Seino, S., Kitamura, A., Abe, T., et al. (2020) Dose-Response Relationships between Body Composition Indices and All-Cause Mortality in Older Japanese Adults. Journal of the American Medical Directors Association, 21, 726-733.
https://doi.org/10.1016/j.jamda.2019.11.018

has been cited by the following article:

• TITLE: Comparison of the Two Algorithms of Skeletal Muscle Mass Index: An Observational Study in a Large Cohort of Chinese Adults

  AUTHORS: Ying Sui, Zhen Huang, Shengyong Dong, Yansong Zheng

  KEYWORDS: Physical Examination, Body Weight, Muscle Mass, Skeletal Muscle Mass Index

  JOURNAL NAME: Health, Vol.14 No.8, August 22, 2022

  ABSTRACT: Objective: To compare the two skeletal muscle mass index (SMI) algorithms. One is SMM [SMM(%) = total skeletal muscle mass (kg)/body weight mass (kg) × 100%]; and the other is SMH [SMH (kg/m2) = total skeletal muscle mass (kg)/height (m)2]. Methods: Body composition, body mass index (BMI) and body fat percentage (BFP) were estimated using a bioelectrical impedance analyzer. SMI was calculated by the two algorithms described above, and measurement parameters were stratified by age, BMI and levels of physical activity. Results: Levels of BMI, BFP, SMM and SMH differed significantly between the sexes. BMI and BFP were positively associated with age, while SMM was negatively associated with age (β = −0.2294, P β = −0.5340, P β = 0.7930, P β = −0.9849, P β = −0.0642, P F = 9528.32, P F = 34395.46, P F = 9706.20, P P P > 0.05). Conclusions: SMM may be a more ideal and accurate clinical algorithm for SMI because it is more tightly associated with other body composition indices, as compared with SMH.