Pomeroy, E, Mushrif-Tripathy, V, Kulkarni, B, Kinra, S, Stock, JT, Cole, TJ, Shirley, MK and Wells, JCK (2018) Estimating body mass and composition from proximal femur dimensions using Dual Energy X-Ray Absorptiometry. Archaeological and Anthropological Sciences. ISSN 1866-9557

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Abstract

Body mass prediction from the skeleton most commonly employs femoral head diameter (FHD). However, theoretical predictions and empirical data suggest the relationship between mass and FHD is strongest in young adults; that bone dimensions reflect lean mass better than body or fat mass; and that other femoral measurements may be superior. Here we generate prediction equations for body mass and its components using femoral head, neck and proximal shaft diameters and body composition data derived from dual energy X-Ray absorptiometry (DXA) scans of young adults (n = 155, 77 females and 78 males, mean age 22.7 ± 1.3 years) from the Andhra Pradesh Children and Parents Study, Hyderabad, India. Sex-specific regression of log-transformed data on femoral measurements predicted lean mass with smaller standard errors of estimate (SEEs) than body mass (12-14 % and 16-17 % respectively), while none of the femoral measurements were significant predictors of fat mass. Subtrochanteric medio-lateral shaft diameter gave lower SEEs for lean mass in both sexes and for body mass in males than FHD, while FHD was a better predictor of body mass in women. Our results provide further evidence that lean mass is more closely related to proximal femur dimensions than body or fat mass, and that proximal shaft diameter is a better predictor than FHD of lean but not always body mass. The mechanisms underlying these relationships have implications for selecting the most appropriate measurement and reference sample for estimating body or lean mass, which also depend on the question under investigation.

Item Type:	Article
Uncontrolled Keywords:	2101 Archaeology, 0403 Geology, 0399 Other Chemical Sciences
Subjects:	Q Science > QM Human anatomy Q Science > QP Physiology
Divisions:	Natural Sciences & Psychology (closed 31 Aug 19)
Publisher:	Springer Verlag
Date Deposited:	05 Jun 2018 11:03
Last Modified:	04 Sep 2021 02:39
URI:	https://researchonline.ljmu.ac.uk/id/eprint/8773

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