Abstract
Under controlled conditions and in some observational studies of runners, airborne fine particulate matter smaller than 2.5 microns in diameter (PM2.5) is associated with exercise performance decrements. To assess the association between event-day fine particulate matter air pollution (PM2.5) and marathon finish times. Using a spatiotemporal machine-learning model, we estimated event-day racecourse-averaged PM2.5 concentrations for nine major US marathons (2003-2019). We obtained 1,506,137 male and 1,058,674 female finish times from 140 event-years of public marathon data. We used linear and quantile mixed models to estimate the mean and percentile-specific year and heat index-adjusted effect of 1µg/m3 higher event-day racecourse-averaged PM2.5 on marathon finish times in sex-stratified samples. Analyzing all finish times, 1µg/m3 higher race-day PM2.5 was associated with 32-s slower average finish times among men (95% confidence limits (CL) 30, 33s) and 25-s slower average finish times among women (95% CL 23, 27s). Quantile-specific associations of event-day PM2.5 with finish times were larger for faster-than-median finishers. While PM2.5 was generally associated with slower finish times in single-event models, there was effect heterogeneity, and most 95% confidence intervals included the null. Greater race-day PM2.5 was associated with slower average marathon finish times, with more pronounced effects in faster-than-median runners. While more research is needed to characterize effect heterogeneity across the performance spectrum, these findings show the impact of PM2.5 on marathon performance and the importance of considering data from multiple competitions when estimating PM2.5 effects from event-level data.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
