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Chronic exposure to air pollution and long-term outcomes after first acute myocardial infarction: a population-based cohort study

Yariv Gerber, David Broday, Yuval, Silvia Koton, David Steinberg, Yaakov Drori, Noa Molchanski, Viki Mayers

Recent efforts in air pollution epidemiological research have been directed toward the identification of potentially susceptible subpopulations, an essential step for ensuring adequate pollution prevention policy. Preliminary data suggest that patients with myocardial infarction (MI) may be particularly vulnerable to the effects of chronic exposure to air pollution. However, methodological limitations inherent in the current literature, in addition to conflicting results, challenge these findings. Oftentimes, high-quality data from well-defined MI cohorts with extensive information on various confounding factors, sufficient follow-up period, and multiple outcomes assessed longitudinally are missing. This work examines the relationships between chronic residential exposure to air pollutants (NOx, SO2, and PMx) and clinical outcomes (including recurrent ischemic event, stroke, heart failure, cardiac death, and all-cause death) in a geographically defined cohort of patients with acute MI followed up for a median of 13 years. The research hypothesis is that exposure to air pollutants is associated with long-term post-MI outcomes independently of established demographic, socioeconomic, and clinical prognostic measures. The research is designed as a historical prospective study, in which data recorded at air quality monitoring stations are used to estimate the exposure to air pollution for each patient based on his/her residential location. These metrics were incorporated into an already complete follow-up investigation of 1,521 consecutive patients aged ≤65 years that have been discharged from all the hospitals in central Israel after first acute MI in 1992-3. Advanced statistical methods were implemented to evaluate the air pollution–outcome associations, including survival analysis, mixed-effects Cox models and competing-risks analyses.