Calculation of BMI based on waist circumference, age, and height in the Peruvian population using a regression equation
Open access
Publication Information
Output type
Original language
EnglishArticle number
e116665Journal (Volume, Issue Number)
Revista Facultad de Medicina (Volume 73, Issue 1)Publication milestones
- Published - 02/07/2025
Publication status
ISSN
0120-0011Publication IDs
- Scopus: 105010892290
Abstract
Introduction: BMI is a potential indicator of health and, therefore, should be considered when assessing an individual's health. Objectives: To develop a regression equation for calculating BMI in the Peruvian population based on waist circumference, height, and age, and to evaluate its predictive capacity to identify overweight/obesity cases (BMI≥25) compared to BMI determined using the Quetelet's index (weight and height). Materials and methods: A cross-sectional analytical study was conducted with secondary data from the Peruvian population (≥18 years) obtained from the Demographic and Family Health Survey (ENDES) (n=60 192; 2022: 30 047; 2023: 30 145). A multiple linear regression model was run using data from the ENDES-2022 survey to obtain the regression equation. The equation's capacity to identify overweight/obesity cases (BMI ≥25) was compared to the Quetelet's index (sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio). Results: The regression equation obtained [BMI=9.007 + (-0.052*age) + (-0.396*waist circumference) + (-0.103*height)] was statistically significant (F=62768.475; p<0.001) and the R2 value was 0.858. When used with data from ENDES-2023 respondents, an R2 value of 0.845 was obtained and a homoscedastic distribution was observed with respect to the BMI values obtained with the Quetelet’s index. The strength of the association between BMI calculated with the equation and BMI obtained with the Quetelet’s index was high for ENDES-2022 (OR=73.54; 95% CI=67.961-78.55) and ENDES-2023 (OR=66.697; 95% CI=66.168-72.136) respondents. Sensitivity and PPV were >90% in both years. Conclusions: It is feasible to determine BMI and classify overweight/obesity cases in the Peruvian population using the regression equation based on waist circumference, height, and age. This may be useful in areas with limited access to accurate scales, either for economic or geographical reasons.
Sustainable Development Goals
- SDG 3 Good Health and Well
