Analysis of the Influence of Anthropometric Dimensions of Postural Ergonomics Using Multiple Linear Regression

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary role of elbow height as the strongest predictor is intuitively sound in ergonomics, as the armrest should align with the user’s natural elbow resting position. Moreover, a strong and reliable tool for calculating optimal seat height based on anthropometry and existing chair dimensions is observed. The regression model also reveals that the optimal backrest angle can be calculated based on multiple user anthropometries. The study demonstrates that the angle of the backrest relative to various anthropometric characteristics functions as a reliable predictor. This means that a comfortable or key predictor posture angle depends on several factors, such as how wide a user’s hips are and how high they sit. This result differs from that of the previous correlation study. Finally, we conclude that the data continually show that anthropometric measures alone are insufficient to understand ergonomics. To create seating solutions that can be tailored to a broad range of users and improve posture and productivity, a multivariable approach is needed that includes clear, data-driven standards