Associations of Long-Term Exposure to Ultrafine Particles and Nitrogen Dioxide With Increased Incidence of Congestive Heart Failure and Acute Myocardial Infarction

Although long-term exposure to traffic-related air pollutants such as nitrogen dioxide has been linked to cardiovascular disease (CVD) mortality, little is known about the association between ultrafine particles (UFPs), defined as particles less than or equal to 0.1 μm in diameter, and incidence of major CVD events. We conducted a population-based cohort study to assess the associations of chronic exposure to UFPs and nitrogen dioxide with incident congestive heart failure (CHF) and acute myocardial infarction. Our study population comprised all long-term Canadian residents aged 30-100 years who lived in Toronto, Ontario, Canada, during the years 1996-2012. We estimated annual concentrations of UFPs and nitrogen dioxide by means of land-use regression models and assigned these estimates to participants' postal-code addresses in each year during the follow-up period. We estimated hazard ratios for the associations of UFPs and nitrogen dioxide with incident CVD using random-effects Cox proportional hazards models. We controlled for smoking and obesity using an indirect adjustment method. Our cohorts comprised approximately 1.1 million individuals at baseline. In single-pollutant models, each interquartile-range increase in UFP exposure was associated with increased incidence of CHF (hazard ratio for an interquartile-range increase (HRIQR) = 1.03, 95% confidence interval (CI): 1.02, 1.05) and acute myocardial infarction (HRIQR = 1.05, 95% CI: 1.02, 1.07). Adjustment for fine particles and nitrogen dioxide did not materially change these estimated associations. Exposure to nitrogen dioxide was also independently associated with higher CHF incidence (HRIQR = 1.04, 95% CI: 1.03, 1.06).

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

BACKGROUND

Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment.

METHODS

We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator.

FINDINGS

The global median health-related SDG index in 2017 was 59·4 (IQR 35·4-67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6-14·0) to a high of 84·9 (83·1-86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030.

INTERPRETATION

The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains-curative interventions in the case of NCDs-towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions-or inaction-today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.

FUNDING

Bill & Melinda Gates Foundation.

Satellite-Based Land-Use Regression for Continental-Scale Long-Term Ambient PM2.5 Exposure Assessment in Australia

Australia has relatively diverse sources and low concentrations of ambient fine particulate matter (<2.5 μm, PM_2.5). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM_2.5, derived by relating satellite-observed aerosol optical depth to ground-level PM_2.5 ("SAT-PM_2.5"). We aimed to determine the validity of such satellite-based LUR models for PM_2.5 in Australia. We used global SAT-PM_2.5 estimates (∼10 km grid) and local land-use predictors to develop four LUR models for year-2015 (two satellite-based, two nonsatellite-based). We evaluated model performance at 51 independent monitoring sites not used for model development. An LUR model that included the SAT-PM_2.5 predictor variable (and six others) explained the most spatial variability in PM_2.5 (adjusted R² = 0.63, RMSE (μg/m³ [%]): 0.96 [14%]). Performance decreased modestly when evaluated (evaluation R² = 0.52, RMSE: 1.15 [16%]). The evaluation R² of the SAT-PM_2.5 estimate alone was 0.26 (RMSE: 3.97 [56%]). SAT-PM_2.5 estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM_2.5 estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM_2.5 exposure assessment in Australia.

Spatial PM2.5, NO2, O3 and BC models for Western Europe - Evaluation of spatiotemporal stability

BACKGROUND

In order to investigate associations between air pollution and adverse health effects consistent fine spatial air pollution surfaces are needed across large areas to provide cohorts with comparable exposures. The aim of this paper is to develop and evaluate fine spatial scale land use regression models for four major health relevant air pollutants (PM_2.5, NO₂, BC, O₃) across Europe.

METHODS

We developed West-European land use regression models (LUR) for 2010 estimating annual mean PM_2.5, NO₂, BC and O₃ concentrations (including cold and warm season estimates for O₃). The models were based on AirBase routine monitoring data (PM_2.5, NO₂ and O₃) and ESCAPE monitoring data (BC), and incorporated satellite observations, dispersion model estimates, land use and traffic data. Kriging was performed on the residual spatial variation from the LUR models and added to the exposure estimates. One model was developed using all sites (100%). Robustness of the models was evaluated by performing a five-fold hold-out validation and for PM_2.5 and NO₂ additionally with independent comparison at ESCAPE measurements. To evaluate the stability of each model's spatial structure over time, separate models were developed for different years (NO₂ and O₃: 2000 and 2005; PM_2.5: 2013).

RESULTS

The PM_2.5, BC, NO₂, O₃ annual, O₃ warm season and O₃ cold season models explained respectively 72%, 54%, 59%, 65%, 69% and 83% of spatial variation in the measured concentrations. Kriging proved an efficient technique to explain a part of residual spatial variation for the pollutants with a strong regional component explaining respectively 10%, 24% and 16% of the R² in the PM_2.5, O₃ warm and O₃ cold models. Explained variance at fully independent sites vs the internal hold-out validation was slightly lower for PM_2.5 (65% vs 66%) and lower for NO₂ (49% vs 57%). Predictions from the 2010 model correlated highly with models developed in other years at the overall European scale.

CONCLUSIONS

We developed robust PM_2.5, NO₂, O₃ and BC hybrid LUR models. At the West-European scale models were robust in time, becoming less robust at smaller spatial scales. Models were applied to 100 × 100 m surfaces across Western Europe to allow for exposure assignment for 35 million participants from 18 European cohorts participating in the ELAPSE study.

Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model

Exposure to ambient fine particulate matter (PM_2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM_2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM_2.5 to interpret globally dispersed PM_2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM_2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m³), mineral dust (1.9-14.7 μg/m³), residual/organic matter (2.1-40.2 μg/m³), and black carbon (1.0-7.3 μg/m³). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m³), industry (6.5 μg/m³), and power generation (5.6 μg/m³) are leading sources of outdoor global population-weighted PM_2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM_2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM_2.5 provides insight into sources and processes that influence the global spatial variation in PM_2.5 composition.

Estimates of the Global Burden of Ambient [Formula: see text], Ozone, and [Formula: see text] on Asthma Incidence and Emergency Room Visits

BACKGROUND

Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma.

OBJECTIVES

We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter ([Formula: see text]), ozone, and nitrogen dioxide ([Formula: see text]) concentrations.

METHODS

We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data.

RESULTS

We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and [Formula: see text], respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for [Formula: see text] and 73% of ozone and [Formula: see text] impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and [Formula: see text] (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India.

CONCLUSIONS

These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP3766.

Long-term exposure to air pollution and the incidence of multiple sclerosis: A population-based cohort study

BACKGROUND

Evidence of the adverse neurological effects of exposure to ambient air pollution is emerging, but little is known about its effect on the development of multiple sclerosis (MS), the most common autoimmune disease of the central nervous system.

OBJECTIVES

To investigate the associations between MS incidence and long-term exposures to fine particles (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃) METHODS: We conducted a population-based cohort study to investigate the associations between long-term exposures to PM_2.5, NO₂, and O₃ and the incidence of MS. Our study population included all Canadian-born residents aged 20-40 years who lived in the province of Ontario, Canada from 2001 to 2013. Incident MS was ascertained from a validated registry. We assigned estimates of annual concentrations of these pollutants to the residential postal codes of subjects for each year during the 13 years of follow-up. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for each pollutant separately using random-effects Cox proportional hazards models. We conducted various sensitivity analyses, such as lagging exposure up to 5 years and adjusting for access to neurological care, annual average temperature, and population density.

RESULTS

Between 2001 and 2013, we identified 6203 incident cases of MS. The adjusted HR of incident MS was 0.96 (95% CI: 0.86-1.07) for PM_2.5, 0.91(95% CI: 0.81-1.02) for NO₂, and 1.09 (95% CI: 0.98-1.23) for O₃. These results were robust to various sensitivity analyses conducted.

CONCLUSIONS

In this large population-based cohort, we did not observe significant associations between MS incidence and long-term exposures to PM_2.5, NO₂, and O₃ in adults in Ontario, 2001-2013.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Data Integration for the Assessment of Population Exposure to Ambient Air Pollution for Global Burden of Disease Assessment

Air pollution is a leading global disease risk factor. Tracking progress (e.g., for Sustainable Development Goals) requires accurate, spatially resolved, routinely updated exposure estimates. A Bayesian hierarchical model was developed to estimate annual average fine particle (PM_2.5) concentrations at 0.1° × 0.1° spatial resolution globally for 2010-2016. The model incorporated spatially varying relationships between 6003 ground measurements from 117 countries, satellite-based estimates, and other predictors. Model coefficients indicated larger contributions from satellite-based estimates in countries with low monitor density. Within and out-of-sample cross-validation indicated improved predictions of ground measurements compared to previous (Global Burden of Disease 2013) estimates (increased within-sample R² from 0.64 to 0.91, reduced out-of-sample, global population-weighted root mean squared error from 23 μg/m³ to 12 μg/m³). In 2016, 95% of the world's population lived in areas where ambient PM_2.5 levels exceeded the World Health Organization 10 μg/m³ (annual average) guideline; 58% resided in areas above the 35 μg/m³ Interim Target-1. Global population-weighted PM_2.5 concentrations were 18% higher in 2016 (51.1 μg/m³) than in 2010 (43.2 μg/m³), reflecting in particular increases in populous South Asian countries and from Saharan dust transported to West Africa. Concentrations in China were high (2016 population-weighted mean: 56.4 μg/m³) but stable during this period.

Associations between Living Near Water and Risk of Mortality among Urban Canadians

BACKGROUND

Increasing evidence suggests that residential exposures to natural environments, such as green spaces, are associated with many health benefits. Only a single study has examined the potential link between living near water and mortality.

OBJECTIVE

We sought to examine whether residential proximity to large, natural water features (e.g., lakes, rivers, coasts, "blue space") was associated with cause-specific mortality.

METHODS

Our study is based on a population-based cohort of nonimmigrant adults living in the 30 largest Canadian cities [i.e., the 2001 Canadian Census Health and Environment Cohort) (CanCHEC)]. Subjects were drawn from the mandatory 2001 Statistics Canada long-form census, who were linked to the Canadian mortality database and to annual income-tax filings, through 2011. We estimated associations between living within of blue space and deaths from several common causes of death. We adjusted models for many personal and contextual covariates, as well as for exposures to residential greenness and ambient air pollution.

RESULTS

Our cohort included approximately 1.3 million subjects at baseline, 106,180 of whom died from nonaccidental causes during follow-up. We found significant, reduced risks of mortality in the range of 12-17% associated with living within of water in comparison with living farther away, among all causes of death examined, except with external/accidental causes. Protective effects were found to be higher among women and all older adults than among other subjects, and protective effects were found to be highest against deaths from stroke and respiratory-related causes.

CONCLUSIONS

Our findings suggest that living near blue spaces in urban areas has important benefits to health, but further work is needed to better understand the drivers of this association. https://doi.org/10.1289/EHP3397.

Ambient air pollution and the prevalence of rhinoconjunctivitis in adolescents: a worldwide ecological analysis

Whether exposure to outdoor air pollution increases the prevalence of rhinoconjunctivitis in children is unclear. Using data from Phase Three of the International Study of Asthma and Allergies in childhood (ISAAC), we investigated associations of rhinoconjunctivitis prevalence in adolescents with model-based estimates of ozone, and satellite-based estimates of fine (diameter < 2.5 μm) particulate matter (PM_2.5) and nitrogen dioxide (NO₂). Information on rhinoconjunctivitis (defined as self-reported nose symptoms without a cold or flu accompanied by itchy watery eyes in the past 12 months) was available on 505,400 children aged 13-14 years, in 183 centres in 83 countries. Centre-level prevalence estimates were calculated and linked geographically with estimates of long-term average concentrations of NO₂, ozone and PM_2.5. Multi-level models were fitted adjusting for population density, climate, sex and gross national income. Information on parental smoking, truck traffic and cooking fuel was available for a restricted set of centres (77 in 36 countries). Between centres within countries, the estimated change in rhinoconjunctivitis prevalence per 100 children was 0.171 (95% confidence interval: - 0.013, 0.354) per 10% increase in PM_2.5, 0.096 (- 0.003, 0.195) per 10% increase in NO₂ and - 0.186 (- 0.390, 0.018) per 1 ppbV increase in ozone. Between countries, rhinoconjunctivitis prevalence was significantly negatively associated with both ozone and PM_2.5. In the restricted dataset, the latter association became less negative following adjustment for parental smoking and open fires for cooking. In conclusion, there were no significant within-country associations of rhinoconjunctivitis prevalence with study pollutants. Negative between-country associations with PM_2.5 and ozone require further investigation.

Effect modification of perinatal exposure to air pollution and childhood asthma incidence

Perinatal exposure to ambient air pollution has been associated with childhood asthma incidence, however, less is known regarding the potential effect modifiers in this association. We examined whether maternal and infant characteristics modified the association between perinatal exposure to air pollution and development of childhood asthma.761 172 births occurring between 2006 and 2012 were identified in the province of Ontario, Canada. Associations between exposure to ambient air pollutants and childhood asthma incidence (up to age 6) were estimated using Cox regression models.110,981 children with asthma were identified. In models adjusted for postnatal exposures, second trimester exposures to particulate matter with a diameter ≤2.5 μm (PM2.5) (Hazard Ratio (HR) per interquartile (IQR) increase=1.07, 95% CI: 1.06-1.09) and nitrogen dioxide (NO2) (HR per IQR increase=1.06, 95% CI: 1.03-1.08) were associated with childhood asthma development. Enhanced impacts were found among children born to mothers with asthma, those who smoked during pregnancy, boys, those born preterm, of low birth weight and among those born to mothers living in urban areas during pregnancy.Prenatal exposure to air pollution may have a differential impact on the risk of asthma development according to maternal and infant characteristics.

Exposure to ambient air pollution and the incidence of dementia: A population-based cohort study

INTRODUCTION

Emerging studies have implicated air pollution in the neurodegenerative processes. Less is known about the influence of air pollution, especially at the relatively low levels, on developing dementia. We conducted a population-based cohort study in Ontario, Canada, where the concentrations of pollutants are among the lowest in the world, to assess whether air pollution exposure is associated with incident dementia.

METHODS

The study population comprised all Ontario residents who, on 1 April 2001, were 55-85years old, Canadian-born, and free of physician-diagnosed dementia (~2.1 million individuals). Follow-up extended until 2013. We used population-based health administrative databases with a validated algorithm to ascertain incident diagnosis of dementia as well as prevalent cases. Using satellite observations, land-use regression model, and an optimal interpolation method, we derived long-term average exposure to fine particulate matter (≤2.5μm in diameter) (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃), respectively at the subjects' historical residences based on a population-based registry. We used multilevel spatial random-effects Cox proportional hazards models, adjusting for individual and contextual factors, such as diabetes, brain injury, and neighborhood income. We conducted various sensitivity analyses, such as lagging exposure up to 10years and considering a negative control outcome for which no (or weaker) association with air pollution is expected.

RESULTS

We identified 257,816 incident cases of dementia in 2001-2013. We found a positive association between PM_2.5 and dementia incidence, with a hazard ratio (HR) of 1.04 (95% confidence interval (CI): 1.03-1.05) for every interquartile-range increase in exposure to PM_2.5. Similarly, NO₂ was associated with increased incidence of dementia (HR=1.10; 95% CI: 1.08-1.12). No association was found for O₃. These associations were robust to all sensitivity analyses examined. These estimates translate to 6.1% of dementia cases (or 15,813 cases) attributable to PM_2.5 and NO₂, based on the observed distribution of exposure relative to the lowest quartile in concentrations in this cohort.

DISCUSSION

In this large cohort, exposure to air pollution, even at the relative low levels, was associated with higher dementia incidence.

Associations between fine particulate matter and mortality in the 2001 Canadian Census Health and Environment Cohort

BACKGROUND

Large cohort studies have been used to characterise the association between long-term exposure to fine particulate matter (PM_2.5) air pollution with non-accidental, and cause-specific mortality. However, there has been no consensus as to the shape of the association between concentration and response.

METHODS

To examine the shape of this association, we developed a new cohort based on respondents to the 2001 Canadian census long-form. We applied new annual PM_2.5 concentration estimates based on remote sensing and ground measurements for Canada at a 1km spatial scale from 1998 to 2011. We followed 2.4 million respondents who were non-immigrants aged 25-90 years and did not reside in an institution over a 10 year period for mortality. Exposures were assigned as a 3-year mean prior to the follow-up year. Income tax files were used to account for residential mobility among respondents using postal codes, with probabilistic imputation used for missing postal codes in the tax data. We used Cox survival models to determine hazard ratios (HRs) for cause-specific mortality. We also estimated Shape Constrained Health Impact Functions (a concentration-response function) for selected causes of death.

RESULTS

In models stratified by age, sex, airshed, and population centre size, and adjusted for individual and neighbourhood socioeconomic variables, HR estimates for non-accidental mortality were HR = 1.18 (95% CI: 1.15-1.21) per 10μg/m³ increase in concentration. We observed higher HRs for cardiovascular disease (HR=1.25; 95% CI: 1.19-1.31), cardio-metabolic disease (HR = 1.27; 95% CI: 1.21-1.33), ischemic heart disease (HR = 1.36; 95% CI: 1.28-1.44) and chronic obstructive pulmonary disease (COPD) mortality (HR = 1.24; 95% CI: 1.11-1.39) compared to HR for all non-accidental causes of death. For non-accidental, cardio-metabolic, ischemic heart disease, respiratory and COPD mortality, the shape of the concentration-response curve was supra-linear, with larger differences in relative risk for lower concentrations. For both pneumonia and lung cancer, there was some suggestion that the curves were sub-linear.

CONCLUSIONS

Associations between ambient concentrations of fine particulate matter and several causes of death were non-linear for each cause of death examined.

Trends in Chemical Composition of Global and Regional Population-Weighted Fine Particulate Matter Estimated for 25 Years

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem, downscaled to 0.1° × 0.1°) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM_2.5). Trends in observed and simulated population-weighted mean PM_2.5 composition over 1989-2013 are highly consistent for PM_2.5 (-2.4 vs -2.4%/yr), secondary inorganic aerosols (-4.3 vs -4.1%/yr), organic aerosols (OA, -3.6 vs -3.0%/yr) and black carbon (-4.3 vs -3.9%/yr) over North America, as well as for sulfate (-4.7 vs -5.8%/yr) over Europe. Simulated trends over 1998-2013 also have overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM_2.5 for 20 of 21 global regions. Over 1989-2013, most (79%) of the simulated increase in global population-weighted mean PM_2.5 of 0.28 μg m^-3yr^-1 is explained by significantly (p < 0.05) increasing OA (0.10 μg m^-3yr^-1), nitrate (0.05 μg m^-3yr^-1), sulfate (0.04 μg m^-3yr^-1), and ammonium (0.03 μg m^-3yr^-1). These four components predominantly drive trends in population-weighted mean PM_2.5 over populous regions of South Asia (0.94 μg m^-3yr^-1), East Asia (0.66 μg m^-3yr^-1), Western Europe (-0.47 μg m^-3yr^-1), and North America (-0.32 μg m^-3yr^-1). Trends in area-weighted mean and population-weighted mean PM_2.5 composition differ significantly.

Urban greenness and mortality in Canada's largest cities: a national cohort study

BACKGROUND

Findings from published studies suggest that exposure to and interactions with green spaces are associated with improved psychological wellbeing and have cognitive, physiological, and social benefits, but few studies have examined their potential effect on the risk of mortality. We therefore undertook a national study in Canada to examine associations between urban greenness and cause-specific mortality.

METHODS

We used data from a large cohort study (the 2001 Canadian Census Health and Environment Cohort [2001 CanCHEC]), which consisted of approximately 1·3 million adult (aged ≥19 years), non-immigrant, urban Canadians in 30 cities who responded to the mandatory 2001 Statistics Canada long-form census. The cohort has been linked by Statistics Canada to the Canadian mortality database and to annual income tax filings through 2011. We measured greenness with images from the moderate-resolution imaging spectroradiometer from NASA's Aqua satellite. We assigned estimates of exposure to greenness derived from remotely sensed Normalized Difference Vegetation Index (NDVI) within both 250 m and 500 m of participants' residences for each year during 11 years of follow-up (between 2001 and 2011). We used Cox proportional hazards models to estimate associations between residential greenness (as a continuous variable) and mortality. We estimated hazard ratios (HRs) and corresponding 95% CIs per IQR (0·15) increase in NDVI adjusted for personal (eg, education and income) and contextual covariates, including exposures to fine particulate matter, ozone, and nitrogen dioxide. We also considered effect modification by selected personal covariates (age, sex, household income adequacy quintiles, highest level of education, and marital status).

FINDINGS

Our cohort consisted of approximately 1 265 000 individuals at baseline who contributed 11 523 770 person-years. We showed significant decreased risks of mortality in the range of 8-12% from all causes of death examined with increased greenness around participants' residence. In the fully adjusted analyses, the risk was significantly decreased for all causes of death (non-accidental HR 0·915, 95% CI 0·905-0·924; cardiovascular plus diabetes 0·911, 0·895-0·928; cardiovascular 0·911, 0·894-0·928; ischaemic heart disease 0·904, 0·882-0·927; cerebrovascular 0·942, 0·902-0·983; and respiratory 0·899, 0·869-0·930). Greenness associations were more protective among men than women (HR 0·880, 95% CI 0·868-0·893 vs 0·955, 0·941-0·969), and among individuals with higher incomes (highest quintile 0·812, 0·791-0·834 vs lowest quintile 0·991, 0·972-1·011) and more education (degree or more 0·816, 0·791-0·842 vs did not complete high school 0·964, 0·950-0·978).

INTERPRETATION

Increased amounts of residential greenness were associated with reduced risks of dying from several common causes of death among urban Canadians. We identified evidence of inequalities, both in terms of exposures to greenness and mortality risks, by personal socioeconomic status among individuals living in generally similar environments, and with reasonably similar access to health care and other social services. The findings support the development of policies related to creating greener and healthier cities.

FUNDING

None.

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND

The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context.

METHODS

We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined.

FINDINGS

Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to 137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9·3% (6·9-11·6) decline in deaths and a 10·8% (8·3-13·1) decrease in DALYs at the global level, while population ageing accounts for 14·9% (12·7-17·5) of deaths and 6·2% (3·9-8·7) of DALYs, and population growth for 12·4% (10·1-14·9) of deaths and 12·4% (10·1-14·9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9-29·7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks.

INTERPRETATION

Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade.

FUNDING

The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

BACKGROUND

The UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030.

METHODS

We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment.

FINDINGS

Globally, the median health-related SDG index was 56·7 (IQR 31·9-66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6-88·9), Iceland (86·0, 84·1-87·6), and Sweden (85·6, 81·8-87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6-11·9), the Central African Republic (11·0, 8·8-13·8), and Somalia (11·3, 9·5-13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past.

INTERPRETATION

GBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations.

FUNDING

Bill & Melinda Gates Foundation.

Long-term exposure to ambient ultrafine particles and respiratory disease incidence in in Toronto, Canada: a cohort study

BACKGROUND

Little is known about the long-term health effects of ambient ultrafine particles (<0.1 μm) (UFPs) including their association with respiratory disease incidence. In this study, we examined the relationship between long-term exposure to ambient UFPs and the incidence of lung cancer, adult-onset asthma, and chronic obstructive pulmonary disease (COPD).

METHODS

Our study cohort included approximately 1.1 million adults who resided in Toronto, Canada and who were followed for disease incidence between 1996 and 2012. UFP exposures were assigned to residential locations using a land use regression model. Random-effect Cox proportional hazard models were used to estimate hazard ratios (HRs) describing the association between ambient UFPs and respiratory disease incidence adjusting for ambient fine particulate air pollution (PM_2.5), NO₂, and other individual/neighbourhood-level covariates.

RESULTS

In total, 74,543 incident cases of COPD, 87,141 cases of asthma, and 12,908 cases of lung cancer were observed during follow-up period. In single pollutant models, each interquartile increase in ambient UFPs was associated with incident COPD (HR = 1.06, 95% CI: 1.05, 1.09) but not asthma (HR = 1.00, 95% CI: 1.00, 1.01) or lung cancer (HR = 1.00, 95% CI: 0.97, 1.03). Additional adjustment for NO₂ attenuated the association between UFPs and COPD and the HR was no longer elevated (HR = 1.01, 95% CI: 0.98, 1.03). PM_2.5 and NO₂ were each associated with increased incidence of all three outcomes but risk estimates for lung cancer were sensitive to indirect adjustment for smoking and body mass index.

CONCLUSIONS

In general, we did not observe clear evidence of positive associations between long-term exposure to ambient UFPs and respiratory disease incidence independent of other air pollutants. Further replication is required as few studies have evaluated these relationships.

Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

BACKGROUND

Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels.

METHODS

We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure-response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure-response functions spanning the global range of exposure.

FINDINGS

Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000-422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015.

INTERPRETATION

Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction.

FUNDING

Bill & Melinda Gates Foundation and Health Effects Institute.

Comparing the Health Effects of Ambient Particulate Matter Estimated Using Ground-Based versus Remote Sensing Exposure Estimates

BACKGROUND

Remote sensing (RS) is increasingly used for exposure assessment in epidemiological and burden of disease studies, including those investigating whether chronic exposure to ambient fine particulate matter (PM2.5) is associated with mortality.

OBJECTIVES

We compared relative risk estimates of mortality from diseases of the circulatory system for PM2.5 modeled from RS with that for PM2.5 modeled using ground-level information.

METHODS

We geocoded the baseline residence of 668,629 American Cancer Society Cancer Prevention Study II (CPS-II) cohort participants followed from 1982 to 2004 and assigned PM2.5 levels to all participants using seven different exposure models. Most of the exposure models were averaged for the years 2002-2004, and one RS estimate was for a longer, contemporaneous period. We used Cox proportional hazards regression to estimate relative risks (RRs) for the association of PM2.5 with circulatory mortality and ischemic heart disease.

RESULTS

Estimates of mortality risk differed among exposure models. The smallest relative risk was observed for the RS estimates that excluded ground-based monitors for circulatory deaths [RR = 1.02, 95% confidence interval (CI): 1.00, 1.04 per 10 μg/m3 increment in PM2.5]. The largest relative risk was observed for the land-use regression model that included traffic information (RR = 1.14, 95% CI: 1.11, 1.17 per 10 μg/m3 increment in PM2.5).

CONCLUSIONS

We found significant associations between PM2.5 and mortality in every model; however, relative risks estimated from exposure models using ground-based information were generally larger than those estimated using RS alone.

Exposure to fine particulate matter air pollution in Canada

BACKGROUND

Exposure to ambient fine particulate matter (PM2.5) has been associated with a greater risk of non-accidental, cardiovascular and respiratory mortality in Canada. Research based on Canadian cohorts suggests that exposure to PM2.5 varies by demographic and socioeconomic characteristics. Studies of NO₂, another pollutant, indicate that persons of lower socioeconomic status and some visible minority groups have greater exposure in urban centres.

DATA AND METHODS

National residential PM2.5 was estimated from a ~1 km² spatial layer for respondents to the 2006 Census long-form questionnaire. Weighted PM2.5 estimates from personal-level estimates were determined for white, Aboriginal, visible minority and immigrant populations, as well as for socioeconomic groups (household income, educational attainment) and stratified by urban core, urban fringe and rural residence. Descriptive statistics were provided for selected comparisons.

RESULTS

In Canada, PM2.5 exposure was 1.61 μg/m³ higher for visible minority (versus white) populations, and 1.55 μg/m³ higher for immigrants (versus non-immigrants). When the relatively high percentages of these groups in large cities were taken into account, exposure differences in urban cores were much smaller. Exposure among urban immigrants did not decrease substantially with time since immigration (< 0.5 μg/m³ between any two years). In urban cores, residents of low-income households had marginally higher exposure (0.56 μg/m³) than did people who were not in low-income households.

INTERPRETATION

Differences between specific population groups in exposure to PM2.5 are due, at least in part, to higher percentages of these groups living in urban cores where air pollution levels are elevated.

Maternal exposure to ambient air pollution and risk of early childhood cancers: A population-based study in Ontario, Canada

BACKGROUND

There are increasing concerns regarding the role of exposure to ambient air pollution during pregnancy in the development of early childhood cancers.

OBJECTIVE

This population based study examined whether prenatal and early life (<1year of age) exposures to ambient air pollutants, including nitrogen dioxide (NO₂) and particulate matter with aerodynamic diameters ≤2.5μm (PM_2.5), were associated with selected common early childhood cancers in Canada.

METHODS

2,350,898 singleton live births occurring between 1988 and 2012 were identified in the province of Ontario, Canada. We assigned temporally varying satellite-derived estimates of PM_2.5 and land-use regression model estimates of NO₂ to maternal residences during pregnancy. Incident cases of 13 subtypes of pediatric cancers among children up to age 6 until 2013 were ascertained through administrative health data linkages. Associations of trimester-specific, overall pregnancy and first year of life exposures were evaluated using Cox proportional hazards models, adjusting for potential confounders.

RESULTS

A total of 2044 childhood cancers were identified. Exposure to PM_2.5, per interquartile range increase, over the entire pregnancy, and during the first trimester was associated with an increased risk of astrocytoma (hazard ratio (HR) per 3.9μg/m3=1.38 (95% CI: 1.01, 1.88) and, HR per 4.0μg/m³=1.40 (95% CI: 1.05-1.86), respectively). We also found a positive association between first trimester NO₂ and acute lymphoblastic leukemia (ALL) (HR=1.20 (95% CI: 1.02-1.41) per IQR (13.3ppb)).

CONCLUSIONS

In this population-based study in the largest province of Canada, results suggest an association between exposure to ambient air pollution during pregnancy, especially in the first trimester and an increased risk of astrocytoma and ALL. Further studies are required to replicate the findings of this study with adjustment for important individual-level confounders.