Purpose: Race has rarely been the focus of biomechanics investigations, despite affecting the incidence of musculoskeletal injury and disease. Existing racial differences in movement mechanics could drive disease development and help identify factors contributing to racial health disparities. This study aimed to 1) Identify racial differences in walking, running, and landing mechanics between African Americans and white Americans and 2) Determine whether racial differences can be explained by anthropometric, strength, and health status factors.
Methods: Venous blood samples, anthropometric measures, lower extremity strength, and a health status assessment were collected for 92 participants (18-30y) in an IRB approved study. After measuring self-selected walking speed, 3D motion capture and force plate data were recorded during 7 trials in the following conditions: regular walking (1.35m/s), fast walking (1.6m/s), running (3.2m/s), and drop vertical jump (31cm box height). Fundamental gait measures and running and landing measures associated with overuse and impact injury risk were extracted using Visual3D and custom Matlab scripts. Multivariate and post-hoc univariate ANOVA models were fit to determine main and interaction effects of gender and race (JMP Pro 15, α=0.05) after which data was separated by gender. Stepwise linear regression models evaluated whether anthropometric, strength, and health status factors explained racial effects.
Results: Several racial differences in walking, running, and landing mechanics were observed in both men and women, but differed between genders. Effect sizes of observed racial differences indicate the potential for both statistical and clinical significance. Although several racial differences during all tasks were explained by anthropometric, strength, and health status factors in women, none were explained by these factors in men. In women, explanatory factors were a combination of innate and modifiable.
Conclusion: Future steps should include the development of racially diverse databases and the identification of potential factors to target in interventions aimed at reducing racial health disparities. / Doctor of Philosophy / Purpose: Race has rarely been the focus of biomechanics studies, but several injuries and diseases occur at different incidence rates between racial groups. This study aimed to 1) Identify racial differences in walking, running, and landing between African Americans and white Americans and 2) Determine whether racial differences are explained by body proportion, strength, and health status factors.
Methods: Blood samples, body proportion measures, lower extremity strength, and a health status assessment were collected for 92 participants (18-30 years old). Motion analysis data was recorded and analyzed during the following tasks: regular walking, fast walking, running, and drop vertical jump. Biomechanical measures were compared between racial groups and genders. When racial differences were found, we evaluated whether the differences could be explained by body proportion, strength, and health status factors.
Results: Several racial differences were found during walking, running, and landing tasks in both men and women, but were dependent on gender. Several observed racial differences in women could be explained by body proportion, strength, and health status factors, but no racial differences could be explained in men. In women, some of the factors that explained racial differences were structural and could not be altered while others were potentially modifiable by exercise or were the product of social environment.
Conclusion: Based on these findings, biomechanical data should be collected from racially diverse populations. Some factors able to explain racial differences could be targeted to reduce racial health disparities.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/106429 |
| Date | 06 May 2020 |
| Creators | Hughes-Oliver, Cherice |
| Contributors | Department of Biomedical Engineering and Mechanics, Queen, Robin M., Arent, Shawn, Socha, John J., Schmitt, Daniel, Madigan, Michael L., Reed, Wornie L. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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