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Year : 2021  |  Volume : 16  |  Issue : 2  |  Page : 100-105

Development of an easy-to-use prediction equation for waist circumference based on BMI and body weight among a sample of Egyptian women

Department of Biological Anthropology, Medical Research and Clinical Studies Institute, National Research Centre, Giza, Egypt

Correspondence Address:
Sahar A. El-Raufe El-Masry
Department of Biological Anthropology, National Research Centre, 33 El-Buhouth Street, Dokki, Giza, Cairo 12622
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jasmr.jasmr_23_21

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Background/aim Although both BMI and waist circumference (WC) estimate the level of fatness, WC may be more crucial because of its deep relationship to cardiovascular diseases. As WC is not ascertained regularly in clinical practice, this study intended to develop and substantiate an easy to use WC prognostic equation based on either BMI or body weight, appropriate for Egyptian women. Patients and methods A cross-sectional study included 505 Egyptian women, aged 20–60 years. Anthropometric measurements (body weight, height, and WC) were evaluated and BMI was estimated. A total of 329 women were used for construction of simplified prediction equations (learning sample) and another 176 women for assessing their legality (validation sample). Pearson’s correlation coefficient, the calibration slope, and R2 for the regression of the measured WC versus the predicted WC were used to assess execution of the equations in the validation sample. Results There were insignificant differences between the two samples in the measurements and BMI classification. The preponderance of the two samples were suffering from obesity (84.5 vs. 79.5%) and overweight (11.9 vs. 17.0%), respectively. The following simple equations were obtained to predict WC of Egyptian women: WC=48.44+(1.471×BMI) or WC=57.53+(0.487×weight). There were insignificant differences in means±SD of the measured versus predicted WC among both samples. Conclusions These equations precisely estimate WC. It should be helpful for medical care practitioners and public health personnel who like to detect persons and populations at risk for cardiovascular disease when the WC data are unobtainable.

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