Particulate air pollution standards and morbidity and mortality: case study

Urban Air Quality Assessment by Fusing Spatial and Temporal Data from Multiple Study Sources Using Refined Estimation Methods

In urban environmental management and public health evaluation efforts, there is an urgent need for fine-grained urban air quality monitoring. However, the high price and sparse distribution of air quality monitoring equipment make it difficult to develop effective and comprehensive fine-scale monitoring at the city scale. This has also led to air quality estimation methods based on incomplete monitoring data, which lack the ability to detect urban air quality differences within a neighborhood. To address this problem, this study proposes a refined urban air quality estimation method that fuses multisource spatio-temporal data. Based on the fact that urban air quality is easily affected by social activities, this method integrates meteorological data with urban social activity data to form a comprehensive environmental data set. It uses the spatio-temporal feature extraction model to extract the multi-source spatio-temporal features of the comprehensive environmental data set. Finally, the improved cascade forest algorithm is used to fit the relationship between the multisource spatio-temporal features and the air quality index (AQI) to construct an air quality estimation model, and the model is used to estimate the hourly PM2.5 index in Beijing on a 1 km × 1 km grid. The results show that the estimation model has excellent performance, and its goodness-of-fit (R2) and root mean square error (RMSE) reach 0.961 and 17.47, respectively. This method effectively achieves the assessment of urban air quality differences within a neighborhood and provides a new strategy for preventing information fragmentation and improving the effectiveness of information representation in the data fusion process.

Best Practices for Gauging Evidence of Causality in Air Pollution Epidemiology

The contentious political climate surrounding air pollution regulations has brought some researchers and policy-makers to argue that evidence of causality is necessary before implementing more stringent regulations. Recently, investigators in an increasing number of air pollution studies have purported to have used "causal analysis," generating the impression that studies not explicitly labeled as such are merely "associational" and therefore less rigorous. Using 3 prominent air pollution studies as examples, we review good practices for how to critically evaluate the extent to which an air pollution study provides evidence of causality. We argue that evidence of causality should be gauged by a critical evaluation of design decisions such as 1) what actions or exposure levels are being compared, 2) whether an adequate comparison group was constructed, and 3) how closely these design decisions approximate an idealized randomized study. We argue that air pollution studies that are more scientifically rigorous in terms of the decisions made to approximate a randomized experiment are more likely to provide evidence of causality and should be prioritized among the body of evidence for regulatory review accordingly. Our considerations, although presented in the context of air pollution epidemiology, can be broadly applied to other fields of epidemiology.

Impact of air quality guidelines on COPD sufferers

Background

COPD is one of the leading causes of morbidity and mortality in both high- and low-income countries and a major public health burden worldwide. While cigarette smoking remains the main cause of COPD, outdoor and indoor air pollution are important risk factors to its etiology. Although studies over the last 30 years helped reduce the values, it is not very clear if the current air quality guidelines are adequately protective for COPD sufferers.

Objective

This systematic review was to summarize the up-to-date literature on the impact of air pollution on the COPD sufferers.

Methods

PubMed and Google Scholar were utilized to search for articles related to our study’s focus. Search terms included “COPD exacerbation”, “air pollution”, “air quality guidelines”, “air quality standards”, “COPD morbidity and mortality”, “chronic bronchitis”, and “air pollution control” separately and in combination. We focused on articles from 1990 to 2015. We also used articles prior to 1990 if they contained relevant information. We focused on articles written in English or with an English abstract. We also used the articles in the reference lists of the identified articles.

Results

Both short-term and long-term exposures to outdoor air pollution around the world are associated with the mortality and morbidity of COPD sufferers even at levels below the current air quality guidelines. Biomass cooking in low-income countries was clearly associated with COPD morbidity in adult nonsmoking females.

Conclusion

There is a need to continue to improve the air quality guidelines. A range of intervention measures could be selected at different levels based on countries’ socioeconomic conditions to reduce the air pollution exposure and COPD burden.

Estudos de séries temporais de poluição atmosférica por queimadas e saúde humana

Queimadas e incêndios florestais de grandes proporções têm sido observados em diversas regiões do planeta. A exposição a altos níveis de poluentes atmosféricos emitidos por queimadas podem causar uma variedade de danos à saúde humana. Neste artigo, sumarizamos a literatura existente sobre estimação de efeitos agudos da poluição atmosférica por queimadas na saúde humana nas regiões em que estas estão concentradas em maior número no planeta, utilizando-se abordagem de séries temporais. Também se buscou identificar lacunas de conhecimento. O estudo consistiu de uma revisão narrativa, em que as características dos estudos selecionados foram agrupadas pelas regiões do planeta em que há maior incidência de queimadas: Amazônia, Estados Unidos, Austrália e Ásia. Os resultados apontaram concentração de estudos na Austrália, poucos estudos realizados na Amazônia e grande heterogeneidade nos resultados sobre efeitos significativos na saúde humana.

Differential exposure to hazardous air pollution in the United States: a multilevel analysis of urbanization and neighborhood socioeconomic deprivation

Population exposure to multiple chemicals in air presents significant challenges for environmental public health. Air quality regulations distinguish criteria air pollutants (CAPs) (e.g., ozone, PM2.5) from hazardous air pollutants (HAPs)—187 chemicals which include carcinogens and others that are associated with respiratory, cardiovascular, neurological and numerous other non-cancer health effects. Evidence of the public’s cumulative exposure and the health effects of HAPs are quite limited. A multilevel model is used to assess differential exposure to HAP respiratory, neurological, and cancer hazards (2005) related to the Townsend Index of Socioeconomic Deprivation (TSI), after adjustment for regional population size and economic activity, and local population density. We found significant positive associations between tract TSI and respiratory and cancer HAP exposure hazards, and smaller effects for neurological HAPs. Tracts in the top quintile of TSI have between 38%–60% higher HAP exposure than the bottom quintile; increasing population size from the bottom quintile to the top quintile modifies HAP exposure hazard related to TSI, increasing cancer HAP exposure hazard by 6% to 20% and increasing respiratory HAP exposure hazard by 12% to 27%. This study demonstrates the value of social epidemiological methods for analyzing differential exposure and advancing cumulative risk assessment.

An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio-Temporal Information

There is substantial observational evidence that long-term exposure to particulate air pollution is associated with premature death in urban populations. Estimates of the magnitude of these effects derive largely from cross-sectional comparisons of adjusted mortality rates among cities with varying pollution levels. Such estimates are potentially confounded by other differences among the populations correlated with air pollution, for example, socioeconomic factors. An alternative approach is to study covariation of particulate matter and mortality across time within a city, as has been done in investigations of short-term exposures. In either event, observational studies like these are subject to confounding by unmeasured variables. Therefore the ability to detect such confounding and to derive estimates less affected by confounding are a high priority. In this article, we describe and apply a method of decomposing the exposure variable into components with variation at distinct temporal, spatial, and time by space scales, here focusing on the components involving time. Starting from a proportional hazard model, we derive a Poisson regression model and estimate two regression coefficients: the "global" coefficient that measures the association between national trends in pollution and mortality; and the "local" coefficient, derived from space by time variation, that measures the association between location-specific trends in pollution and mortality adjusted by the national trends. Absent unmeasured confounders and given valid model assumptions, the scale-specific coefficients should be similar; substantial differences in these coefficients constitute a basis for questioning the model. We derive a backfitting algorithm to fit our model to very large spatio-temporal datasets. We apply our methods to the Medicare Cohort Air Pollution Study (MCAPS), which includes individual-level information on time of death and age on a population of 18.2 million for the period 2000-2006. Results based on the global coefficient indicate a large increase in the national life expectancy for reductions in the yearly national average of PM2.5. However, this coefficient based on national trends in PM2.5 and mortality is likely to be confounded by other variables trending on the national level. Confounding of the local coefficient by unmeasured factors is less likely, although it cannot be ruled out. Based on the local coefficient alone, we are not able to demonstrate any change in life expectancy for a reduction in PM2.5. We use additional survey data available for a subset of the data to investigate sensitivity of results to the inclusion of additional covariates, but both coefficients remain largely unchanged.

Improving the linkages between air pollution epidemiology and quantitative risk assessment

BACKGROUND

Air pollution epidemiology plays an integral role in both identifying the hazards of air pollution as well as supplying the risk coefficients that are used in quantitative risk assessments. Evidence from both epidemiology and risk assessments has historically supported critical environmental policy decisions. The extent to which risk assessors can properly specify a quantitative risk assessment and characterize key sources of uncertainty depends in part on the availability, and clarity, of data and assumptions in the epidemiological studies.

OBJECTIVES

We discuss the interests shared by air pollution epidemiology and risk assessment communities in ensuring that the findings of epidemiological studies are appropriately characterized and applied correctly in risk assessments. We highlight the key input parameters for risk assessments and consider how modest changes in the characterization of these data might enable more accurate risk assessments that better represent the findings of epidemiological studies.

DISCUSSION

We argue that more complete information regarding the methodological choices and input data used in epidemiological studies would support more accurate risk assessments-to the benefit of both disciplines. In particular, we suggest including additional details regarding air quality, demographic, and health data, as well as certain types of data-rich graphics.

CONCLUSIONS

Relatively modest changes to the data reported in epidemiological studies will improve the quality of risk assessments and help prevent the misinterpretation and mischaracterization of the results of epidemiological studies. Such changes may also benefit epidemiologists undertaking meta-analyses. We suggest workshops as a way to improve the dialogue between the two communities.

Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error

In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 μm. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.

Targeting the components most responsible for airborne particulate matter health risks

Exposure to ambient air particulate matter (PM) causes more mortality and morbidity than any other regulated environmental pollutant, but PM is ill defined (US Environmental Protection Agency, 2004). Although regulations to protect people from PM have progressively improved, the ultimate goal is to identify the components most responsible for adverse effects so regulations can be more targeted.

Health effects of particulate air pollution

In the 1980's it was generally felt that particulate air pollution concentrations in the United States were not a hazard to the public health. However, in the early 1990's the application of econometric time-series studies and prospective cohort studies suggested increased mortality associated with acute (daily) and chronic (decades) exposures to particulate air pollution commonly observed in the developed world. The epidemiologic evidence was not supported by evidence of causal associations from other disciplines. Nevertheless, the EPA moved to tighten controls on fine particulate air pollution. The debate over the science was played out in public hearings and the courts. The experience provides lessons on the use of epidemiologic data in setting public policy.

Fine Particulate Air Pollution and Total Mortality Among Elderly Californians, 1973–2002

Fine particulate air pollution has been associated with increases in long-term mortality in selected cohort studies, and this association has been influential in the establishment of air quality regulations for fine particles (PM(2.5)). However, this epidemiologic evidence has been questioned because of methodological issues, conflicting findings, and lack of an accepted causal mechanism. To further evaluate this association, the long-term relation between fine particulate air pollution and total mortality was examined in a cohort of 49, 975 elderly Californians, with a mean age of 65 yr as of 1973. These subjects, who resided in 25 California counties, were enrolled in 1959, recontacted in 1972, and followed from 1973 through 2002; 39, 846 deaths were identified. Proportional hazards regression models were used to determine their relative risk of death (RR) and 95% confidence interval (CI) during 1973-2002 by county of residence. The models adjusted for age, sex, cigarette smoking, race, education, marital status, body mass index, occupational exposure, exercise, and a dietary factor. For the 35, 789 subjects residing in 11 of these counties, county-wide exposure to fine particles was estimated from outdoor ambient concentrations measured during 1979-1983 and RRs were calculated as a function of these PM(2.5) levels (mean of 23.4 microg/m(3)). For the initial period, 1973-1982, a small positive risk was found: RR was 1.04 (1.01-1.07) for a 10-microg/m(3) increase in PM(2.5). For the subsequent period, 1983-2002, this risk was no longer present: RR was 1.00 (0.98-1.02). For the entire follow-up period, RR was 1.01 (0.99-1.03). The RRs varied somewhat among major subgroups defined by sex, age, education level, smoking status, and health status. None of the subgroups that had significantly elevated RRs during 1973-1982 had significantly elevated RRs during 1983-2002. The RRs showed no substantial variation by county of residence during any of the three follow-up periods. Subjects in the two counties with the highest PM(2.5) levels (mean of 36.1 microg/m(3)) had no greater risk of death than those in the two counties with the lowest PM(2.5) levels (mean of 13.1 microg/m(3)). These epidemiologic results do not support a current relationship between fine particulate pollution and total mortality in elderly Californians, but they do not rule out a small effect, particularly before 1983.

Ambient air pollution and population health: overview

In November 2003 approximately 200 researchers, stakeholders, and policymakers from more than 40 countries gathered to discuss the science and policy implications of air pollution and human health as part of the AIRNET/NERAM Strategies for Clean Air and Health initiative. The purpose of this paper is to review the more than 35 research posters presented at the conference, including exposure, toxicological, and epidemiological studies of air pollution. Collectively, these papers support previous evidence that both short- and long-term exposures to particulate air pollution have adverse population health impacts, including effects on children. Cellular studies also suggest that air pollution can cause mutagenic and oxidative effects, raising concerns about carcinogenicity and cellular regeneration. Studies of biomarkers, such as Clara-cell proteins and lymphocyte damage assessment, provide further evidence of air pollution effects at the cellular level. Other studies have focused on improvements to measurement and sources of air pollution. These studies suggest that particle mass rather than particle composition may be a more useful indicator of potential human health risk. It is well known that emissions from transportation sources are a major contributor to ambient air pollution in large urban centres. Epidemiologic researchers are able to reduce bias due to misclassification and improve exposure assessment models by allocating air pollution exposure according to distance from traffic sources or land-use patterns. The close association between traffic patterns and air pollution concentrations provides a potential basis for the development of transport policies and regulations with population health improvements as a primary objective. The results of the research presented here present opportunities and challenges for the development of policies for improvements to air quality and human health. However, there remains the challenge of how best to achieve these reductions.

Health effects associated with exposure to ambient air pollution

The World Health Organization has identified ambient air pollution as a high public health priority, based on estimates of air pollution related death and disability-adjusted life years derived in its Global Burden of Disease initiative. The NERAM Colloquium Series on Health and Air Quality was initiated to strengthen the linkage between scientists, policymakers, and other stakeholders by reviewing the current state of science, identifying policy-relevant gaps and uncertainties in the scientific evidence, and proposing a path forward for research and policy to improve air quality and public health. The objective of this paper is to review the current state of science addressing the impacts of air pollution on human health. The paper is one of four background papers prepared for the 2003 NERAM/AirNet Conference on Strategies for Clean Air and Health, the third meeting in the international Colloquium Series. The review is based on the framework and findings of the U.S. National Research Committee (NRC) on Research Priorities for Airborne Particulate Matter and addresses key questions underlying air quality risk management policy decisions.

Reanalysis of the Harvard Six Cities Study, part I: validation and replication

Because the results of the Harvard Six Cities Study played a critical role in the establishment of the current U.S. ambient air quality objective for fine particles (PM(2.5)), the U.S. Environmental Protection Agency, industry, and nongovernmental organizations called for an independent reanalysis of this study to validate the original findings reported by Dockery and colleagues in the New England Journal of Medicine (vol. 329, pp. 1753-1759) in 1993. Validation of the original findings was accomplished by a detailed statistical audit and replication of original results. With the exception of occupational exposure to dust (14 discrepancies of 249 questionnaires located for evaluation) and fumes (15/249), date of death (2/250), and cause of death (2/250), the audit identified no discrepancies between the original questionnaires and death certificates in the audit sample and the analytic file used by the original investigators. The data quality audit identified a computer programming problem that had resulted in early censorship in 5 of the 6 cities, which resulted in the loss of approximately 1% of the reported person-years of follow-up; the reanalysis team updated the Six Cities cohort to include the missing person-years of observation, resulting in the addition of 928 person-years of observation and 14 deaths. The reanalysis team was able to reproduce virtually all of the original numerical results, including the 26% increase in all-cause mortality in the most polluted city (Stubenville, OH) as compared to the least polluted city (Portage, WI). The audit and validation of the Harvard Six Cities Study conducted by the reanalysis team generally confirmed the quality of the data and the numerical results reported by the original investigators. The discrepancies noted during the audit were not of epidemiologic importance, and did not substantively alter the original risk estimates associated with particulate air pollution, nor the main conclusions reached by the original investigators.

Reanalysis of the Harvard Six Cities Study, part II: sensitivity analysis

Following the validation and replication of the Harvard Six Cities Study (Krewski et al., this issue), we conducted a wide range of sensitivity analyses to explore the observed associations between long-term exposure to fine particle or sulfate air pollution and mortality. We examined the impact of alternative risk models on estimates of risk, taking into account covariates not included in the original analyses. These risk models provided a basis for identifying covariates that may confound or modify the association between fine particle or sulfate air pollution and mortality, and for identifying sensitive population subgroups. The possibility of confounding due to occupational exposures was also investigated. Residence histories were coded for the study subjects and were used to examine temporal patterns of exposure and risk. Our sensitivity analyses showed the mortality risk estimates for fine particle and sulfate air pollution to be highly robust against alternative risk models of the Cox proportional hazards family, including models with additional covariates from the original questionnaires not included in the original published analyses. There was limited evidence of departures from the proportional hazards assumption. Flexible exposure-response models provided some evidence of departures from linearity at both low and high sulfate concentrations. Incorporating information on changes over time in cigarette smoking and body mass index had little effect on the association between fine particles and mortality. There was limited evidence of variation in risk with attained age, gender, smoking status, occupational exposure to dust and fumes, marital status, heart or lung diseases, or lung function. However, air pollution risk did appear to decreasing with increasing educational attainment. Extensive adjustment for occupation using aggregate indices of occupational "dirtiness" and occupational exposure to known lung carcinogens had little impact on the mortality risks associated with particulate air pollution. Our evaluation of population mobility indicated that relatively few subjects moved from their original city of residence. Attempts to identify critical exposure time windows were limited by the lack of marked interindividual variation in temporal exposure patterns throughout the study period. Overall, this extensive sensitivity analysis both supported the conclusions reached by the original investigators and demonstrated the robustness of these conclusions to alternative analytic approaches.

Mortality and long-term exposure to ambient air pollution: ongoing analyses based on the American Cancer Society cohort

This article provides an overview of previous analysis and reanalysis of the American Cancer Society (ACS) cohort, along with an indication of current ongoing analyses of the cohort with additional follow-up information through to 2000. Results of the first analysis conducted by Pope et al. (1995) showed that higher average sulfate levels were associated with increased mortality, particularly from cardiopulmonary disease. A reanalysis of the ACS cohort, undertaken by Krewski et al. (2000), found the original risk estimates for fine-particle and sulfate air pollution to be highly robust against alternative statistical techniques and spatial modeling approaches. A detailed investigation of covariate effects found a significant modifying effect of education with risk of mortality associated with fine particles declining with increasing educational attainment. Pope et al. (2002) subsequently reported results of a subsequent study using an additional 10 yr of follow-up of the ACS cohort. This updated analysis included gaseous copollutant and new fine-particle measurements, more comprehensive information on occupational exposures, dietary variables, and the most recent developments in statistical modeling integrating random effects and nonparametric spatial smoothing into the Cox proportional hazards model. Robust associations between ambient fine particulate air pollution and elevated risks of cardiopulmonary and lung cancer mortality were clearly evident, providing the strongest evidence to date that long-term exposure to fine particles is an important health risk. Current ongoing analysis using the extended follow-up information will explore the role of ecologic, economic, and, demographic covariates in the particulate air pollution and mortality association. This analysis will also provide insight into the role of spatial autocorrelation at multiple geographic scales, and whether critical instances in time of exposure to fine particles influence the risk of mortality from cardiopulmonary and lung cancer. Information on the influence of covariates at multiple scales and of critical exposure time windows can assist policymakers in establishing timelines for regulatory interventions that maximize population health benefits.

Clearing the air and breathing freely: the health politics of air pollution and asthma

This study examines the growing debate around environmental causes of asthma in the context of federal regulatory disputes, scientific controversy, and environmental justice activism. A multifaceted form of social discovery of the effect of air pollution on asthma has resulted from multipartner and multiorganizational approaches and from intersectoral policy that deals with social inequality and environmental justice. Scientists, activists, health voluntary organizations, and some government agencies and officials have identified various elements of the asthma and air pollution connection. To tackle these issues, they have worked through a variety of collaborations and across different sectors of environmental regulation, public health, health services, housing, transportation, and community development. The authors examine the role of activist groups in discovering the increased rates of asthma and framing it as a social and environmental issue; give an overview of the current knowledge base on air pollution and asthma, and the controversies within science; and situate that science in the regulatory debate, discussing the many challenges to the air quality researchers. They then examine the implications of the scientific and regulatory controversies over linking air pollution to increases in asthma. The article concludes with a discussion of how alliances between activists and scientists lead to new research strategies and innovations.

Time-series studies of particulate matter

Studies of air pollution and human health have evolved from descriptive studies of the early phenomena of large increases in adverse health effects following extreme air pollution episodes to time-series analyses based on the use of sophisticated regression models. In fact, advanced statistical methods are necessary to address the challenges inherent in the detection of a relatively small pollution risk in the presence of potential confounders. This paper reviews the history, methods, and findings of the time-series studies estimating health risks associated with short-term exposure to particulate matter (PM), though much of the discussion is applicable to epidemiological studies of air pollution in general. We review the critical role of epidemiological studies in setting regulatory standards and the history of PM epidemiology and time-series analysis. We also summarize recent time-series results and conclude with a discussion of current and future directions of time-series analysis of particulates, including research on mortality displacement and the resolution of results from cohort and time-series studies.

Air pollution and health

The health effects of air pollution have been subject to intense study in recent years. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in mortality and hospital admissions due to respiratory and cardiovascular disease. These effects have been found in short-term studies, which relate day-to-day variations in air pollution and health, and long-term studies, which have followed cohorts of exposed individuals over time. Effects have been seen at very low levels of exposure, and it is unclear whether a threshold concentration exists for particulate matter and ozone below which no effects on health are likely. In this review, we discuss the evidence for adverse effects on health of selected air pollutants.

What's wrong with the National Ambient Air Quality Standard (NAAQS) for fine particulate matter (PM(2.5))?

Associations between airborne concentrations of fine particulate matter (PM(2.5)) and mortality rates have been investigated primarily by ecologic or semiecologic epidemiology studies. Many investigators and regulatory agencies have inferred that the weak, positive association often observed is causal, that it applies to all forms of airborne PM(2.5), and that current ambient levels of PM(2.5) require reduction. Before implementing stringent regulations of ambient PM(2.5), analysts should pause to consider whether the accumulated evidence is sufficient, and sufficiently detailed, to support the PM(2.5) National Ambient Air Quality Standard. We take two tacks. First, we analyze the toxicologic evidence, finding it inconsistent with the notion that current ambient concentrations of all forms of fine particulate matter should affect pulmonary, cardiac, or all-cause mortality rates. More generally, we note that the thousands of forms of PM(2.5) are remarkably diverse, yet the PM(2.5) NAAQS presumes them to be identical toxicologically, and presumes that reducing ambient concentrations of any form of PM(2.5) will improve public health. Second, we examine the epidemiologic evidence in light of two related examples of semiecologic associations, examples that both inform the PM-mortality association and have been called into question by individual-level data. Taken together, the toxicologic evidence and lessons learned from analogous epidemiologic associations should encourage further investigation of the association between particulate matter and mortality rates before additional regulation is implemented, and certainly before the association is characterized as causal and applicable to all PM(2.5).