Análisis estadístico de regresión lineal múltiple para la predicción de distancia de marcha en función de variables antropométricas

Miguel Eduardo Pionce-Soledispa

Authors

Pionce-Soledispa Miguel Eduardo Contraloría General del Estado – Universidad de Guayaquil. Guayaquil, Ecuador. https://orcid.org/0000-0001-9976-9941

Keywords:

biomechanics, functional capacity, locomotor assessment, predictive modeling, physical performance

Abstract

DOI: https://doi.org/10.46296/ig.v8i16.0305

Abstract

This study aimed to develop a multiple linear regression model to predict the distance covered in 20 steps based on basic anthropometric variables in a functionally healthy population. A cross-sectional observational study was conducted with 403 participants over 18 years old without physical limitations affecting gait, evaluating age, weight, height, and sex as independent variables. Multiple linear regression with backward elimination using Akaike information criterion was applied, comparing models with and without intercept. The initial model with intercept showed limitations in its explanatory capacity, achieving an adjusted R² of 0.3754, which motivated the evaluation of structural alternatives. Intercept elimination produced dramatic improvements in predictive capacity, increasing the adjusted R² to 0.9872 and resulting in the final equation Y = 0.8702(Age) + 3.4580(Weight) + 6.3203(Height). Height emerged as the most significant predictor (t = 20.929, p < 2e-16), confirming its biomechanical importance in locomotor performance, followed by weight (t = 4.835, p = 1.9e-06). Contrary to expectations, age showed no statistical significance (p = 0.277) in the final model. Results confirm the feasibility of developing highly effective predictive tools based on simple anthropometric measurements, offering a practical and accessible approach for functional assessment in clinical and sports contexts without requiring costly specialized equipment.

Keywords: biomechanics, functional capacity, locomotor assessment, predictive modeling, physical performance.

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