Characterisation of personalised air pollution exposure in pregnant women participating in a birth cohort study

Abstract

AbstractBackgroundAir pollution is a health risk in pregnant women and children. Despite the importance of refined exposure assessment, the characterisation of personalised air pollution exposure remains a challenge in paediatric and perinatal epidemiology.ObjectiveWe used portable personal air monitors to characterise personalised exposure to air pollutants in pregnant women.MethodsBetween November 2019 and May 2022, we offered personal air monitors to pregnant women participating in a birth cohort in New York City. During pregnancy, women used air monitors, which measured particulate matter (PM), nitrogen dioxide (NO2), and volatile organic compounds (average use = 14 days). Data were stored in real‐time on a secure database via synchronisation with a smartphone application. Of 497 women who agreed to use air monitors, 273 women (55%) were successful in using air monitors for longer than a day. For these participants, we identified daily patterns of exposure to air pollutants using functional principal component analysis (3827 days of air monitoring).ResultsCompared to women with no pollution data (n = 224), women who successfully used monitors were more likely to be non‐Hispanic White and Asian (vs. Hispanic), nulliparous, unemployed, married/partnered, and received the device in‐person (vs. mailed). We identified different daily patterns of exposure to air pollutants. The most dominant pattern for all pollutants was low exposure levels with little variations within 24 h, followed by a pattern that showed differences between day and night levels. NO2 had higher daily variations compared to PM.ConclusionsSmall wearables are useful for the measurement of personalised air pollution exposure in birth cohorts and identify daily patterns that cannot be captured otherwise. Successful participation, however, depends on certain individual characteristics. Future studies should consider strategies in design and analysis to account for selective participation.