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Temporal and spatial effect of air pollution on hospital admissions for myocardial infarction: a case-crossover study
Xiaoxiao Liu1, Stefania Bertazzon1, Paul J Villeneuve1
1Departments of Community Health Sciences (Liu, Coward, Tanyingoh, Windsor, Underwood, Rabi, Ghali, James, Kaplan) and of Geography (Liu, Bertazzon), University of Calgary, Calgary, Alta.; Department of History, Archaeology, Geography, Fine & Performing Arts (Bertazzon), University of Florence, Florence, Italy; School of Mathematics and Statistics and Department of Neuroscience, and CHAIM Research Centre (Villeneuve), Carleton University, Ottawa, Ont.; Air Health Science Division (Johnson), Health Canada, Ottawa, Ont.; Environmental Health Science and Research Bureau (Stieb), Health Canada, Vancouver, BC; Departments of Medicine (Coward, Tanyingoh, Windsor, Underwood, Hill, Rabi, Wilton, James, Kaplan); of Clinical Neurosciences (Hill, Ghali); and of Cardiac Sciences (Wilton), University of Calgary, Calgary, Alta.; Department of Medicine (Graham, McMurtry), University of Alberta; Mazankowski Alberta Heart Institute (McMurtry), Edmonton, Alta.
Background:
In studies showing associations between ambient air pollution and myocardial infarction (MI), data have been lacking on the inherent spatial variability of air pollution. The aim of this study was to determine whether the long-term spatial distribution of air pollution influences short-term temporal associations between air pollution and admission to hospital for MI.
Methods:
We identified adults living in Calgary who were admitted to hospital for an MI between 2004 and 2012. We evaluated associations between short-term exposure to air pollution (ozone [O3], nitrogen dioxide [NO2], sulfur dioxide [SO2], carbon monoxide [CO], particulate matter < 10 μm in diameter [PM10] and particulate matter < 2.5 μm in diameter [PM2.5]), and hospital admissions for MI using a time-stratified, case-crossover study design. Air Quality Health Index (AQHI) scores were calculated from a composition of O3, NO2 and PM2.5. Conditional logistic regression models were stratified by low, medium and high levels of neighbourhood NO2 concentrations derived from land use regression models; results of these analyses are presented as odds ratios (ORs) with 95% confidence intervals (CIs).
Results:
From 2004 to 2012, 6142 MIs were recorded in Calgary. Individuals living in neighbourhoods with higher long-term air pollution concentrations were more likely to be admitted to hospital for MI after short-term elevations in air pollution (e.g., 5-day average NO2: OR 1.20, 95% CI 1.03-1.40, per interquartile range [IQR]) as compared with regions with lower air pollution (e.g., 5-day average NO2: OR 0.90, 95% CI 0.78-1.04, per IQR). In high NO2 tertiles, the AQHI score was associated with MI (e.g., 5-day average OR 1.13, 95% CI 1.02-1.24, per IQR; 3-day average OR 1.13, 95% CI 1.04-1.23, per IQR).
Interpretation:
Our results show that the effect of air pollution on hospital admissions for MI was stronger in areas with higher NO2 concentrations than that in areas with lower NO2 concentrations. Individuals living in neighbourhoods with higher traffic-related pollution should be advised of the health risks and be attentive to special air quality warnings.
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