Personal exposure to fine particulate matter (PM_2.5) and self-reported asthma-related health

PM_2.5 (fine particulate matter ≤2.5 μm in diameter) is a key pollutant that can produce acute asthma exacerbations and longer-term deterioration of respiratory health. Individual exposure to PM_2.5 is unique and varies across microenvironments. Low-cost sensors (LCS) can collect data at a spatiotemporal resolution previously unattainable, allowing the study of exposures across microenvironments. The aim of this study is to investigate the acute effects of personal exposure to PM_2.5 on self-reported asthma-related health. Twenty-eight non-smoking adults with asthma living in Scotland collected PM_2.5 personal exposure data using LCS. Measurements were made at a 2-min time resolution for a period of 7 days as participants conducted their typical daily routines. Concurrently, participants were asked to keep a detailed time-activity diary, logging their activities and microenvironments, along with hourly information on their respiratory health and medication use. Health outcomes were modelled as a function of hourly PM_2.5 concentration (plus 1- and 2-h lag) using generalized mixed-effects models adjusted for temperature and relative humidity. Personal exposures to PM_2.5 varied across microenvironments, with the largest average microenvironmental exposure observed in private residences (11.5 ± 48.6 μg/m³) and lowest in the work microenvironment (2.9 ± 11.3 μg/m³). The most frequently reported asthma symptoms, wheezing, chest tightness and cough, were reported on 3.4%, 1.6% and 1.6% of participant-hours, respectively. The odds of reporting asthma symptoms increased per interquartile range (IQR) in PM_2.5 exposure (odds ratio (OR) 1.29, 95% CI 1.07-1.54) for same-hour exposure. Despite this, no association was observed between reliever inhaler use (non-routine, non-exercise related) and PM_2.5 exposure (OR 1.02, 95% CI 0.71-1.48). Current air quality monitoring practices are inadequate to detect acute asthma symptom prevalence resulting from PM_2.5 exposure; to detect these requires high-resolution air quality data and health information collected in situ. Personal exposure monitoring could have significant implications for asthma self-management and clinical practice.