PP416 - A SIMPLE ANTHROPOMETRIC EQUATION TO PREDICT BODY WEIGHT IN ADULTS

PP416

A SIMPLE ANTHROPOMETRIC EQUATION TO PREDICT BODY WEIGHT IN ADULTS

F. ESTRADA-MOYA^1,2,*, N. Marin Okamoto³, K. Escalante Rincón³, B. Avelar Martínez³, J. A. Luna Morán³, A. E. Serralde-Zúñiga¹

¹Servicio de Nutriología Clínica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, ²Sección de Estudios de Posgrado e Investigación, Instituto Politécnico Nacional, ³Servicio de Nutriología Clínica, Hospital Ángeles del Pedregal, Mexico City, Mexico

Rationale: Standardized weighing is often impractical or even impossible in clinical settings due to equipment limitations or patient mobility restrictions.¹ Several predictive equations have been developed; however, many lack accuracy in diverse populations or rely on complex measurements.² This study aimed to develop an equation based on simple anthropometric measurements for weight prediction.

Methods: This cross-sectional study included healthy adult volunteers who underwent standardized anthropometric assessments performed by two nutritionists using standardized techniques, together with the collection of demographic and clinical data. Body weight was measured using calibrated equipment and was used as the dependent variable for model development. Simple anthropometric measures were evaluated as predictors for body weight estimation. A weight prediction equation was developed using multivariable regression analysis. Statistical analyses were performed using STATA statistical software.

Results: A total of 275 healthy adult volunteers were included in the analysis with a median age of 37 years (28–48), 76% were female. The prediction model demonstrated excellent goodness of fit (adjusted R²=0.845, p<0.001). Residual validation confirmed the absence of systematic bias (mean prediction error ≈0), with a root mean square error (RMSE) of 5.57, showing random error patterns in the residuals vs. fitted values plot.

Equation: -109.7495+(0.5587*height in cm)+(0.6869*waist circumference in cm)+(0.8260*calf circumference in cm) -1.9491(if male)

Conclusion: The developed equation provides a practical option for estimating body weight when direct measurement is not feasible, particularly in individuals with mobility restrictions. The strong correlation and low prediction error suggest that simple anthropometric markers may support weight assessment in clinical practice.

Disclosure of Interest: None declared