Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Cancer mortality risk from short-term PM2.5 exposure and temporal variations in Brazil

Although some studies have found that short-term PM2.5 exposure is associated with lung cancer deaths, its impact on other cancer sites is unclear. To answer this research question, this time-stratified case-crossover study used individual cancer death data between January 1, 2000, and December 31, 2019, extracted from the Brazilian mortality information system to quantify the associations between short-term PM2.5 exposure and cancer mortality from 25 common cancer sites. Daily PM2.5 concentration was aggregated at the municipality level as the key exposure. The study included a total of 34,516,120 individual death records, with the national daily mean PM2.5 exposure 15.3 (SD 4.3) μg/m3. For every 10-μg/m3 increase in three-day average PM2.5 exposure, the odds ratio (OR) for all-cancer mortality was 1.04 (95% CI 1.03-1.04). Apart from all-cancer deaths, PM2.5 exposure may impact cancers of oesophagus (1.04, 1.00-1.08), stomach (1.05, 1.02-1.08), colon-rectum (1.04, 1.01-1.06), lung (1.04, 1.02-1.06), breast (1.03, 1.00-1.06), prostate (1.07, 1.04-1.10), and leukaemia (1.05, 1.01-1.09). During the study period, acute PM2.5 exposure contributed to an estimated 1,917,994 cancer deaths, ranging from 0 to 6,054 cases in each municipality. Though there has been a consistent downward trend in PM2.5-related all-cancer mortality risks from 2000 to 2019, the impact remains significant, indicating the continued importance of cancer patients avoiding PM2.5 exposure. This nationwide study revealed a notable association between acute PM2.5 exposure and heightened overall and site-specific cancer mortality for the first time to our best knowledge. The findings suggest the importance of considering strategies to minimize such exposure in cancer care guidelines. ENVIRONMENTAL IMPLICATION: The 20-year analysis of nationwide death records in Brazil revealed that heightened short-term exposure to PM2.5 is associated with increased cancer mortality at various sites, although this association has gradually decreased over time. Despite the declining impact, the research highlights the persistent adverse effects of PM2.5 on cancer mortality, emphasizing the importance of continued research and preventive measures to address the ongoing public health challenges posed by air pollution.

Air pollution changes due to COVID-19 lockdowns and attributable mortality changes in four countries

COVID-19 lockdowns reduced nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions in many countries. We aim to quantify the changes in these pollutants and to assess the attributable changes in mortality in Jiangsu, China; California, U.S.; Central-southern Italy; and Germany during COVID-19 lockdowns in early 2020. Accounting for meteorological impacts and air pollution time trends, we use a machine learning-based meteorological normalization technique and the difference-in-differences approach to quantify the changes in NO2 and PM2.5 concentrations due to lockdowns. Using region-specific estimates of the association between air pollution and mortality derived from a causal modeling approach using data from 2015 to 2019, we assess the changes in mortality attributable to the air pollution changes caused by the lockdowns in early 2020. During the lockdowns, NO2 reductions avoided 1.41 (95% empirical confidence interval [eCI]: 0.94, 1.88), 0.44 (95% eCI: 0.17, 0.71), and 4.66 (95% eCI: 2.03, 7.44) deaths per 100,000 people in Jiangsu, China; California, U.S.; and Central-southern Italy, respectively. Mortality benefits attributable to PM2.5 reductions were also significant, albeit of a smaller magnitude. For Germany, the mortality benefits attributable to NO2 changes were not significant (0.11; 95% eCI: -0.03, 0.25), and an increase in PM2.5 concentrations was associated with an increase in mortality of 0.35 (95% eCI: 0.22, 0.48) deaths per 100,000 people during the lockdown. COVID-19 lockdowns overall improved air quality and brought attributable health benefits, especially associated with NO2 improvements, with notable heterogeneity across regions. This study underscores the importance of accounting for local characteristics when policymakers adapt successful emission control strategies from other regions.

Short term exposure to low level ambient fine particulate matter and natural cause, cardiovascular, and respiratory morbidity among US adults with health insurance: case time series study

OBJECTIVE

To estimate the excess relative and absolute risks of hospital admissions and emergency department visits for natural causes, cardiovascular disease, and respiratory disease associated with daily exposure to fine particulate matter (PM2.5) at concentrations below the new World Health Organization air quality guideline limit among adults with health insurance in the contiguous US.

DESIGN

Case time series study.

SETTING

US national administrative healthcare claims database.

PARTICIPANTS

50.1 million commercial and Medicare Advantage beneficiaries aged ≥18 years between 1 January 2010 and 31 December 2016.

MAIN OUTCOME MEASURES

Daily counts of hospital admissions and emergency department visits for natural causes, cardiovascular disease, and respiratory disease based on the primary diagnosis code.

RESULTS

During the study period, 10.3 million hospital admissions and 24.1 million emergency department visits occurred for natural causes among 50.1 million adult enrollees across 2939 US counties. The daily PM2.5 levels were below the new WHO guideline limit of 15 μg/m3 for 92.6% of county days (7 360 725 out of 7 949 713). On days when daily PM2.5 levels were below the new WHO air quality guideline limit of 15 μg/m3, an increase of 10 μg/m3 in PM2.5 during the current and previous day was associated with higher risk of hospital admissions for natural causes, with an excess relative risk of 0.91% (95% confidence interval 0.55% to 1.26%), or 1.87 (95% confidence interval 1.14 to 2.59) excess hospital admissions per million enrollees per day. The increased risk of hospital admissions for natural causes was observed exclusively among adults aged ≥65 years and was not evident in younger adults. PM2.5 levels were also statistically significantly associated with relative risk of hospital admissions for cardiovascular and respiratory diseases. For emergency department visits, a 10 μg/m3 increase in PM2.5 during the current and previous day was associated with respiratory disease, with an excess relative risk of 1.34% (0.73% to 1.94%), or 0.93 (0.52 to 1.35) excess emergency department visits per million enrollees per day. This association was not found for natural causes or cardiovascular disease. The higher risk of emergency department visits for respiratory disease was strongest among middle aged and young adults.

CONCLUSIONS

Among US adults with health insurance, exposure to ambient PM2.5 at concentrations below the new WHO air quality guideline limit is statistically significantly associated with higher rates of hospital admissions for natural causes, cardiovascular disease, and respiratory disease, and with emergency department visits for respiratory diseases. These findings constitute an important contribution to the debate about the revision of air quality limits, guidelines, and standards.

Fine and coarse particulate air pollution and hospital admissions for a wide range of respiratory diseases: a nationwide case-crossover study

BACKGROUND

The associations between fine and coarse particulate matter (PM2.5 and PM2.5-10) air pollution and hospital admissions for full-spectrum respiratory diseases were rarely investigated, especially for age-specific associations. We aim to estimate the age-specific associations of short-term exposures to PM2.5 and PM2.5-10 with hospital admissions for full-spectrum respiratory diseases in China.

METHODS

We conducted an individual-level case-crossover study based on a nationwide hospital-based registry including 153 hospitals across 20 provincial regions in China in 2013-20. We applied conditional logistic regression models and distributed lag models to estimate the exposure- and lag-response associations.

RESULTS

A total of 1 399 955 hospital admission records for various respiratory diseases were identified. The associations of PM2.5 and PM2.5-10 with total respiratory hospitalizations lasted for 4 days, and an interquartile range increase in PM2.5 (34.5 μg/m3) and PM2.5-10 (26.0 μg/m3) was associated with 1.73% [95% confidence interval (95% CI): 1.34%, 2.12%)] and 1.70% (95% CI: 1.31%, 2.10%) increases, respectively, in total respiratory hospitalizations over lag 0-4 days. Acute respiratory infections (i.e. pneumonia, bronchitis and bronchiolitis) were consistently associated with PM2.5 or PM2.5-10 exposure across different age groups. We found the disease spectrum varied by age, including rarely reported findings (i.e. acute laryngitis and tracheitis, and influenza) among children and well-established associations (i.e. chronic obstructive pulmonary disease, asthma, acute bronchitis and emphysema) among older populations. Besides, the associations were stronger in females, children and older populations.

CONCLUSIONS

This nationwide case-crossover study provides robust evidence that short-term exposure to both PM2.5 and PM2.5-10 was associated with increased hospital admissions for a wide range of respiratory diseases, and the spectra of respiratory diseases varied by age. Females, children and older populations were more susceptible.

It's electric! An environmental equity perspective on the lifecycle of our energy sources

Energy policy decisions are driven primarily by economic and reliability considerations, with limited consideration given to public health, environmental justice, and climate change. Moreover, epidemiologic studies relevant for public policy typically focus on immediate public health implications of activities related to energy procurement and generation, considering less so health equity or the longer-term health consequences of climate change attributable to an energy source. A more integrated, collective consideration of these three domains can provide more robust guidance to policymakers, communities, and individuals. Here, we illustrate how these domains can be evaluated with respect to natural gas as an energy source. Our process began with a detailed overview of all relevant steps in the process of extracting, producing, and consuming natural gas. We synthesized existing epidemiologic and complementary evidence of how these processes impact public health, environmental justice, and climate change. We conclude that, in certain domains, natural gas looks beneficial (e.g., economically for some), but when considered more expansively, through the life cycle of natural gas and joint lenses of public health, environmental justice, and climate change, natural gas is rendered an undesirable energy source in the United States. A holistic climate health equity framework can inform how we value and deploy different energy sources in the service of public health.

Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015)

BACKGROUND

Numerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention's complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges.

METHOD

We applied the parametric g-computation to estimate the cumulative risks of nonaccidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5 in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored the benefits of hypothetical intervention strategies compared with the natural course that a) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 μg/m3, 7.04 μg/m3, 5 μg/m3, and 4 μg/m3), and b) reduced the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the 3-y average PM2.5 concentration with 1-y lag at the postal code of respondents' annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders, including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication.

RESULTS

All hypothetical intervention strategies explored led to lower 11-y cumulative mortality risks than the estimated value under the natural course without intervention, with the smallest reduction of 0.20 per 1,000 participants (95% CI: 0.06, 0.34) under the threshold of 8.8 μg/m3, and the largest reduction of 3.40 per 1,000 participants (95% CI: -0.23, 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining the status quo, increased over time but flattened toward the end of the follow-up period. Estimates among those ≥65 years of age were greater with a similar pattern. Our estimates were robust to different model specifications.

DISCUSSION

We found evidence that any intervention further reducing the long-term exposure to PM2.5 would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real-world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research. https://doi.org/10.1289/EHP11095.

Long-term trends in mortality risk associated with short-term exposure to air pollution in 10 Japanese cities between 1977 and 2015

BACKGROUND AND AIM

Short-term associations between air pollution and mortality have been well reported in Japan, but the historical changes in mortality risk remain unknown. We examined temporal changes in the mortality risks associated with short-term exposure to four criteria air pollutants in selected Japanese cities.

METHODS

We collected daily mortality data for non-accidental causes (n = 5,748,206), cardiovascular (n = 1,938,743) and respiratory diseases (n = 777,266), and air pollutants (sulfur dioxide [SO₂], nitrogen dioxide [NO₂], suspended particulate matter [SPM], and oxidants [Ox]) in 10 cities from 1977 to 2015. We performed two-stage analysis with 5-year stratification to estimate the relative risk (RR) of mortality per 10-unit increase in the 2-day moving average of air pollutant concentrations. In the first stage, city-specific associations were assessed using a quasi-Poisson generalized linear regression model. In the second stage, city-specific estimates were pooled using a random-effects meta-analysis. Linear trend and ratio of relative risks (RRR) were computed to examine temporal changes.

RESULTS

When stratifying the analysis by every 5 years, average concentrations in each sub-period decreased for SO₂, NO₂, and SPM (14.2-2.3 ppb, 29.4-17.5 ppb, 52.1-20.6 μg/m³, respectively) but increased for Ox (29.1-39.1 ppb) over the study period. We found evidence of a negative linear trend in the risk of cardiovascular mortality associated with SPM across sub-periods. However, the risks of non-accidental and respiratory mortality per 10-unit increase in SPM concentration were significantly higher in the most recent period than in the earliest period. Other gaseous pollutants did not show such temporal risk change. The risks posed by these pollutants were slightly to moderately heterogeneous in the different cities.

CONCLUSIONS

The mortality risks associated with short-term exposure to SPM changed, with different trends by cause of death, in 10 cities over 39 years whereas the risks for other gaseous pollutants were relatively stable.

Time-varying association between fetal death and gestational exposure to ambient fine particles: a nationwide epidemiological study of 49 million fetuses in the contiguous US from 1989 to 2004

BACKGROUND

Gestational exposure to fine particulate matter (PM2.5) has been reported to be associated with an increased risk of fetal death in recent studies, but earlier studies in the past century have usually reported a non-significant association. As such, it remains unknown whether this adverse effect of PM2.5 exposure varies with time.

METHODS

Nearly 49.2 million eligible birth and fetal death records from 1989 to 2004 were selected from the United States (US) birth and fetal death certificate datasets. For each record, the level of prenatal exposure to PM2.5 was taken as the average concentration in the mother's residential county during the entire gestational period, according to well-established estimates of monthly levels across the contiguous US. We first stratified the dataset by the month of the last menstrual period (LMP) and then independently evaluated the nationwide association between PM2.5 exposure and fetal death within each stratum using five typical logit models: unadjusted, covariate-adjusted, propensity-score, double robust, and diagnostic-score models. Finally, we conducted a meta-analysis to pool estimated LMP-specific associations and explored how the overall association varied by LMP month.

RESULTS

Different models showed temporal heterogeneity in the estimated association between PM2.5 exposure and fetal death. According to the meta-analysis, double robust model estimates were more homogeneous than the rest, and thus the model outcome was recognized as the main result. For each 1-µg/m3 increase in prenatal exposure to PM2.5, the pooled odds ratio (OR) of fetal death was estimated to be 1.08 [95% confidence interval (CI): 1.05, 1.10]. The LMP-specific ORs exhibited a slightly increasing trend and a significant seasonal pattern. Compared with the pooled OR among samples with the LMP in spring, the estimates for summer, fall and winter were higher by 11.1% (95% CI: 6.2%, 16.3%), 27.8% (95% CI: 22.1%, 33.8%) and 28.8% (95% CI: 23.7%, 34.1%), respectively. We also found that temporal patterns in the association between PM2.5 exposure and fetal death could be explained by several population-level indicators or modifiers (i.e. ethnicity, maternal age, gestational weight gain, previous pregnancy of abnormal termination and diabetes).

CONCLUSIONS

Prenatal exposure to PM2.5 can increase the risk of fetal death. The effects of PM2.5 exposure may be modified by complex factors, which leads to a time-varying association.

Temporal Heterogeneity of Short-Term Effects of Particulate Matter on Stroke Outpatients in Seven Major Cities of the Republic of Korea

Although particulate matter (PM) is a major risk factor for stroke, its effects on hospital outpatients admitted for stroke have not been documented in Korea. In addition, recent studies have reported that the effects of PM₁₀ on circulatory mortality changed over time. We aimed to estimate the effects of PM₁₀ on stroke and their temporal heterogeneity in seven major cities of Korea during the period 2002-2015. The study period was divided into five years of moving time windows, and city-specific PM₁₀ effects on ischemic and hemorrhagic stroke outpatients were calculated. We pooled the estimates using meta-analysis and plotted them into a sequence to identify their temporal trends. A 10 µg/m³ increase of PM₁₀ was significantly associated with increments in hospital outpatients admitted for ischemic stroke (0.24%, 95% CI: 0.04%, 0.44%), but not for hemorrhagic stroke (0.33%, 95% CI: -0.06%, 0.73%). Effect estimates for strokes increased during the period 2003-2013 but decreased after. For the first time, we have estimated the effects of PM₁₀ on hospital outpatients admitted for stroke in Korea. The observed temporal trend in PM₁₀ effects was similar to patterns of circulatory mortality, suggesting that the temporal heterogeneity in PM₁₀ effects might be due to systematic causes rather than random fluctuations.

Extended two-stage designs for environmental research

BACKGROUND

The two-stage design has become a standard tool in environmental epidemiology to model multi-location data. However, its standard form is rather inflexible and poses important limitations for modelling complex risks associated with environmental factors. In this contribution, we illustrate multiple design extensions of the classical two-stage method, all implemented within a unified analytic framework.

METHODS

We extended standard two-stage meta-analytic models along the lines of linear mixed-effects models, by allowing location-specific estimates to be pooled through flexible fixed and random-effects structures. This permits the analysis of associations characterised by combinations of multivariate outcomes, hierarchical geographical structures, repeated measures, and/or longitudinal settings. The analytic framework and inferential procedures are implemented in the R package mixmeta.

RESULTS

The design extensions are illustrated in examples using multi-city time series data collected as part of the National Morbidity, Mortality and Air Pollution Study (NMMAPS). Specifically, four case studies demonstrate applications for modelling complex associations with air pollution and temperature, including non-linear exposure-response relationships, effects clustered at multiple geographical levels, differential risks by age, and effect modification by air conditioning in a longitudinal analysis.

CONCLUSIONS

The definition of several design extensions of the classical two-stage design within a unified framework, along with its implementation in freely-available software, will provide researchers with a flexible tool to address novel research questions in two-stage analyses of environmental health risks.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population

While associations between short-term exposure to fine particulate matter (PM_2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM_2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM_2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM_2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 μg/m³ increase in PM_2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM_2.5-related health burden. This study raises the importance of considering environmental justice issues in PM_2.5-related health impacts with respect to how associations may change over time.