A new approach for estimation of body mass index using waist and hip circumference in type 2 diabetes patients.
Academic Article
Overview
abstract
BACKGROUND: Body mass index (BMI), derived by dividing weight (Kg) by the square of height (m), is a useful anthropometric parameter, with multiple applications. It is dependent upon accurate measurement of its component parameters. Where measurement of height and weight with calibrated instruments is not possible, other objective parameters are required to maintain accuracy. OBJECTIVES: We aimed to propose an alternate prediction model for the estimation of BMI based on statistical linear regression equation using hip and waist circumferences. Our objective was to ascertain the accuracy of estimated BMI when compared with observed BMI of patients, and to propose a model for BMI prediction which would overcome problems encountered in the prediction of body mass index of critically ill or immobile patients, needed for applications such as BMI based calculations in ventilation protocols in ICUs. METHODS: This cross sectional survey was done by reviewing hospital records of adult subjects of both genders (n=24,485; 10,687 males and 13,798 females), aged 20 years and above, who were diagnosed with type 2 diabetes. Two different prediction models were designed for males and females keeping morphological and physiological differences in gender. The measured waist and hip circumference values were used to estimate BMI. RESULTS: Data analysis revealed a significant linear relationship between BMI, waist and hip circumference in all categories [waist circumference (r=0.795, p=0.000), hip circumference (r=0.838, p=0.000)]. Estimated regression models for males and females were BMI=-10.71+0.212 (hip cir)+0.170 (waist circumference); and BMI=-15.168+0.143 (hip circumference)+0.30 (waist circumference) respectively. CONCLUSION: Estimation of BMI using this prediction model based upon measured waist and hip circumferences, is an alternate and reliable method for the calculation of BMI.
