Nicholas A Howell1, Jack V Tu2, Rahim Moineddin3, Hong Chen4, Anna Chu5, Perry Hystad6, Gillian L Booth7. 1. Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, Toronto, Ontario M5B 1T8, Canada; Institute for Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario M5T 3M6, Canada; ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada. Electronic address: Nicholas.howell@mail.utoronto.ca. 2. Institute for Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario M5T 3M6, Canada; ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Schulich Heart Centre, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Department of Medicine, University of Toronto, 190 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada. 3. ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, 500 University Avenue, Toronto, Ontario M5G 1V7, Canada. 4. ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Public Health Ontario, 480 University Ave, Toronto, Ontario M5G 1V2, Canada; Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario M5T 3M7, Canada. 5. ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada. 6. College of Public Health and Human Sciences, Oregon State University, 160 SW 26th St., Corvallis, OR 97331, United States of America. 7. Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, Toronto, Ontario M5B 1T8, Canada; Institute for Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario M5T 3M6, Canada; ICES, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Department of Medicine, University of Toronto, 190 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada.
Abstract
BACKGROUND: Living in unwalkable neighborhoods has been associated with heightened risk for diabetes and hypertension. However, highly walkable environments may have higher concentrations of traffic-related air pollution, which may contribute to increased cardiovascular disease risk. We therefore aimed to assess how walkability and traffic-related air pollution jointly affect risk for hypertension and diabetes. METHODS: We used a cross-sectional, population-based sample of individuals aged 40-74 years residing in selected large urban centres in Ontario, Canada on January 1, 2008, assembled from administrative databases. Walkability and traffic-related air pollution (NO2) were assessed using validated tools and linked to individuals based on neighborhood of residence. Logistic regression was used to estimate adjusted associations between exposures and diagnoses of hypertension or diabetes accounting for potential confounders. RESULTS: Overall, 2,496,458 individuals were included in our analyses. Low walkability was associated with higher odds of hypertension (lowest vs. highest quintile OR = 1.34, 95% CI: 1.32, 1.37) and diabetes (lowest vs. highest quintile OR = 1.25, 95% CI: 1.22, 1.29), while NO2 exhibited similar trends (hypertension: OR = 1.09 per 10 p.p.b., 95% CI: 1.08, 1.10; diabetes: OR = 1.16, 95% CI: 1.14, 1.17). Significant interactions were identified between walkability and NO2 on risk for hypertension (p < 0.0001 and diabetes (p < 0.0001). At higher levels of pollution (40 p.p.b.), differences in the probability of hypertension (lowest vs. highest walkability quintile: 0.26 vs. 0.25) or diabetes (lowest vs. highest walkability quintile: 0.15 vs. 0.15) between highly walkable and unwalkable neighborhoods were diminished, compared to differences observed at lower levels of pollution (5 p.p.b.) (hypertension, lowest vs. highest walkability quintile: 0.21 vs. 0.13; diabetes, lowest vs. highest walkability quintile: 0.09 vs. 0.06). CONCLUSIONS: Walkability and traffic-related air pollution interact to jointly predict risk for hypertension and diabetes. Although walkable neighborhoods appear to have beneficial effects, they may accentuate the harmful effects of air pollution on cardiovascular risk factors. Crown
BACKGROUND: Living in unwalkable neighborhoods has been associated with heightened risk for diabetes and hypertension. However, highly walkable environments may have higher concentrations of traffic-related air pollution, which may contribute to increased cardiovascular disease risk. We therefore aimed to assess how walkability and traffic-related air pollution jointly affect risk for hypertension and diabetes. METHODS: We used a cross-sectional, population-based sample of individuals aged 40-74 years residing in selected large urban centres in Ontario, Canada on January 1, 2008, assembled from administrative databases. Walkability and traffic-related air pollution (NO2) were assessed using validated tools and linked to individuals based on neighborhood of residence. Logistic regression was used to estimate adjusted associations between exposures and diagnoses of hypertension or diabetes accounting for potential confounders. RESULTS: Overall, 2,496,458 individuals were included in our analyses. Low walkability was associated with higher odds of hypertension (lowest vs. highest quintile OR = 1.34, 95% CI: 1.32, 1.37) and diabetes (lowest vs. highest quintile OR = 1.25, 95% CI: 1.22, 1.29), while NO2 exhibited similar trends (hypertension: OR = 1.09 per 10 p.p.b., 95% CI: 1.08, 1.10; diabetes: OR = 1.16, 95% CI: 1.14, 1.17). Significant interactions were identified between walkability and NO2 on risk for hypertension (p < 0.0001 and diabetes (p < 0.0001). At higher levels of pollution (40 p.p.b.), differences in the probability of hypertension (lowest vs. highest walkability quintile: 0.26 vs. 0.25) or diabetes (lowest vs. highest walkability quintile: 0.15 vs. 0.15) between highly walkable and unwalkable neighborhoods were diminished, compared to differences observed at lower levels of pollution (5 p.p.b.) (hypertension, lowest vs. highest walkability quintile: 0.21 vs. 0.13; diabetes, lowest vs. highest walkability quintile: 0.09 vs. 0.06). CONCLUSIONS: Walkability and traffic-related air pollution interact to jointly predict risk for hypertension and diabetes. Although walkable neighborhoods appear to have beneficial effects, they may accentuate the harmful effects of air pollution on cardiovascular risk factors. Crown
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