Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women

Bharati Kulkarni, Hannah Kuper, Amy Taylor, Jonathan C. Wells, K. V. Radhakrishna, Sanjay Kinra, Yoav Ben-Shlomo, George Davey Smith, Shah Ebrahim, Nuala M. Byrne, Andrew P. Hills

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19 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1156-1162
Number of pages7
JournalJournal of Applied Physiology
Volume115
Issue number8
DOIs
Publication statusPublished - 15 Oct 2013
Externally publishedYes

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Photon Absorptiometry
Epidemiologic Studies
Skinfold Thickness
Body Composition
Population Groups
Hip
Healthy Volunteers
Body Mass Index
Extremities
Weights and Measures
Muscles

Cite this

Kulkarni, Bharati ; Kuper, Hannah ; Taylor, Amy ; Wells, Jonathan C. ; Radhakrishna, K. V. ; Kinra, Sanjay ; Ben-Shlomo, Yoav ; Smith, George Davey ; Ebrahim, Shah ; Byrne, Nuala M. ; Hills, Andrew P. / Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women. In: Journal of Applied Physiology. 2013 ; Vol. 115, No. 8. pp. 1156-1162.
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title = "Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women",
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.",
author = "Bharati Kulkarni and Hannah Kuper and Amy Taylor and Wells, {Jonathan C.} and Radhakrishna, {K. V.} and Sanjay Kinra and Yoav Ben-Shlomo and Smith, {George Davey} and Shah Ebrahim and Byrne, {Nuala M.} and Hills, {Andrew P.}",
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Kulkarni, B, Kuper, H, Taylor, A, Wells, JC, Radhakrishna, KV, Kinra, S, Ben-Shlomo, Y, Smith, GD, Ebrahim, S, Byrne, NM & Hills, AP 2013, 'Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women' Journal of Applied Physiology, vol. 115, no. 8, pp. 1156-1162. https://doi.org/10.1152/japplphysiol.00777.2013

Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women. / Kulkarni, Bharati; Kuper, Hannah; Taylor, Amy; Wells, Jonathan C.; Radhakrishna, K. V.; Kinra, Sanjay; Ben-Shlomo, Yoav; Smith, George Davey; Ebrahim, Shah; Byrne, Nuala M.; Hills, Andrew P.

In: Journal of Applied Physiology, Vol. 115, No. 8, 15.10.2013, p. 1156-1162.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Kulkarni, Bharati

AU - Kuper, Hannah

AU - Taylor, Amy

AU - Wells, Jonathan C.

AU - Radhakrishna, K. V.

AU - Kinra, Sanjay

AU - Ben-Shlomo, Yoav

AU - Smith, George Davey

AU - Ebrahim, Shah

AU - Byrne, Nuala M.

AU - Hills, Andrew P.

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