Muhammad Ghias, Khadija Irfan Khawaja, Faisal Masud, Salman Atiq, Muhammad Khalid Pervaiz


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.
Keywords: Body mass index, BMI, waist circumference, hip circumference, Multiple Linear
Regression model, Correlation, Diabetes mellitus

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