Monitoring vs. modeled exposure data in time-series studies of ambient air pollution and acute health outcomes.
Stefanie T EbeltRohan R D'SouzaHaofei YuNoah ScovronickShannon MossHoward H ChangPublished in: Journal of exposure science & environmental epidemiology (2022)
This study compared and interpreted the use of monitoring and modeled exposure metrics in a daily time-series analysis of air pollution and cardiorespiratory emergency department visits. The results suggest that the use of routinely-collected ambient monitoring data in population-based short-term air pollution and health studies is a sound approach for exposure assignment in large metropolitan regions. CMAQ-, LUR-, and satellite-based metrics may allow for health effects estimation when monitoring data are sparse, if paired with thorough data characterization. These results are useful for interpretation of existing health effects literature and for improving exposure assessment in future air pollution epidemiology studies.
Keyphrases
- air pollution
- particulate matter
- emergency department
- lung function
- electronic health record
- big data
- healthcare
- systematic review
- public health
- case control
- mental health
- body composition
- risk factors
- risk assessment
- machine learning
- liver failure
- social media
- hepatitis b virus
- extracorporeal membrane oxygenation
- respiratory failure
- climate change
- health promotion
- mechanical ventilation