Anthropometric Correlates and Prediction of Body Fat Measured by Bioelectric Impedance Analysis among Women
Raimi Th, Oluwayemi Io
Abstract
Raimi Th, Oluwayemi Io
Abstract
Context: Obesity may be defined based on percentage body fat. Because of the difficulty in measuring body fat in routine clinical practice, a number of surrogates such as body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) have been proposed. Aims: To determine the correlation between obesity indices and body fat, and the predictive ability of these indices to identify percentage body fat among women. Settings and Design: Cross-sectional. Methods and Material: Seventy nine women who participated in health screening were included in the study. BMI, WC, and WHtR of the participants were determined by standard protocols. Percentage body fat and visceral fat were measured by bioelectrical impedance analysis. Statistical analysis: Pearson correlation between percentage body fat and the obesity indices was determined. The area under curve (AUC) on the ROC was used to determine the best anthropometric index which identifies individuals with obesity. Results: The participant’s mean age was 42.4±9.1 years. There was a significant correlation between body fat and the anthropometric indices (p<0.001), but the correlation was best with BMI. The AUC on the ROC for BMI, WC, and WHtR, respectively were 0.831 (95% CI 0.669-0.993, p<0.001), 0.780 (95% CI 0.627-0.933, p=0.002), and 0.725 (95% CI 0.571-0.880, p=0.013). Conclusions: There is positive correlation between percentage body fat and anthropometric indices. Body mass index is as good as waist circumference, but better than waist to height ratio in predicting body fat. BMI should not be abandoned in the clinical evaluation of people with obesity.
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Context: Obesity may be defined based on percentage body fat. Because of the difficulty in measuring body fat in routine clinical practice, a number of surrogates such as body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) have been proposed. Aims: To determine the correlation between obesity indices and body fat, and the predictive ability of these indices to identify percentage body fat among women. Settings and Design: Cross-sectional. Methods and Material: Seventy nine women who participated in health screening were included in the study. BMI, WC, and WHtR of the participants were determined by standard protocols. Percentage body fat and visceral fat were measured by bioelectrical impedance analysis. Statistical analysis: Pearson correlation between percentage body fat and the obesity indices was determined. The area under curve (AUC) on the ROC was used to determine the best anthropometric index which identifies individuals with obesity. Results: The participant’s mean age was 42.4±9.1 years. There was a significant correlation between body fat and the anthropometric indices (p<0.001), but the correlation was best with BMI. The AUC on the ROC for BMI, WC, and WHtR, respectively were 0.831 (95% CI 0.669-0.993, p<0.001), 0.780 (95% CI 0.627-0.933, p=0.002), and 0.725 (95% CI 0.571-0.880, p=0.013). Conclusions: There is positive correlation between percentage body fat and anthropometric indices. Body mass index is as good as waist circumference, but better than waist to height ratio in predicting body fat. BMI should not be abandoned in the clinical evaluation of people with obesity.
Key concepts: Bioelectrical impedance analysis, Medicine, Waist, Body mass index, Anthropometry, Waist-to-height ratio, Body fat percentage, Obesity