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Association of PM2.5 with diabetes, asthma, and high blood pressure incidence in Canada: A spatiotemporal analysis of the impacts of the energy generation and fuel sales.

Association of PM2.5 with diabetes, asthma, and high blood pressure incidence in Canada: A spatiotemporal analysis of the impacts of the energy generation and fuel sales.
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Requia WJ, Adams MD, Koutrakis P,


Requia WJ, Adams MD, Koutrakis P, (click to view)

Requia WJ, Adams MD, Koutrakis P,

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The Science of the total environment 2017 02 04584-585() 1077-1083 pii S0048-9697(17)30183-3
Abstract

Numerous studies have reported an association between fine particulate matter (PM2.5) and human health. Often these relationships are influenced by environmental factor that varies spatially and/or temporally. To our knowledge, there are no studies in Canada that have considered energy generation and fuel sales as PM2.5 effects modifiers. Determining exposure and disease-specific risk factors over space and time is crucial for disease prevention and control. In this study, we evaluated the association of PM2.5 with diabetes, asthma, and High Blood Pressure (HBP) incidence in Canada. Then we explored the impact of the energy generation and fuel sales on association changes. We fit an age-period-cohort as the study design, and we applied an over-dispersed Poisson regression model to estimate the risk. We conducted a sensitivity analysis to explore the impact of variation in clean energy rates and fuel sales on outcomes changes. The study included 117 health regions in Canada between 2007 and 2014. Our findings showed strong association of PM2.5 with diabetes, asthma, and HBP incidence. A two-year increase of 10μg/m(3) in PM2.5 was associated with an increased risk of 5.34% (95% CI: 2.28%; 12.53%) in diabetes incidence, 2.24% (95% CI: 0.93%; 5.38%) in asthma incidence, and 8.29% (95% CI: 3.44%; 19.98%) in HBP incidence. Our sensitivity analysis findings suggest higher risks of diabetes, asthma and HBP incidence when there is low clean energy generation. On the other hand, we found lower risk when we considered high rate of clean energy generation. For example, considering only diabetes incidence, we found that the risk in health regions with low rates of clean electricity is approximately 700% higher than the risk in health regions with high rates of clean electricity. Furthermore, our analysis suggested that the risk in regions with low fuel sales is 66% lower than the risk is health regions with low rates of clean electricity. Our study provides support for the creation of effective environmental health public policies that take into account the risk factors present in Canadians health regions.

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