Abstract
Lean body mass (LBM) and muscle mass remain difficult to quantify in large epidemiological studies due to the unavailability of inexpensive methods. We therefore developed anthropometric prediction equations to estimate the LBM and appendicular lean soft tissue (ALST) using dual-energy X-ray absorptiometry (DXA) as a reference method. Healthy volunteers (n = 2,220; 36% women; age 18-79 yr), representing a wide range of body mass index (14–44 kg/m2), participated in this study. Their LBM, including ALST, was assessed by DXA along with anthropometric measurements. The sample was divided into prediction (60%) and validation (40%) sets. In the prediction set, a number of prediction models were constructed using DXA-measured LBM and ALST estimates as dependent variables and a combination of anthropometric indices as independent variables. These equations were cross-validated in the validation set. Simple equations using age, height, and weight explained >90% variation in the LBM and ALST in both men and women. Additional variables (hip and limb circumferences and sum of skinfold thicknesses) increased the explained variation by 5–8% in the fully adjusted models predicting LBM and ALST. More complex equations using all of the above anthropometric variables could predict the DXA-measured LBM and ALST accurately, as indicated by low standard error of the estimate (LBM: 1.47 kg and 1.63 kg for men and women, respectively), as well as good agreement by Bland-Altman analyses (Bland JM, Altman D. Lancet 1: 307–310, 1986). These equations could be a valuable tool in large epidemiological studies assessing these body compartments in Indians and other population groups with similar body composition.
Highlights
LEAN BODY MASS (LBM), the metabolically active compartment of the body, plays a central role in a number of physiologic processes [24]
Dual-energy X-ray absorptiometry (DXA) can estimate appendicular lean soft tissue (ALST), which is used as a surrogate of skeletal muscle mass [11, 12], and the majority of the operative definitions of sarcopenia uses cutpoints based on estimation of ALST by DXA [4, 7]
There were no significant differences in age and physical characteristics of men in the two groups, but women in the validation group were younger and lighter and had lower LBM and ALST compared with women in the prediction group
Summary
LEAN BODY MASS (LBM), the metabolically active compartment of the body, plays a central role in a number of physiologic processes [24]. Anthropometry is one of the oldest techniques of body composition assessment, which has been validated by cadaver studies and other gold-standard methods [5, 21, 23]. It offers distinct advantages of being simple, portable, noninvasive, and inexpensive. The use of anthropometry to assess body composition, continues to play an important role in clinical practice and in large population-based studies. Anthropometric assessment of body composition relies on prediction equations derived from gold-standard methods. We developed equations to predict LBM and ALST based on anthropometric variables using DXA as a reference method in a sample of Indian adults
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