Lifting capacity prediction model using physical performance measures among construction workers

Abstract

Abstract Manual materials handling is performed in many workplaces and is a significant risk factor for musculoskeletal injuries. The identification of lifting capacity is important to reduce the occurrence of musculoskeletal injuries. Lifting capacity is difficult to evaluate at the workplace. Therefore, there is a need to develop an alternate method that is easy and could be performed at the workplace. The study aimed to develop a lifting capacity prediction model for construction workers based on muscle strength and endurance. In this study, 65 construction workers were recruited; their socio-demographic and physical characteristics like core strength and endurance, grip strength, and lower limb flexibility were assessed. The lifting capacity was assessed using progressive isoinertial lifting evaluation. Stepwise multiple linear regression was carried out to develop the prediction model. The study suggested that age, BMI, grip strength, flexibility, prone plank, and trunk lateral flexor endurance tests have significantly influenced lifting capacity. Hence prediction model is developed using these variables. The regression model developed would help in easy estimation of lifting capacity among construction workers, which could be even administered with minimal skills by site supervisors or managers. It might help in the decision-making during pre-placement or return to work evaluations, thereby minimizing the incidence of low back disorders.