Comparison of the associations between appendicular lean mass adjustment methods and cardiometabolic factors
- Authors
- Song, Y.-M.[Song, Y.-M.]; Lee, K.[Lee, K.]
- Issue Date
- 27-Nov-2020
- Publisher
- Elsevier B.V.
- Keywords
- Appendicular lean mass; Body-size; Cardiometabolic factors; Genetic correlations
- Citation
- Nutrition, Metabolism and Cardiovascular Diseases, v.30, no.12, pp.2271 - 2278
- Indexed
- SCIE
SCOPUS
- Journal Title
- Nutrition, Metabolism and Cardiovascular Diseases
- Volume
- 30
- Number
- 12
- Start Page
- 2271
- End Page
- 2278
- URI
- https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/6439
- DOI
- 10.1016/j.numecd.2020.07.036
- ISSN
- 0939-4753
- Abstract
- 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. © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University
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Collections - Medicine > Department of Medicine > 1. Journal Articles
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