Original Study Development and Validation of a Height and Mid-Arm Circumference (MAC)-Based Weight Estimation Formula

Abstract

Introduction: Accurate weight measurement is crucial in clinical settings for medication dosing, nutritional management, fluid balance, diagnostics, and ventilator settings. Traditional weight measurement methods can be challenging for neurological patients, especially those with impaired mobility. This study aims to develop and validate a weight estimation formula using height and mid-arm circumference (MAC) to address these issues.

Methods: This cross-sectional study was conducted at the Neurosurgery outpatient department of Neuro Cardio and Multispecialty Hospital in Biratnagar, involving 120 adults aged 18-75 years. Convenience random sampling was used. Data were analyzed using MS Excel and IBM SPSS Statistics 26.0. A linear regression equation was developed to estimate weight based on height and MAC. The validation included R² analysis, t-tests, Bland-Altman analysis, percentage error calculation, and scatterplot diagrams.

Results: The simple formula for weight estimation using linear regression equation was derived: Weight (kg) = −73 + 0.32 × Height (cm) + 3 × MAC (cm). Method C (age and gender-neutral) was the most accurate, with an R-squared value of 0.858, a t-value of 2.387, and a p-value of 0.019. In addition, Bland-Altman analysis showed the least bias and limits of agreement (LOA) of -0.996 and -9.95 to 7.97 respectively. Method C also had higher percentages of estimates within 10%, 20%, and 30% of actual weight (83.3%, 96.7%, and 100%, respectively). Scatterplot analysis indicated better linearity for Method C.

Conclusions: Method C is recommended for bedside weight estimation in neurological patients due to its simplicity and precision.