A preliminary exploration of the regression equation for performance in amateur half-marathon runners: a perspective based on respiratory muscle function.

This document presents a study on the relationship between physical characteristics, respiratory muscle capacity, and performance in amateur half-marathon runners. The aim of this study was to establish a preliminary predictive model to provide insights into training and health management for runners. Participants were recruited from the 2023 Beijing Olympic Forest Park Half-Marathon, comprising 233 individuals. Personal information including age, gender, height, weight, and other relevant factors were collected, and standardized testing methods were used to measure various parameters. Correlation analysis revealed significant associations between gender, height, weight, maximum expiratory pressure, maximal inspiratory pressure, and half-marathon performance. Several regression equations were developed to estimate the performance of amateur marathon runners, with a focus on gender, weight, maximum expiratory pressure, and height as predictive factors. The study found that respiratory muscle training can delay muscle fatigue and improve athletic performance. Evaluating the level of respiratory muscle capacity in marathon athletes is crucial for defining the potential speed limitations and achieving optimal performance. The information from this study can assist amateur runners in optimizing their training methods and maintaining their physical wellbeing.