Validation of anthropometric-based weight prediction equations among Ugandan adults: A Cross-sectional study

Z Zakaria Mukasa J Juliet Ntuulo Mutanda R Ronnie Kasirye E Emmanuel Olal C Christopher Lwanga V Victoria Nankabirwa F Fred Nuwaha

Abstract

Introduction Effective patient management often requires accurate weight estimation. However, the appropriate weight-measuring equipment is not always available in emergencies and low-resource settings. Hence, emergency clinicians resort to less reliable methods of weight estimation, often with negative consequences. In this study, we assess the accuracy of anthropometric-based weight prediction equations in Ugandan adults. Methods A cross-sectional study was conducted at Kira Health Center IV. Recruitment was done between 05-01-2022 and 21-02-2022. A sample of 240 adults, 18 years and above, was selected by quota sampling, stratified by sex and nutritional status. Anthropometric measurements, including weight, height, knee height, subscapular skin fold thickness, and circumference measurements, were taken. The predicted weight was computed using the proposed equations, and their accuracy was assessed using Bland-Altman analysis, and the percentage of weight estimates within 10% and 20% of the actual weight. Results Out of 240 participants, 50% were females. The median (interquartile range) was 29 (24 –38 ) years for age, 64.5 (54−76) kg, and 162.5 (156.5–170.1) cm, for weight and height, respectively. Rabito equation 3 (Weight = (0.5759x(Mid Arm Circumference)) + (0.5263x(Abdominal Circumference)) + (1.2452x(Calf Circumference)) – (4.8689xSex)-32.9241) was the most accurate, with a percentage of estimates with 10% of the actual weight of 77.08%. Conclusion In emergency settings with an absent patient-reported weight or an appropriate weighing scale, using Rabito equation 3 for weight prediction can be used as an accurate alternative. However, fine-tuning will be required before its recommendation for general use.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 12
Published December 26, 2025
Pages e0306416
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (7)

Z

Zakaria Mukasa

J

Juliet Ntuulo Mutanda

R

Ronnie Kasirye

E

Emmanuel Olal

C

Christopher Lwanga

V

Victoria Nankabirwa

F

Fred Nuwaha