June 11 | 2018

Do green neighbourhoods promote urban health justice?

Isabelle Anguelovski, Helen Cole, James Connolly, Margarita Triguero-Mas

The Lancet, Public Health. Vol 3, No. 6, e270 June 2018

DOI: https://doi.org/10.1016/S2468-2667(18)30096-3

For the past 30 years, a search for social and health justice has shaped many cities in North America and Europe. Residents of these cities have mobilised to address the effects of neighbourhood disinvestment, pollution, harmful land uses, and low-quality green spaces on health. In cities such as Leipzig or Barcelona, these movements have transformed neighbourhoods. However, while green amenities are important selling points for attracting high-income populations, the resulting increased property values shape a new conundrum, embodied in the exclusion and displacement associated with so-called green gentrification

June 4 | 2018

Healthy cities: key to a healthy future in China

William Summerskill, Helena Hui Wang, Richard Horton

The Lancet, Vol 391, No. 10135, p2086–2087, 26 May 2018 DOI: https://doi.org/10.1016/S0140-6736(18)30608-1


By 2030, up to one in eight people will live in a city in China. As urbanisation accelerates around the world, and particularly in Asia, the pivotal role of cities to influence the health of their inhabitants has never been greater. Hence, the UN Sustainable Development Goal 11 is to make cities inclusive, safe, resilient, and sustainable.


May28 | 2018

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

Son Y, Osornio-Vargas ÁR, O’Neill MS, Hystad P, Texcalac-Sangrador JL, Ohman-Strickland P, Meng Q, Schwander S.

Sci Total Environ. 2018 May 17;639:40-48. https://doi.org/10.1016/j.scitotenv.2018.05.144


The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM2.5, PM10, O3, NO2, CO and SO2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM2.5, PM10 and SO2. Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments.

May 21 | 2018

Kernel Density Estimation as a Measure of Environmental Exposure Related to Insulin Resistance in Breast Cancer Survivors

Marta M. Jankowska, Loki Natarajan, Suneeta Godbole, Kristin Meseck, Dorothy D. Sears, Ruth E. Patterson and Jacqueline Kerr

Cancer Epidemiol Biomarkers Prev; 26(7); 1078–84. Published July 2017

DOI: 10.1158/1055-9965.EPI-16-0927



Environmental factors may influence breast cancer; however, most studies have measured environmental exposure in neighborhoods around home residences (static exposure). We hypothesize that tracking environmental exposures over time and space (dynamic exposure) is key to assessing total exposure. This study compares breast cancer survivors’ exposure to walkable and recreation-promoting environments using dynamic Global Positioning System (GPS) and static home-based measures of exposure in relation to insulin resistance.


GPS data from 249 breast cancer survivors living in San Diego County were collected for one week along with fasting blood draw. Exposure to recreation spaces and walkability was measured for each woman’s home address within an 800 m buffer (static), and using a kernel density weight of GPS tracks (dynamic). Participants’ exposure estimates were related to insulin resistance (using the homeostatic model assessment of insulin resistance, HOMA-IR) controlled by age and body mass index (BMI) in linear regression models.


The dynamic measurement method resulted in greater variability in built environment exposure values than did the static method. Regression results showed no association between HOMA-IR and home-based, static measures of walkability and recreation area exposure. GPS-based dynamic measures of both walkability and recreation area were significantly associated with lower HOMA-IR (P < 0.05).


Dynamic exposure measurements may provide important evidence for community- and individual-level interventions that can address cancer risk inequities arising from environments wherein breast cancer survivors live and engage.

Impact: This is the first study to compare associations of dynamic versus static built environment exposure measures with insulin outcomes in breast cancer survivors.

May 14 | 2018

Environmental noise pollution and risk of preeclampsia.

Auger N, Duplaix M, Bilodeau-Bertrand M, Lo E, Smargiassi A.

Environ Pollut. 2018 Apr 25;239:599-606. Doi. 10.1016/j.envpol.2018.04.060



Environmental noise exposure is associated with a greater risk of hypertension, but the link with preeclampsia, a hypertensive disorder of pregnancy, is unclear.


We sought to determine the relationship between environmental noise pollution and risk of preeclampsia during pregnancy.


We analyzed a population-based cohort comprising 269,263 deliveries on the island of Montreal, Canada between 2000 and 2013. We obtained total environmental noise pollution measurements (LAeq24, Lden, Lnight) from land use regression models, and assigned noise levels to each woman based on the residential postal code. We computed odds ratios (OR) and 95% confidence intervals (CI) for the association of noise with preeclampsia in mixed logistic regression models with participants as a random effect, and adjusted for air pollution, neighbourhood walkability, maternal age, parity, multiple pregnancy, comorbidity, socioeconomic deprivation, and year of delivery. We assessed whether noise exposure was more strongly associated with severe or early onset preeclampsia than mild or late onset preeclampsia.


Prevalence of preeclampsia was higher for women exposed to elevated environmental noise pollution levels (LAeq24h ≥ 65 dB(A) = 37.9 per 1000 vs. <50 dB(A) = 27.9 per 1000). Compared with 50 dB(A), an LAeq24h of 65.0 dB(A) was not significantly associated the risk of preeclampsia (OR 1.09, 95% CI 0.99-1.20). Associations were however present with severe (OR 1.29, 95% CI 1.09-1.54) and early onset (OR 1.71, 95% CI 1.20-2.43) preeclampsia, with results consistent across all noise indicators. The associations were much weaker or absent for mild and late preeclampsia.


Environmental noise pollution may be a novel risk factor for pregnancy-related hypertension, particularly more severe variants of preeclampsia.

April 30 | 2018

Using electronic health record data for environmental and place based population health research: a systematic review.

Schinasi LH, Auchincloss AH, Forrest CB, Diez Roux AV.

Ann Epidemiol. 2018 Mar 21. pii: S1047-2797(18)30059-0. [Epub ahead of print] DOI:10.1016/j.annepidem.2018.03.008 



We conducted a systematic review of literature published on January 2000-May 2017 that spatially linked electronic health record (EHR) data with environmental information for population health research.


We abstracted information on the environmental and health outcome variables and the methods and data sources used.


The automated search yielded 669 articles; 128 articles are included in the full review. The number of articles increased by publication year; the majority (80%) were from the United States, and the mean sample size was approximately 160,000. Most articles used cross-sectional (44%) or longitudinal (40%) designs. Common outcomes were health care utilization (32%), cardiometabolic conditions/obesity (23%), and asthma/respiratory conditions (10%). Common environmental variables were sociodemographic measures (42%), proximity to medical facilities (15%), and built environment and land use (13%). The most common spatial identifiers were administrative units (59%), such as census tracts. Residential addresses were also commonly used to assign point locations, or to calculate distances or buffer areas.


Future research should include more detailed descriptions of methods used to geocode addresses, focus on a broader array of health outcomes, and describe linkage methods. Studies should also explore using longitudinal residential address histories to evaluate associations between time-varying environmental variables and health outcomes.

April 23 | 2018

Associations between Neighborhood Walkability and Incident and Ongoing Asthma in Children.

Elinor Simons , Sharon D Dell ; Rahim Moineddin , and Teresa To

Ann Am Thorac Soc. 2018 Apr 17. DOI:10.1513/AnnalsATS.201708-693OC



Childhood asthma has shown variable associations with children’s physical activity. Neighborhood walkability captures community features that promote walking and is protective against some chronic conditions, such as obesity and diabetes.


We evaluated associations between home neighborhood walkability and incident and ongoing childhood asthma.


This population-based cohort study used prospectively-collected administrative healthcare data for the province of Ontario housed at the Institute for Clinical Evaluative Sciences. We followed an administrative data cohort of 326,383 Toronto children born between 1997 and 2003 until ages 8-15 years. Home neighborhood walkability quintile was measured using a validated Walkability Index with four dimensions: population density, dwelling density, access to retail and services, and street connectivity. Incident asthma was defined by time of entry into the validated Ontario Asthma Surveillance Information System (OASIS) database, which requires two outpatient visits for asthma within two consecutive years or any hospitalization for asthma, and follows children with asthma longitudinally starting at any age. Associations between walkability and incident asthma were examined using Cox proportional hazards models. Associations between ongoing asthma and walkability in each year of life were examined using generalized linear mixed models.


Twenty-one percent of children (n = 69,628) developed incident asthma and were followed longitudinally in the OASIS asthma database. Low birth home neighborhood walkability was associated with an increased incidence of asthma (HR 1.11, 95% CI, 1.08-1.14). Among children with asthma, low walkability in a given year of a child`s life was associated with greater odds of ongoing asthma in the same year (OR 1.12, 95% CI, 1.09-1.14).


Children living in neighborhoods with low walkability were at increased risk of incident and ongoing asthma. Neighborhood walkability improvement, for example by adding pedestrian paths to improve street connectivity, offers potential strategies to contribute to primary asthma prevention.

APRIL 16 | 2018

Roadside vegetation design characteristics that can improve local, near-road air quality.

Baldauf, R., V. Isakov, A. Venkatram, P. Deshmukh, B. Yang, K. Zhang, R. Logan.

Transportation Research Part D: Transport and Environment. Elsevier BV, AMSTERDAM, Netherlands, 52:354-361, (2017) https://doi.org/10.1016/j.trd.2017.03.013


As public health concerns have increased due to the rising number of studies linking adverse health effects with exposures to traffic-related air pollution near large roadways, interest in methods to mitigate these exposures have also increased. Several studies have investigated the use of roadside features in reducing near-road air pollution concentrations since this method is often one of the few short-term options available. Since roadside vegetation has other potential benefits, the impact of this feature has been of particular interest. The literature has been mixed on whether roadside vegetation reduces nearby pollutant concentrations or whether this feature has no effect or even potentially increases downwind air pollutant concentrations. However, these differences in study results highlight key characteristics of the vegetative barrier that can result in pollutant reductions or increase local pollutant levels. This paper describes the characteristics of roadside vegetation that previous research shows can result in improved local air quality, as well as identify characteristics that should be avoided in order to protect from unintended increases in nearby concentrations. These design conditions include height, thickness, coverage, porosity/density, and species characteristics that promote improved air quality. These design considerations can inform highway departments, urban and transportation planners, and developers in understanding how best to preserve existing roadside vegetation or plant vegetative barriers in order to reduce air pollution impacts near transportation facilities. These designs can also be used to mitigate impacts from other air pollution sources where emissions occur near ground-level.

April 9 | 2018

Socio-economic inequalities in exposure to industrial air pollution emissions in Quebec public schools

Emmanuelle Batisse, Sophie Goudreau, Jill Baumgartner, Audrey Smargiassi

Can J Public Health. 2018 Jan 22;108(5-6):e503-e509. http://dx.doi.org/10.17269/cjph.108.6166


OBJECTIVES: We aimed to assess the relationships between deprivation at Quebec public schools, their proximity to polluting industries, and their exposure to industrial air emission sources including ambient fine particulate matter (PM2.5), sulphur dioxide (SO2) and nitrogen dioxide (NO2).

METHODS: We obtained four indicators of school deprivation using data from the 2006 Canadian census called the low-income threshold indicator, the neighbourhood SES indicator, and the social and material deprivation indicators of Pampalon. Using proximity spatial tools, we constructed three buffers of 2.5, 5 and 7.5 km around each school and summed up total emissions of PM2.5, SO2and NO2 for each school. Industrial air emissions were estimated using data from the 2006 Canadian National Pollutant Release Inventory. The Pearson correlations and LOESS regressions and natural log-transformed industrial air emissions were evaluated for Quebec public schools within the three buffers.

RESULTS: Of the 2189 public schools in Quebec, 608 (27.8%), 1108 (50.6%) and 1384 (63.2%) schools were located near at least one industry emitting one or more pollutants of interest in buffers of 2.5 km, 5 km and 7.5 km of schools respectively. Weak positive Pearson correlations (r) were found between log-transformed tons of industrial emissions of PM2.5, SO2 and NO2 and both the social deprivation (r = {0.23; 0.33}) and low-income threshold (r = {0.17; 0.29}) indicators in a buffer of 2.5 km. However, we found negative associations between emissions and the neighbourhood SES (r = {0.06; 0.16}) and material deprivation (r = {−0.04; 0.08}) indicators.

CONCLUSION: Our study suggests that schools in Quebec with higher rates of socio-economic deprivation among their students may be more likely to be exposed to higher emissions of industrial air pollutants.


April 2 | 2018

Childhood exposure to green space – A novel risk-decreasing mechanism for schizophrenia?

Engemann K, Pedersen CB, Arge L, Tsirogiannis C, Mortensen PB, Svenning JC.

Schizophr Res. 2018 Mar 21. pii: S0920-9964(18)30178-6. doi:10.1016/j.schres.2018.03.026. [Epub ahead of print] 



Schizophrenia risk has been linked to urbanization, but the underlying mechanism remains unknown. Green space is hypothesized to positively influence mental health and might mediate risk of schizophrenia by mitigating noise and particle pollution exposure, stress relief, or other unknown mechanisms. The objectives for this study were to determine if green space are associated with schizophrenia risk, and if different measures of green space associate differently with risk. We used satellite data from the Landsat program to quantify green space in a new data set for Denmark at 30 × 30 m resolution for the years 1985–2013. The effect of green space at different ages and within different distances from each person’s place of residence on schizophrenia risk was estimated using Cox regression on a very large longitudinal population-based sample of the Danish population (943,027 persons). Living at the lowest amount of green space was associated with a 1.52-fold increased risk of developing schizophrenia compared to persons living at the highest level of green space. This association remained after adjusting for known risk factors for schizophrenia: urbanization, age, sex, and socioeconomic status. The strongest protective association was observed during the earliest childhood years and closest to place of residence. This is the first nationwide population-based study to demonstrate a protective association between green space during childhood and schizophrenia risk; suggesting limited green space as a novel environmental risk factor for schizophrenia. This study supports findings from other studies highlighting positive effects of exposure to natural environments for human health.