Predicting soft tissue thicknesses overlying the iliac crests and greater trochanters of younger and older adults.

Soft tissues overlying the hip play a critical role in protecting against fractures during fall-related hip impacts. Consequently, the development of an efficient and cost-effective method for estimating hip soft tissue thicknesses in living people may prove to be valuable for assessing an individual's injury risk and need to adopt preventative measures. The present study used multiple linear stepwise regression to generate prediction equations from participant characteristics (i.e., height, sex) and anthropometric measurements of the pelvis, trunk, and thigh to estimate soft tissue thickness at the iliac crests (IC) and greater trochanters (GT) in younger (16-35 years of age: 37 males, 37 females) and older (36-65 years of age: 38 males, 38 females) adults. Equations were validated against soft tissue thicknesses measured from full body Dual-energy X-ray Absorptiometry scans of independent samples (younger: 13 males, 13 females; older: 13 males, 12 females). Younger adult prediction equations exhibited adjusted R2 values ranging from 0.704 to 0.791, with more explained variance for soft tissue thicknesses at the GT than the IC; corresponding values for the older adult equations were higher overall and ranged from 0.819 to 0.852. Predicted and actual soft tissue thicknesses were significantly correlated for both the younger (R2 = 0.466 to 0.738) and older (R2 = 0.842 to 0.848) adults, averaging ≤ 0.75cm of error. This research demonstrates that soft tissue thicknesses overlying the GT and IC can be accurately predicted from equations using anthropometric measurements. These equations can be used by clinicians to identify individuals at higher risk of hip fractures who may benefit from the use of preventative measures.

Three-dimensional video analysis of helmet-to-ground impacts in North American youth football.

This study presents a video analysis of helmet-to-ground impacts in youth football (≤14 years). A total of 21 non-injurious helmet-to-ground impact cases were assessed from game video of two age divisions (9-12 years: n = 9; 13-14 years: n = 12) using a novel multi-camera videogrammetry approach. Descriptive parameters related to the game situation and impact mechanisms were documented. Motion analysis software was used to manually track and compute three-dimensional helmet kinematics and uncertainty of the motion tracking analysis was assessed. Overall, the impact cases primarily followed a body-to-body, body-to-ground, helmet-to-ground contact progression. Impact locations on the helmet were mostly distributed across the rear and side helmet shell. The resultant pre-impact velocities for these cases averaged 4.04 ± 1.24 m/s at an angle of -49.6° to the ground. The average resultant impact-induced change in helmet velocity was 3.32 ± 1.14 m/s; the time interval associated with the duration of helmet-to-ground contact was approximately 0.06 s. The average maximum uncertainty (±) error of the position coordinates from the helmet tracking was 1.5 ± 0.3 cm. In summary, this video-based methodology can effectively be used to quantify helmet impact velocities and locations in youth football games. To date, the acquisition of such information has largely been limited to professional football game footage. Therefore, the data reported here may help inform the development of more representative assessment methods for youth-specific helmet test standards.

Head, Neck, Trunk, and Pelvis Tissue Mass Predictions for Young Adults Using Anthropometric Measures and Dual-Energy X-Ray Absorptiometry.

Accurate prediction of wobbling mass (WM), fat mass (FM), lean mass (LM), and bone mineral content (BMC) of living people using regression equations developed from anthropometric measures (lengths, circumferences, breadths, skinfolds) has previously been reported, but only for the extremities. Multiple linear stepwise regression was used to generate comparable equations for the head, neck, trunk, and pelvis of young adults (38 males, 38 females). Equations were validated using actual tissue masses from an independent sample of 13 males and 13 females by manually segmenting full-body dual-energy x-ray absorptiometry scans. Prediction equations exhibited adjusted R2 values ranging from .249 to .940, with more explained variance for LM and WM than BMC and FM, especially for the head and neck. Mean relative errors between predicted and actual tissue masses ranged from -11.07% (trunk FM) to 7.61% (neck FM). Actual and predicted tissue masses from all equations were significantly correlated (R2 = .329 to .937), except head BMC (R2 = .046). These results show promise for obtaining in-vivo head, neck, trunk, and pelvis tissue mass estimates in young adults. Further research is needed to improve head and neck FM and BMC predictions and develop tissue mass prediction equations for older populations.

3D peak and cumulative low back and shoulder loads and postures during greenhouse pepper harvesting using a video-based approach.

BACKGROUND: In agricultural field work many tasks have been cited as high priority risk factors for the development of work-related musculoskeletal disorders (WRMDs). Although video-based biomechanical approaches have been effective in documenting the physical demands and risks associated with various occupational and non-occupational tasks, to date, this method has yet to be used to document jobs such as crop harvesting in a greenhouse environment. OBJECTIVE: To document and assess the postural characteristics and 3D peak and cumulative low back and shoulder loads associated with greenhouse pepper harvesting using a video-based posture sampling approach. METHODS: Nine male (28.2 (4.1) years) pepper harvesters from a greenhouse in Southwestern Ontario, Canada were videotaped during a normal shift. 3DMatch was used to document working trunk and shoulder postures, from which 3D peak and cumulative forces and moments were quantified. RESULTS: On average, workers spent the majority of their time in neutral trunk postures (lateral bend: 99.1%; axial twist: 59.9%; flexion: 89.8%). Consistent results were found for the left and right shoulder, with the arms held in a neutral flexion posture 50% of the time or more. Four participants experienced peak L4/L5 compression forces (between 4116.3 N and 5937.0 N) which exceeded the NIOSH Action Limit (3400 N) during the cart pushing/pulling task, but remained below the threshold during picking. Mean cumulative L4/L5 extension and shoulder flexion moments ranged in magnitude from 18.5 Nm to 28.2 Nm, and between 19.4 Nm and 23.2 Nm, respectively, across all tasks. CONCLUSIONS: The postural characteristics and biomechanical loads associated with greenhouse pepper harvesting were quantified with a video-based biomechanical approach. Further investigations of the physical risk factors for low back and shoulder musculoskeletal disorders is warranted in pepper harvesting, given the postures and loads documented in this study.