Estimation of Body Fat and Body Fat Distribution in 11-Year Old Children Using Magnetic Resonance Imaging, Hydrostatic Weighing, Skinfolds and Anthropometry.

Peters, D.M. ORCID: https://orcid.org/0000-0002-7873-7737, Fox, K.R., Armstrong, N., Sharpe, P. and Bell, M. (1994) Estimation of Body Fat and Body Fat Distribution in 11-Year Old Children Using Magnetic Resonance Imaging, Hydrostatic Weighing, Skinfolds and Anthropometry. American Journal of Human Biology, 6 (2). pp. 237-243. ISSN Elecronic: 1520-6300

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Abstract

From early pubescence, both degree and distribution of fatness have been related to health risk factors. Measures that are capable of providing estimates of overall fatness and the extent of high risk fat patterning are, therefore, advantageous. The objective of this study was to compare estimates of body fatness and fat distribution using magnetic resonance imaging with the traditional methods of hydrostatic weighing, skinfolds, and anthropometry in 11-year-old boys and girls. Subjects were 25 boys and 25 girls, representative of their age cohort's body mass index (BMI) range. Total fat using MRI was obtained by summing subcutaneous and internal fat areas from four transaxial scans at the chest, waist, hips, and thigh. Mean MRI total fat (MRI FAT) was 357 (±152) cm2 with a range of 172–739 cm2 for boys and 427 (±174) cm2 with a range of 209–995 for girls. Correlation analyses revealed strong relationships between MRI FAT and UWW FAT (r = 0.73 boys, r = 0.77 girls), and the sum of four skinfolds (r = 0.94 boys, r = 0.88 girls). Analysis of the MRI data alone revealed that MRI FAT variation is largely explained by subcutaneous fat deposition at the waist in boys and at the level of the buttocks in girls, with most skinfolds correlating highly with MRI FAT in both sexes. Results of stepwise multiple regression showed that an abdominal skinfold and thigh circumference explained 95% of MRI FAT in boys, and 86% of the variance in girls. These data show that magnetic resonance images can provide useful information for the identification of discriminating field measures of fatness and its distribution in 11-year-old

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