Fine Particulate Matter and Total Mortality in Cancer Prevention Study Cohort Reanalysis

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.

Fine particulate air pollution and human mortality: 25+ years of cohort studies

Much of the key epidemiological evidence that long-term exposure to fine particulate matter air pollution (PM_2.5) contributes to increased risk of mortality comes from survival studies of cohorts of individuals. Although the first two of these studies, published in the mid-1990s, were highly controversial, much has changed in the last 25 + years. The objectives of this paper are to succinctly compile and summarize the findings of these cohort studies using meta-analytic tools and to address several of the key controversies. Independent reanalysis and substantial extended analysis of the original cohort studies have been conducted and many additional studies using a wide variety of cohorts, including cohorts constructed from public data and leveraging natural experiments have been published. Meta-analytic estimates of the mean of the distribution of effects from cohort studies that are currently available, provide substantial evidence of adverse air pollution associations with all-cause, cardiopulmonary, and lung cancer mortality.

Characteristics of cohort studies of long-term exposure to PM2.5: a systematic review

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM_2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts' participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

Commentary: EPA's proposed expansion of dose-response analysis is a positive step towards improving its ecological risk assessment

The United States Environmental Protection Agency (US EPA) has recently proposed changes to strengthen the transparency of its pivotal regulatory science policy and procedures. In this context, the US EPA aims to enhance the transparency of dose-response data and models, proposing to consider for the first time non-linear biphasic dose-response models. While the proposed changes have the potential to lead to markedly improved ecological risk assessment compared to past and current approaches, we believe there remain open issues for improving the quality of ecological risk assessment, such as the consideration of adaptive, dynamic and interactive effects. Improved risk assessment including adaptive and dynamic non-linear models (beyond classic threshold models) can enhance the quality of regulatory decisions and the protection of ecological health. We suggest that other countries consider adopting a similar scientific-regulatory posture with respect to dose-response modeling via the inclusion of non-linear biphasic models, that incorporate the dynamic potential of biological systems to adapt (i.e., enhancing positive biological endpoints) or maladapt to low levels of stressor agents.

Requirements for Transparency and Communicability of Regulatory Science

This article presents the results of a study attempting to provide examples that implement transparency and communicability elements of Ethical Rules Principle of Best Available Regulatory Science (BARS) and Metrics for Evaluation of Regulatory Science Claims (MERSC). It starts with an overview of regulatory science and briefly summarizes principles of BARS and key pillars of MERSC. Subsequently, the BARS/MERSC system is used to evaluate the linear nonthreshold (LNT) process used in cancer assessments and the similar process used for evaluating in particulate matter (PM) exposure. The study identifies 3 parts in dose-response curves, where the first part is reproducible science and the second part includes uncertainties and often requires the application of precautionary principle. The primary reason for disagreements on LNT and PM is a lack of recognition that the third part is based on desire of regulators to be protective, a policy decision process. Two PM epidemiological examples are included in this study to demonstrate the point. The regulatory process would benefit from recognizing the distinction between science and policy and excluding policy from regulatory science. Furthermore, the society would greatly benefit from increased transparency in the regulatory process and compliance with the Jeffersonian communication principle.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

Analyzing individual exposure in urban areas offers several challenges where both the individual's activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals' activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual's time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives.