Air Pollution and Mortality in the Medicare Population

Assessing Health Risks and Socioeconomic Disparities Associated with Ambient Air Pollution and Point Sources across the United States

Air quality in the United States (U.S.) has significantly improved over the last few decades. Nevertheless, many parts of the country still suffer from high levels of air pollution, including numerous non-attainment areas. This study aims to provide a systematic analysis to quantify the impact of air pollution on human health across the entire U.S. By combining the 2023 Centers for Disease Control and Prevention health surveys, criteria air pollutants, and socioeconomic status at the census tract level, we seek to (1) assess the impacts of air pollution on human health, and (2) investigate environmental health and air pollution disparities across the U.S. Our analysis suggests that fine particulate matter (PM2.5) is associated with most diseases, while ozone (O3) is highly correlated with the prevalence of cancer and kidney disease. Sulfur dioxide (SO2) is positively correlated with multiple health outcomes, whereas nitrogen oxide (NO) shows mixed correlations across different diseases. Health risks significantly increase as the levels of PM2.5 and O3 exceed 14 μg m-3 and 40 ppb, respectively. Furthermore, there is a strong correlation between disease prevalence, air pollution levels, and socioeconomic status. Minority and low-income groups across the U.S. are exposed to higher levels of PM2.5 and are prone to greater health risks, including asthma, high blood pressure, mental health, physical health, diabetes, and kidney disease. Notably, individuals exposed to PM2.5 levels greater than 9.0 μg m-3 have a higher risk of self-rating their health as poor status (RR: 1.202, 95% CI: 1.200, 1.203). Residents living within a 5-km radius of point source emissions from the oil and gas sector experience significant health impacts, particularly to naphthalene and other polycyclic aromatic hydrocarbons emitted during oil and gas production. This study highlights significant health disparities driven by environmental pollution inequality, particularly impacting low-income and minority groups across the U.S.

The impact of bias due to exponentiation in the estimation of hazard, risk, and odds ratios: an empirical investigation from 1,495,059 effect sizes from MEDLINE/PubMed abstracts

BACKGROUND

Parameter estimation using regression methods plays a vital role in medical research. Often a non-linear transformation of a regression parameter is preferred for its more intuitive interpretation. Important examples in medical research are odds ratios, risk ratios, and hazard ratios, which are obtained by exponentiating the estimated regression coefficients of the logit link binomial generalized linear model, log link Poisson generalized linear model or Cox proportional hazards model, respectively. A lot of attention has been devoted to studying and removing the bias of the estimators on the scale of the regression, but the bias of the transformed parameters is rarely addressed.

METHODS

Two approaches for reducing the bias due to the exponentiation are reviewed and applied to odds ratios, risk ratios, and hazard ratios reported in the abstracts published in the MEDLINE subset of English-language PubMed records.

RESULTS

We show that correcting for the bias due to the exponentiation may yield substantially different estimates, potentially resulting in a large shrinkage of the reported effect size estimates.

CONCLUSION

Given the wide availability of methods to reduce the bias on the scale of regression, we encourage their routine use to improve estimation. In situations where the consequences of biased estimation are larger at the exponentiated scale than at the scale of regression, as for example in some policy and planning settings, we additionally encourage the removal of the bias due to the exponentiation.

Social factors, health policy, and environment: implications for cardiovascular disease across the globe

Cardiovascular disease (CVD) is the leading cause of deaths worldwide, with 80% occurring in low- and middle-income countries. These countries are characterized by rapid urbanization, poorly funded health systems, poor access to prevention and treatment strategies, and increasing age and a higher prevalence of chronic disease. Rapid urbanization has contributed to the significant environmental and societal changes affecting daily life habits and cardiovascular health. There is growing awareness that environmental and social exposures and policies can influence CVD directly or through behavioural risk factors. However, much of this knowledge comes from studies in high-income countries and is applied to low- and middle-income countries without evidence to indicate this is appropriate. This state-of-the-art review will present and synthesize key findings from the Prospective Urban Rural Epidemiology study and related studies that have aimed to understand the environmental, social, and policy determinants of cardiovascular health in countries across varying levels of economic development through an urban/rural lens. Emerging from these findings are future policy and research recommendations to accelerate the reduction of the global burden of CVD.

Physical Activity, Air Pollution, and Mortality: A Systematic Review and Meta-analysis

BACKGROUND

As whether the positive effects of physical activity on mortality outweigh the negative effects of exposure to pollution is still under debate, we conducted a systematic review and meta-analysis on the risk of mortality for combined exposure to physical activity and air pollution.

METHODS

PubMed, Cochrane, Embase and ScienceDirect databases were searched for studies assessing the risk of mortality for combined exposure to physical activity and air pollution.

RESULTS

We included eight studies for a total of 1,417,945 individuals (mean 57.7 years old, 39% men) - 54,131 died. We confirmed that air pollution increased the risk of mortality by 36% (OR 1.36, 95CI 1.05-1.52), whereas physical activity in a non-polluted environment decreased the risk of mortality by 31% (OR 0.69, 95CI 0.42-0.95). Our meta-analysis demonstrated that combined exposure to physical activity and air pollution decreased the risk of mortality by 26% (OR 0.74, 95CI 0.63-0.85). This risk decreased whatever the level of physical activity: by 19% (OR 0.81, 95CI 0.69-0.93) for low, by 32% (OR 0.68, 95CI 0.44-0.93) for moderate, and by 30% (OR 0.70, 95CI 0.49-0.91) for high physical activity in air pollution.

CONCLUSION

We confirmed that air pollution increased mortality by 36% in our meta-analysis. Despite the controversial benefit-risk, we demonstrated a reduction of mortality by 26% for combined exposure to physical activity and air pollution - nearly comparable to the reduction of mortality when practicing physical activity without air pollution (- 31%). However, the limited number of included studies precluded the demonstration of a dose-response relationship between levels of physical activity and air pollution, and reduction of mortality.

Community Engagement to Inform Multilevel Analyses of the Role of Neighborhood Factors in Cancer Control Behaviors in African Americans

BACKGROUND

Although community engagement has had a substantial presence in public health research, community input to inform geospatial and health analyses remains underutilized and novel. This article reports on community engagement activities to solicit stakeholder perspectives on the role of neighborhood conditions in health and cancer. We discuss how this community input refined an a priori conceptual model to be tested in the larger Families, Friends, and Neighborhoods Study.

METHODS

We conducted semistructured virtual interviews with 82 stakeholders (e.g., community and faith leaders, educators, and healthcare workers) across four states (Maryland, Connecticut, Alabama, and Missouri). Participants discussed the impact where a person lives can have on their health and cancer risk. We subsequently convened a virtual group discussion with 17 randomly selected interviewees. Our study team individually reviewed discussion notes, which were synthesized into a consensus document.

RESULTS

In addition to constructs from the original conceptual model, participants identified neighborhood-level factors not present in the original model, including K-12 educational quality, local property investment, homelessness, public transportation infrastructure, proximity to healthcare facilities, environmental toxin exposures, access to healthy foods, and cost of living. These factors will be incorporated into the Families, Friends, and Neighborhoods Study analytic models.

CONCLUSIONS

Although geospatial analyses in health research have not traditionally employed community engagement techniques, this study illustrates the value of informing multilevel analytic models with the lived experiences of those negatively affected by neighborhood conditions that underlie the risk, prevention, and screening behaviors driving cancer incidence and mortality.

IMPACT

Future social epidemiology research can be enriched through community engagement.

Loss of life expectancy attributed to long-term ozone exposure in Chinese older adults: Cross-cohort analysis from 3 national cohorts

BACKGROUND

Cohort evidence linking ozone (O3) exposure with mortality was sparsely investigated among the elderly in low- and middle-income countries. This study aims to quantify mortality risk and burden attributed to chronic O3 exposure in Chinese older adults.

METHODS

A total of 30,874 older adults aged ≥65 years were recruited from 3 national dynamic cohorts across 29 provincial regions in China, 2005-2018. Annual warm-season (April-September) O3 and year-round PM2.5 concentrations were estimated through well-validated satellite-based spatiotemporal models and were assigned to participants for each survey year. Time-dependent Fragility Cox models with random intercept for study cohort were employed to quantify O3-mortality association, adjusting for demographic, behavioral, health, and environmental covariates. A counterfactual causal framework was used for assessment of O3-attributable premature deaths in older adults based on exposure-response relationship derived from multi-cohort two-pollutant analysis (+PM2.5). Years of life lost and loss of life expectancy were subsequently evaluated based on the burden estimation model by incorporating the comparative risk assessment method and reference life tables.

RESULTS

16,939 death events occurred during 0.16 million person-years of follow-up surveys. Each 10-ppb increase in O3 exposure was linked with a hazard ratio of 1.076 (95% confidence interval [CI]: 1.050, 1.102) for all-cause mortality. By achieving the counterfactual target (WHO AQG 2021) of 60 μg/m3 for warm-season O3, 0.88 (95% CI: 0.60, 1.14) million premature deaths could be avoidable among Chinese older population in 2019, yielding an inconspicuous reduction of 0.11 million compared to the estimate in 2011 (0.99 million, 95% CI: 0.68, 1.28). O3-attributable deaths amounted to 9.05 (95% CI: 6.19, 11.70) million years of life lost in 2019, equivalent to a loss of life expectancy of 0.93 (95% CI: 0.63, 1.20) years for older population in China.

CONCLUSIONS

Our multi-cohort analysis suggested that reducing ambient O3 exposure could increase the life expectancy of Chinese older adults, which may contribute to the development of healthy aging strategies and national cleaning air policies.

Intercomparison of Modeled Urban-Scale Vehicle NOx and PM2.5 Emissions-Implications for Equity Assessments

Accurate characterization of emissions is essential for understanding spatiotemporal variations of air pollutants and their societal impacts, including population exposure, health outcomes, and environmental justice implications. Characterizing emissions from the transportation sector is challenging due to uncertainties in emission-producing processes and in fleet composition and activity-factors that lead to differences across modeled vehicle emissions data sets. Here, we compare four data sets─Fuel-Inventory Vehicle Emissions, Neighborhood Emission Mapping Operation, Lake Michigan Air Director Consortium-Northwestern University, and University of Vermont─over the Greater Chicago region at three shared spatial resolutions (1.0, 1.3, and 4 km2). While domain-level data set agreement is strongest at the coarsest resolution, at finer resolutions we find notable inconsistencies, particularly at local scales. At 1 km2, simulated domain total NOx emissions across the four data sets differ up to 82% (∼32-58 k tons/year), while grid cell maximum PM2.5 emissions vary up to 272% (∼1.5-5.5 tons/km2/year). Intercompared emissions data sets share similar inputs; however, divergent outcomes arise from differences in emission factors, simulated vehicle processes, and characterization of traffic data. While domain-level emission burdens among racial/ethnic subgroups are generally ranked similarly across data sets, the magnitude of relative disparities can vary up to 11%-a potentially consequential factor to consider in downstream impact analyses.

The impact of climate change on respiratory health: current understanding and knowledge gaps

PURPOSE OF REVIEW

To present an overview of the impact of climate change upon human respiratory health.

RECENT FINDINGS

Climate change is directly impacting air quality. Particulate matter clearly increases mortality rates. Ozone, a longstanding suspect in climate-related injury, turns out not to have the major impact that had been projected at current levels of exposure. The key factors in global warming have been clearly identified, but while these factors collectively cause deleterious changes, a close look at the literature shows that it is unclear to what extent each factor individually is a driver of a specific process. This article summarizes some of those studies.

SUMMARY

A better understanding of which components of climate change most impact human health is needed in order to re-define environmental standards. PM 2.5 needs to be broken down by chemical composition to study the differential impacts of different sources of PM 2.5 . The detection and study of climate-related changes in respiratory infectious diseases is in a state of relative infancy.

Environmental consequences of interacting effects of changes in stratospheric ozone, ultraviolet radiation, and climate: UNEP Environmental Effects Assessment Panel, Update 2024

This Assessment Update by the Environmental Effects Assessment Panel (EEAP) of the United Nations Environment Programme (UNEP) addresses the interacting effects of changes in stratospheric ozone, solar ultraviolet (UV) radiation, and climate on the environment and human health. These include new modelling studies that confirm the benefits of the Montreal Protocol in protecting the stratospheric ozone layer and its role in maintaining a stable climate, both at low and high latitudes. We also provide an update on projected levels of solar UV-radiation during the twenty-first century. Potential environmental consequences of climate intervention scenarios are also briefly discussed, illustrating the large uncertainties of, for example, Stratospheric Aerosol Injection (SAI). Modelling studies predict that, although SAI would cool the Earth's surface, other climate factors would be affected, including stratospheric ozone depletion and precipitation patterns. The contribution to global warming of replacements for ozone-depleting substances (ODS) are assessed. With respect to the breakdown products of chemicals under the purview of the Montreal Protocol, the risks to ecosystem and human health from the formation of trifluoroacetic acid (TFA) as a degradation product of ODS replacements are currently de minimis. UV-radiation and climate change continue to have complex interactive effects on the environment due largely to human activities. UV-radiation, other weathering factors, and microbial action contribute significantly to the breakdown of plastic waste in the environment, and in affecting transport, fate, and toxicity of the plastics in terrestrial and aquatic ecosystems, and the atmosphere. Sustainability demands continue to drive industry innovations to mitigate environmental consequences of the use and disposal of plastic and plastic-containing materials. Terrestrial ecosystems in alpine and polar environments are increasingly being exposed to enhanced UV-radiation due to earlier seasonal snow and ice melt because of climate warming and extended periods of ozone depletion. Solar radiation, including UV-radiation, also contributes to the decomposition of dead plant material, which affects nutrient cycling, carbon storage, emission of greenhouse gases, and soil fertility. In aquatic ecosystems, loss of ice cover is increasing the area of polar oceans exposed to UV-radiation with possible negative effects on phytoplankton productivity. However, modelling studies of Arctic Ocean circulation suggests that phytoplankton are circulating to progressively deeper ocean layers with less UV irradiation. Human health is also modified by climate change and behaviour patterns, resulting in changes in exposure to UV-radiation with harmful or beneficial effects depending on conditions and skin type. For example, incidence of melanoma has been associated with increased air temperature, which affects time spent outdoors and thus exposure to UV-radiation. Overall, implementation of the Montreal Protocol and its Amendments has mitigated the deleterious effects of high levels of UV-radiation and global warming for both environmental and human health.

Low-level PM 2.5 Exposure, Cardiovascular and Nonaccidental Mortality, and Related Health Disparities in 12 US States

BACKGROUND

Investigations into long-term fine particulate matter (PM 2.5 ) exposure's impact on nonaccidental and cardiovascular (CVD) deaths primarily involve nonrepresentative adult populations at concentrations above the new Environmental Protection Agency annual PM 2.5 standard.

METHODS

Using generalized linear models, we studied PM 2.5 exposure on rates of five mortality outcomes (all nonaccidental, CVD, myocardial infarction, stroke, and congestive heart failure) in 12 US states from 2000 to 2016. We aggregated predicted annual PM 2.5 exposures from a validated ensemble exposure model, ambient temperature from Daymet predictions, and mortality rates to all census tract-years within the states. We obtained covariates from the decennial Census and the American Community Surveys and assessed effect measure modification by race and education with stratification.

RESULTS

For each 1-µg/m 3 increase in annual PM 2.5 , we found positive associations with all five mortality outcomes: all nonaccidental (1.08%; 95% confidence interval [CI]: 0.96%, 1.20%), all CVD (1.27%; 95% CI: 1.14%, 1.41%), myocardial infarction (1.89%; 95% CI: 1.67%, 2.11%), stroke (1.08%; 95% CI: 0.87%, 1.30%), and congestive heart failure (2.20%; 95% CI: 1.97%, 2.44%). Positive associations persisted at <8 µg/m 3 PM 2.5 levels and among populations with only under 65. In our study, race, but not education, modifies associations. High-educated Black had a 2.90% larger increased risk of CVD mortality (95% CI: 2.42%, 3.39%) compared with low-educated non-Black.

CONCLUSION

Long-term PM 2.5 exposure is associated with nonaccidental and CVD mortality in 12 states, below the new Environmental Protection Agency standard, for both low PM 2.5 regions and the general population. Vulnerability to CVD mortality persists among Black individuals regardless of education level.

Cardiovascular effects of household air pollution on cardiovascular diseases incidence

Cardiovascular diseases (CVD) are the main cause of death globally, especially in low- and middle-income countries (LMICs), where the largest number of inhabitants on the planet are concentrated. Air pollution inside and outside the home by microparticles 2 5 (PM2·5) has become an important risk factor for the presence of CVD and other chronic non-communicable diseases, particularly in LMICs. The use of solid fuels as an energy source for cooking food and heating inside the home has negative effects not only on human health but also on the health of the planet, as it contributes to deforestation and the consequent effect on climate change. In this narrative review we update how air pollution inside the home from cooking food with firewood and charcoal impacts the risk of CVD, the factors that determine the use of these polluting fuels, and the actions necessary for the massive transition toward the use of non-polluting energy, highlighting the development of university research to offer a stove that uses green hydrogen as a non-polluting energy source.

The impacts of air pollution on mortality and hospital readmission among Medicare beneficiaries with Alzheimer's disease and Alzheimer's disease-related dementias: a national retrospective cohort study in the USA

BACKGROUND

Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) are prevalent neurodegenerative disorders, posing a critical worldwide public health challenge. Ambient air pollution has been identified as a potential risk factor for AD progression based on toxicological and epidemiological studies. We aimed to evaluate the impacts of air pollution-including fine particulate matter (PM2·5), nitrogen dioxide (NO2), summer ozone (O3), and oxidant-on readmission or death among Medicare enrollees previously hospitalised with an AD/ADRD diagnosis code.

METHODS

We constructed a population-based nationwide retrospective cohort including all Medicare fee-for-service beneficiaries (aged ≥65 years) in the contiguous USA (2000-16) hospitalised with AD/ADRD, and followed them up from the year after their first hospitalisation until (1) year of death (mortality cohort) and (2) year of second hospitalisation for any cause (readmission cohort). We calculated annual average PM2·5, NO2, summer O3, and oxidant concentrations for each individual at their residential ZIP code in each year after their first hospitalisation with AD/ADRD. We applied Cox proportional hazard models for the mortality and readmission cohorts stratifying on individual risk factors and adjusting for socioeconomic status, seasonal temperatures, and relative humidity.

FINDINGS

Our cohort consisted of 5 544 118 individuals, of whom 4 543 759 (82·0%) died and 3 880 894 (70·0%) were readmitted to the hospital during the study period. The average follow-up times were 3·34 years (SD 2·60) for the mortality cohort and 1·98 years (SD 1·65) for the readmission cohort. In both the mortality and readmission cohorts we found significant associations with each pollutant. For an IQR increase in NO2, we found a hazard ratio (HR) for mortality of 1·012 (95% CI 1·009-1·015) and an HR for readmission of 1·110 (1·104-1·117). In the readmission cohort, we found an HR of 1·084 (1·079-1·089) for an IQR increase (3·87 μg/m3) in PM2·5. The results slightly decreased in multi-pollutant models. The results of effect modification for mortality and readmission varied by pollutant, but higher risks were found among Black males and among those eligible for Medicaid in general.

INTERPRETATION

We provide new evidence that among a susceptible population with previous AD/ADRD-related hospitalisations, annual air pollution exposure since first hospitalisation is associated with risk of readmission and death.

FUNDING

National Institute on Aging.

Fine particulate matter and nonaccidental and cause-specific mortality: Do associations vary by exposure assessment method?

Background

There is considerable heterogeneity in fine particulate matter (PM2.5)-mortality associations between studies, potentially due to differences in exposure assessment methods. Our aim was to evaluate associations of PM2.5 predicted from different models with nonaccidental and cause-specific mortality.

Methods

We followed 107,906 participants of the Nurses' Health Study cohort from 2001 to 2016. PM2.5 concentrations were estimated from spatiotemporal models developed by researchers at the University of Washington (UW), Pennsylvania State University (PSU), and Harvard TH Chan School of Public Health (HSPH). We calculated 12-month moving average concentrations and we used time-varying Cox proportional hazard ratios (HRs).

Results

There were 30,242 nonaccidental deaths in 1,435,098 person-years. We observed high correlations and similar temporal trends between the PM2.5 predictions. We found no associations of UW, PSU, or HSPH PM2.5 with nonaccidental mortality, but suggestive positive associations with cancer, cardiovascular, and respiratory disease mortality. There were small differences in HRs between the PM2.5 predictions. All three predictions showed the strongest associations with cancer mortality: HRs (95% confidence interval, expressed per 5 µg/m3 increase) were 1.06 (1.01, 1.12) for UW, 1.08 (1.03, 1.13) for PSU, and 1.05 (1.00, 1.10) for HSPH. In a subset restricted to participants who were always exposed to PM2.5 below 12 µg/m3, we observed positive associations with nonaccidental mortality.

Conclusion

We found that differences between PM2.5 exposure assessment methods could lead to minor differences in strengths of associations between PM2.5 and cause-specific mortality in a population of US female nurses.

Impact of a 10-year shift in ambient air quality on mortality in Canada: a causal analysis of multiple pollutants

BACKGROUND

The impact of past air quality improvements on health and equity at low pollution levels near the revised WHO air quality guidelines remains largely unknown. Less is known about the influence of simultaneous reductions in multiple major pollutants. Leveraging real-world improvements in air quality across Canada, we sought to directly evaluate their health benefits by quantifying the impact of a joint shift in three criteria pollutants on mortality in a national cohort.

METHODS

In this population-based cohort study, we assembled a cohort of 2·7 million adults living in Canada in 2007 who were followed up through 2016. Annual mean concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), and ozone (O3) were assigned to participants' residential locations. For each pollutant individually and combined, we conducted a causal analysis of the impact of the decadal shift in annual exposure from the pre-baseline level (2004-06) on the risk of non-accidental mortality using the parametric g-formula, a structural causal model. To check the robustness of our results, we conducted multiple sensitivity analyses, including exploring alternative exposure scenarios. We also evaluated differential benefits across regions and socio-demographic subgroups.

FINDINGS

Between 2007 and 2016, annual mean exposures to PM2·5 and NO2 decreased (from 7·1 μg/m3 [SD 2·3] to 5·5 μg/m3 [1·9] for PM2·5 and from 11·1 ppb [SD 6·6] to 8·0 ppb [4·9] for NO2), whereas O3 declined initially and then rebounded (from 38·6 [SD 8·3] ppb to 36·0 [6·0] ppb and then 38·1 [5·4] ppb). Compared to pre-baseline (2004-06) levels, the joint change in the pollution exposures beginning in 2007 resulted in, per million population, 70 (95% CI 29-111) fewer deaths by 2009, 416 (283-549) fewer deaths by 2012, and 609 (276-941) fewer deaths by 2016, corresponding to a -0·7% change in mortality risk over the decade. Stratified analyses showed greater beneficial impacts in men, adults aged 50 years and older, low income-earners, and residents in regions undergoing substantial air quality improvements. Had all regions experienced pollution reductions similar to the most improved region, approximately three times as many deaths would have been averted (2191 fewer deaths per million). Conversely, if the observed air quality improvements had been delayed in all regions by 3 years, there would have been 429 more deaths per million by 2016.

INTERPRETATION

In Canada, substantial health gains were associated with air quality improvements at levels near the revised WHO guidelines between 2007 and 2016, with notable heterogeneity observed across socio-demographic subgroups and regions. These findings indicate that modest declines in air pollution can considerably improve health and equity, even in low-exposure environments.

FUNDING

Health Canada.

National PM2.5 spatiotemporal model integrating intensive monitoring data and land use regression in a likelihood-based universal kriging framework in the United States: 2000-2019

Nationwide PM2.5 exposure models typically rely on regulatory monitoring data as the only ground-level measurements. In this study, we develop a high-resolution spatiotemporal PM2.5 model for the contiguous United States from 2000 to 2019 with dense monitoring data at both regulatory and residential sites. Specifically, we combine publicly-available data from 1843 regulatory monitors with our own set of multiple 2-week measurements at 939 residential locations. As we show, these additional data enhance the spatiotemporal prediction capabilities of the model. The model can handle varying data densities and regional variations; it predicts two-week average PM2.5 concentrations at fine spatial scale for the contiguous United States. Cross-validation performance indicates a spatial R2 of 0.93 and a root mean square error (RMSE) of 1.19 (μg/m3), and a temporal R2 of 0.85 and RMSE of 2.05 (μg/m3). Regional spatial R2 ranged from 0.80 (northwest) to 0.93 (northeast and central). Over time, the average PM2.5 across the United Stats decreased from 7.6 μg/m3 in 2000 to 4.7 μg/m3 in 2019. Our model effectively captured local PM2.5 gradients, highlighting its ability to address fine-scale variations related to local sources and roadways.

Socioeconomic disparities in mortality from indoor air pollution: A multi-country study

BACKGROUND

Indoor air pollution is a major public health concern, contributing to approximately 2.9 million deaths and 81.1 million disability-adjusted life years lost annually. This issue disproportionately affects underprivileged communities that depend on solid fuels for cooking. As a result, these communities suffer from heightened exposure to indoor air pollutants, which increases the risk of morbidity, mortality, and worsening health disparities.

OBJECTIVE

This study investigates the association between socioeconomic status and mortality related to indoor air pollution across multiple countries.

METHODS

Data from the 2019 Demographic and Health Survey, WHO, and World Bank were utilized to examine the impact of socioeconomic status on indoor air pollution-related mortality. The primary outcome was mortality associated with solid fuel use, with income quintiles as the independent variable. Linear and logistic regression analyses were applied to assess these relationships.

RESULTS

Logistic regression analysis revealed a strong negative association where household income increases and indoor air pollution-related mortality significantly decreases. Specifically, Households in the highest income quartile showed a 22% reduction progressively in the odds of mortality risk compared to the lowest income quintile. Additionally, access to clean fuel correlated with a 0.59 times lower odds of mortality, highlighting the clean energy sources' protecting effect.

CONCLUSION

The findings highlight the critical need to prioritize clean fuel access, particularly in low-income communities, to reduce indoor air pollution mortality. Policies should focus on increasing clean energy accessibility and supporting vulnerable populations through targeted subsidies and poverty alleviation programs to reduce indoor air pollution exposure disparities.

Key drivers and source mechanisms of oxidative potential in fine particles from an industrial city of Northern China Plain

The oxidative potential (OP) of particulate matter (PM) is crucial for understanding its ability to generate reactive oxygen species. However, the major chemical drivers influencing OP still need to be better understood. This study investigated the seasonal variations of OP and identified key drivers and source mechanisms in the industrial city of Zibo, located in North China Plain. We used the XGBoost model and Positive Matrix Factorization (PMF) to identify key drivers and source mechanisms. In 2022, PM2.5 samples were collected from an urban site in Zibo, and major chemical components were analyzed. OP was quantified using the dithiothreitol (DTT) method. The results revealed that the annual average DTTv in Zibo City for 2022 was 1.1 nmol/min/m3, with the highest DTTv levels observed in autumn, followed by spring, summer, and winter. Using the XGBoost model, we identified that metal elements such as Pb, Ba, and Cu, along with water-soluble ions NO3- and SO42-, significantly contributed to DTTv. Source apportionment analysis via PMF identified five major sources of PM2.5. Throughout the study period, secondary particles were the predominant contributors to PM2.5 (49 %), while coal combustion had the lowest contribution (7 %). To further elucidate the sources of OP in PM2.5, we integrated the measured OP with source contributions derived from PMF. The findings indicated that secondary particles and industrial sources contributed the most to DTTv, accounting for 40 % and 21 %, respectively. The OP sources exhibited seasonal variations: secondary particles were the primary contributors in winter, while dust sources dominated in spring. In summer, vehicle emissions increased substantially, and industrial emissions became the major source in autumn. This study highlighted the critical drivers and source mechanisms of OP in industrial cities and would be beneficial for future air quality control and risk reduction.

Interactive effects between extreme temperatures and PM2.5 on cause-specific mortality in thirteen U.S. states

The extent and robustness of the interaction between exposures to heat and ambient PM2.5 is unclear and little is known of the interaction between exposures to cold and ambient PM2.5. Clarifying these interactions, if any, is crucial due to the omnipresence of PM2.5 in the atmosphere and increasing scope and frequency of extreme temperature events. To investigate both of these interactions, we merged 6 073 575 individual-level mortality records from thirteen states spanning seventeen years with 1 km daily PM2.5 predictions from sophisticated prediction model and 1 km meteorology from Daymet V4. A time-stratified, bidirectional case-crossover design was used to control for confounding by individual-level, long-term and cyclic weekly characteristics. We fitted conditional logistic regressions with an interaction term between PM2.5 and extreme temperature events to investigate the potential interactive effects on mortality. Ambient PM2.5 exposure has the greatest effect on mortality by all internal causes in the 2 d moving average exposure window. Additionally, we found consistently synergistic interactions between a 10 μg m-3 increase in the 2 d moving average of PM2.5 and extreme heat with interaction odds ratios of 1.013 (95% CI: 1.000, 1.026), 1.024 (95% CI: 1.002, 1.046), and 1.033 (95% CI: 0.991, 1.077) for deaths by all internal causes, circulatory causes, and respiratory causes, respectively, which represent 75%, 156%, and 214% increases in the coefficient estimates for PM2.5 on those days. We also found evidence of interactions on the additive scale with corresponding relative excess risks due to interaction (RERIs) of 0.013 (95% CI: 0.003, 0.021), 0.020 (95% CI: 0.008, 0.031), and 0.017 (95% CI: -0.015, 0.036). Interactions with other PM2.5 exposure windows were more pronounced. For extreme cold, our results were suggestive of an antagonistic relationship. These results suggest that ambient PM2.5 interacts synergistically with exposure to extreme heat, yielding greater risks for mortality than only either exposure alone.

Spatiotemporal modeling of long-term PM2.5 concentrations and population exposure in Greece, using machine learning and statistical methods

The lack of high-resolution, long-term PM2.5 observations in Greece and the Eastern Mediterranean hampers the development of spatial models that are crucial for providing representative exposure estimates to health studies. This work presents a spatial modeling approach to address this gap and assess PM2.5 spatial variability for the first time on a national level in Greece, by integrating in situ observations, meteorology, emissions and satellite AOD data among others. A high-resolution (1 km2) gridded dataset of PM2.5 concentrations across Greece from 2015 to 2022 was developed, and seven statistical, machine learning, and hybrid models were evaluated under different prediction scenarios. Random Forest (RF) models demonstrated superior performance, (R2 = 0.73, MAE = 2.2 μg m-3), validated against ground-based measurements. Winter months consistently showed the highest PM2.5 levels, averaging 16.8 μg m-3, over the domain, due to residential biomass burning (BB) and limited atmospheric dispersion. Summer months had the lowest concentrations, averaging 10.3 μg m-3, while substantial decreases nationwide were observed during the 2020 COVID-19 lockdown. Population exposure analysis indicated that the entire Greek population was exposed to long-term PM2.5 concentrations exceeding the WHO air quality guideline (AQG) of 5 μg m-3. Moreover, the dataset revealed elevated PM2.5 levels across several regions of mainland Greece. Notably, 70 % to 90 % of the population experience levels exceeding 10 μg m-3 in Central and Northern regions of continental Greece like Thessaly, Central Macedonia, and Ioannina. The Ioannina region, which is severely impacted by residential BB, recorded pollution levels up to five times the WHO AQG highlighting the urgent need for targeted interventions. The high-resolution RF model's superior performance for monthly average concentrations, compared to the Copernicus Atmosphere Monitoring Service (CAMS) dataset, renders it a reliable tool for long-term PM2.5 assessment in Greece that can support air quality management and health studies.

Long-term Associations Between Time-varying Exposure to Ambient PM 2.5 and Mortality: An Analysis of the UK Biobank

BACKGROUND

Evidence for long-term mortality risks of PM 2.5 comes mostly from large administrative studies with incomplete individual information and limited exposure definitions. Here we assess PM 2.5 -mortality associations in the UK Biobank cohort using detailed information on confounders and exposure.

METHODS

We reconstructed detailed exposure histories for 498,090 subjects by linking residential data with high-resolution PM 2.5 concentrations from spatiotemporal machine-learning models. We split the time-to-event data and assigned yearly exposures over a lag window of 8 years. We fitted Cox proportional hazard models with time-varying exposure controlling for contextual- and individual-level factors, as well as trends. In secondary analyses, we inspected the lag structure using distributed lag models and compared results with alternative exposure sources and definitions.

RESULTS

In fully adjusted models, an increase of 10 μg/m³ in PM 2.5 was associated with hazard ratios of 1.27 (95% confidence interval: 1.06, 1.53) for all-cause, 1.24 (1.03, 1.50) for nonaccidental, 2.07 (1.04, 4.10) for respiratory, and 1.66 (0.86, 3.19) for lung cancer mortality. We found no evidence of association with cardiovascular deaths (hazard ratio = 0.88, 95% confidence interval: 0.59, 1.31). We identified strong confounding by both contextual- and individual-level lifestyle factors. The distributed lag analysis suggested differences in relevant exposure windows across mortality causes. Using more informative exposure summaries and sources resulted in higher risk estimates.

CONCLUSIONS

We found associations of long-term PM 2.5 exposure with all-cause, nonaccidental, respiratory, and lung cancer mortality, but not with cardiovascular mortality. This study benefits from finely reconstructed time-varying exposures and extensive control for confounding, further supporting a plausible causal link between long-term PM 2.5 and mortality.

Interactive effects of atmospheric oxidising pollutants and heat waves on the risk of residential mortality

BACKGROUND

The impact of heat waves and atmospheric oxidising pollutants on residential mortality within the framework of global climate change has become increasingly important.

OBJECTIVE

In this research, the interactive effects of heat waves and oxidising pollutants on the risk of residential mortality in Fuzhou were examined. Methods We collected environmental, meteorological, and residential mortality data in Fuzhou from 1 January 2016, to 31 December 2021. We then applied a generalised additive model, distributed lagged nonlinear model, and bivariate three-dimensional model to investigate the effects and interactions of various atmospheric oxidising pollutants and heat waves on the risk of residential mortality.

RESULTS

Atmospheric oxidising pollutants increased the risk of residential mortality at lower concentrations, and O3 and Ox were positively associated with a maximum risk of 2.19% (95% CI: 0.74-3.66) and 1.29% (95% CI: 0.51-2.08). The risk of residential mortality increased with increasing temperature, with a strong and long-lasting effect and a maximum cumulative lagged effect of 1.11% (95% CI: 1.01, 1.23). Furthermore, an interaction between atmospheric oxidising pollutants and heat waves may have occurred: the larger effects in the longest cumulative lag time on residential mortality per 10 µg/m3 increase in O3, NO2 and Ox during heat waves compared to non-heat waves were [-3.81% (95% CI: -14.82, 8.63)]; [-0.45% (95% CI: -2.67, 1.81)]; [67.90% (95% CI: 11.55, 152.71)]; 16.37% (95% CI: 2.43, 32.20)]; [-3.00% (95% CI: -20.80, 18.79)]; [-0.30% (95% CI: -3.53, 3.04)]. The risk on heat wave days was significantly higher than that on non-heat wave days and higher than the separate effects of oxidising pollutants and heat waves.

CONCLUSIONS

Overall, we found some evidence suggesting that heat waves increase the impact of oxidising atmospheric pollutants on residential mortality to some extent.

Short-term exposure to outdoor nitrogen dioxide and respiratory mortality, with high-risk populations: a nationwide time-stratified case-crossover study

Numerous existing studies reported the negative impacts of outdoor nitrogen dioxide (NO2) on respiratory mortality. However, the evidence of related high-risk populations was considerably limited, especially associated with ages, causes of death, and district-level characteristics. In addition, most earlier studies were based on monitored areas, thus previous risk estimates of NO2 could be biased to provide nationwide risk estimates and high-risk populations. Therefore, this study performed a nationwide time-stratified case-crossover study to evaluate the association between short-term ambient NO2 and respiratory mortality in South Korea (2015-2019). A machine learning-ensemble daily NO2 prediction model was used to cover unmonitored areas. To examine high-risk populations, we assessed NO2 risk estimates by age group, sex, cause of mortality, and district-level characteristics. In the total population, NO2 was weakly associated with increased mortality risk due to respiratory disease (OR [odds ratio]: 1.011, 95% CI [confidence interval]: 0.995-1.027), and the association became evident only in individuals aged 80 y or older (1.022, 1.000-1.044), especially related to pneumonia. Further, in people aged 60-69 years, NO2 was marginally associated with mortality for chronic lower respiratory diseases. Lower district-level socioeconomic status and medical services were marginally related to higher respiratory mortality risks related to NO2. The excess respiratory mortality fractions and YLL (year of life lost) attributable to NO2 were 4.13% and 93,851.63 years, and around 70% of the excess deaths were due to noncompliance with the World Health Organization air quality guidelines (daily average NO2 > 25 µg/m3). This study provides evidence for high-risk populations and the appropriateness of target-specific action plans against NO2. In addition, based on the excess death estimates, we suggest stricter NO2 standards are required.

Changes in traffic-related air pollution exposures and associations with adverse birth outcomes over 20 years in Texas

BACKGROUND

Billions of dollars have been spent implementing regulations to reduce traffic-related air pollution (TRAP) from exhaust pipe emissions. However, few health studies have evaluated the change in TRAP emissions and associations with infant health outcomes. We hypothesize that the magnitude of association between vehicle exposure measures and adverse birth outcomes has decreased over time, parallelling regulatory improvements in exhaust pipe emissions.

METHODS

Using birth records in Texas from 1996 to 2016, we calculated residential exposure measures related to TRAP: nitrogen dioxide (NO2, a marker of the TRAP mixture), vehicle miles travelled within 500 m of homes (VMT500), a measure of traffic volume, and highway proximity. Using an accountability study framework, our analysis examined term birthweight, term low birthweight (TLBW) (<2500 g), preterm birth (PTB) (<37 weeks) and very preterm birth (VPTB) (<32 weeks). We implemented linear and logistic regression models to examine overall and time-stratified associations, including trends by race/ethnicity and socioeconomic groups.

RESULTS

Among exposures for 6 158 518 births, NO2 exposures decreased 59% over time but VMT500 remained relatively stable. TRAP-related exposure measures were persistently associated with harmful birth outcomes [e.g. OR1996-2016 of 1.07 (95% CI: 1.04, 1.08) for TLBW comparing the highest vs lowest NO2 quintile]. The magnitude of associations decreased for total VMT500 and TLBW (-60%, OR1996: 1.08 to OR2016: 1.03 for the highest vs lowest quintile) and PTB (-65%) and VTPT (-61%), but not for term birthweight.

CONCLUSIONS

We observed evidence of small improvements in birth outcomes associated with reductions in exhaust pipe emissions over a 20-year period in Texas.

Confounding effects of socioeconomic status on the association between long-term PM2.5 exposure and mortality in Korea

BACKGROUND

This study assesses the national distribution of ambient fine particulate matter (PM2.5) exposure across socioeconomic status (SES) and its confounding on long-term PM2.5 mortality in Korea, aiming to minimize SES influence.

METHODS

A nationwide cohort of 5% of Koreans, aged 30 or older, from 2007 to 2019, from the National Health Information Database, was analysed. PM2.5 exposure levels were estimated at the city level using the Community Multiscale Air Quality system. Mortality data were obtained from Statistics Korea. The study examined annual PM2.5 exposure by SES indicators and its confounding on mortality risks associated with PM2.5, using time-varying Cox proportional hazards models.

RESULTS

The study followed 1 453 036 individuals from 2007 to 2019, totalling 17 760 227 person-years (PYs). The non-accidental (A00-R99), cardiovascular (I00-I99) and respiratory (J00-J99) mortality rates per 1000 PY were 7.6, 1.9 and 0.8, respectively. We observed a trend of decreasing PM2.5 exposure levels but increased mortality among medical aid beneficiaries, those with lower household incomes and those residing in neighbourhoods with a higher area deprivation index. When adjusting for these SES covariates, the long-term mortality effects of PM2.5 shifted in the direction of increased risk [hazard ratio (HR) for cardiovascular mortality in the unadjusted model = 0.968 (95% CI: 0.909-0.959); HR in the fully adjusted model = 1.053 (95% CI: 1.004-1.105)].

CONCLUSION

In regions where SES and PM2.5 concentrations are positively correlated, as in Korea, it is crucial to rigorously control for SES confounding to avoid underestimating the mortality effects associated with PM2.5.

Climate Policy Reduces Racial Disparities in Air Pollution from Transportation and Power Generation

Energy system optimization models facilitate analyses on a national or regional scale. However, understanding the impacts of climate policy on specific populations requires a much higher spatial resolution. Here, we link an energy system optimization model to an integrated assessment model via an emission downscaling algorithm, translating air pollution emissions from nine U.S. regions to U.S. counties. We simulate the impacts of six distinct policy scenarios, including a current policy and a 2050 net-zero target, on NOx, SO2, and PM2.5 emissions from on-road transportation and electricity generation. We compare different policies based on their ability to reduce emission exposure and exposure disparity across racial groups, allowing decision-makers to assess the air pollution impacts of various policy instruments more holistically. Modeled policies include a clean electricity standard, an on-road ICE vehicle ban, a carbon tax, and a scenario that reaches net-zero GHG emissions by 2050. While exposure and disparities decrease in all scenarios, our results reveal persistent disparities until at least 2040, particularly for Black non-Hispanic Americans. Our estimates of avoided deaths due to air pollution emphasize the importance of policy timing, showing that thousands of lives can be saved by taking action in the near-term.

Risk assessment of PM2.5 from fossil energy consumption on the respiratory health of the elderly

Air pollution mainly comes from fossil energy consumption (FEC), and it brings great threat to public health. The respiratory system of the elderly is highly susceptible to the effects of air pollution due to the decline in body functions. PM2.5 is a major component of air pollution, so the study of the impact of PM2.5 generated by FEC on the respiratory health of the elderly is of great significance. The existing studies have focused more on the effect of PM2.5 on mortality, and this paper is a useful addition to the existing studies by examining the effect of PM2.5 from FEC on the health of the elderly from the perspective of prevalence. In this paper, the binary Logistic regression model was used to calculate the exposure-response relationship coefficient for respiratory health in older adults using the data in 2018 from the Chinese Longitudinal Healthy Longevity Survey. And referring to the Dynamic Projection model for Emissions in China, the changes in the number of older persons suffering from respiratory diseases due to PM2.5 from FEC in the baseline scenario, the clean air scenario, and the on-time peak-clean air scenario were predicted. The results indicated that: (1) PM2.5 from FEC mainly came from coal; (2) PM2.5 from FEC was detrimental to the respiratory health of the elderly, and older seniors were more affected as they age; (3) In the on-time peak-clean air scenario, the number of elderly people suffering from respiratory diseases due to PM2.5 from FEC was growing at the slowest rate. Based on the above results, this paper raised recommendations for reducing the effect of PM2.5 from FEC on the health of the elderly.

Source-Specific PM2.5 and Atherosclerotic Cardiovascular Disease Mortality

BACKGROUND

Fine particulate matter (PM2.5) exposure is adversely linked to atherosclerotic cardiovascular disease (ASCVD). However, most studies focused on PM2.5 mass rather than its chemical composition and specific sources. Particulate pollution sources can have distinct, cumulative, and potentially synergistic health impacts. We investigated the associations of source-specific PM2.5 exposure with ASCVD mortality in the United States, considering the combined associations and regional variations.

METHODS

We used data from the Centers for Medicare & Medicaid Services (including data from 65,838,403 participants) from 2000 to 2016. We estimated PM2.5 exposure using machine-learning models and attributed components to five source categories. We used Poisson survival models to assess the associations with the source categories.

RESULTS

Higher ASCVD mortality rate (rate ratio [95% confidence interval (CI)] per interquartile range increase) was associated with oil combustion (1.051 [1.049 to 1.052]), industrial pollution (1.054 [1.052 to 1.056]), coal and biomass burning (1.065 [1.062 to 1.067]), and motor vehicle pollution (1.044 [1.042 to 1.046]). These associations persisted even after limiting our sample to ZIP code-years with PM2.5<9 μg/m3 - the current National Ambient Air Quality Standard. In these areas the observed rate ratio for a one-unit increase in PM2.5 mass was 1.028 (95% CI, 1.026 to 1.029).

CONCLUSIONS

We found higher ASCVD mortality rate associated with PM2.5, with differential effects across sources. These data highlight the importance of considering local population characteristics and exposure patterns when assessing health risks associated with PM2.5.

Long-term exposures to low concentrations of source-specific air pollution, road-traffic noise, and systemic inflammation and cardiovascular disease biomarkers

OBJECTIVES

Air pollution and traffic noise are detrimental to cardiovascular health. However, the effects of different sources of these exposures on cardiovascular biomarkers remain unclear. We explored the associations of long-term exposure to source-specific air pollution (vehicular exhausts and residential woodsmoke) at low concentrations and road-traffic noise with systemic inflammation and cardiovascular disease biomarkers.

MATERIAL AND METHODS

Modeled outdoor exposure to fine particulate matter (aerodynamic diameter ≤2.5 μm; PM2.5) from vehicular exhausts and residential woodsmoke, nitrogen dioxide (NO2) from road traffic, and road-traffic noise were linked to the home addresses of the participants (Finnish residents aged 25-74) in the FINRISK study 1997-2012. The participants were located in the cities of Helsinki, Vantaa, and the region of Turku, Finland. The outcomes were high-sensitivity C-reactive protein (CRP), a biomarker for systemic inflammation, and cardiovascular disease biomarkers N-terminal pro-B-type natriuretic peptide (NT-proBNP) and troponin I. We performed cross-sectional analyses with linear and additive models and adjusted for potential confounders.

RESULTS

We found no association between PM2.5 from vehicular exhausts (% CRP difference for 1 μg/m3 increase in PM2.5: -0.9, 95% confidence interval, CI: -7.2, 5.8), or from residential woodsmoke (% difference: -8.1, 95% CI: -21.7, 7.9) and CRP (N = 4147). Road-traffic noise >70 dB tended to be positively associated with CRP (% CRP difference versus noise reference category of ≤45 dB: 18.3, 95% CI: -0.5, 40.6), but the association lacked significance and robustness (N = 7142). Otherwise, we found no association between road-traffic noise and CRP, nor between NO2 from road traffic and NT-proBNP (N = 1907) or troponin I (N = 1951).

CONCLUSION

Long-term exposures to source-specific, fairly low-level air pollution from vehicular exhausts and residential woodsmoke, or road-traffic noise were not associated with systemic inflammation and cardiovascular disease biomarkers in this urban area.

Individual and joint exposures to PM2.5 constituents and mortality risk among the oldest-old in China

Cohort evidence linking long-term survival of older adults with exposure to fine particulate matter (PM2.5) constituents remains scarce in China. By constructing a dynamic cohort based on the Chinese Longitudinal Healthy Longevity Study, we aimed to assess the individual and joint associations of major PM2.5 constituents with all-cause death in Chinese oldest-old (.80 years) adults. Time-dependent Cox proportional hazards models were adopted to estimate death risks of long-term exposure to PM2.5 constituents. Among 14,884 participants, totaling 56,342 person-years of follow-up, 12,346 deaths were identified. The highest mortality risk associated with an interquartile range (IQR) increase in exposure was 1.081 (95% confidence interval [CI]: 1.055-1.108) for sulfate (IQR=4.1 μg m-3), followed by 1.078 (95% CI: 1.056-1.101) for black carbon (IQR=1.6 μg m-3), 1.056 (95% CI: 1.028-1.084) for ammonium (IQR=3.2 μg m-3), 1.050 (95% CI: 1.021-1.080) for nitrate (IQR=5.8 μg m-3), and 1.049 (95% CI: 1.024-1.074) for organic matter (IQR=10.3 μg m-3). In joint exposure, each IQRequivalent rise of all five PM2.5 constituents was associated with an 8.2% (95% CI: 4.0%-12.6%) increase in mortality risk. The weight analysis indicated the predominant role of sulfate and black carbon in driving PM2.5-related mortality. Octogenarians (aged 80-89 years) and rural dwellers were at significantly greater risk of mortality from individual and joint exposures to PM2.5 constituents. This study suggests that later-life exposure to PM2.5 constituents, particularly sulfate and black carbon, may curtail long-term survival of the oldest-old in China.

Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis

In recent years, the precision of exposure assessment methods has been rapidly improved and more widely adopted in epidemiological studies. However, such methodological advancement has introduced additional heterogeneity among studies. The precision of exposure assessment has become a potential confounding factors in meta-analyses, whose impacts on effect calculation remain unclear. To explore, we conducted a meta-analysis to integrate the long- and short-term exposure effects of PM2.5, NO2, and O3 on all-cause, cardiovascular, and respiratory mortality in the Chinese population. Literature was identified through Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure before August 28, 2023. Sub-group analyses were performed to quantify the impact of exposure assessment precisions and pollution levels on the estimated risk. Studies achieving merely city-level resolution and population exposure are classified as using traditional assessment methods, while those achieving sub-kilometer simulations and individual exposure are considered finer assessment methods. Using finer assessment methods, the RR (under 10 μg/m3 increment, with 95% confidence intervals) for long-term NO2 exposure to all-cause mortality was 1.13 (1.05-1.23), significantly higher (p-value = 0.01) than the traditional assessment result of 1.02 (1.00-1.03). Similar trends were observed for long-term PM2.5 and short-term NO2 exposure. A decrease in short-term PM2.5 levels led to an increase in the RR for all-cause and cardiovascular mortality, from 1.0035 (1.0016-1.0053) and 1.0051 (1.0021-1.0081) to 1.0055 (1.0035-1.0075) and 1.0086 (1.0061-1.0111), with weak between-group significance (p-value = 0.13 and 0.09), respectively. Based on the quantitative analysis and literature information, we summarized four key factors influencing exposure assessment precision under a conceptualized framework: pollution simulation resolution, subject granularity, micro-environment classification, and pollution levels. Our meta-analysis highlighted the urgency to improve pollution simulation resolution, and we provide insights for researchers, policy-makers and the public. By integrating the most up-to-date epidemiological research, our study has the potential to provide systematic evidence and motivation for environmental management.

Modification of gut and airway microbiota on ozone-induced airway inflammation

Ground-level ozone (O3) has been shown to induce airway inflammation, the underlying mechanisms remain unclear. The aim of this study was to determine whether gut and airway microbiota dysbiosis, and airway metabolic alterations were associated with O3-induced airway inflammation. Thirty-six 8-week-old male C57BL/6 N mice were divided into 2 groups: sterile water group and broad-spectrum antibiotics group (Abx). Each group was further divided into two subgroups, filtered air group (Air) and O3 group (O3), with 9 mice in each subgroup. Mice in the Air and O3 groups were exposed to filtered air or 1 ppm O3, 4 h/d for 5 consecutive days, respectively. Mice in Abx + Air and Abx + O3 groups were exposed to filtered air or O3, respectively, after drinking broad-spectrum Abx. 24 h after the final O3 exposure, mouse feces and bronchoalveolar lavage fluids (BALF) were collected and subjected to measurements of airway oxidative stress and inflammation biomarkers, 16S rRNA sequencing and metabolite profiling. Hematoxylin-eosin staining of lung tissues was applied to examine the pathological changes of lung tissue. The results showed that O3 exposure resulted in airway oxidative stress and inflammation, as well as gut and airway microbiota dysbiosis, and airway metabolism alteration. Abx pre-treatment markedly changed gut and airway microbiota and promoted O3-induced metabolic disorder and airway inflammation. Spearman correlation analyses indicated that inter-related gut and airway microbiota dysbiosis and airway metabolic disorder were associated with O3-induced airway inflammation. Together, inhaled O3 causes airway inflammation, which may implicate gut and airway microbiota dysbiosis and airway metabolic alterations.

Environmental Risk Factors for Acute Respiratory Distress Syndrome

Several environmental exposures increase susceptibility to the acute respiratory distress syndrome (ARDS). Specifically, chronic exposure to ambient air pollution, cigarette smoke, and alcohol "prime" the lung via epithelial injury, endothelial dysfunction, and immunomodulatory mechanisms, increasing the risk and severity of ARDS following an array of acute insults. Future research of these pathways may reveal therapeutic targets. Relevant emerging threats, such as electronic cigarettes and vaping, wildfire smoke, and the environmental hazards associated with climate change, may also be associated with ARDS. Building upon existing public policy interventions can prevent substantial morbidity and mortality from ARDS.

Midlife and late-life environmental exposures on dementia risk in the Wisconsin Longitudinal Study: The modifying effects of ApoE

INTRODUCTION

Late-life air pollution exposure is associated with an increased risk for dementia, with this effect exacerbated among apolipoprotein E-4 (ApoE-4) carriers. However, whether midlife occupational exposures likewise influence dementia outcomes, and varies as a function of ApoE-4 status is unknown.

METHODS

Using data from 3814 participants in the Wisconsin Longitudinal Study (WLS), we employed weighted logistic regression to evaluate associations between midlife occupational respiratory exposures and late-life air pollution on all-cause dementia risk, stratified by ApoE-4 status.

RESULTS

Midlife occupational exposure was associated with increased odds of all-cause dementia preferentially among ApoE-4 noncarriers (odds ratio [OR] = 1.59, p = 0.01), whereas higher late-life urban air pollution exposure was associated with increased dementia risk among ApoE-4 carriers (OR = 1.258, p = 0.029).

DISCUSSION

Associations between environmental exposures and dementia risk vary based on the timing of exposure and ApoE-4 status. While late-life environmental exposures are associated with dementia among ApoE-4 carriers, for noncarriers midlife environmental exposure confers the greatest risk.

HIGHLIGHTS

The effect of adult environmental respiratory exposures on subsequent dementia risk varies as a function of both ApoE-4 carrier status and exposure timing. Midlife occupational exposure to respiratory hazards is preferentially associated with increased dementia odds among ApoE-4 noncarriers. Late-life exposure to ambient air pollution is associated with dementia risk, but only among ApoE-4 carriers. While higher exposure to PM2.5 increases the risk for dementia, higher exposure to ozone was associated with reduced risk for dementia among ApoE-4 carriers.

The temporal trend and disparity in short-term health impacts of fine particulate matter in California (2006-2019)

Most epidemiological studies assume that the relationship between short-term air pollution exposure and health outcomes is constant over time, which ignores potential changes in population composition and particulate matter emission sources. Limited studies have assessed changes in the relationship between fine particulate matter (PM2.5) and adverse health outcomes over time, with mixed results. Additionally, there is a need to identify which subgroups are disproportionately impacted over time by PM2.5-related health consequences. Therefore, we aimed to examine whether temporal trends exist in the relationships between daily PM2.5 exposure and circulatory and respiratory acute care utilization in California from 2006 to 2019. We further assessed whether certain subpopulations are more susceptible to PM2.5 exposure by demographic characteristics and extreme wildfire frequency. Daily PM2.5 concentrations estimated from a stacked ensemble model and daily cause-specific acute care utilization and demographic data from the California Department of Health Care Access and Information. We analyzed this relationship using modified two-stage Bayesian hierarchical models, where we first did not consider temporal trends, then stratified by two periods, and finally flexibly considered non-linear changes over time. Increases in circulatory (0.56 %; 95 % credible interval (CI): 0.17 %, 0.96 %) and respiratory acute care utilization risk (2.61 %; 95%CI: 2.29 %, 2.94 %) were found with every 10 μg/m3 increase in PM2.5 on the same day and previous two days. These risks were found to increase over time, where 0.13 % (95%CI: 0.02 %, 0.22 %) and 1.40 % (95%CI: 1.24 %, 1.54 %) increases were identified for circulatory and respiratory acute care utilizations, respectively, from the first (2006-2012) to second period (2013-2019). Differences by age, sex, race/ethnicity, and extreme wildfire frequency were noted. These findings confirm that air pollution guidelines should consider the dynamic nature of epidemiological dose-response and can provide insight for targeted air pollution control and adaptation policies designed to reduce PM2.5 exposure, particularly for the most susceptible subpopulations.

Comparison of associations between proximity to major roads and all-cause mortality across a spectrum of cardiovascular diseases

Background

Global urbanization is leading to increased exposure to traffic-related air pollution (TRAP), which is associated with adverse health events. While individuals with cardiovascular disease (CVD) are known to have elevated susceptibility to air pollution exposure, no studies have evaluated how mortality risks associated with TRAP exposure differ based on the presence of CVD.

Methods

We used three electronic health record-based cohorts to examine associations between proximity to major roadways and all-cause mortality. The three cohorts were a random sample of the hospital population, individuals with a prior myocardial infarction, and individuals with diagnosed heart failure (HF). We used Cox proportional hazards models to evaluate associations while adjusting for age, race, sex, and census block group socioeconomic status.

Results

Residing <250 m from a major roadway was associated with a hazard ratio (HR) of 1.13 (95% confidence interval = 1.05, 1.23) for individuals with HF, an HR of 1.07 (95% confidence interval = 0.96, 1.20) for those with a prior myocardial infarction, and an HR of 1.03 (95% confidence interval = 0.89, 1.20) for a random sample of hospital patients. This pattern persisted across several sensitivity analyses including alternative definitions of proximity to major roadways and matching the cohorts on demographics.

Conclusion

These results highlight the differences in air quality-related health risks based on underlying CVD. Individuals with HF consistently had the highest environmental health risks. These results may better inform risks related to TRAP exposure in populations with differing underlying CVD.

Assessment of long-term exposure to traffic-related air pollution: An exposure framework

BACKGROUND

Exposure to ambient air pollution is associated with morbidity and mortality, making it an important public health concern. Emissions from motorized traffic are a common source of air pollution but evaluating the contribution of traffic-related air pollution (TRAP) emissions to health risks is challenging because it is difficult to disentangle the contribution of individual air pollution sources to exposure contrasts in an epidemiological study.

OBJECTIVE

This paper describes a new framework to identify whether air pollution differences reflect contrasts in TRAP exposures. Because no commonly measured pollutant is entirely specific to on-road motor vehicles, this exposure framework combined information on pollutants, spatial scale (i.e., geographic extent), and exposure assessment methods and their spatial scale to determine whether the estimated effect of air pollution in a given study was related to differences in TRAP.

METHODS

The exposure framework extended beyond the near-road environment to include differences in exposure to TRAP at neighborhood resolution ( ≤ 5 km) across urban, regional, and national scales. It also embedded a stricter set of criteria to identify studies that provided the strongest evidence that exposure contrasts were related to differences in traffic emissions.

RESULTS

Application of the framework to the transparent selection of epidemiological studies for a systematic review produced insights on assessing and improving comparability of TRAP exposure measures, particularly for indirect measures such as distances from roads. It also highlighted study design challenges related to the duration of measurements and the structure of epidemiological models.

IMPACT STATEMENT

This manuscript describes a new exposure framework to identify studies of traffic-related air pollution, a case study of its application in an HEI systematic review, and its implications for exposure science and air pollution epidemiology experts. It identifies challenges and provides recommendations for the field going forward. It is important to bring this information to the attention of researchers in air pollution exposure science and epidemiology because applying the broader lessons learned will improve the conduct and reporting of studies going forward.

Capabilities of satellite Geostationary Environment Monitoring Spectrometer (GEMS) NO2 data for hourly ambient NO2 exposure modeling

The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary instrument that monitors hourly gaseous air pollutant levels, including nitrogen dioxide (NO2). Using the first-of-its-kind capabilities of GEMS NO2 data, we examined how well GEMS NO2 levels can explain the spatiotemporal variabilities in hourly NO2 concentrations in the Republic of Korea for the year 2022. A correlation analysis between hourly GEMS NO2 levels and ground NO2 concentrations showed a higher spatial correlation [Pearson r = 0.56 (SD = 0.20)] than a temporal one [Pearson r = 0.42 (SD = 0.14)], on average. To take advantage of the enhanced spatial predictability of GEMS NO2 data, we employed a mixed effects model to allow hour-specific relationships between GEMS NO2 and NO2 concentrations on a given day in each region and subsequently estimated hourly NO2 concentrations in all urban and rural areas. The 10-fold cross validation demonstrated R2 = 0.72, mean absolute error (MAE) = 3.7 ppb, and root mean squared error (RMSE) = 5.5 ppb. The hourly variations of the relationships were attributed particularly to those of wind speed among meteorological parameters considered in this study. The spatial distributions of hourly estimated NO2 concentrations were highly correlated between hours [average r = 0.91 (SD = 0.06)]. Nonetheless, they represented the diurnal patterns of urban versus rural NO2 contrasts during the day [urban/rural NO2 ratios from 1.22 (5 p.m.) to 1.37 (12 p.m.)]. The newly retrieved GEMS NO2 data enable temporally as well as spatially resolved NO2 exposure assessment. In combination with the time-activity patterns of individual subjects, the GEMS NO2 data can generate 'sub-population' exposure estimates and therefore enhance health effect studies.

Relationship between short-term ozone exposure, cause-specific mortality, and high-risk populations: A nationwide, time-stratified, case-crossover study

BACKGROUND

Previous studies reported that short-term exposure to ground-level ozone is associated with mortality risk. However, due to the limited monitored areas, existing studies were limited in assessing the nationwide risk and suggesting specific vulnerable populations to the ozone-mortality risk.

METHODS

We performed a nationwide time-stratified case-crossover study to evaluate the association between short-term ozone and cause-specific mortality in South Korea (2015-2019). A machine learning-ensemble prediction model (a test R2 > 0.96) was used to assess the short-term ozone exposure. Stratification analysis was conducted to examine the high-risk populations, and the excess mortality due to non-compliance with the WHO guideline was also assessed.

RESULTS

For all-cause mortality (1,343,077 cases), the risk associated with ozone (lag0- 1) was weakly identified (odd ratio: 1.005 with 95% CI: 0.997-1.014), and the risk was prominent in mortality with circulatory system diseases. In addition, based on the point estimates, the ozone-mortality risk was higher in people aged less than 65y, and this pattern was also observed in circulatory system disease deaths and urban areas.

CONCLUSIONS

This study provides national estimates of mortality risks associated with short-term ozone. Results showed that the benefits of stricter air quality standards could be greater in vulnerable populations.

The last decade of air pollution epidemiology and the challenges of quantitative risk assessment

Epidemiologic research and quantitative risk assessment play a crucial role in transferring fundamental scientific knowledge to policymakers so they can take action to reduce the burden of ambient air pollution. This commentary addresses several challenges in quantitative risk assessment of air pollution that require close attention. The background to this discussion provides a summary of and conclusions from the epidemiological evidence on ambient air pollution and health outcomes accumulated since the 1990s. We focus on identifying relevant exposure-health outcome pairs, the associated concentration-response functions to be applied in a risk assessment, and several caveats in their application. We propose a structured and comprehensive framework for assessing the evidence levels associated with each exposure-health outcome pair within a health impact assessment context. Specific issues regarding the use of global or regional concentration-response functions, their shape, and the range of applicability are discussed.

Air pollution exposure and head and neck cancer incidence

To investigate air pollution's effect in the form of PM2.5 (particulate matter measuring less than 2.5 microns) on head and neck aerodigestive cancer incidence, an epidemiological cohort analysis was performed using data from the Surveillance Epidemiology and End Results national cancer database from the years 2002-2012. The relationship between US county mean PM2.5 levels and head and neck cancer (HNC) incidence rates were examined using a linear mixed model. Lagged effect of the pollutant's effect on HNC incidence was analyzed. Our results showed a significant association between the incidence of HNC and certain subtypes with PM2.5 exposure after controlling for demographic characteristics, smoking and alcohol use. We observed the highest association at a 5-year lag period (β = 0.24, p value < 0.001). We observed significant associations at no lag (β = 0.16, p value = 0.02) and up to a 20-year lag period (β = 0.15, p value < 0.001). PM2.5 exposure is associated with an increased incidence of HNC, with the strongest association at a 5-year lag period. To better understand the relationships between exposure and cancer pathogenesis, further subgroup analysis is needed.

Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California

California's diverse geography and meteorological conditions necessitate models capturing fine-grained patterns of air pollution distribution. This study presents the development of high-resolution (100 m) daily land use regression (LUR) models spanning 1989-2021 for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California. These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. The modeling process incorporated historical air quality observations utilizing continuous regulatory, fixed site saturation, and Google Streetcar mobile monitoring data. The model performance (adjusted R2) for NO2, PM2.5, and O3 was 84 %, 65 %, and 92 %, respectively. Over the years, NO2 concentrations showed a consistent decline, attributed to regulatory efforts and reduced human activities on weekends. Traffic density and weather conditions significantly influenced NO2 levels. PM2.5 concentrations also decreased over time, influenced by aerosol optical depth (AOD), traffic density, weather, and land use patterns, such as developed open spaces and vegetation. Industrial activities and residential areas contributed to higher PM2.5 concentrations. O3 concentrations exhibited no significant annual trend, with higher levels observed on weekends and lower levels associated with traffic density due to the scavenger effect. Weather conditions and land use, such as commercial areas and water bodies, influenced O3 concentrations. To extend the prediction of daily NO2, PM2.5, and O3 to 1989, models were developed for predictors such as daily road traffic, normalized difference vegetation index (NDVI), Ozone Monitoring Instrument (OMI)-NO2, monthly AOD, and OMI-O3. These models enabled effective estimation for any period with known daily weather conditions. Longitudinal analysis revealed a consistent NO2 decline, regulatory-driven PM2.5 decreases countered by wildfire impacts, and spatially variable O3 concentrations with no long-term trend. This study enhances understanding of air pollution trends, aiding in identifying lifetime exposure for statewide populations and supporting informed policy decisions and environmental justice advocacy.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

ACPM Position Statement: Air Pollution and Environmental Justice

The American Lung Association's "State of the Air" 2023 report reveals almost 36% of Americans live with unhealthy levels of air pollution. Studies link air pollution with acute respiratory symptoms and exacerbation of respiratory and cardiovascular diseases. Differential air pollution exposures between white and nonwhite communities are significant components of environmental injustices. Even during the coronavirus disease 2019 (COVID-19) lockdown, when the United States experienced significant decreases in polluting activities, these differences persisted. The American College of Preventive Medicine's Science and Translation Committee conducted a nonsystematic literature review to explore initiatives addressing air pollution as a key component of environmental justice, the state of the science regarding health impacts, and evidence supporting mitigations to reduce those impacts. We recommend advocacy for cleaner energy sources and increasing green space; and increasing research, surveillance, and education and training on linkages between air pollutants and health. We recommend preventive medicine physicians raise awareness about increased risks of cardiovascular disease, cancer, asthma, and reduced lung function with air pollution exposure. Preventive medicine physicians may also educate patients and other practitioners about exposures, and how "conventional" disease prevention strategies may have unintended consequences; and influence healthcare leaders to improve efficiency and reduce emissions. We also recommend physicians utilize social determinants of health Z-Codes to capture environmental factors. Private payers should incorporate pollution exposure data into social determinants of health risk adjustments for Medicare Advantage programs. Medicaid agencies should develop provider recommendations for pediatric populations, and states should finance in-home interventions for asthma.

An ILC2-chitinase circuit restores lung homeostasis after epithelial injury

Environmental exposures increase the risk for severe lung disease, but specific drivers of persistent epithelial injury and immune dysfunction remain unclear. Here, we identify a feedback circuit triggered by chitin, a common component of airborne particles, that affects lung health after epithelial injury. In mice, epithelial damage disrupts lung chitinase activity, leading to environmental chitin accumulation, impaired epithelial renewal, and group 2 innate lymphoid cell (ILC2) activation. ILC2s, in turn, restore homeostasis by inducing acidic mammalian chitinase (AMCase) in regenerating epithelial cells and promoting chitin degradation, epithelial differentiation, and inflammatory resolution. Mice lacking AMCase or ILC2s fail to clear chitin and exhibit increased mortality and impaired epithelial regeneration after injury. These effects are ameliorated by chitinase replacement therapy, demonstrating that chitin degradation is crucial for recovery after various forms of lung perturbation. Thus, the ILC2-chitinase response circuit may serve as a target for alleviating persistent postinjury lung epithelial and immune dysfunction.

Long-Term Exposure to Nitrogen Dioxide and Ozone and Mortality: Update of the WHO Air Quality Guidelines Systematic Review and Meta-Analysis

Objectives

We performed a systematic review and meta-analysis on long-term exposure to nitrogen dioxide (NO2) and ozone (O3) with mortality, to expand evidence that informed 2021 the WHO Air Quality Guidelines and guide the Health Risks of Air Pollution in Europe project.

Methods

We included cohorts investigating NO2 and O3 mortality from all-causes, respiratory diseases, chronic obstructive pulmonary disease (COPD), acute lower respiratory infections (ALRI); and NO2 mortality from circulatory, ischemic heart, cerebrovascular diseases and lung cancer. We pooled estimates by random-effects models and investigated heterogeneity. We assessed the certainty of the evidence using the Grading of Recommendations Assessment Development approach and Evaluation (GRADE).

Results

We selected 83 studies for NO2 and 26 for O3 for the meta-analysis. NO2 was associated with all outcomes, except for cerebrovascular mortality. O3 was associated with respiratory mortality following annual exposure. There was high heterogeneity, partly explained by region and pollutant levels. Certainty was high for NO2 with COPD and ALRI, and annual O3 with respiratory mortality.

Conclusion

An increasing body of evidence, with new results from countrywide areas and the Western Pacific, supports certainty, including new outcomes.

Childhood Air Pollution Exposure Associated with Self-reported Bronchitic Symptoms in Adulthood

Rationale: Few studies have examined the effects of long-term childhood air pollution exposure on adult respiratory health, including whether childhood respiratory effects underlie this relation. Objectives: To evaluate associations between childhood air pollution exposure and self-reported adult bronchitic symptoms while considering child respiratory health in the Southern California Children's Health Study. Methods: Exposures to nitrogen dioxide (NO2), ozone, and particulate matter <2.5 μm and <10 μm in diameter (PM10) assessed using inverse-distance-squared spatial interpolation based on childhood (birth to age 17 yr) residential histories. Bronchitic symptoms (bronchitis, cough, or phlegm in the past 12 mo) were ascertained via a questionnaire in adulthood. Associations between mean air pollution exposure across childhood and self-reported adult bronchitic symptoms were estimated using logistic regression. We further adjusted for childhood bronchitic symptoms and asthma to understand whether associations operated beyond childhood respiratory health impacts. Effect modification was assessed for family history of asthma, childhood asthma, and adult allergies. Measurements and Main Results: A total of 1,308 participants were included (mostly non-Hispanic White [56%] or Hispanic [32%]). At adult assessment (mean age, 32.0 yr; standard deviation [SD], 4.7), 25% reported bronchitic symptoms. Adult bronchitic symptoms were associated with NO2 and PM10 childhood exposures. Odds ratios per 1-SD increase were 1.69 (95% confidence interval, 1.14-2.49) for NO2 (SD, 11.1 ppb) and 1.51 (95% confidence interval, 1.00-2.27) for PM10 (SD, 14.2 μg/m3). Adjusting for childhood bronchitic symptoms or asthma produced similar results. NO2 and PM10 associations were modified by childhood asthma, with greater associations among asthmatic individuals. Conclusions: Childhood NO2 and PM10 exposures were associated with adult bronchitic symptoms. Associations were not explained by childhood respiratory health impacts; however, participants with childhood asthma had stronger associations.

Long-term exposure to PM2.5 and mortality: a national health insurance cohort study

BACKGROUND

Previous studies with large data have been widely reported that exposure to fine particulate matter (PM2.5) is associated with all-cause mortality; however, most of these studies adopted ecological time-series designs or have included limited study areas or individuals residing in well-monitored urban areas. However, nationwide cohort studies including cause-specific mortalities with different age groups were sparse. Therefore, this study examined the association between PM2.5 and cause-specific mortality in South Korea using the nationwide cohort.

METHODS

A longitudinal cohort with 187 917 National Health Insurance Service-National Sample Cohort participants aged 50-79 years in enrolment between 2002 and 2019 was used. Annual average PM2.5 was collected from a machine learning-based ensemble model (a test R2 = 0.87) as an exposure. We performed a time-varying Cox regression model to examine the association between long-term PM2.5 exposure and mortality. To reduce the potential estimation bias, we adopted generalized propensity score weighting method.

RESULTS

The association with long-term PM2.5 (2-year moving average) was prominent in mortalities related to diabetes mellitus [hazard ratio (HR): 1.03 (95% CI: 1.01, 1.06)], circulatory diseases [HR: 1.02 (95% CI: 1.00, 1.03)] and cancer [HR: 1.01 (95% CI: 1.00, 1.02)]. Meanwhile, circulatory-related mortalities were associated with a longer PM2.5 exposure period (1 or 2-year lags), whereas respiratory-related mortalities were associated with current-year PM2.5 exposure. In addition, the association with PM2.5 was more evident in people aged 50-64 years than in people aged 65-79 years, especially in heart failure-related deaths.

CONCLUSIONS

This study identified the hypothesis that long-term exposure to PM2.5 is associated with mortality, and the association might be different by causes of death. Our result highlights a novel vulnerable population: the middle-aged population with risk factors related to heart failure.

Spatiotemporally Detailed Quantification of Air Quality Benefits of Emissions Reductions-Part I: Benefit-per-Ton Estimates for Canada and the U.S

The U.S. EPA's Community Multiscale Air Quality (CMAQ)-adjoint model is used to map monetized health benefits (defined here as benefits of reduced mortality from chronic PM2.5 exposure) in the form of benefits per ton (of emissions reduced) for the U.S. and Canada for NOx, SO2, ammonia, and primary PM2.5 emissions. The adjoint model provides benefits per ton (BPTs) that are location-specific and applicable to various sectors. BPTs show significant variability across locations, such that only 20% of primary PM2.5 emissions in each country makes up more than half of its burden. The greatest benefits in terms of BPTs are for primary PM2.5 reductions, followed by ammonia. Seasonal differences in benefits vary by pollutant: while PM2.5 benefits remain high across seasons, BPTs for reducing ammonia are much higher in the winter due to the increased ammonium nitrate formation efficiency. Based on our location-specific BPTs, we estimate a total of 91,000 U.S. premature mortalities attributable to natural and anthropogenic emissions.

The association of short-term increases in ambient PM2.5 and temperature exposures with stillbirth: racial/ethnic disparities among Medicaid recipients

Racial/ethnic disparities in the association between short-term (eg, days, weeks), ambient fine particulate matter (PM2.5) and temperature exposures and stillbirth in the United States have been understudied. A time-stratified, case-crossover design using a distributed lag nonlinear model (0- to 6-day lag) was used to estimate stillbirth odds due to short-term increases in average daily PM2.5 and temperature exposures among 118 632 Medicaid recipients from 2000 to 2014. Disparities by maternal race/ethnicity (Black, White, Hispanic, Asian, American Indian) and zip code-level socioeconomic status (SES) were assessed. In the temperature-adjusted model, a 10 μg m-3 increase in PM2.5 concentration was marginally associated with increased stillbirth odds at lag 1 (0.68%; 95% CI, -0.04% to 1.40%) and lag 2 (0.52%; 95% CI, -0.03 to 1.06) but not lag 0-6 (2.80%; 95% CI, -0.81 to 6.45). An association between daily PM2.5 concentrations and stillbirth odds was found among Black individuals at the cumulative lag (0-6 days: 9.26% 95% CI, 3.12%-15.77%) but not among other races or ethnicities. A stronger association between PM2.5 concentrations and stillbirth odds existed among Black individuals living in zip codes with the lowest median household income (lag 0-6: 14.13%; 95% CI, 4.64%-25.79%). Short-term temperature increases were not associated with stillbirth risk among any race/ethnicity. Black Medicaid enrollees, and especially those living in lower SES areas, may be more vulnerable to stillbirth due to short-term increases in PM2.5 exposure. This article is part of a Special Collection on Environmental Epidemiology.