Predicting joint loading in Asian overweight and obese females with flexible flatfoot: a regression analysis of anthropometric parameters and gait dynamics.

Current methods for obtaining accurate joint loading data lack simplicity, efficiency, and cost-effectiveness. This study aims to generate joint loading prediction models using anthropometric parameters and walking speed in overweight or obese females with flexible flatfoot. Sixteen participants' motion capture data from walking trails and anthropometric parameters were collected. The lower limb joint contact forces and the walking speed were calculated via a musculoskeletal model. Regression analysis was used to generate the prediction model. The second peak of knee joint contact force revealed a strong negative correlation with hip circumference and a weak positive correlation with age (p < 0.001 and adjusted R = 0.720). The peak ankle joint contact force exhibited a strong positive correlation with walking speed while strong negative correlations with waist circumference and lower limb length (p < 0.001 and adjusted R = 0.782). The first peak of vertical GRF displayed a medium negative correlation with walking speed (p < 0.001 and adjusted R = 0.750). Anthropometric parameters and walking speed are effective predictors of joint loading. This rapid, low-cost estimation method can be applied to areas such as flexible flatfoot that require assessment of joint stress, thereby saving costs and time.