Shelby Sanregret, Austin Kohler, Andrew Moore, Maleah Holland-Winkler. Augusta University, Augusta, GA

BACKGROUND: The physically stressful tasks that firefighters are often required to perform for their occupation increase their risk for injury. As a result, many experience pain in regions such as the back. Body mass index (BMI) has been weakly linked to low back pain in firefighters, however, BMI may not be the ideal body composition assessment for this population. Similar to athletes, firefighters may have more lean body mass than the normal population, which would place them at a higher BMI. To assess the relationship between body composition and back pain in firefighters more accurately, body fat percentage should be measured. Therefore, the aim of this study was to determine the relationship between body fat percentage and back pain in firefighters. The relationships between back pain and BMI and back pain and age were also assessed. METHODS: 72 firefighters participated in this correlational study. Age, height, weight, and body fat percentage were measured and recorded. Each participant completed the Oswestry Low Back Pain Disability Questionnaire, which was then scored to measure back pain severity. Pearson product-moment correlation coefficient (r) was calculated between back pain score and each of the following variables: body fat percentage, BMI, and age with a predetermined alpha level of .05. RESULTS: Of the 72 firefighters assessed, only 47 reported back pain. Therefore, only 47 were included in the correlational analyses. The relationship between back pain and age was not significant (r = 0.058, p = .715). The relationships between back pain and BMI (r = 0.298, p = .055) and between back pain and body fat percentage (r = 0.304, p = .050) were not significant, but approached statistical significance. CONCLUSION: Within this population of firefighters, there was no significant correlation between age and back pain found. However, both BMI and body fat percentage showed a trend for a positive linear relationship with back pain. Data is still being collected in this population to determine the best indicators of back pain.

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