0088 Bidirectional association between daily physical activity and postconcussion symptoms among youth

Statement of purpose We investigated the longitudinal and bidirectional association between daily physical activity and postconcussion symptoms (PCS) among concussed youth aged 11–17 years. Methods/Approach We prospectively enrolled youth aged 11–17 years with a physician-confirmed concussion within 72 hours of injury. We measured daily physical activity using an ActiGraph and daily PCS using the Postconcussion Symptom Scale from day 1 to day 7 postinjury. We grouped daily step count and PCS into three waves: days 1–3 (Wave 1), days 4–5 (Wave 2), and days 6–7 (Wave 3) postinjury. We examined the bidirectional associations between daily step counts and PCS in the 3-wave, longitudinal design using both a traditional cross-lagged panel model (CLPM) and a random-intercept cross-lagged panel model (RI-CLPM). Results Participants included 83 concussed youth (54 boys [65%]; mean age 14.2 years; 59 White participants [72%]; and 70 sports-related concussions [84%]). The mean daily step counts were 9,167 at Wave 1, 10,143 at Wave 2, and 10,786 at Wave 3, while the mean daily PCS scores were 27.7, 21.0, and 15.9. In the CLPM, daily step counts and PCS scores showed significant positive autoregressive associations across all waves. In contrast, in the RI-CLPM, the only significant autoregressive association was the path for PCS scores from Wave 1 to Wave 2 (p=.002). In the CLPM, only one cross-lagged path was significant, with higher PCS scores at Wave 1 being associated with lower daily step counts at Wave 2 (p=.047). No cross-lagged paths were significant in the RI- CLPM. Conclusion While youth who engaged in more physical activity reported fewer PCS, only one cross- lagged association was significant. Future randomized controlled trials are needed to better understand the effects of physical activity on PCS. Significance This study is the first to assess the bidirectional association between physical activity and PCS using cross-lagged panel analyses.