The probability of diabetes and hypertension by levels of neighborhood walkability and traffic-related air pollution across 15 municipalities in Southern Ontario, Canada: A dataset derived from 2,496,458 community dwelling-adults
Nicholas A. Howell,
Jack V. Tu,
Rahim Moineddin,
Hong Chen,
Anna Chu,
Perry Hystad,
Gillian L. Booth
Affiliations
Nicholas A. Howell
Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, Ontario, 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; Institute for Clinical and Evaluative Sciences, 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5, Canada; Corresponding author. Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, Ontario, Ontario, M5B 1T8, Canada.
Jack V. Tu
Institute for Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario, M5T 3M6, Canada; Institute for Clinical and Evaluative Sciences, 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
Rahim Moineddin
Institute for Clinical and Evaluative Sciences, 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
Hong Chen
Institute for Clinical and Evaluative Sciences, 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
Anna Chu
Institute for Clinical and Evaluative Sciences, 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5, Canada
Perry Hystad
College of Public Health and Human Sciences, Oregon State University, 160 SW 26th St., Corvallis, OR, 97331, United States of America
Gillian L. Booth
Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, Ontario, 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; Institute for Clinical and Evaluative Sciences, 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5, Canada; Department of Medicine, University of Toronto, 190 Elizabeth Street, Toronto, Ontario, M5G 2C4, Canada
Individuals’ risk for cardiovascular disease is shaped by lifestyle factors such as participation in physical activity. Some studies have suggested that rates of physical activity may be higher in walkable neighborhoods that are more supportive of engaging in physical activity in daily life. However, walkable neighborhoods may also contain increased levels of traffic-related air pollution (TRAP). Traffic-related air pollution, often measured through a surrogate marker (e.g. NO2), has been associated cardiovascular disease risk and risk factors [1–4]. The higher levels of TRAP in walkable neighborhoods may in turn increase the likelihood of developing conditions like hypertension and diabetes. Our recent work assessed how walkability and TRAP jointly affect the odds of diabetes and hypertension in a sample of community-dwelling adults from Southern Ontario, Canada [5]. This article contains additional data on the probability and odds of hypertension and diabetes according to their walkability and TRAP exposures. Data on cardiovascular risk factors were collected using health administrative databases and environmental exposures were assessed using national land use regression models predicting ground level concentrations of NO2 and validated walkability indices. The included data were generated using logistic regression accounting for exposures, covariates, and neighborhood clustering. These data may be used as primary data in future health risk assessments and systematic reviews, or to aid in the design of studies examining interactions between built environment and TRAP exposures (e.g. sample size calculations). Keywords: Walkability, Traffic-related air pollution, NO2, Diabetes, Hypertension, Cardiovascular risk factors, Health administrative data