Bioimpedance analysis with a novel predictive equation - A reliable technique to estimate fat free mass in birth weight based cohorts of Asian Indian males.


Journal

Diabetes & metabolic syndrome
ISSN: 1878-0334
Titre abrégé: Diabetes Metab Syndr
Pays: Netherlands
ID NLM: 101462250

Informations de publication

Date de publication:
Historique:
received: 12 11 2018
entrez: 16 1 2019
pubmed: 16 1 2019
medline: 2 5 2019
Statut: ppublish

Résumé

To validate bioimpedance based predictive equations for fat free mass (FFM) against DEXA and to derive a novel birth weight based predictive equation for FFM in a birth weight based cohort of healthy Asian Indian men. Whole body composition was done using DEXA and bioimpedance in 117 young Asian Indian men, born of normal birth weight (n = 59, birth weight ≥2.5 kg) or low birth weight (n = 58, birth weight < 2.5 kg). Predictive accuracy of 11 different bioimpedance based equations for FFM was evaluated using Pearson's correlation analysis and the root of mean squared prediction error (RMSE) analysis. The mean FFM (on DEXA) and total lean mass & impedance index (on bioimpedance) were significantly higher in the low birth weight cohort. Significantly higher body fat percentage was noted on bioimpedance, for the normal birth weight cohort, but not on DEXA. In addition, the mean values of predicted FFM were significantly higher in the low birth weight cohort for 9 different predictive equations. Specifically, the mean FFM values obtained using the predictive equations of Schaefer et al., Hoot cooper et al. and Hughes et al. were in close agreement with the actual FFM values on DEXA. A novel predictive equation (CMC equation) for FFM based on birth weight was derived. FFM = 32.637 + (-0.222*age) + (-32.51*waist-to-hip ratio) + (0.33*body mass index) + (1.58 * 1 or 2 (1 = normal birth weight, 2 = low birth weight) + (0.510*waist circumference). Our study findings substantiate the validity of Bio-impedance analysis (BIA) as a reliable and noninvasive tool for estimating body composition measures in birth-weight based cohorts of Asian Indian males. Further, we have devised a novel BIA-based predictive equation that can be useful in larger epidemiological studies to look at alterations in body fat in this cohort.

Identifiants

pubmed: 30641798
pii: S1871-4021(18)30542-3
doi: 10.1016/j.dsx.2018.11.070
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

738-742

Informations de copyright

Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Auteurs

Riddhi Dasgupta (R)

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (CMC), India. Electronic address: riddhi_dg@rediffmail.com.

Shajith Anoop (S)

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (CMC), India.

Prasanna Samuel (P)

Department of Biostatistics, Christian Medical College, Vellore, India.

Mathews E Kurian (ME)

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (CMC), India.

Mercy Inbakumari (M)

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (CMC), India.

Geethanjali Finney (G)

Department of Biochemistry, Christian Medical College, Vellore, India.

Nihal Thomas (N)

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (CMC), India.

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