Air pollution and mortality in New Zealand: cohort study

Long-term exposure to air pollution on cardio-respiratory, and lung cancer mortality: a systematic review and meta-analysis

Air pollution is a major cause of specific deaths worldwide. This review article aimed to investigate the results of cohort studies for air pollution connected with the all-cause, cardio-respiratory, and lung cancer mortality risk by performing a meta-analysis. Relevant cohort studies were searched in electronic databases (PubMed/Medline, Web of Science, and Scopus). We used a random effect model to estimate the pooled relative risks (RRs) and their 95% CIs (confidence intervals) of mortality. The risk of bias for each included study was also assessed by Office of Health Assessment and Translation (OHAT) checklists. We applied statistical tests for heterogeneity and sensitivity analyses. The registration code of this study in PROSPERO was CRD42023422945. A total of 88 cohort studies were eligible and included in the final analysis. The pooled relative risk (RR) per 10 μg/m3 increase of fine particulate matter (PM2.5) was 1.080 (95% CI 1.068-1.092) for all-cause mortality, 1.058 (95% CI 1.055-1.062) for cardiovascular mortality, 1.066 (95%CI 1.034-1.097) for respiratory mortality and 1.118 (95% CI 1.076-1.159) for lung cancer mortality. We observed positive increased associations between exposure to PM2.5, PM10, black carbon (BC), and nitrogen dioxide (NO2) with all-cause, cardiovascular and respiratory diseases, and lung cancer mortality, but the associations were not significant for nitrogen oxides (NOx), sulfur dioxide (SO2) and ozone (O3). The risk of mortality for males and the elderly was higher compared to females and younger age. The pooled effect estimates derived from cohort studies provide substantial evidence of adverse air pollution associations with all-cause, cardiovascular, respiratory, and lung cancer mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-024-00900-6.

Assessing the Global Impact of Ambient Air Pollution on Cancer Incidence and Mortality: A Comprehensive Meta-Analysis

PURPOSE

This study aims to examine the association between exposure to major ambient air pollutants and the incidence and mortality of lung cancer and some nonlung cancers.

METHODS

This meta-analysis used PubMed and EMBASE databases to access published studies that met the eligibility criteria. Primary analysis investigated the association between exposure to air pollutants and cancer incidence and mortality. Study quality was assessed using the Newcastle Ottawa Scale. Meta-analysis was conducted using R software.

RESULTS

The meta-analysis included 61 studies, of which 53 were cohort studies and eight were case-control studies. Particulate matter 2.5 mm or less in diameter (PM2.5) was the exposure pollutant in half (55.5%), and lung cancer was the most frequently studied cancer in 59% of the studies. A pooled analysis of exposure reported in cohort and case-control studies and cancer incidence demonstrated a significant relationship (relative risk [RR], 1.04 [95% CI, 1.02 to 1.05]; I2, 88.93%; P < .05). A significant association was observed between exposure to pollutants such as PM2.5 (RR, 1.08 [95% CI, 1.04 to 1.12]; I2, 68.52%) and nitrogen dioxide (NO2) (RR, 1.03 [95% CI, 1.01 to 1.05]; I2, 73.52%) and lung cancer incidence. The relationship between exposure to the air pollutants and cancer mortality demonstrated a significant relationship (RR, 1.08 [95% CI, 1.07 to 1.10]; I2, 94.77%; P < .001). Among the four pollutants, PM2.5 (RR, 1.15 [95% CI, 1.08 to 1.22]; I2, 95.33%) and NO2 (RR, 1.05 [95% CI, 1.02 to 1.08]; I2, 89.98%) were associated with lung cancer mortality.

CONCLUSION

The study confirms the association between air pollution exposure and lung cancer incidence and mortality. The meta-analysis results could contribute to community cancer prevention and diagnosis and help inform stakeholders and policymakers in decision making.

Evidence of the adverse effects of air pollution on the population's health in Spain: analysis of the economic costs of premature deaths

Exposure to ambient air pollution increases mortality and morbidity, leading disabilities, and premature deaths. Air pollution has been identified as a leading cause of global disease burden, especially in low- and middle-income countries in 2015 (Global Burden of Diseases, Injuries and Risk Factors Study, 2015). This study explores the relation between mortality rates and particulate matter (PM) concentrations in the 50 Spanish regions for the period 2002-2017. Moreover, we estimated the premature deaths due to PM in Spain according to welfare and production losses in 2017. Random-effects models were developed to evaluate the relation between mortality rates and PM concentrations. The economic cost of premature deaths was assessed using the Willingness to Pay approach to quantify welfare losses and the Human Capital method to estimate production losses. PM10 concentrations are positively related to mortality due to respiratory diseases and stroke. Based on 10,342 premature deaths in 2017, losses in welfare amount to EUR 36,227 million (3.1% of Spanish GDP). The economic value of current and future production losses reached EUR 229 million (0.02% of GDP). From a social perspective, air pollution is a public health concern that greatly impacts health and quality of life. Results highlight the need to implement or strengthen regulatory, fiscal, and health public policies to substantially benefit the population's health by reducing their exposure to air pollution.

Traffic-Related Air Pollution and Risk of Lung, Breast, and Urinary Tract Cancer in Halifax, Nova Scotia

OBJECTIVES

We assessed the association of traffic-related air pollution (TRAP) with the incidence of lung, breast, and urinary tract cancer in Halifax, Nova Scotia.

METHODS

Our case-control study included 2315 cancers and 8501 age-sex-matched controls. Land-use regression was used to estimate TRAP concentrations. Logistic regression was used to assess cancer risk in relation to TRAP, adjusting for community social and material deprivation.

RESULTS

There was no association between the risk of lung, breast, or urinary tract cancer in relation to TRAP. Lung cancer risk was significantly increased in the most deprived communities, whereas breast cancer risk was highest in the least deprived communities.

CONCLUSIONS

In a city characterized by low levels of ambient air pollution, there was no evidence of a linear increased lung, breast, or urinary tract cancer risk in relation to TRAP.

Recent advances in small cell lung cancer: the future is now?

Small cell lung cancer is a relevant clinical issue as it is a highly malignant cancer, often diagnosed in advanced stage. Similarly to non-small cell lung cancer, tobacco smoking is currently the main risk factor. Its incidence, at least in males, has declined over the past decades, due to the worldwide decreased percentage of active smokers. The typical small cells of this tumor type are characterized by a high Proliferation Index, chromosomal deletions such as 3p(14-23) involving the tumor-suppressor gene FHIT, alterations of the MYC or Notch family proteins and the frequent expression of neuroendocrine markers. The combination of thoracic radiotherapy and chemotherapy is the standard treatment for limited stage disease, while platinum-based chemotherapy is the most effective choice for extensive stage disease. Unfortunately, whatever chemotherapy is used, the results are disappointing. No regimen has proved to be effective in the long run, indeed small cell lung cancer rapidly progresses after a frequent initial strong response, and the mortality rate remains still high. The advent of immunotherapy is actually changing the landscape in oncology. As well as in other cancers, recent trials have demonstrated the efficacy of the combination of immune checkpoint inhibitors and chemotherapy, opening new perspectives for the future of our patients.

Association of Household Utility of Cleaner Fuel With Lower Hypertension Prevalence and Blood Pressure in Chinese Adults

Objectives: To investigate whether lower hypertension prevalence or blood pressure was associated with cleaner household fuel usage for cooking and heating among Chinese adults. Methods: We enrolled 44,862 Chinese adults at the baseline of the prospective urban and rural epidemiology (PURE) study in China during 2005-2009, as a subset of the PURE-global China site. Multilevel logistic regression and generalized linear mixed models were conducted to estimate the adjusted odds ratio (AOR) and regression coefficient for hypertension and blood pressure respectively, while subgroup analysis by ambient PM2.5 concentration and location was also examined. Results: Compared with the least clean household solid fuel group, gas (AOR = 0.91, 95% CI: 0.83, 0.99) or electricity (AOR = 0.72, 95% CI: 0.60, 0.87) was associated with significantly lower levels of hypertension prevalence and blood pressure, and a similar pattern of the association was consistently observed among participants with high ambient PM2.5 exposure and those living in urban areas. Conclusion: Household utility of cleaner fuel type was associated with lower hypertension prevalence and blood pressure in Chinese adults. Our study urges the utilization of cleaner household energy to mitigate the burden of hypertension.

Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE): Phase 2

INTRODUCTION

Mortality is associated with long-term exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter; PM2.5), although the magnitude and form of these associations remain poorly understood at lower concentrations. Knowledge gaps include the shape of concentration-response curves and the lowest levels of exposure at which increased risks are evident and the occurrence and extent of associations with specific causes of death. Here, we applied improved estimates of exposure to ambient PM2.5 to national population-based cohorts in Canada, including a stacked cohort of 7.1 million people who responded to census year 1991, 1996, or 2001. The characterization of the shape of the concentration-response relationship for nonaccidental mortality and several specific causes of death at low levels of exposure was the focus of the Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE) Phase 1 report. In the Phase 1 report we reported that associations between outdoor PM2.5 concentrations and nonaccidental mortality were attenuated with the addition of ozone (O3) or a measure of gaseous pollutant oxidant capacity (Ox), which was estimated from O3 and nitrogen dioxide (NO2) concentrations. This was motivated by our interests in understanding both the effects air pollutant mixtures may have on mortality and also the role of O3 as a copollutant that shares common sources and precursor emissions with those of PM2.5. In this Phase 2 report, we further explore the sensitivity of these associations with O3 and Ox, evaluate sensitivity to other factors, such as regional variation, and present ambient PM2.5 concentration-response relationships for specific causes of death.

METHODS

PM2.5 concentrations were estimated at 1 km2 spatial resolution across North America using remote sensing of aerosol optical depth (AOD) combined with chemical transport model (GEOS-Chem) simulations of the AOD:surface PM2.5 mass concentration relationship, land use information, and ground monitoring. These estimates were informed and further refined with collocated measurements of PM2.5 and AOD, including targeted measurements in areas of low PM2.5 concentrations collected at five locations across Canada. Ground measurements of PM2.5 and total suspended particulate matter (TSP) mass concentrations from 1981 to 1999 were used to backcast remote-sensing-based estimates over that same time period, resulting in modeled annual surfaces from 1981 to 2016.

Annual exposures to PM2.5 were then estimated for subjects in several national population-based Canadian cohorts using residential histories derived from annual postal code entries in income tax files. These cohorts included three census-based cohorts: the 1991 Canadian Census Health and Environment Cohort (CanCHEC; 2.5 million respondents), the 1996 CanCHEC (3 million respondents), the 2001 CanCHEC (3 million respondents), and a Stacked CanCHEC where duplicate records of respondents were excluded (Stacked CanCHEC; 7.1 million respondents). The Canadian Community Health Survey (CCHS) mortality cohort (mCCHS), derived from several pooled cycles of the CCHS (540,900 respondents), included additional individual information about health behaviors. Follow-up periods were completed to the end of 2016 for all cohorts. Cox proportional hazard ratios (HRs) were estimated for nonaccidental and other major causes of death using a 10-year moving average exposure and 1-year lag. All models were stratified by age, sex, immigrant status, and where appropriate, census year or survey cycle. Models were further adjusted for income adequacy quintile, visible minority status, Indigenous identity, educational attainment, labor-force status, marital status, occupation, and ecological covariates of community size, airshed, urban form, and four dimensions of the Canadian Marginalization Index (Can-Marg; instability, deprivation, dependency, and ethnic concentration). The mCCHS analyses were also adjusted for individual-level measures of smoking, alcohol consumption, fruit and vegetable consumption, body mass index (BMI), and exercise behavior.

In addition to linear models, the shape of the concentration-response function was investigated using restricted cubic splines (RCS). The number of knots were selected by minimizing the Bayesian Information Criterion (BIC). Two additional models were used to examine the association between nonaccidental mortality and PM2.5. The first is the standard threshold model defined by a transformation of concentration equaling zero if the concentration was less than a specific threshold value and concentration minus the threshold value for concentrations above the threshold. The second additional model was an extension of the Shape Constrained Health Impact Function (SCHIF), the eSCHIF, which converts RCS predictions into functions potentially more suitable for use in health impact assessments. Given the RCS parameter estimates and their covariance matrix, 1,000 realizations of the RCS were simulated at concentrations from the minimum to the maximum concentration, by increments of 0.1 μg/m3. An eSCHIF was then fit to each of these RCS realizations. Thus, 1,000 eSCHIF predictions and uncertainty intervals were determined at each concentration within the total range.

Sensitivity analyses were conducted to examine associations between PM2.5 and mortality when in the presence of, or stratified by tertile of, O3 or Ox. Additionally, associations between PM2.5 and mortality were assessed for sensitivity to lower concentration thresholds, where person-years below a threshold value were assigned the mean exposure within that group. We also examined the sensitivity of the shape of the nonaccidental mortality-PM2.5 association to removal of person-years at or above 12 μg/m3 (the current U.S. National Ambient Air Quality Standard) and 10 μg/m3 (the current Canadian and former [2005] World Health Organization [WHO] guideline, and current WHO Interim Target-4). Finally, differences in the shapes of PM2.5-mortality associations were assessed across broad geographic regions (airsheds) within Canada.

RESULTS

The refined PM2.5 exposure estimates demonstrated improved performance relative to estimates applied previously and in the MAPLE Phase 1 report, with slightly reduced errors, including at lower ranges of concentrations (e.g., for PM2.5 <10 μg/m3).

Positive associations between outdoor PM2.5 concentrations and nonaccidental mortality were consistently observed in all cohorts. In the Stacked CanCHEC analyses (1.3 million deaths), each 10-μg/m3 increase in outdoor PM2.5 concentration corresponded to an HR of 1.084 (95% confidence interval [CI]: 1.073 to 1.096) for nonaccidental mortality. For an interquartile range (IQR) increase in PM2.5 mass concentration of 4.16 μg/m3 and for a mean annual nonaccidental death rate of 92.8 per 10,000 persons (over the 1991-2016 period for cohort participants ages 25-90), this HR corresponds to an additional 31.62 deaths per 100,000 people, which is equivalent to an additional 7,848 deaths per year in Canada, based on the 2016 population. In RCS models, mean HR predictions increased from the minimum concentration of 2.5 μg/m3 to 4.5 μg/m3, flattened from 4.5 μg/m3 to 8.0 μg/m3, then increased for concentrations above 8.0 μg/m3. The threshold model results reflected this pattern with -2 log-likelihood values being equal at 2.5 μg/m3 and 8.0 μg/m3. However, mean threshold model predictions monotonically increased over the concentration range with the lower 95% CI equal to one from 2.5 μg/m3 to 8.0 μg/m3. The RCS model was a superior predictor compared with any of the threshold models, including the linear model.

In the mCCHS cohort analyses inclusion of behavioral covariates did not substantially change the results for both linear and nonlinear models. We examined the sensitivity of the shape of the nonaccidental mortality-PM2.5 association to removal of person-years at or above the current U.S. and Canadian standards of 12 μg/m3 and 10 μg/m3, respectively. In the full cohort and in both restricted cohorts, a steep increase was observed from the minimum concentration of 2.5 μg/m3 to 5 μg/m3. For the full cohort and the <12 μg/m3 cohort the relationship flattened over the 5 to 9 μg/m3 range and then increased above 9 μg/m3. A similar increase was observed for the <10 μg/m3 cohort followed by a clear decline in the magnitude of predictions over the 5 to 9 μg/m3 range and an increase above 9 μg/m3. Together these results suggest that a positive association exists for concentrations >9 μg/m3 with indications of adverse effects on mortality at concentrations as low as 2.5 μg/m3.

Among the other causes of death examined, PM2.5 exposures were consistently associated with an increased hazard of mortality due to ischemic heart disease, respiratory disease, cardiovascular disease, and diabetes across all cohorts. Associations were observed in the Stacked CanCHEC but not in all other cohorts for cerebrovascular disease, pneumonia, and chronic obstructive pulmonary disease (COPD) mortality. No significant associations were observed between mortality and exposure to PM2.5 for heart failure, lung cancer, and kidney failure.

In sensitivity analyses, the addition of O3 and Ox attenuated associations between PM2.5 and mortality. When analyses were stratified by tertiles of copollutants, associations between PM2.5 and mortality were only observed in the highest tertile of O3 or Ox. Across broad regions of Canada, linear HR estimates and the shape of the eSCHIF varied substantially, possibly reflecting underlying differences in air pollutant mixtures not characterized by PM2.5 mass concentrations or the included gaseous pollutants. Sensitivity analyses to assess regional variation in population characteristics and access to healthcare indicated that the observed regional differences in concentration-mortality relationships, specifically the flattening of the concentration-mortality relationship over the 5 to 9 μg/m3 range, was not likely related to variation in the makeup of the cohort or its access to healthcare, lending support to the potential role of spatially varying air pollutant mixtures not sufficiently characterized by PM2.5 mass concentrations.

CONCLUSIONS

In several large, national Canadian cohorts, including a cohort of 7.1 million unique census respondents, associations were observed between exposure to PM2.5 with nonaccidental mortality and several specific causes of death. Associations with nonaccidental mortality were observed using the eSCHIF methodology at concentrations as low as 2.5 μg/m3, and there was no clear evidence in the observed data of a lower threshold, below which PM2.5 was not associated with nonaccidental mortality.

A systematic review on solid fuel combustion exposure and respiratory health in adults in Europe, USA, Canada, Australia and New Zealand

Epidemiological studies performed in low- and middle-income countries have shown a positive association between solid fuel burning exposure and adverse health effects, including respiratory effects in adults. However, the evidence is less clear in other countries. We performed a systematic review of epidemiological studies conducted in Europe, North America (Canada and USA only), Australia and New Zealand on the association between outdoor and indoor exposure to solid fuel (biomass and coal) combustion and respiratory outcomes in adults. We identified 34 articles. The epidemiological evidence is still limited. Positive associations were found between indoor coal, wood and combined solid fuel combustion exposure and lung cancer risk, although based on a limited number of studies. A significant association was found between indoor solid fuel exposure and COPD risk. Inconsistent results were found considering indoor coal, wood and mixed solid fuel burning exposure and other respiratory outcomes (i.e. lower respiratory infections, upper respiratory infections and other upper respiratory tract diseases, asthma and respiratory symptoms). Inconsistent results were found considering the relationship between the exposure to outdoor wood burning exposure and overall respiratory mortality, asthma, COPD and respiratory symptoms in adults. The available epidemiological evidence between outdoor exposure to residential coal burning and respiratory outcomes suggests an increased risk of adverse respiratory effects. The studies considering the impact of the introduction of measures in order to reduce solid fuel burning on air quality and health showed an improvement in air quality resulting in a reduction of adverse respiratory effects. The identified epidemiological studies have several limitations. Additional and better conducted epidemiological studies are needed to establish whether exposure occurring indoors and outdoors to solid fuel combustion pollutants is associated with adverse respiratory outcomes in adults.

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Implementation of Causal Inference Methods

This report provides a final summary of the principal findings and key conclusions of a study supported by an HEI grant aimed at "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution." It is the second and final report on this topic. The study was designed to advance four critical areas of inquiry and methods development. First, it focused on predicting short- and long-term exposures to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at high spatial resolution (1 km × 1 km) for the continental United States over the period 2000-2016 and linking these predictions to health data. Second, it developed new causal inference methods for estimating exposure-response (ER) curves (ERCs) and adjusting for measured confounders. Third, it applied these methods to claims data from Medicare and Medicaid beneficiaries to estimate health effects associated with short- and long-term exposure to low levels of ambient air pollution. Finally, it developed pipelines for reproducible research, including approaches for data sharing, record linkage, and statistical software. Our HEI-funded work has supported an extensive portfolio of analyses and the development of statistical methods that can be used to robustly understand the health effects of short- and long-term exposure to low levels of ambient air pollution. Our Phase 1 report (Dominici et al. 2019) provided a high-level overview of our statistical methods, data analysis, and key findings, grouped into the following five areas: (1) exposure prediction, (2) epidemiological studies of ambient exposures to air pollution at low levels, (3) sensitivity analysis, (4) methodological contributions in causal inference, and (5) an open access research data platform. The current, final report includes a comprehensive overview of the entire research project.

Considering our (1) massive study population, (2) numerous sensitivity analyses, and (3) transparent assessment of covariate balance indicating the quality of causal inference for simulating randomized experiments, we conclude that conditionally on the required assumptions for causal inference, our results collectively indicate that long-term PM2.5 exposure is likely to be causally related to mortality. This conclusion assumes that the causal inference assumptions hold and, more specifically, that we accounted adequately for confounding bias. We explored various modeling approaches, conducted extensive sensitivity analyses, and found that our results were robust across approaches and models. This work relied on publicly available data, and we have provided code that allows for reproducibility of our analyses.

Our work provides comprehensive evidence of associations between exposures to PM2.5, NO2, and O3 and various health outcomes. In the current report, we report more specific results on the causal link between long-term exposure to PM2.5 and mortality, even at PM2.5 levels below or equal to 12 μg/m3, and mortality among Medicare beneficiaries (ages 65 and older). This work relies on newly developed causal inference methods for continuous exposure.

For the period 2000-2016, we found that all statistical approaches led to consistent results: a 10-μg/m3 decrease in PM2.5 led to a statistically significant decrease in mortality rate ranging between 6% and 7% (= 1 - 1/hazard ratio [HR]) (HR estimates 1.06 [95% CI, 1.05 to 1.08] to 1.08 [95% CI, 1.07 to 1.09]). The estimated HRs were larger when studying the cohort of Medicare beneficiaries that were always exposed to PM2.5 levels lower than 12 μg/m3 (1.23 [95% CI, 1.18 to 1.28] to 1.37 [95% CI, 1.34 to 1.40]).

Comparing the results from multiple and single pollutant models, we found that adjusting for the other two pollutants slightly attenuated the causal effects of PM2.5 and slightly elevated the causal effects of NO2 exposure on all-cause mortality. The results for O3 remained almost unchanged.

We found evidence of a harmful causal relationship between mortality and long-term PM2.5 exposures adjusted for NO2 and O3 across the range of annual averages between 2.77 and 17.16 μg/m3 (included >98% of observations) in the entire cohort of Medicare beneficiaries across the continental United States from 2000 to 2016. Our results are consistent with recent epidemiological studies reporting a strong association between long-term exposure to PM2.5 and adverse health outcomes at low exposure levels. Importantly, the curve was almost linear at exposure levels lower than the current national standards, indicating aggravated harmful effects at exposure levels even below these standards.

There is, in general, a harmful causal impact of long-term NO2 exposures to mortality adjusted for PM2.5 and O3 across the range of annual averages between 3.4 and 80 ppb (included >98% of observations). Yet within low levels (annual mean ≤53 ppb) below the current national standards, the causal impacts of NO2 exposures on all-cause mortality are nonlinear with statistical uncertainty.

The ERCs of long-term O3 exposures on all-cause mortality adjusted for PM2.5 and NO2 are almost flat below 45 ppb, which shows no statistically significant effect. Yet we observed an increased hazard when the O3 exposures were higher than 45 ppb, and the HR was approximately 1.10 when comparing Medicare beneficiaries with annual mean O3 exposures of 50 ppb versus those with 30 ppb.

institutions, including those that support the Health Effects Institute; therefore, it may not reflect the views or policies of these parties, and no endorsement by them should be inferred.

A list of abbreviations and other terms appears at the end of this volume.

Long term exposure to air pollution, mortality and morbidity in New Zealand: Cohort study

OBJECTIVES

To investigate associations between long-term exposure to PM_2.5, NO₂, mortality and morbidity in New Zealand, a country with low levels of exposure.

DESIGN

Retrospective cohort study.

SETTING

The New Zealand resident population.

METHOD

The main analyses included all adults aged 30 years and over with complete data on covariates: N = 2,223,507. People who died, or were admitted to hospital, (2013-2016) were linked anonymously to the 2013 census, and to estimates of ambient PM_2.5, and NO₂ concentration. We fitted Poisson regression models of mortality and morbidity in adults (≥30) for all natural causes of death, and by sub- group of major cause. Person-time of exposure, censored at the time of death, was included as an offset. We adjusted for confounding by age, sex, ethnicity, income, education, smoking status and ambient temperature. Further analyses stratified by ethnic group, and investigated respiratory hospital admissions in children.

RESULTS

There were statistically significant positive associations between pollutants and natural causes of death: RR (per 10 μg/m³) for PM_2.5 1.11 (1.07 to 1.15) and for NO₂ 1.10 (1.07 to 1.12). For morbidity, the strongest associations were for PM_2.5 and ischaemic heart disease in adults, RR: 1.29 (1.23 to 1.35) and for NO₂ and asthma in children, RR: 1.18 (1.09 to 1.28). In models restricted to specific ethnic groups, we found no consistent differences in any of the associations.

CONCLUSIONS

The results for NO₂ are higher than those published previously. Other studies have reported that the dose-response for PM_2.5 may be higher at low concentrations, but less is known about NO₂. It is possible NO₂ is acting as a proxy for other traffic-related pollutants that are causally related to health impacts. This study underlines the importance of controlling pollution caused by motor vehicles.

Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM2.5, BC, NO2, and O3: An Analysis of European Cohorts in the ELAPSE Project

INTRODUCTION

Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM2.5, but increasingly associations with nitrogen dioxide (NO2) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO2. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O3). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM2.5, NO2, BC, and O3) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM2,5.

METHODS

We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM2.5, NO2, and O3. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE study (European Study of Cohorts for Air Pollution Effects; Beelen et al. 2014a) and within seven very large European administrative cohorts. By combining well-characterized ESCAPE cohorts and large administrative cohorts in one study the strengths and weaknesses of each approach can be addressed. The large administrative cohorts are more representative of national or citywide populations, have higher statistical power, and can efficiently control for area-level confounders, but have fewer possibilities to control for individual-level confounders. The ESCAPE cohorts have detailed information on individual confounders, as well as country-specific information on area-level confounding. The data from the seven included ESCAPE cohorts and one additional non-ESCAPE cohort have been pooled and analyzed centrally. More than 300,000 adults were included in the pooled cohort from existing cohorts in Sweden, Denmark, Germany, the Netherlands, Austria, France, and Italy. Data from the administrative cohorts have been analyzed locally, without transfer to a central database. Privacy regulations prevented transfer of data from administrative cohorts to a central database. More than 28 million adults were included from national administrative cohorts in Belgium, Denmark, England, the Netherlands, Norway, and Switzerland as well as an administrative cohort in Rome, Italy. We developed central exposure assessment using Europewide hybrid land use regression (LUR) models, which incorporated European routine monitoring data for PM2.5, NO2, and O3, and ESCAPE monitoring data for BC and PM2.5 composition, land use, and traffic data supplemented with satellite observations and chemical transport model estimates. For all pollutants, we assessed exposure at a fine spatial scale, 100 × 100 m grids. These models have been applied to individual addresses of all cohorts including the administrative cohorts. In sensitivity analyses, we applied the PM2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O3 exposures on a larger spatial scale for comparison with previous studies. Identification of outcomes included linkage with mortality, cancer incidence, hospital discharge registries, and physician-based adjudication of cases. We analyzed natural-cause, cardiovascular, ischemic heart disease, stroke, diabetes, cardiometabolic, respiratory, and COPD mortality. We also analyzed lung cancer incidence, incidence of coronary and cerebrovascular events, and incidence of asthma and COPD (pooled cohort only). We applied the Cox proportional hazard model with increasing control for individual- and area-level covariates to analyze the associations between air pollution and mortality and/or morbidity for both the pooled cohort and the individual administrative cohorts. Age was used as the timescale because of evidence that this results in better adjustment for potential confounding by age. Censoring occurred at the time of the event of interest, death from other causes, emigration, loss to follow-up for other reasons, or at the end of follow-up, whichever came first. A priori we specified three confounder models, following the modeling methods of the ESCAPE study. Model 1 included only age (time axis), sex (as strata), and calendar year of enrollment. Model 2 added individual-level variables that were consistently available in the cohorts contributing to the pooled cohort or all variables available in the administrative cohorts, respectively. Model 3 further added area-level socioeconomic status (SES) variables. A priori model 3 was selected as the main model. All analyses in the pooled cohort were stratified by subcohort. All analyses in the administrative cohorts accounted for clustering of the data in neighborhoods by adjusting the variance of the effect estimates. The main exposure variable we analyzed was derived from the Europewide hybrid models based on 2010 monitoring data. Sensitivity analyses were conducted using earlier time periods, time-varying exposure analyses, local exposure models, and the PM2.5 models from the Canadian MAPLE project. We first specified linear single-pollutant models. Two-pollutant models were specified for all combinations of the four main pollutants. Two-pollutant models for particle composition were analyzed with PM2.5 and NO2 as the second pollutant. We then investigated the shape of the concentration-response function using natural splines with two, three, and four degrees of freedom; penalized splines with the degrees of freedom determined by the algorithm and shape-constrained health impact functions (SCHIF) using confounder model 3. Additionally, we specified linear models in subsets of the concentration range, defined by removing concentrations above a certain value from the analysis, such as for PM2.5 25 μg/m3 (EU limit value), 20, 15, 12 μg/m3 (U.S. EPA National Ambient Air Quality Standard), and 10 μg/m3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM2.5, we evaluated 10, 7.5, and 5 μg/m3 as potential thresholds. Performance of threshold models versus the corresponding no-threshold linear model were evaluated using the Akaike information criterion (AIC).

RESULTS

In the pooled cohort, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values (25 μg/m3 and 40 μg/m3, respectively). More than 50,000 had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3). More than 25,000 subjects had a residential PM2.5 exposure below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and diabetes mortality. In our main model, the hazard ratios (HRs) (95% [confidence interval] CI) were 1.13 (CI = 1.11, 1.16) for an increase of 5 μg/m3 PM2.5, 1.09 (CI = 1.07, 1.10) for an increase of 10 μg/m3 NO2, and 1.08 (CI = 1.06, 1.10) for an increase of 0.5 × 10-5/m BC for natural-cause mortality. The highest HRs were found for diabetes mortality. Associations with O3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM2.5, NO2, and BC, we generally observed a supralinear association with steeper slopes at low exposures and no evidence of a concentration below which no association was found. Subset analyses further confirmed that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM2.5 and NO2, the U.S. NAAQS values for PM2.5, and the WHO guidelines for PM2.5 and NO2. The mortality associations were robust to alternative specifications of exposure, including different time periods, PM2.5 from the MAPLE project, and estimates from the local ESCAPE model. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. HRs in two-pollutant models were attenuated but remained elevated and statistically significant for PM2.5 and NO2. In two-pollutant models of PM2.5 and NO2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM2.5 and 1.05 (CI = 1.03, 1.07) for NO2. Associations with O3 were attenuated but remained negative in two-pollutant models with NO2, BC, and PM2.5. We found significant positive associations between PM2.5, NO2, and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO2 was significantly related to acute coronary heart disease and PM2.5 was significantly related to lung cancer incidence. We generally observed linear to supralinear associations with no evidence of a threshold, with the exception of the association between NO2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM2.5 below 20 μg/m3 and possibly 12 μg/m3. Associations remained even when NO2 was below 30 μg/m3 and in some cases 20 μg/m3. In two-pollutant models, NO2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM2.5 was not associated with these outcomes in two-pollutant models with NO2. PM2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3) and more than 1.9 million had residential PM2.5 exposures below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and lung cancer mortality, with moderate to high heterogeneity between cohorts. We found positive but statistically nonsignificant associations with diabetes mortality. In our main model meta-analysis, the HRs (95% CI) for natural-cause mortality were 1.05 (CI = 1.02, 1.09) for an increase of 5 μg/m3 PM2.5, 1.04 (CI = 1.02, 1.07) for an increase of 10 μg/m3 NO2, and 1.04 (CI = 1.02, 1.06) for an increase of 0.5 × 10-5/m BC, and 0.95 (CI = 0.93, 0.98) for an increase of 10 μg/m3 O3. The shape of the concentration-response functions differed between cohorts, though the associations were generally linear to supralinear, with no indication of a level below which no associations were found. Subset analyses documented that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. BC and NO2 remained significantly associated with mortality in two-pollutant models with PM2.5 and O3. The PM2.5 HR attenuated to unity in a two-pollutant model with NO2. The negative O3 association was attenuated to unity and became nonsignificant. The mortality associations were robust to alternative specifications of exposure, including time-varying exposure analyses. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. Effect estimates in the youngest participants (<65 years at baseline) were much larger than in the elderly (>65 years at baseline). Effect estimates obtained with the ELAPSE PM2.5 model did not differ from the MAPLE PM2.5 model on average, but in individual cohorts, substantial differences were found.

CONCLUSIONS

Long-term exposure to PM2.5, NO2, and BC was positively associated with natural-cause and cause-specific mortality in the pooled cohort and the administrative cohorts. Associations were found well below current limit values and guidelines for PM2.5 and NO2. Associations tended to be supralinear, with steeper slopes at low exposures with no indication of a threshold. Two-pollutant models documented the importance of characterizing the ambient mixture with both NO2 and PM2.5. We mostly found negative associations with O3. In two-pollutant models with NO2, the negative associations with O3 were attenuated to essentially unity in the mortality analysis of the administrative cohorts and the incidence analyses in the pooled cohort. In the mortality analysis of the pooled cohort, significant negative associations with O3 remained in two-pollutant models. Long-term exposure to PM2.5, NO2, and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM2.5, NO2, and BC. For acute coronary heart disease, an increased HR was observed for NO2. For lung cancer, an increased HR was found only for PM2.5. Associations mostly showed steeper slopes at low exposures with no indication of a threshold.

Cohort studies of long-term exposure to outdoor particulate matter and risks of cancer: A systematic review and meta-analysis

Robust evidence is needed for the hazardous effects of outdoor particulate matter (PM) on mortality and morbidity from all types of cancers. To summarize and meta-analyze the association between PM and cancer, published articles reporting associations between outdoor PM exposure and any type of cancer with individual outcome assessment that provided a risk estimate in cohort studies were identified via systematic searches. Of 3,256 records, 47 studies covering 13 cancer sites (30 for lung cancer, 12 for breast cancer, 11 for other cancers) were included in the quantitative evaluation. The pooled relative risks (RRs) for lung cancer incidence or mortality associated with every 10-μg/m³ PM_2.5 or PM₁₀ were 1.16 (95% confidence interval [CI], 1.10–1.23; I² = 81%) or 1.22 (95% CI, 1.02–1.45; I² = 96%), respectively. Increased but non-significant risks were found for breast cancer. Other cancers were shown to be associated with PM exposure in some studies but not consistently and thus warrant further investigation.

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Updated evidence for the association between PM and lung cancer risk has been provided

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Associations between PM and cancer risks from 13 sites were summarized

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Further studies should be conducted to fill the research gaps

Fairness in Transport Policy: A New Approach to Applying Distributive Justice Theories

The transport system influences everyone’s wellbeing on a daily basis. These impacts are both positive and negative and are borne directly and indirectly at a range of spatial and temporal scales and across different groups in society. Furthermore, they are often distributed unfairly and the people who are least able to use transport networks frequently bear the greatest costs. People also have various transport needs and these needs change throughout their lives. Due to these complexities, there is no straightforward answer as to how we should provide transport fairly. Policies and actions to decarbonise the transport system are urgently needed, but their equity effects are also important. We give a brief overview of distributive justice and equity in transport literature. We then develop a conceptual framework of distributive justice and a set of four principles to guide the application of the framework to transport policy. We then apply these to recent transport policies in Aotearoa/New Zealand, a country that shares common features with most highly motorised countries. We apply the Capabilities Approach to transport policy in a novel way that conceptualises transport policy as a social conversion factor which influences people’s ability to convert resources and opportunities into the things (‘beings and doings’) that they have reason to value. The consideration of transport policy as a conversion factor, rather than focusing on a specific capability, emphasises the role of transport policy as a promoter of a wide range of capabilities and highlights the inequitable distribution of positive and negative effects on people’s health and wellbeing. It also illuminates issues of power structures and procedural fairness in transport policy that are otherwise not covered by distributive justice approaches. Taking a broader view of distributive justice theory in transport provides a clearer picture of the impacts of transport on wellbeing and provides theory-based guidance on the actions to improve transport justice that can be readily integrated into existing policy institutions.

Long-term exposure to PM and all-cause and cause-specific mortality: A systematic review and meta-analysis

As new scientific evidence on health effects of air pollution is generated, air quality guidelines need to be periodically updated. The objective of this review is to support the derivation of updated guidelines by the World Health Organization (WHO) by performing a systematic review of evidence of associations between long-term exposure to particulate matter with diameter under 2.5 µm (PM_2.5) and particulate matter with diameter under 10 µm (PM₁₀), in relation to all-cause and cause-specific mortality. As there is especially uncertainty about the relationship at the low and high end of the exposure range, the review needed to provide an indication of the shape of the concentration-response function (CRF). We systematically searched MEDLINE and EMBASE from database inception to 9 October 2018. Articles were checked for eligibility by two reviewers. We included cohort and case-control studies on outdoor air pollution in human populations using individual level data. In addition to natural-cause mortality, we evaluated mortality from circulatory diseases (ischemic heart disease (IHD) and cerebrovascular disease (stroke) also specifically), respiratory diseases (Chronic Obstructive Pulmonary Disease (COPD) and acute lower respiratory infection (ALRI) also specifically) and lung cancer. A random-effect meta-analysis was performed when at least three studies were available for a specific exposure-outcome pair. Risk of bias was assessed for all included articles using a specifically developed tool coordinated by WHO. Additional analyses were performed to assess consistency across geographic region, explain heterogeneity and explore the shape of the CRF. An adapted GRADE (Grading of Recommendations Assessment, Development and Evaluation) assessment of the body of evidence was made using a specifically developed tool coordinated by WHO. A large number (N = 107) of predominantly cohort studies (N = 104) were included after screening more than 3000 abstracts. Studies were conducted globally with the majority of studies from North America (N = 62) and Europe (N = 25). More studies used PM_2.5 (N = 71) as the exposure metric than PM₁₀ (N = 42). PM_2.5 was significantly associated with all causes of death evaluated. The combined Risk Ratio (RR) for PM_2.5 and natural-cause mortality was 1.08 (95%CI 1.06, 1.09) per 10 µg/m³. Meta analyses of studies conducted at the low mean PM_2.5 levels (<25, 20, 15, 12, 10 µg/m³) yielded RRs that were similar or higher compared to the overall RR, consistent with the finding of generally linear or supra-linear CRFs in individual studies. Pooled RRs were almost identical for studies conducted in North America, Europe and Western Pacific region. PM₁₀ was significantly associated with natural-cause and most but not all causes of death. Application of the risk of bias tool showed that few studies were at a high risk of bias in any domain. Application of the adapted GRADE tool resulted in an assessment of "high certainty of evidence" for PM_2.5 with all assessed endpoints except for respiratory mortality (moderate). The evidence was rated as less certain for PM₁₀ and cause-specific mortality ("moderate" for circulatory, IHD, COPD and "low" for stroke mortality. Compared to the previous global WHO evaluation, the evidence base has increased substantially. However, studies conducted in low- and middle- income countries (LMICs) are still limited. There is clear evidence that both PM_2.5 and PM₁₀ were associated with increased mortality from all causes, cardiovascular disease, respiratory disease and lung cancer. Associations remained below the current WHO guideline exposure level of 10 µg/m³ for PM_2.5. Systematic review registration number (PROSPERO ID): CRD42018082577.

Particulate air pollution from different sources and mortality in 7.5 million adults - The Dutch Environmental Longitudinal Study (DUELS)

BACKGROUND

Long-term exposure to particulate air pollution has been associated with mortality in urban cohort studies. Few studies have investigated the association between emission contributions from different particle sources and mortality in large-scale population registries, including non-urban populations.

OBJECTIVES

The aim of the study was to evaluate the associations between long-term exposure to particulate air pollution from different source categories and non-accidental mortality in the Netherlands based on existing national databases.

METHODS

We used existing Dutch national databases on mortality, individual characteristics, residence history, neighbourhood characteristics and modelled air pollution concentrations from different sources and air pollution components: particulate matter PM10, primary particulate matter PM10 (PPM10), particulate matter PM2.5, primary particulate matter PM2.5 (PPM2.5), elemental carbon (EC), nitrogen dioxide (NO₂) and secondary inorganic aerosol (SIA) in PM10 (SIA10) or in PM2.5 (SIA2.5). We established a cohort of 7.5 million individuals 30 years or older. We followed the cohort for eight years (2008-2015). We applied Cox proportional hazard regression models adjusting for potential individual and area-specific confounders.

RESULTS

We found statistically significant associations between total and primary particulate matter (PM10 and PM2.5), elemental carbon and mortality. Adjustment for nitrogen dioxide did not change the associations. Secondary inorganic aerosol showed less consistent associations. All primary PM sources were associated with mortality, except agricultural emissions and, depending on the statistical model, industrial PM emissions.

CONCLUSIONS

We could not identify one or more specific source categories of particulate air pollution as main determinants of the mortality effects found in this and in a previous study. This suggests that present policy measures should be focussed on the wider spectrum of air pollution sources instead of on specific sources.

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Phase 1

INTRODUCTION

This report provides a summary of major findings and key conclusions supported by a Health Effects Institute grant aimed at "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Pollution." Our study was designed to advance four critical areas of inquiry and methods development.

METHODS

First, our work focused on predicting short- and long-term exposures to ambient PM2.5 mass (particulate matter ≤ 2.5μm in aerodynamic diameter) and ozone (O3) at high spatial resolution (1 km × 1 km) for the continental United States during the period 2000-2012 and linking these predictions to health data. Second, we developed new causal inference methods for exposure-response (ER) that account for exposure error and adjust for measured confounders. We applied these methods to data from the New England region. Third, we applied standard regression methods using Medicare claims data to estimate health effects that are associated with short- and long-term exposure to low levels of ambient air pollution. We conducted sensitivity analyses to assess potential confounding bias due to lack of extensive information on behavioral risk factors in the Medicare population using the Medicare Current Beneficiary Survey (MCBS) (nationally representative sample of approximately 15,000 Medicare enrollees per year), which includes abundant data on individual-level risk factors including smoking. Finally, we have begun developing tools for reproducible research - including approaches for data sharing, record linkage, and statistical software.

RESULTS

Our HEI-funded work has supported an extensive portfolio of analysis and the development of statistical methods that can be used to robustly understand the health effects of long- and short-term exposure to low levels of ambient air pollution. This report provides a high-level overview of statistical methods, data analysis, and key findings, as grouped into the following four areas: (1) Exposure assessment and data access; (2) Epidemiological studies of ambient exposures to air pollution at low levels; (3) Methodological contributions in causal inference; and (4) Open science research data platform.

CONCLUSION

Our body of work, advanced by HEI, lends extensive evidence that short- and long-term exposure to PM2.5 and O3 is harmful to human health, increasing the risks of hospitalization and death, even at levels that are well below the National Ambient Air Quality Standards (NAAQS).

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

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Source Contributions to Ambient Fine Particulate Matter for Canada

Understanding the sectoral contribution of emissions to fine particulate matter (PM_2.5) offers information for air quality management, and for investigation of association with health outcomes. This study evaluates the contribution of different emission sectors to PM_2.5 in 2013 for Canada using the GEOS-Chem chemical transport model, downscaled with satellite-based PM_2.5. Despite the low population-weighted PM_2.5 concentrations of 5.5 μg m^-3 across Canada, we find that over 70% of population-weighted PM_2.5 originates from Canadian sources followed by 30% from the contiguous United States. The three leading sectoral contributors to population-weighted PM_2.5 over Canada are wildfires with 1.0 μg m^-3 (17%), transportation with 0.96 μg m^-3 (16%), and residential combustion with 0.91 μg m^-3 (15%). The relative contribution to population-weighted PM_2.5 of different sectors varies regionally with residential combustion as the leading contributor in Central Canada (19%), while wildfires dominate over Northern Canada (59%), Atlantic Canada (34%), and Western Canada (18%). The contribution from U.S. sources is larger over Central Canada (33%) than over Western Canada (17%), Atlantic Canada (17%), and Northern Canada (<2%). Sectoral trend analysis showed that the contribution from anthropogenic sources to population-weighted PM_2.5 decreased from 7.1 μg m^-3 to 3.4 μg m^-3 over the past two decades.

A systematic review on global pollution status of particulate matter-associated potential toxic elements and health perspectives in urban environment

Airborne particulate matter (PM) that is a heterogeneous mixture of particles with a variety of chemical components and physical features acts as a potential risk to human health. The ability to pose health risk depends upon the size, concentration and chemical composition of the suspended particles. Potential toxic elements (PTEs) associated with PM have multiple sources of origin, and each source has the ability to generate multiple particulate PTEs. In urban areas, automobile, industrial emissions, construction and demolition activities are the major anthropogenic sources of pollution. Fine particles associated with PTEs have the ability to penetrate deep into respiratory system resulting in an increasing range of adverse health effects, at ever-lower concentrations. In-depth investigation of PTEs content and mode of occurrence in PM is important from both environmental and pathological point of view. Considering this air pollution risk, several studies had addressed the issues related to these pollutants in road and street dust, indicating high pollution level than the air quality guidelines. Observed from the literature, particulate PTEs pollution can lead to respiratory symptoms, cardiovascular problems, lungs cancer, reduced lungs function, asthma and severe case mortality. Due to the important role of PM and associated PTEs, detailed knowledge of their impacts on human health is of key importance.

Estimated Long-Term (1981-2016) Concentrations of Ambient Fine Particulate Matter across North America from Chemical Transport Modeling, Satellite Remote Sensing, and Ground-Based Measurements

Accurate data concerning historical fine particulate matter (PM_2.5) concentrations are needed to assess long-term changes in exposure and associated health risks. We estimated historical PM_2.5 concentrations over North America from 1981 to 2016 for the first time by combining chemical transport modeling, satellite remote sensing, and ground-based measurements. We constrained and evaluated our estimates with direct ground-based PM_2.5 measurements when available and otherwise with historical estimates of PM_2.5 from PM₁₀ measurements or total suspended particle (TSP) measurements. The estimated PM_2.5 concentrations were generally consistent with direct ground-based PM_2.5 measurements over their duration from 1988 onward ( R² = 0.6 to 0.85) and to a lesser extent with PM_2.5 inferred from PM₁₀ measurements from 1985 to 1998 ( R² = 0.5 to 0.6). The collocated comparison of the trends of population-weighted annual average PM_2.5 from our estimates and ground-based measurements was highly consistent (RMSD = 0.66 μg m^-3). The population-weighted annual average PM_2.5 over North America decreased from 22 ± 6.4 μg m^-3 in 1981, to 12 ± 3.2 μg m^-3 in 1998, and to 7.9 ± 2.1 μg m^-3 in 2016, with an overall trend of -0.33 μg m^-3 yr^-1 (95% CI: -0.35, -0.31).

Air pollution and hospital admissions for cardiovascular diseases in Ahvaz, Iran

Cardiovascular disease is one of the main causes of death in Iran. The aim of this study was to determine the relation between air pollution and cardiovascular hospital admissions in Ahwaz, Iran. Daily information about cardiovascular hospital admissions (based on the ICD-10) and data on air pollutants during 2008-2018 were inquired. A quasi-Poisson regression combined with linear distributed lag models; adjusted for trend, seasonality, temperature, relative humidity, weekdays and holidays was used to assess the relation between hospital admission for cardiovascular diseases and the average daily air pollution. The results of this study showed a significant increase in cardiovascular hospital admissions in the total population and women's population in relation to O₃. There was a significant increase in hospital admissions for cardiovascular diseases in the whole population as well as gender and age groups associated with NO₂ and NO. A significant increase was found in hospital admissions for cardiovascular diseases in relation to CO in the 65-74-year-old population. Finally, the results of this study showed that there was a significant increase in hospital admissions for cardiovascular disease associated with SO₂. The main results of the present study confirm the deleterious short term impact of air pollution on cardiovascular morbidity in Ahvaz city. This evidence empasizes the need to implement policies for reducing air pollution.

A general method for evaluating the effects of air pollutants on lung cancer prevalence

It is widely accepted that some air pollutants are related to lung cancer prevalence. An effective method is proposed to quantitatively evaluate the effects of air pollutants and the interactions between them. The method consisted of three parts: data decomposition, comparable data generation and relationship inference. Firstly, very limited monitoring data published by Geographic Information System were applied to calculate the inhalable air pollution of relatively massive patient samples. Then the investigated area was partitioned into a number of districts, and the comparable data containing air pollutant concentrations and lung cancer prevalence in all districts were generated. Finally, the relationships between pollutants and lung cancer prevalence were concluded by an information fusion tool: Choquet integral. As an example, the proposed method was applied in the investigation of air pollution in Tianjin, China. Overall, SO₂, O₃ and PM_2.5 were the top three factors for lung cancer. And there was obvious positive interaction between O₃ and PM_2.5 and negative interaction among SO₂, O₃ and PM₁₀. The effect of SO₂ on men was larger than on women. O₃ and SO₂ were the most important factors for the adenocarcinoma and squamous cell carcinoma, respectively. The effect of SO₂ or NO₂ on squamous cell carcinoma is obviously larger than that on adenocarcinoma, while the effect of O₃ or PM_2.5 on adenocarcinoma is obviously larger than that on squamous cell carcinoma. The results provide important suggestions for management of pollutants and improvement of environmental quality. The proposed method without any parameter is general and easily realized, and it sets the foundation for further researches in other cities/countries. Implications: For total lung cancer prevalence, male and female lung cancer prevalence, and adenocarcinoma and squamous cell carcinoma prevalence, the proposed method not only quantify the effect of single pollutant (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) but also reveals the correlations between different pollutants such as positive interaction or negative interaction. The proposed method without any geographic predictor and parameter is much easier to realize, and it sets the foundation for further research in other cities/countries. The study results provide important suggestions for the targeted management of different pollutants and the improvement of human lung health.

Long-Term Exposure to Air Pollutants and Cancer Mortality: A Meta-Analysis of Cohort Studies

The aim of this study was to examine the relationship between main air pollutants and all cancer mortality by performing a meta-analysis. We searched PubMed, EMBASE (a biomedical and pharmacological bibliographic database of published literature produced by Elsevier), and the reference lists of other reviews until April 2018. A random-effects model was employed to analyze the meta-estimates of each pollutant. A total of 30 cohort studies were included in the final analysis. Overall risk estimates of cancer mortality for 10 µg/m³ per increase of particulate matter (PM)2.5, PM10, and NO₂ were 1.17 (95% confidence interval (CI): 1.11⁻1.24), 1.09 (95% CI: 1.04⁻1.14), and 1.06 (95% CI: 1.02⁻1.10), respectively. With respect to the type of cancer, significant hazardous influences of PM2.5 were noticed for lung cancer mortality and non-lung cancer mortality including liver cancer, colorectal cancer, bladder cancer, and kidney cancer, respectively, while PM10 had harmful effects on mortality from lung cancer, pancreas cancer, and larynx cancer. Our meta-analysis of cohort studies indicates that exposure to the main air pollutants is associated with increased mortality from all cancers.

Outdoor particulate matter (PM10) exposure and lung cancer risk in the EAGLE study

Objective

Cohort studies in Europe, but not in North-America, showed an association between exposure to outdoor particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and lung cancer risk. Only a case-control study on lung cancer and PM₁₀ in South Korea has so far been performed. For the first time in Europe we analyzed quantitatively this association using a case-control study design in highly polluted areas in Italy.

Methods

The Environment And Genetics in Lung cancer Etiology (EAGLE) study, a population-based case-control study performed in the period 2002–2005 in the Lombardy Region, north-west Italy, enrolled 2099 cases and 2120 controls frequency-matched for area of residence, gender, and age. For this study we selected subjects with complete active and passive smoking history living in the same municipality since 1980 until study enrollment. Fine resolution annual PM₁₀ estimates obtained by applying land use regression modeling to satellite data calibrated with fixed site monitor measurements were used. We assigned each subject the PM₁₀ average estimates for year 2000 based on enrollment address. We used logistic regression models to calculate odds ratios (OR) and 95% confidence intervals (CI) adjusted for matching variables, education, smoking, and dietary and occupational variables.

Results

We included 3473 subjects, 1665 cases (1318 men, 347 women) and 1808 controls (1368 men, 440 women), with PM₁₀ individual levels ranging from 2.3 to 53.8 μg/m³ (mean: 46.3). We found increasing lung cancer risk with increasing PM₁₀ category (P-value for trend: 0.04). The OR per 10 μg/m³ was 1.28 (95% CI: 0.95–1.72). The association appeared stronger for squamous cell carcinoma (OR 1.44, 95% CI: 0.90–2.29).

Conclusion

In a population living in highly polluted areas in Italy, our study added suggestive evidence of a positive association between PM₁₀ exposure and lung cancer risk. This study emphasizes the need to strengthen policies to reduce airborne pollution.

Short-term effects of air pollution on respiratory mortality in Ahvaz, Iran

Background: Urban air pollutants may affect respiratory mortality. This study was conducted to investigate this effect in Ahvaz, one of the most polluted cities in the world. Methods: The impact of 7 major air pollutants including O3, PM10, NO2, CO, and SO2 were evaluated on respiratory mortality in different gender and age groups using a quasi-Poisson, second degree polynomial constrained, distributed lag model, with single and cumulative lag structures adjusted by trend, seasonality, temperature, relative humidity, weekdays, and holiday. Data were analyzed using the dlnm package in R x64 3.2.5 software. Significance level was set at less than 0.05. Results: In adjusted models, for each IQR increase of O3 in the total population, the risk ratio (RR) for respiratory deaths in 0 to 14- day lags was, respectively, 1.009 (95% CI:1.001-1.016) and 1.009 (95% CI:1.002-1.017), and it was 1.021 (95% CI: 1.002-1.040) in cumulative 0 to 14- day lags. For PM10, in the total population and in adjusted models after 0 to 14- day lags and in cumulative lags of 0 to 14 for an IQR increase in the mean concentration of PM10, the RR for respiratory deaths increased significantly and was, respectively, 1.027 (95% CI:1.002-1.051), 1.029 (95% CI:1.006-1.052), and 1.065 (95% CI:1.005-1.128). NO2 showed a significant association with respiratory deaths only in the 18 to 60 year- old age group and in 9- day lags (RR= 1.318, 95% CI:1.002-1.733). Finally, the results showed that for an IQR increase in the mean concentration of CO and SO2, the adjusted RR for respiratory deaths in 9- day lags in the total population was, respectively, RR= 1.058 (95% CI:1.008-1.111) and 1.126 (95% CI:1.034-1.220). Conclusion: Air pollution in Ahvaz is probably causing increased respiratory mortality.

Long-term exposure to urban air pollution and lung cancer mortality: A 12-year cohort study in Northern China

Cohort evidence that links long-term exposures to air pollution and mortality comes largely from the United States and European countries. We investigated the relationship between long-term exposures to particulate matter <10μm in diameter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and mortality of lung cancer in Northern China. A cohort of 39,054 participants were followed during 1998-2009. Annual average concentrations for PM10, NO2, and SO2 were determined based on data collected from central monitoring stations. Lung cancer deaths (n=140) were obtained from death certificates, and hazard ratios (HRs) were estimated using Cox proportional hazards models, adjusting for age, gender, BMI, education, marital status, smoking status, passive smoking, occupation, alcohol consumption, etc. Each 10mg/m(3) increase in PM10 concentrations was associated with a 3.4%-6.0% increase in lung cancer mortality in the time-varying exposure model and a 4.0%-13.6% increase in the baseline exposure model. In multi-pollutant models, the magnitude of associations was attenuated, most strongly for PM10. The association was different in men and women, also varying across age categories and different smoking status. Substantial differences exist in the risk estimates for participants based on assignment method for air pollution exposure.

Long-term exposure to fine particulate matter air pollution and the risk of lung cancer among participants of the Canadian National Breast Screening Study

Recently, air pollution has been classified as a carcinogen largely on the evidence of epidemiological studies of lung cancer. However, there have been few prospective studies that have evaluated associations between fine particulate matter (PM2.5 ) and cancer at lower concentrations. We conducted a prospective analysis of 89,234 women enrolled in the Canadian National Breast Screening Study between 1980 and 1985, and for whom residential measures of PM2.5 could be assigned. The cohort was linked to the Canadian Cancer Registry to identify incident lung cancers through 2004. Surface PM2.5 concentrations were estimated using satellite data. Cox proportional hazards models were used to characterize associations between PM2.5 and lung cancer. Hazard ratios (HRs) and 95% confidence intervals (CIs) computed from these models were adjusted for several individual-level characteristics, including smoking. The cohort was composed predominantly of Canadian-born (82%), married (80%) women with a median PM2.5 exposure of 9.1 µg/m(3) . In total, 932 participants developed lung cancer. In fully adjusted models, a 10 µg/m(3) increase in PM2.5 was associated with an elevated risk of lung cancer (HR: 1.34; 95% CI = 1.10, 1.65). The strongest associations were observed with small cell carcinoma (HR: 1.53; 95% CI = 0.93, 2.53) and adenocarcinoma (HR: 1.44; 95% CI = 1.06, 1.97). Stratified analyses suggested increased PM2.5 risks were limited to those who smoked cigarettes. Our findings are consistent with previous epidemiological investigations of long-term exposure to PM2.5 and lung cancer. Importantly, they suggest associations persist at lower concentrations such as those currently found in Canadian cities.

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects’ residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO₂ following two steps: (i) retrospective reconstitution of NO₂ concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs.

A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution

The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models.

Rapid Assessment of Environmental Health Impacts for Policy Support: The Example of Road Transport in New Zealand

An integrated environmental health impact assessment of road transport in New Zealand was carried out, using a rapid assessment. The disease and injury burden was assessed from traffic-related accidents, air pollution, noise and physical (in)activity, and impacts attributed back to modal source. In total, road transport was found to be responsible for 650 deaths in 2012 (2.1% of annual mortality): 308 from traffic accidents, 283 as a result of air pollution, and 59 from noise. Together with morbidity, these represent a total burden of disease of 26,610 disability-adjusted life years (DALYs). An estimated 40 deaths and 1874 DALYs were avoided through active transport. Cars are responsible for about 52% of attributable deaths, but heavy goods vehicles (6% of vehicle kilometres travelled, vkt) accounted for 21% of deaths. Motorcycles (1 per cent of vkt) are implicated in nearly 8% of deaths. Overall, impacts of traffic-related air pollution and noise are low compared to other developed countries, but road accident rates are high. Results highlight the need for policies targeted at road accidents, and especially at heavy goods vehicles and motorcycles, along with more general action to reduce the reliance on private road transport. The study also provides a framework for national indicator development.

Pollutional haze as a potential cause of lung cancer

Along with fast economic growth over the past few decades, the world is faced with cumulatively serious environmental pollution and now is paying increased attention to pollutional haze. In the last few years, multiple epidemiological studies and animal models have provided compelling evidences that inhalation of pollutional haze could be linked to several adverse health effects. Since the respiratory tract is the crucial passageway of entry of pollutional haze, the lung is the main affected organ. Therefore, here, we reviewed some of the important information around long-term exposure to pollutional haze and lung cancer, as well as highlight important roles of pollutional haze in human lung carcinogenesis, providing evidence for pollutional haze acting as another risk factor for lung cancer.

Characterizing the Spatial and Temporal Patterns of Open Burning of Municipal Solid Waste (MSW) in Indian Cities

Open-burning of municipal solid waste (MSW) is a major source of PM emissions in developing world cities, but few studies have characterized this phenomenon at the city and intracity (neighborhood) scale relevant to human health impacts. This paper develops a consistent field method for measuring the spatial frequency of the incidence of MSW-burning and presents results in three neighborhoods of varying socioeconomic status (SES) in Delhi, India, observed in winter and summer over 2 years. Daily MSW-burning incidents ranged from 24 to 130/km2-day during winter and 5-87/km2-day during summer, with the highest intensity in low SES neighborhoods. Distinct seasonal and diurnal patterns are observed. The daily mass of MSW-burned was also estimated at 90-1170 kg/km2-day and 13-1100 kg/km2-day in highest to low SES neighborhoods, in winter and summer, respectively. The scaled-up estimate of total MSW-burned for Delhi city ranged from 190 to 246 tons/day, about 2%-3% of total generated MSW; morning-burning contributed >65% of the total. MSW composition varied systematically across neighborhoods and season. Agra had much higher MSW-burning (39-202 incidents/km2-day; 672-3485 kg/km2-day) in the summer. The field method thus captures differences in MSW-burning across cities, neighborhoods, diurnally and seasonally, important for more fine grained air pollution modeling, and for tracking/monitoring policy effectiveness on-ground.

Long-term effects of elemental composition of particulate matter on inflammatory blood markers in European cohorts

BACKGROUND

Epidemiological studies have associated long-term exposure to ambient particulate matter with increased mortality from cardiovascular and respiratory disorders. Systemic inflammation is a plausible biological mechanism behind this association. However, it is unclear how the chemical composition of PM affects inflammatory responses.

OBJECTIVES

To investigate the association between long-term exposure to elemental components of PM and the inflammatory blood markers high-sensitivity C-reactive protein (hsCRP) and fibrinogen as part of the European ESCAPE and TRANSPHORM multi-center projects.

METHODS

In total, 21,558 hsCRP measurements and 17,428 fibrinogen measurements from cross-sections of five and four cohort studies were available, respectively. Residential long-term concentrations of particulate matter <10μm (PM10) and <2.5μm (PM2.5) in diameter and selected elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, zinc) were estimated based on land-use regression models. Associations between components and inflammatory markers were estimated using linear regression models for each cohort separately. Cohort-specific results were combined using random effects meta-analysis. As a sensitivity analysis the models were additionally adjusted for PM mass.

RESULTS

A 5ng/m(3) increase in PM2.5 copper and a 500ng/m(3) increase in PM10 iron were associated with a 6.3% [0.7; 12.3%] and 3.6% [0.3; 7.1%] increase in hsCRP, respectively. These associations between components and fibrinogen were slightly weaker. A 10ng/m(3) increase in PM2.5 zinc was associated with a 1.2% [0.1; 2.4%] increase in fibrinogen; confidence intervals widened when additionally adjusting for PM2.5.

CONCLUSIONS

Long-term exposure to transition metals within ambient particulate matter, originating from traffic and industry, may be related to chronic systemic inflammation providing a link to long-term health effects of particulate matter.

Air Pollution and Mortality in Seven Million Adults: The Dutch Environmental Longitudinal Study (DUELS)

BACKGROUND

Long-term exposure to air pollution has been associated with mortality in urban cohort studies. Few studies have investigated this association in large-scale population registries, including non-urban populations.

OBJECTIVES

The aim of the study was to evaluate the associations between long-term exposure to air pollution and nonaccidental and cause-specific mortality in the Netherlands based on existing national databases.

METHODS

We used existing Dutch national databases on mortality, individual characteristics, residence history, neighborhood characteristics, and national air pollution maps based on land use regression (LUR) techniques for particulates with an aerodynamic diameter ≤ 10 μm (PM10) and nitrogen dioxide (NO2). Using these databases, we established a cohort of 7.1 million individuals ≥ 30 years of age. We followed the cohort for 7 years (2004-2011). We applied Cox proportional hazard models adjusting for potential individual and area-specific confounders.

RESULTS

After adjustment for individual and area-specific confounders, for each 10-μg/m3 increase, PM10 and NO2 were associated with nonaccidental mortality [hazard ratio (HR) = 1.08; 95% CI: 1.07, 1.09 and HR = 1.03; 95% CI: 1.02, 1.03, respectively], respiratory mortality (HR = 1.13; 95% CI: 1.10, 1.17 and HR = 1.02; 95% CI: 1.01, 1.03, respectively), and lung cancer mortality (HR = 1.26; 95% CI: 1.21, 1.30 and HR = 1.10 95% CI: 1.09, 1.11, respectively). Furthermore, PM10 was associated with circulatory disease mortality (HR = 1.06; 95% CI: 1.04, 1.08), but NO2 was not (HR = 1.00; 95% CI: 0.99, 1.01). PM10 associations were robust to adjustment for NO2; NO2 associations remained for nonaccidental mortality and lung cancer mortality after adjustment for PM10.

CONCLUSIONS

Long-term exposure to PM10 and NO2 was associated with nonaccidental and cause-specific mortality in the Dutch population of ≥ 30 years of age.

Carcinogenicity of ambient air pollution: use of biomarkers, lessons learnt and future directions

The association between ambient air pollution (AAP) exposure and lung cancer risk has been investigated in prospective studies and the results are generally consistent, indicating that long-term exposure to air pollution can cause lung cancer. Biomarkers can enhance research on the health effects of air pollution by improving exposure assessment, increasing the understanding of mechanisms, and enabling the investigation of individual susceptibility. In this review, we assess DNA adducts as biomarkers of exposure to AAP and early biological effect, and DNA methylation as biomarker of early biological change and discuss critical issues arising from their incorporation in AAP health impact evaluations, such as confounding, individual susceptibilities, timing, intensity and duration of exposure, and investigated tissue. DNA adducts and DNA methylation are treated as paradigms. However, the lessons, learned from their use in the examination of AAP carcinogenicity, can be applied to investigations of other biomarkers involved in AAP carcinogenicity.

Ambient particulate matter and lung cancer incidence and mortality: a meta-analysis of prospective studies

BACKGROUND

Chronic exposure to ambient particulate matter (PM) has been suggested to be associated with an increased risk of lung cancer, but the results were inconsistent. We performed a systematic review and meta-analysis of prospective studies to assess the association between exposure to PM and the incidence and mortality of lung cancer in adults.

METHODS

We searched PUBMED and EMBASE databases for prospective cohort studies that evaluated the association between PM2.5 (diameter < 2.5 μm), PM10 (diameter < 10 μm) and lung cancer incidence and mortality. Relative risks (RRs) and 95% confidence interval (CI) were calculated using fixed-effect or random-effects models when appropriate.

RESULTS

We initially identified 1987 citations, and 19 prospective cohort studies were finally included in our meta-analysis. The pooled adjusted RRs for lung cancer mortality were 1.09 (95% CI: 1.06-1.11; I(2) = 18.3%, P = 0.26) for 10 µg/m(3) increase in the concentration of PM2.5 (12 studies), and 1.05 (95% CI: 1.03-1.07; I(2) = 41.9%, P = 0.11) for 10 µg/m(3) increase in the concentration of PM10 (seven studies). The increased risk of lung cancer mortality associated with PM2.5 and PM10 was consistent across most subgroups. PM10 (three studies) and PM2.5 (two studies) were not found to be significantly associated with lung cancer incidence.

CONCLUSIONS

Ambient PM2.5 and PM10 pollutions are prospectively associated with a significantly increased risk of lung cancer mortality. More studies addressing the association between PM and lung cancer incidence are required.

Particulate matter air pollution exposure, distance to road, and incident lung cancer in the nurses' health study cohort

BACKGROUND

A body of literature has suggested an elevated risk of lung cancer associated with particulate matter and traffic-related pollutants.

OBJECTIVE

We examined the relation of lung cancer incidence with long-term residential exposures to ambient particulate matter and residential distance to roadway, as a proxy for traffic-related exposures.

METHODS

For participants in the Nurses' Health Study, a nationwide prospective cohort of women, we estimated 72-month average exposures to PM2.5, PM2.5-10, and PM10 and residential distance to road. Follow-up for incident cases of lung cancer occurred from 1994 through 2010. Cox proportional hazards models were adjusted for potential confounders. Effect modification by smoking status was examined.

RESULTS

During 1,510,027 person-years, 2,155 incident cases of lung cancer were observed among 103,650 participants. In fully adjusted models, a 10-μg/m3 increase in 72-month average PM10 [hazard ratio (HR) = 1.04; 95% CI: 0.95, 1.14], PM2.5 (HR = 1.06; 95% CI: 0.91, 1.25), or PM2.5-10 (HR = 1.05; 95% CI: 0.92, 1.20) was positively associated with lung cancer. When the cohort was restricted to never-smokers and to former smokers who had quit at least 10 years before, the associations appeared to increase and were strongest for PM2.5 (PM10: HR = 1.15; 95% CI: 1.00, 1.32; PM2.5: HR = 1.37; 95% CI: 1.06, 1.77; PM2.5-10: HR = 1.11; 95% CI: 0.90, 1.37). RESULTS were most elevated when restricted to the most prevalent subtype, adenocarcinomas. Risks with roadway proximity were less consistent.

CONCLUSIONS

Our findings support those from other studies indicating increased risk of incident lung cancer associated with ambient PM exposures, especially among never- and long-term former smokers.

Outdoor particulate matter exposure and lung cancer: a systematic review and meta-analysis

BACKGROUND

Particulate matter (PM) in outdoor air pollution was recently designated a Group I carcinogen by the International Agency for Research on Cancer (IARC). This determination was based on the evidence regarding the relationship of PM2.5 and PM10 to lung cancer risk; however, the IARC evaluation did not include a quantitative summary of the evidence.

OBJECTIVE

Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between PM and lung cancer.

METHODS

We conducted meta-analyses of studies examining the relationship of exposure to PM2.5 and PM10 with lung cancer incidence and mortality. In total, 18 studies met our inclusion criteria and provided the information necessary to estimate the change in lung cancer risk per 10-μg/m3 increase in exposure to PM. We used random-effects analyses to allow between-study variability to contribute to meta-estimates.

RESULTS

The meta-relative risk for lung cancer associated with PM2.5 was 1.09 (95% CI: 1.04, 1.14). The meta-relative risk of lung cancer associated with PM10 was similar, but less precise: 1.08 (95% CI: 1.00, 1.17). Estimates were robust to restriction to studies that considered potential confounders, as well as subanalyses by exposure assessment method. Analyses by smoking status showed that lung cancer risk associated with PM2.5 was greatest for former smokers [1.44 (95% CI: 1.04, 1.22)], followed by never-smokers [1.18 (95% CI: 1.00, 1.39)], and then current smokers [1.06 (95% CI: 0.97, 1.15)]. In addition, meta-estimates for adenocarcinoma associated with PM2.5 and PM10 were 1.40 (95% CI: 1.07, 1.83) and 1.29 (95% CI: 1.02, 1.63), respectively.

CONCLUSION

The results of these analyses, and the decision of the IARC Working Group to classify PM and outdoor air pollution as carcinogenic (Group 1), further justify efforts to reduce exposures to air pollutants that can arise from many sources.

Outdoor particulate matter exposure and lung cancer: a systematic review and meta-analysis

BACKGROUND

Particulate matter (PM) in outdoor air pollution was recently designated a Group I carcinogen by the International Agency for Research on Cancer (IARC). This determination was based on the evidence regarding the relationship of PM2.5 and PM10 to lung cancer risk; however, the IARC evaluation did not include a quantitative summary of the evidence.

OBJECTIVE

Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between PM and lung cancer.

METHODS

We conducted meta-analyses of studies examining the relationship of exposure to PM2.5 and PM10 with lung cancer incidence and mortality. In total, 18 studies met our inclusion criteria and provided the information necessary to estimate the change in lung cancer risk per 10-μg/m3 increase in exposure to PM. We used random-effects analyses to allow between-study variability to contribute to meta-estimates.

RESULTS

The meta-relative risk for lung cancer associated with PM2.5 was 1.09 (95% CI: 1.04, 1.14). The meta-relative risk of lung cancer associated with PM10 was similar, but less precise: 1.08 (95% CI: 1.00, 1.17). Estimates were robust to restriction to studies that considered potential confounders, as well as subanalyses by exposure assessment method. Analyses by smoking status showed that lung cancer risk associated with PM2.5 was greatest for former smokers [1.44 (95% CI: 1.04, 1.22)], followed by never-smokers [1.18 (95% CI: 1.00, 1.39)], and then current smokers [1.06 (95% CI: 0.97, 1.15)]. In addition, meta-estimates for adenocarcinoma associated with PM2.5 and PM10 were 1.40 (95% CI: 1.07, 1.83) and 1.29 (95% CI: 1.02, 1.63), respectively.

CONCLUSION

The results of these analyses, and the decision of the IARC Working Group to classify PM and outdoor air pollution as carcinogenic (Group 1), further justify efforts to reduce exposures to air pollutants that can arise from many sources.

Long-term exposure to air pollution and cardiovascular mortality: an analysis of 22 European cohorts

BACKGROUND

Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death.

METHODS

Data from 22 European cohort studies were used. Using a standardized protocol, study area-specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 10 μm to 2.5 μm (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates.

RESULTS

The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87-1.69) per 5 μg/m and for PM10, 1.22 (0.91-1.63) per 10 μg/m.

CONCLUSION

In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.

Inequalities in noncommunicable disease mortality in the ten largest Japanese cities

The burden of noncommunicable diseases and social inequalities in health among urban populations is becoming a common problem around the world. This phenomenon is further compounded by population aging. Japan faces the task of maintaining its high level of population health while dealing with these challenges. This study focused on the ten largest cities in Japan and, using publicly available administrative data, analyzed standardized mortality ratios to examine inequalities in relative mortality levels due to major noncommunicable disease at both city and subcity levels. On average, the ten major cities had excess mortality due to cancer and lower mortality due to heart disease and cerebrovascular disease compared to the country as a whole. Substantial inequalities in relative mortality were observed both between and within cities, especially for heart disease and cerebrovascular disease among men. Inequalities in relative mortality levels within cities appear to be increasing over time even while relative mortality levels are decreasing overall. The widely observed health inequalities signal the need for actions to ensure health equity while addressing the burden of noncommunicable diseases. Increasingly, more countries will have to deal with these challenges of inequity, urbanization, aging, and noncommunicable diseases. Local health governance informed by locally specific data on health determinants and outcomes is essential for developing contextualized interventions to improve health and health equity in major urban areas.

Epidemiology of lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

BACKGROUND

Ever since a lung cancer epidemic emerged in the mid-1900 s, the epidemiology of lung cancer has been intensively investigated to characterize its causes and patterns of occurrence. This report summarizes the key findings of this research.

METHODS

A detailed literature search provided the basis for a narrative review, identifying and summarizing key reports on population patterns and factors that affect lung cancer risk.

RESULTS

Established environmental risk factors for lung cancer include smoking cigarettes and other tobacco products and exposure to secondhand tobacco smoke, occupational lung carcinogens, radiation, and indoor and outdoor air pollution. Cigarette smoking is the predominant cause of lung cancer and the leading worldwide cause of cancer death. Smoking prevalence in developing nations has increased, starting new lung cancer epidemics in these nations. A positive family history and acquired lung disease are examples of host factors that are clinically useful risk indicators. Risk prediction models based on lung cancer risk factors have been developed, but further refinement is needed to provide clinically useful risk stratification. Promising biomarkers of lung cancer risk and early detection have been identified, but none are ready for broad clinical application.

CONCLUSIONS

Almost all lung cancer deaths are caused by cigarette smoking, underscoring the need for ongoing efforts at tobacco control throughout the world. Further research is needed into the reasons underlying lung cancer disparities, the causes of lung cancer in never smokers, the potential role of HIV in lung carcinogenesis, and the development of biomarkers.

The impact of atmospheric particulate matter on cancer incidence and mortality in the city of São Paulo, Brazil

This study aimed to verify the impact of inhalable particulate matter (PM(10)) on cancer incidence and mortality in the city of São Paulo, Brazil. Statistical techniques were used to investigate the relationship between PM(10) on cancer incidence and mortality in selected districts. For some types of cancer (skin, lung, thyroid, larynx, and bladder) and some periods, the correlation coefficients ranged from 0.60 to 0.80 for incidence. Lung cancer mortality showed more correlations during the overall period. Spatial analysis showed that districts distant from the city center showed higher than expected relative risk, depending on the type of cancer. According to the study, urban PM(10) can contribute to increased incidence of some cancers and may also contribute to increased cancer mortality. The results highlight the need to adopt measures to reduce atmospheric PM(10) levels and the importance of their continuous monitoring.

Mortality associations with long-term exposure to outdoor air pollution in a national English cohort

RATIONALE

Cohort evidence linking long-term exposure to outdoor particulate air pollution and mortality has come largely from the United States. There is relatively little evidence from nationally representative cohorts in other countries.

OBJECTIVES

To investigate the relationship between long-term exposure to a range of pollutants and causes of death in a national English cohort.

METHODS

A total of 835,607 patients aged 40-89 years registered with 205 general practices were followed from 2003-2007. Annual average concentrations in 2002 for particulate matter with a median aerodynamic diameter less than 10 (PM(10)) and less than 2.5 μm (PM(2.5)), nitrogen dioxide (NO(2)), ozone, and sulfur dioxide (SO(2)) at 1 km(2) resolution, estimated from emission-based models, were linked to residential postcode. Deaths (n = 83,103) were ascertained from linkage to death certificates, and hazard ratios (HRs) for all- and cause-specific mortality for pollutants were estimated for interquartile pollutant changes from Cox models adjusting for age, sex, smoking, body mass index, and area-level socioeconomic status markers.

MEASUREMENTS AND MAIN RESULTS

Residential concentrations of all pollutants except ozone were positively associated with all-cause mortality (HR, 1.02, 1.03, and 1.04 for PM(2.5), NO(2), and SO(2), respectively). Associations for PM(2.5), NO(2), and SO(2) were larger for respiratory deaths (HR, 1.09 each) and lung cancer (HR, 1.02, 1.06, and 1.05) but nearer unity for cardiovascular deaths (1.00, 1.00, and 1.04).

CONCLUSIONS

These results strengthen the evidence linking long-term ambient air pollution exposure to increased all-cause mortality. However, the stronger associations with respiratory mortality are not consistent with most US studies in which associations with cardiovascular causes of death tend to predominate.