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Abstract
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PURPOSE: To determine risk factors associated with concussion among the general collegiate population using a unique data linkage methodology.
METHODS: Student health medical, counseling, and disability access service data were linked with university enrollment data to provide a comprehensive, de-identified dataset of students who sought care at the student health center for concussion from 2016-2020. Using chi-squared tests ad logistic regression, characteristics of students with and without concussion were evaluated.
RESULTS: During the study period, 506 concussions from 474 students were identified (cumulative incidence rate of 51.7 per 10,000 students). Significant predictors of concussion included: younger age (<21 years): OR=3.52 (95% CI, 2.78, 4.50), Greek affiliation: OR=1.89 (95% CI, 1.56, 2.30), and utilization of counseling and psychological services: OR=1.92 (95% CI 1.59, 2.32). Of the students with concussion, 47% had at least one other concussion within the preceding year. History of prior hospitalization or medical imaging for head injury increased subsequent concussion risk by 4.5 fold.
CONCLUSION: Linking unique datasets provides a richer understanding of the characteristics and risk factors associated with student concussions than analysis of a single data source. This comprehensive dataset will enable future targeted interventions to prevent and treat college student concussions.
Language: en |