Sex-Dependent Estimation of Spinal Loads During Static Manual Material Handling Activities—Combined in vivo and in silico Analyses

Manual material handling (MMH) is considered as one of the main contributors to low back pain. While males traditionally perform MMH tasks, recently the number of females who undertake these physically-demanding activities is also increasing. To evaluate the risk of mechanical injuries, the majority of previous studies have estimated spinal forces using different modeling approaches that mostly focus on male individuals. Notable sex-dependent differences have, however, been reported in torso muscle strength and anatomy, segmental mass distribution, as well as lifting strategy during MMH. Therefore, this study aimed to use sex-specific models to estimate lumbar spinal and muscle forces during static MHH tasks in 10 healthy males and 10 females. Motion-capture, surface electromyographic from select trunk muscles, and ground reaction force data were simultaneously collected while subjects performed twelve symmetric and asymmetric static lifting (10 kg) tasks. AnyBody Modeling System was used to develop base-models (subject-specific segmental length, muscle architecture, and kinematics data) for both sexes. For females, female-specific models were also developed by taking into account for the female’s muscle physiological cross-sectional areas, segmental mass distributions, and body fat percentage. Males showed higher absolute L5-S1 compressive and shear loads as compared to both female base-models (25.3% compressive and 14% shear) and female-specific models (41% compressive and 23.6% shear). When the predicted spine loads were normalized to subjects’ body weight, however, female base-models showed larger loads (9% compressive and 16.2% shear on average), and female-specific models showed 2.4% smaller and 9.4% larger loads than males. Females showed larger forces in oblique abdominal muscles during both symmetric and asymmetric lifting tasks, while males had larger back extensor muscle forces during symmetric lifting tasks. A stronger correlation between measured and predicted muscle activities was found in females than males. Results indicate that female-specific characteristics affect the predicted spinal loads and must be considered in musculoskeletal models. Neglecting sex-specific parameters in these models could lead to the overestimation of spinal loads in females.