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ASSESSMENT OF LABORATORY DEVICES FOR ESTIMATING BODY COMPOSITION IN A HISPANIC POPULATION

Abstract

Ronald Lee Snarr1, Brett S. Nickerson, FACSM2. 1Missouri State University, Springfield, MO. 2Texas A&M International University, Laredo, TX.

BACKGROUND: Body composition algorithms are typically validated using diverse populations without accounting for ethnicity. Yet, studies have observed variations in the distribution and composition of fat mass (FM) and fat-free mass (FFM) among ethnicities. Thus, potentially increasing the rate of error in FM and FFM values for minority populations. PURPOSE: The purpose was to determine the agreement between dual-energy x-ray absorptiometry (DXA) and multi-frequency bioelectrical impedance analysis (BIA) for estimating body fat percentage (BF%), FM, and FFM in a Hispanic population. METHODS: One-hundred eighty-one individuals (males: n=84; females: n=97) of Hispanic descent had body composition estimated via DXA and BIA. Participants completed all testing wearing compression gear and provided a urine sample to assess hydration status. Adequate hydration was considered at a urine specific gravity value <1.029. Agreement between DXA and BIA BF%, FM, and FFM was assessed using Pearson correlations, linear regression, and Bland-Altman analyses. Analyses yielded the standard error of the estimate (SEE), constant error (CE), 95% limits of agreement (LOA), and proportional bias for the entire group and within sexes. RESULTS: For BF%, BIA displayed similar CE±95% LOA for the sample (-3.17±5.45%), males (-3.2±5.5%), and females (-3.2±5.4%) compared to DXA. Correlation analyses indicated near-perfect associations (sample: r=0.96, males: r=0.93, and females: r=0.93); however, a moderate proportional bias was present for females (r=0.48). The sample (r=0.22) and males (r=-0.04) had trivial-to-no proportional bias. Regarding FM, BIA exhibited CE±95% LOA values of -1.4±4.2 kg for the sample, -1.9±4.6 kg for males, and -0.9±3.6 kg for females. All groups displayed near-perfect associations (sample: r=0.99, males: r=0.97, and females: r=0.99), despite a strong proportional bias for females (r=0.68) and moderate bias for the sample (r=0.36). No proportional bias was observed for males (r=-0.02). For FFM, males demonstrated the largest CE±95% LOA (1.6±4.6), compared to the sample (1.2±3.9 kg) and females (0.9±3.4 kg) when BIA was compared to DXA. Near-perfect associations were observed for all groups (sample: r=0.98; males: r=0.97; females: r=0.97). No proportional biases existed for the sample (r=-0.01) or males (r=-0.10); however, females exhibited a moderate, negative bias (r=-0.38). CONCLUSION: Due to the observed moderate-to-strong proportional biases within body composition estimates, the need for ethnic-specific algorithms is warranted, particularly for the Hispanic female population.

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