Environmental health research opportunities through CPTP and CANUE | February 13th | 2020

About the Speaker: Dr. Jeffrey Brook
Dr. Jeffrey Brook is CANUE’s Principal Investigator and Scientific Director. He is also an Assistant Professor at the University of Toronto’s Dalla Lana School of Public Health and Department of Chemical Engineering and Applied Chemistry. He has 25 years of experience as an Environment Canada scientist working at the science-policy interface. He is one of Canada’s leading experts in air quality, recognized at all levels of government and academically, including for his substantial contributions in air pollution health research. Dr. Brook has led scientific assessments to inform policy nationally and internationally, and advised multi-stakeholder groups shaping policy.

This webinar will provide an overview of the CANUE data and research opportunities made possible by linking CPTP’s individual lifestyle, genetic and behavioural data with CANUE’s environmental exposure metrics. This collaboration provides health researchers easy access to standardized urban environmental exposures, allowing them to tackle real-world problems related to exposures and the subsequent health outcomes. Ultimately, new knowledge enabled by the CANUE-CPTP partnership will help identify cost-effective actions that promote healthy childhood development and aging, reduce the burden of chronic disease, and minimize the impact of changing environments.

Webinar registrationhttp://bit.ly/CPTPwebinarFeb13


January 27 | 2020

Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study.

Yuchi W, Sbihi H, Davies H, Tamburic L, Brauer M.

Environ Health. 2020 Jan 21;19(1):8. DOI:10.1186/s12940-020-0565-4




Emerging evidence links road proximity and air pollution with cognitive impairment. Joint effects of noise and greenness have not been evaluated. We investigated associations between road proximity and exposures to air pollution, and joint effects of noise and greenness, on non-Alzheimer’s dementia, Parkinson’s and Alzheimer’s disease and multiple sclerosis within a population-based cohort.


We assembled administrative health database cohorts of 45-84 year old residents (N ~ 678,000) of Metro Vancouver, Canada. Cox proportional hazards models were built to assess associations between exposures and non-Alzheimer’s dementia and Parkinson’s disease. Given reduced case numbers, associations with Alzheimer’s disease and multiple sclerosis were evaluated in nested case-control analyses by conditional logistic regression.


Road proximity was associated with all outcomes (e.g. non-Alzheimer’s dementia hazard ratio: 1.14, [95% confidence interval: 1.07-1.20], for living < 50 m from a major road or < 150 m from a highway). Air pollutants were associated with incidence of Parkinson’s disease and non-Alzheimer’s dementia (e.g. Parkinson’s disease hazard ratios of 1.09 [1.02-1.16], 1.03 [0.97-1.08], 1.12 [1.05-1.20] per interquartile increase in fine particulate matter, Black Carbon, and nitrogen dioxide) but not Alzheimer’s disease or multiple sclerosis. Noise was not associated with any outcomes while associations with greenness suggested protective effects for Parkinson’s disease and non-Alzheimer’s dementia.


Road proximity was associated with incidence of non-Alzheimer’s dementia, Parkinson’s disease, Alzheimer’s disease and multiple sclerosis. This association may be partially mediated by air pollution, whereas noise exposure did not affect associations. There was some evidence of protective effects of greenness.

January 21 | 2020

Global trends toward urban street-network sprawl.

Barrington-Leigh C, Millard-Ball A.

Proc Natl Acad Sci U S A. 2020 Jan 14. pii: 201905232. [Epub ahead of print] DOI:10.1073/pnas.1905232116



We present a global time series of street-network sprawl-that is, sprawl as measured through the local connectivity of the street network. Using high-resolution data from OpenStreetMap and a satellite-derived time series of urbanization, we compute and validate changes over time in multidimensional street connectivity measures based on graph-theoretic and geographic concepts. We report on global, national, and city-level trends since 1975 in the street-network disconnectedness index (SNDi), based on every mapped node and edge in the world. Streets in new developments in 90% of the 134 most populous countries have become less connected since 1975, while just 29% show an improving trend since 2000. The same period saw a near doubling in the relative frequency of a street-network type characterized by high circuity, typical of gated communities. We identify persistence in street-network sprawl, indicative of path-dependent processes. Specifically, cities and countries with low connectivity in recent years also had relatively low preexisting connectivity in our earliest time period. We discuss implications for policy intervention in road building in new and expanding cities as a top priority for sustainable urban development.

January 14 | 2020

Mortality-Air Pollution Associations in Low-Exposure Environments (MAPLE): Phase 1.

Brauer M, Brook JR, Christidis T, Chu Y, Crouse DL, Erickson A, Hystad P, Li C, Martin RV, Meng J, Pappin AJ, Pinault LL, Tjepkema M, van Donkelaar A, Weichenthal S, Burnett RT.

Res Rep Health Eff Inst. 2019 Nov;(203):1-87. https://www.healtheffects.org/system/files/brauer-rr-203-phase1-report_0.pdf



Fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter, or PM2.5) is associated with mortality, but the lower range of relevant concentrations is unknown. Novel satellite-derived estimates of outdoor PM2.5 concentrations were applied to several large population-based cohorts, and the shape of the relationship with nonaccidental mortality was characterized, with emphasis on the low concentrations (<12 μg/m3) observed throughout Canada.


Annual satellite-derived estimates of outdoor PM2.5 concentrations were developed at 1-km2 spatial resolution across Canada for 2000-2016 and backcasted to 1981 using remote sensing, chemical transport models, and ground monitoring data. Targeted ground-based measurements were conducted to measure the relationship between columnar aerosol optical depth (AOD) and ground-level PM2.5. Both existing and targeted ground-based measurements were analyzed to develop improved exposure data sets for subsequent epidemiological analyses.

Residential histories derived from annual tax records were used to estimate PM2.5 exposures for subjects whose ages ranged from 25 to 90 years. About 8.5 million were from three Canadian Census Health and Environment Cohort (CanCHEC) analytic files and another 540,900 were Canadian Community Health Survey (CCHS) participants. Mortality was linked through the year 2016. Hazard ratios (HR) were estimated with Cox Proportional Hazard models using a 3-year moving average exposure with a 1-year lag, with the year of follow-up as the time axis. All models were stratified by 5-year age groups, sex, and immigrant status. Covariates were based on directed acyclical graphs (DAG), and included contextual variables (airshed, community size, neighborhood dependence, neighborhood deprivation, ethnic concentration, neighborhood instability, and urban form). A second model was examined including the DAG-based covariates as well as all subject-level risk factors (income, education, marital status, indigenous identity, employment status, occupational class, and visible minority status) available in each cohort. Additional subject-level behavioral covariates (fruit and vegetable consumption, leisure exercise frequency, alcohol consumption, smoking, and body mass index [BMI]) were included in the CCHS analysis.

Sensitivity analyses evaluated adjustment for covariates and gaseous copollutants (nitrogen dioxide [NO2] and ozone [O3]), as well as exposure time windows and spatial scales. Estimates were evaluated across strata of age, sex, and immigrant status. The shape of the PM2.5-mortality association was examined by first fitting restricted cubic splines (RCS) with a large number of knots and then fitting the shape-constrained health impact function (SCHIF) to the RCS predictions and their standard errors (SE). This method provides graphical results indicating the RCS predictions, as a nonparametric means of characterizing the concentration-response relationship in detail and the resulting mean SCHIF and accompanying uncertainty as a parametric summary.

Sensitivity analyses were conducted in the CCHS cohort to evaluate the potential influence of unmeasured covariates on air pollution risk estimates. Specifically, survival models with all available risk factors were fit and compared with models that omitted covariates not available in the CanCHEC cohorts. In addition, the PM2.5 risk estimate in the CanCHEC cohort was indirectly adjusted for multiple individual-level risk factors by estimating the association between PM2.5 and these covariates within the CCHS.


Satellite-derived PM2.5 estimates were low and highly correlated with ground monitors. HR estimates (per 10-μg/m3 increase in PM2.5) were similar for the 1991 (1.041, 95% confidence interval [CI]: 1.016-1.066) and 1996 (1.041, 1.024-1.059) CanCHEC cohorts with a larger estimate observed for the 2001 cohort (1.084, 1.060-1.108). The pooled cohort HR estimate was 1.053 (1.041-1.065). In the CCHS an analogous model indicated a HR of 1.13 (95% CI: 1.06-1.21), which was reduced slightly with the addition of behavioral covariates (1.11, 1.04-1.18). In each of the CanCHEC cohorts, the RCS increased rapidly over lower concentrations, slightly declining between the 25th and 75th percentiles and then increasing beyond the 75th percentile. The steepness of the increase in the RCS over lower concentrations diminished as the cohort start date increased. The SCHIFs displayed a supralinear association in each of the three CanCHEC cohorts and in the CCHS cohort.

In sensitivity analyses conducted with the 2001 CanCHEC, longer moving averages (1, 3, and 8 years) and smaller spatial scales (1 km2 vs. 10 km2) of exposure assignment resulted in larger associations between PM2.5 and mortality. In both the CCHS and CanCHEC analyses, the relationship between nonaccidental mortality and PM2.5 was attenuated when O3 or a weighted measure of oxidant gases was included in models. In the CCHS analysis, but not in CanCHEC, PM2.5 HRs were also attenuated by the inclusion of NO2. Application of the indirect adjustment and comparisons within the CCHS analysis suggests that missing data on behavioral risk factors for mortality had little impact on the magnitude of PM2.5-mortality associations. While immigrants displayed improved overall survival compared with those born in Canada, their sensitivity to PM2.5 was similar to or larger than that for nonimmigrants, with differences between immigrants and nonimmigrants decreasing in the more recent cohorts.


In several large population-based cohorts exposed to low levels of air pollution, consistent associations were observed between PM2.5 and nonaccidental mortality for concentrations as low as 5 μg/m3. This relationship was supralinear with no apparent threshold or sublinear association.

January 6 | 2020

Drop-And-Spin Virtual Neighborhood Auditing: Assessing Built Environment for Linkage to Health Studies.

Plascak JJ, Rundle AG, Babel RA, Llanos AAM, LaBelle CM, Stroup AM, Mooney SJ.

Am J Prev Med. 2020 Jan;58(1):152-160. DOI: 10.1016/j.amepre.2019.08.032



Various built environment factors might influence certain health behaviors and outcomes. Reliable, resource-efficient methods that are feasible for assessing built environment characteristics across large geographies are needed for larger, more robust studies. This paper reports the item response prevalence, reliability, and rating time of a new virtual neighborhood audit protocol, drop-and-spin auditing, developed for assessment of walkability and physical disorder characteristics across large geographic areas.


Drop-and-spin auditing, a method where a Google Street View scene was rated by spinning 360° around a point location, was developed using a modified version of the virtual audit tool Computer Assisted Neighborhood Visual Assessment System. Approximately 8,000 locations within Essex County, New Jersey were assessed by 11 trained auditors. Using a standardized protocol, 32 built environment items per a location within Google Street View were audited. Test-retest and inter-rater κ statistics were from a 5% subsample of locations. Data were collected in 2017-2018 and analyzed in 2018.


Roughly 70% of Google Street View scenes had sidewalks. Among those, two thirds were in good condition. At least 5 obvious items of garbage or litter were present in 41% of Google Street View scenes. Maximum test-retest reliability indicated substantial agreement (κ ≥0.61) for all items. Inter-rater reliability of each item, generally, was lower than test-retest reliability. The median time to rate each item was 7.3 seconds.


Compared with segment-based protocols, drop-and-spin virtual neighborhood auditing is quicker and similarly reliable for assessing built environment characteristics. Assessment of large geographies may be more feasible using drop-and-spin virtual auditing.