Running on Fumes: An Analysis of Fine Particulate Matter's Impact on Finish Times in Nine Major US Marathons, 2003-2019.

Abstract

Under controlled conditions and in some observational studies of runners, airborne fine particulate matter smaller than 2.5 microns in diameter (PM_2.5) is associated with exercise performance decrements. To assess the association between event-day fine particulate matter air pollution (PM_2.5) and marathon finish times. Using a spatiotemporal machine-learning model, we estimated event-day racecourse-averaged PM_2.5 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 1 µg/m³ higher event-day racecourse-averaged PM_2.5 on marathon finish times in sex-stratified samples. Analyzing all finish times, 1 µg/m³ higher race-day PM_2.5 was associated with 32-s slower average finish times among men (95% confidence limits (CL) 30, 33 s) and 25-s slower average finish times among women (95% CL 23, 27 s). Quantile-specific associations of event-day PM_2.5 with finish times were larger for faster-than-median finishers. While PM_2.5 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 PM_2.5 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 PM_2.5 on marathon performance and the importance of considering data from multiple competitions when estimating PM_2.5 effects from event-level data.