Ghias Muhammad, Khawaja Khadija Irfan, Masud Faisal, Atiq Salman, Pervaiz Muhammad Khalid
Department of Biostatistics, Services Institute of Medical Sciences, Services Hospital, Lahore, Pakistan.
J Ayub Med Coll Abbottabad. 2010 Apr-Jun;22(2):111-6.
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.
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.
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.
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.
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.
体重指数（BMI）通过体重（千克）除以身高（米）的平方得出，是一个有用的人体测量参数，有多种应用。它取决于其组成参数的准确测量。在无法使用校准仪器测量身高和体重的情况下，需要其他客观参数来保持准确性。
我们旨在基于使用臀围和腰围的统计线性回归方程，提出一种用于估计BMI的替代预测模型。我们的目标是确定估计的BMI与患者观察到的BMI相比的准确性，并提出一种BMI预测模型，该模型将克服在预测重症或行动不便患者的体重指数时遇到的问题，这些问题在重症监护病房通气方案中基于BMI的计算等应用中是必需的。
通过回顾20岁及以上被诊断为2型糖尿病的成年男女（n = 24,485；男性10,687名，女性13,798名）的医院记录进行了这项横断面调查。考虑到性别在形态和生理上的差异，为男性和女性设计了两种不同的预测模型。使用测量的腰围和臀围值来估计BMI。
数据分析显示，在所有类别中，BMI、腰围和臀围之间存在显著的线性关系[腰围（r = 0.795，p = 0.000），臀围（r = 0.838，p = 0.000）]。男性和女性的估计回归模型分别为BMI = -10.71 + 0.212（臀围）+ 0.170（腰围）；以及BMI = -15.168 + 0.143（臀围）+ 0.30（腰围）。
使用基于测量的腰围和臀围的该预测模型估计BMI，是一种计算BMI的替代且可靠的方法。
