Simple Skeletal Muscle Mass Estimation Formulas: What We Can Learn From Them.

Steven B Heymsfield,Abishek Stanley,Moonseong Heo,Angelo Pietrobelli

doi:10.3389/fendo.2020.00031

Abstract

One century ago Harris and Benedict published a short report critically examining the relations between body size, body shape, age, and basal metabolic rate. At the time, basal metabolic rate was a vital measurement in diagnosing diseases such as hypothyroidism. Their conclusions and basal metabolic rate prediction formulas still resonate today. Using the Harris-Benedict approach as a template, we systematically examined the relations between body size, body shape, age, and skeletal muscle mass (SM), the main anatomic feature of sarcopenia. The sample consisted of 12,330 non-Hispanic (NH) white and NH black participants in the US National Health and Nutrition Survey who had complete weight, height, waist circumference, age, and dual-energy X-ray (DXA) absorptiometry data. A conversion formula was used to derive SM from DXA-measured appendicular lean soft tissue mass. Weight, height, waist circumference, and age alone and in combination were significantly correlated with SM (all, p < 0.001). Advancing analyses through the aforementioned sequence of predictor variables allowed us to establish how at the anatomic level these body size, body shape, and age measures relate to SM much in the same way the Harris-Benedict equations provide insights into the structural origins of basal heat production. Our composite series of SM prediction equations should prove useful in modeling efforts and in generating hypotheses aimed at understanding how SM relates to body size and shape across the adult lifespan.

Highlights

We examine the individual and combined effects of weight, height, waist circumference, and age on skeletal muscle mass (SM) prediction in a large sample (n = 12,330) of National Health and Nutrition Survey (NHANES) non-Hispanic (NH) white and NH black participants [7, 8]
Benedict published a short paper examining “the relationship between certain of the physical and physiological measurements of the individual” [1]. Reporting their meticulous studies in 136 men and 103 women, Harris and Benedict carefully examined the relationships between body size, body shape, and age with basal metabolic rate (BMR)
Additional or other circumferences might prove useful in this context, as for example in the studies of total or appendicular skeletal muscle mass prediction from three [16], two [17], and one non-waist circumference [18] models

Summary

Introduction

We examine the individual and combined effects of weight, height, waist circumference, and age on SM prediction in a large sample (n = 12,330) of National Health and Nutrition Survey (NHANES) non-Hispanic (NH) white and NH black participants [7, 8]. Skeletal muscle mass prediction models need to consider race/ethnicity as independent variables after controlling for weight, height, and age [8]. These observations are consistent with the findings of Furushima et al [14] who found appendicular skeletal muscle mass prediction equations based on measures similar to those used in the current study are specific for Japanese men and women relative to those reported in non-Asian populations.

Results

Conclusion