BMI had correlations with three and one risk factors, respectively.
Conclusion:
ALM/wt and ALM/BMI are better indicators for cardiometabolic risk factors; genetic factors may contribute more to the correlations between ALM/ht2 and those traits.

