Relationship between body mass, lean mass, fat mass, and limb bone cross-sectional geometry: Implications for estimating body mass and physique from the skeleton.

Emma Pomeroy,Tim J Cole,Jonathan C K Wells,Jay T Stock,Alison Macintosh

doi:10.1002/ajpa.23398

Abstract

ObjectivesEstimating body mass from skeletal dimensions is widely practiced, but methods for estimating its components (lean and fat mass) are poorly developed. The ability to estimate these characteristics would offer new insights into the evolution of body composition and its variation relative to past and present health. This study investigates the potential of long bone cross‐sectional properties as predictors of body, lean, and fat mass.Materials and MethodsHumerus, femur and tibia midshaft cross‐sectional properties were measured by peripheral quantitative computed tomography in sample of young adult women (n = 105) characterized by a range of activity levels. Body composition was estimated from bioimpedance analysis.ResultsLean mass correlated most strongly with both upper and lower limb bone properties (r values up to 0.74), while fat mass showed weak correlations (r ≤ 0.29). Estimation equations generated from tibial midshaft properties indicated that lean mass could be estimated relatively reliably, with some improvement using logged data and including bone length in the models (minimum standard error of estimate = 8.9%). Body mass prediction was less reliable and fat mass only poorly predicted (standard errors of estimate ≥11.9% and >33%, respectively).DiscussionLean mass can be predicted more reliably than body mass from limb bone cross‐sectional properties. The results highlight the potential for studying evolutionary trends in lean mass from skeletal remains, and have implications for understanding the relationship between bone morphology and body mass or composition.

Highlights

The pattern of strength of correlations was similar for body mass, lean mass, and fat mass across the different bones and cross-sections, except that medullary area had the lowest correlations with lean mass and body mass, but highest correlations with fat mass
Ordinary least squares (OLS) regression models derived for log-transformed TA, J and circumference at the tibia midshaft had SEEs of 10% for lean mass and 12-13% for body mass, but only 33% for fat mass
These results for lean mass compare favourably with SEEs of 17.5% and 14.4% reported by Ruff et al (1991) for body mass estimated from femoral head diameter and CA at the subtrochanteric level for white females

Summary

Objectives

Estimating body mass from skeletal dimensions is widely practiced, but methods for estimating its components (lean and fat mass) are poorly developed. This study investigates the potential of long bone cross-sectional properties as predictors of body, lean, and fat mass. Estimation equations generated from tibial midshaft properties indicated that lean mass could be estimated relatively reliably, with some improvement using logged data and including bone length in the models (minimum standard error of estimate = 8.9%). Body mass prediction was less reliable and fat mass only poorly predicted (standard errors of estimate ≥11.9% and >33% respectively). The results highlight the potential for studying evolutionary trends in lean mass from skeletal remains, and have implications for understanding the relationship between bone morphology and body mass or composition

Methods

Results

Conclusion