July 29 | 2019

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

James E. Bennett , Helen Tamura-Wicks , Robbie M. Parks, Richard T. Burnett, C. Arden Pope III, Matthew J. Bechle, Julian D. Marshall, Goodarz Danaei, Majid Ezzati. 

PLOS | Medicine Published: July 23, 2019 https://doi.org/10.1371/journal.pmed.1002856




Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States.

Methods and findings

We used vital registration and population data with information on sex, age, cause of death, and county of residence. We used four Bayesian spatiotemporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county-specific random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 μg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248–17,945) in females and 14,757 deaths (12,617–16,919) in males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13–0.17) for women and 0.13 years (0.11–0.15) for men. The life expectancy loss due to PM2.5was largest around Los Angeles and in some southern states such as Arkansas, Oklahoma, and Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income and higher poverty rate than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county-specific random intercepts.


According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate.

July 22 | 2019

Spatial variations in ambient ultrafine particle concentrations and risk of congenital heart defects.

Lavigne E, Lima I, Hatzopoulou M, Van Ryswyk K, Decou ML, Luo W, van Donkelaar A, Martin RV, Chen H, Stieb DM, Crighton E, Gasparrini A, Elten M, Yasseen AS 3rd, Burnett RT, Walker M, Weichenthal S.

Environ Int. 2019 Jul 1;130:104953. DOI: 10.1016/j.envint.2019.104953 [Epub ahead of print]



Cardiovascular malformations account for nearly one-third of all congenital anomalies, making these the most common type of birth defects. Little is known regarding the influence of ambient ultrafine particles (<0.1 μm) (UFPs) on their occurrence.


This population-based study examined the association between prenatal exposure to UFPs and congenital heart defects (CHDs).


A total of 158,743 singleton live births occurring in the City of Toronto, Canada between April 1st 2006 and March 31st 2012 were identified from a birth registry. Associations between exposure to ambient UFPs between the 2nd and 8th week post conception when the foetal heart begins to form and CHDs identified at birth were estimated using random-effects logistic regression models, adjusting for personal- and neighbourhood-level covariates. We also investigated multi-pollutant models accounting for co-exposures to PM2.5, NO2 and O3.


A total of 1468 CHDs were identified. In fully adjusted models, UFP exposures during weeks 2 to 8 of pregnancy were not associated with overall CHDs (Odds Ratio (OR) per interquartile (IQR) increase = 1.02, 95% CI: 0.96-1.08). When investigating subtypes of CHDs, UFP exposures were associated with ventricular septal defects (Odds Ratio (OR) per interquartile (IQR) increase = 1.13, 95% CI: 1.03-1.33), but not with atrial septal defect (Odds Ratio (OR) per interquartile (IQR) increase = 0.89, 95% CI: 0.74-1.06).


This is the first study to evaluate the association between prenatal exposure to UFPs and the risk of CHDs. UFP exposures during a critical period of embryogenesis were associated with an increased risk of ventricular septal defect.

July 15 | 2019

Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes. 

Jesus Serrano-Lomelin, Charlene C. Nielsen, M. Shazan M. Jabbar, Osnat Wine, Colin Bellinger, Paul J. Villeneuvee, Dave Stieb, Nancy Aelicks, Khalid Aziz, Irena Buka, Sue Chandra, Susan Crawford, Paul Demers, Anders C. Erickson, Perry Hystad, Manoj Kumar, Erica Phipps, Prakesh S. Shah, YanYuan, Osmar R. Zaiane, Alvaro R. Osornio-Vargas.

Environment International Volume 131, October 2019, https://doi.org/10.1016/j.envint.2019.104972




Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches.


We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO.


We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006–2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density.


From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses.


This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes.

July 10 | 2019

Air pollution, lung function and COPD: results from the population-based UK Biobank study.

Dany Doiron, Kees de Hoogh, Nicole Probst-Hensch, Isabel Fortier, Yutong Cai, Sara De Matteis, Anna L. Hansell.

European Respiratory Journal 2019;  https://doi.org/10.1183/13993003.02140-2018


Ambient air pollution increases the risk of respiratory mortality but evidence for impacts on lung function and chronic obstructive pulmonary disease (COPD) is less well established. The aim was to evaluate whether ambient air pollution is associated with lung function and COPD, and explore potential vulnerability factors.

We used UK Biobank data on 3 03 887 individuals aged 40–69 years, with complete covariate data and valid lung function measures. Cross-sectional analyses examined associations of Land Use Regression-based estimates of particulate matter (PM2.5, PM10 and PMcoarse) and nitrogen dioxide (NO2) concentrations with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), the FEV1/FVC ratio, and COPD (FEV1/FVC <lower limit of normal). Effect modification was investigated for sex, age, obesity, smoking status, household income, asthma status, and occupations previously linked to COPD.

Higher exposures to each pollutant were significantly associated with lower lung function. A 5 µg·m−3 increase in PM2.5 concentration was associated with lower FEV1 (−83.13 mL [95%CI: −92.50, −73.75]) and FVC (−62.62 mL [95%CI: −73.91, −51.32]). COPD prevalence was associated with higher concentrations of PM2.5 (OR 1.52 [95%CI: 1.42, 1.62], per 5 µg·m−3), PM10 (OR 1.08 [95%CI: 1.00, 1.16], per 5 µg·m−3), and NO2 (OR 1.12 [95%CI: 1.10, 1.14], per 10 µg·m−3), but not with PMcoarse. Stronger lung function associations were seen for males, individuals from lower income households, and “at-risk” occupations, and higher COPD associations for obese, lower income, and non-asthmatic participants.

Ambient air pollution was associated with lower lung function and increased COPD prevalence in this large study.

July 2 | 2019

Interaction between neighborhood walkability and traffic-related air pollution on hypertension and diabetes: The CANHEART cohort.

Howell NA, Tu JV, Moineddin R, Chen H, Chu A, Hystad P, Booth GL.

Environ Int. 2019 Jun 19:104799. DOI: 10.1016/j.envint.2019.04.070




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.


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.


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 NO2exhibited 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).


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.