Some limitations of the current study should be noted. First, in previous literature reports, manyresearchers established and disclosed various equations using professional BIA devices for estimatingbody composition [ 17 , 43 ]. We did not examine these because there are too many published equationsto examine them all, the majority of them are not designed for the Asian population, at least half of theequations include age, and these equations were developed against multiple different gold standards(MRI, CT, underwater weighting, stable isotope dilution, and DXA) for estimating different bodycomposition parts. We cannot state the superiority of the current equation compared with previouslyestablished and disclosed equations, which was not the focus of the current analysis. Second, EWGSOPstated that CT and MRI are gold standards for estimating SMM, and ALM of DXA is considered to bean alternative preferred method [ 7 ]. However, whole body CT scan requires a high level of radiationexposure, and whole body MRI requires time-consuming post-scan image processing to obtain SMM;thus, we used ALM derived from DXA as the reference. Theoretically, ALM of DXA reflects whole leantissue mass and is not perfectly equal to SMM. In addition, muscle quality and muscle compositionchange with aging [ 50 – 57 ], but the current study does not examine these effect. As another limitation,Prado et al. [ 58 ] stated that a single cutoff may not suitable for all ages; they used a large dataset ofDXA ALM with 13,236 individuals from the 1999 to 2004 NHANES cohort and LMS curve-fittingprocedure to establish age and gender specific cutoffs. Our current sample size is much lower than theprevious study, thus we need collect more data to develop age and gender specific cut offs based onthe LMS method. Further research is needed. Strengths of this study include the adequate sample sizeto develop and validate a new equation and establish sarcopenia cut off values, and the theoreticalequation development in the present study.