Long-Term PM10 Exposure and Cause-Specific Mortality in the Latium Region (Italy): A Difference-in-Differences Approach

Assessing long-term effects of gaseous air pollution exposure on mortality in the United States using a variant of difference-in-differences analysis

Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010-1.126) for total mortality, 1.067 (1.009-1.128) for nonaccidental mortality, and 1.125 (1.060-1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

Long-term exposure to wildland fire smoke PM2.5 and mortality in the contiguous United States

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and non-accidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous U.S., 2007-2020. Controlling for non-smoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a non-linear association between 12-month moving average concentration of smoke PM2.5 and monthly non-accidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 μg/m3, non-accidental mortality increased by 0.16-0.63 and 2.11 deaths per 100,000 people per month when the 12-month moving average of PM2.5 concentration was of 0.1-5 and 5+ μg/m3, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 non-accidental deaths/year (95% CI: 6,754, 16,075) in the contiguous U.S. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 above. Positive interaction effects with extreme heat (monthly number of days with daily mean air temperature higher than the county's 90th percentile warm season air temperature) were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short- and long-term exposure.

Hidden danger: The long-term effect of ultrafine particles on mortality and its sociodemographic disparities in New York State

Although previous studies have shown increased health risks of particulate matters, few have evaluated the long-term health impacts of ultrafine particles (UFPs or PM0.1, ≤ 0.1 µm in diameter). This study assessed the association between long-term exposure to UFPs and mortality in New York State (NYS), including total non-accidental and cause-specific mortalities, sociodemographic disparities and seasonal trends. Collecting data from a comprehensive chemical transport model and NYS Vital Records, we used the interquartile range (IQR) and high-level UFPs (≥75 % percentile) as indicators to link with mortalities. Our modified difference-in-difference model controlled for other pollutants, meteorological factors, spatial and temporal confounders. The findings indicate that long-term UFPs exposure significantly increases the risk of non-accidental mortality (RR=1.10, 95 % CI: 1.05, 1.17), cardiovascular mortality (RR=1.11, 95 % CI: 1.05, 1.18) particularly for cerebrovascular (RR=1.21, 95 % CI: 1.10, 1.35) and pulmonary heart diseases (RR=1.33, 95 % CI: 1.13, 1.57), and respiratory mortality (borderline significance, RR=1.09, 95 % CI: 1.00, 1.18). Hispanics (RR=1.13, 95 % CI: 1.00, 1.29) and non-Hispanic Blacks (RR=1.40, 95 % CI: 1.16, 1.68) experienced significantly higher mortality risk after exposure to UFPs, compared to non-Hispanic Whites. Children under five, older adults, non-NYC residents, and winter seasons are more susceptible to UFPs' effects.

Relationships between long-term exposure to major PM2.5 constituents and outpatient visits and hospitalizations in Guangdong, China

Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.

Short-Term Exposure to Fine Particulate Matter and Nitrogen Dioxide and Mortality in 4 Countries

Importance

The association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space.

Objective

To estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach.

Design, Setting, and Participants

This cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023.

Exposure

Day-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations.

Main Outcomes and Measures

Day-to-day changes in county- or municipality-level all-cause mortality rates.

Results

Among the 8 963 352 deaths in the 4 study regions, a 10-μg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-μg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2).

Conclusions and Relevance

The findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.

Long-term exposure to ambient fine particulate matter constituents and mortality from total and site-specific gastrointestinal cancer

BACKGROUND

Ambient fine particulate matter (PM2.5) exposure has been associated with an increased risk of gastrointestinal cancer mortality, but the attributable constituents remain unclear.

OBJECTIVES

To investigate the association of long-term exposure to PM2.5 constituents with total and site-specific gastrointestinal cancer mortality using a difference-in-differences approach in Jiangsu province, China during 2015-2020.

METHODS

We split Jiangsu into 53 spatial units and computed their yearly death number of total gastrointestinal, esophagus, stomach, colorectum, liver, and pancreas cancer. Utilizing a high-quality grid dataset on PM2.5 constituents, we estimated 10-year population-weighted exposure to black carbon (BC), organic carbon (OC), sulfate, nitrate, ammonium, and chloride in each spatial unit. The effect of constituents on gastrointestinal cancer mortality was assessed by controlling time trends, spatial differences, gross domestic product (GDP), and seasonal temperatures.

RESULTS

Overall, 524,019 gastrointestinal cancer deaths were ascertained in 84.77 million population. Each interquartile range increment of BC (0.46 μg/m3), OC (4.56 μg/m3), and nitrate (1.41 μg/m3) was significantly associated with a 27%, 26%, and 34% increased risk of total gastrointestinal cancer mortality, respectively, and these associations remained significant in PM2.5-adjusted models and constituent-residual models. We also identified robust associations of BC, OC, and nitrate exposures with site-specific gastrointestinal cancer mortality. The mortality risk generally displayed increased trends across the total exposure range and rose steeper at higher levels. We did not identify robust associations for sulfate, ammonium, or chlorine exposure. Higher mortality risk ascribed to constituent exposures was identified in total gastrointestinal and liver cancer among women, stomach cancer among men, and total gastrointestinal and stomach cancer among low-GDP regions.

CONCLUSIONS

This study offers consistent evidence that long-term exposure to PM2.5-bound BC, OC, and nitrate is associated with total and site-specific gastrointestinal cancer mortality, indicating that these constituents need to be controlled to mitigate the adverse effect of PM2.5 on gastrointestinal cancer mortality.

Racial/ethnic disparities in PM2.5-attributable cardiovascular mortality burden in the United States

Average ambient fine particulate matter (PM2.5) concentrations have decreased in the US in recent years, but the health benefits of this improvement among different racial/ethnic groups are unknown. We estimate the associations between long-term exposure to ambient PM2.5 and cause-specific cardiovascular disease (CVD) mortality rate and assess the PM2.5-attributable CVD deaths by race/ethnicity across 3,103 US counties during 2001-2016 (n = 595,776 county-months). A 1 µg m-3 increase in PM2.5 concentration was associated with increases of 7.16 (95% confidence interval (CI): 3.81, 10.51) CVD deaths per 1,000,000 Black people per month, significantly higher than the estimates for non-Hispanic white people (1.76 (95% CI: 1.37, 2.15); difference in coefficients: 5.40 (95% CI: 2.03, 8.77), P = 0.001). No significant difference in this association was observed between Hispanic (2.66 (95% CI: -0.03, 5.35)) and non-Hispanic white people (difference in coefficients: 0.90 (95% CI: -1.81, 3.61), P = 0.523). From 2001 to 2016, the absolute disparity in PM2.5-attributable CVD mortality burden was reduced by 44.04% between non-Hispanic Black and white people and by 2.61% between Hispanic and non-Hispanic white people. However, in 2016, the burden remained 3.47 times higher for non-Hispanic Black people and 0.45 times higher for Hispanic people than for non-Hispanic white people. We call for policies that aim to reduce both exposure and vulnerability to PM2.5 for racial/ethnic minorities.

Long-term exposure to ambient fine particulate matter-bound polycyclic aromatic hydrocarbons and cancer mortality: A difference-in-differences approach

The association of ambient fine particulate matter (PM2.5) exposure with cancer mortality was controversial, which may ascribe to the difference in PM2.5 constituents. Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic constituents in PM2.5, which are suspected to account for PM2.5-induced cancer mortality but are yet to be investigated. We aimed to assess the association between long-term exposure to PM2.5-bound PAHs and cancer mortality and estimate the attributable mortality. A difference-in-differences approach was used to investigate the causal effect of long-term exposure to PM2.5-bound PAHs on cancer mortality. We divided Jiangsu province, China into 53 spatial units and summarized the annual number of cancer deaths in each spatial unit during 2016-2020. Annual population-weighted exposure to PM2.5-bound PAHs of each spatial unit was assessed by an inverse distance weighting method. The association between PM2.5-bound PAHs exposures and cancer mortality was evaluated by controlling spatial differences, temporal trends, PM2.5 mass exposures, temperatures, and socioeconomic status. Records of 793,269 cancer deaths were identified among 84.7 million population. Each ln-unit increase of exposure to total benzo[a]pyrene equivalents (∑BaPeq), total carcinogenic PAHs (∑PAH7c), and total PAHs (∑PAHs) was significantly associated with a 3.21%, 3.48%, and 2.64% increased risk of cancer mortality, respectively; the risk increased monotonically at low-level exposures but attenuated or flattened afterward (all p for nonlinearity <0.05). Similar exposure-response associations were identified for specific PAHs except that the associations for both fluoranthene and benzo[a]anthracene were linear. We estimated that exposure to ∑BaPeq, ∑PAH7c, and ∑PAHs contributed to 5.73%, 8.73%, and 7.33% of cancer deaths, respectively. In conclusion, long-term exposure to PM2.5-bound PAHs was associated with an increased risk of cancer mortality and contributed to substantial cancer deaths. Our findings highlight the importance to prevent deaths from cancer by reducing PM2.5-bound PAHs exposures and the necessity to take into consideration specific constituents in particulate pollution management in future.

Potential causal links between long-term ambient particulate matter exposure and cerebrovascular mortality: Insights from a large cohort in southern China

Cohort studies conducted in North America and Europe have linked cerebrovascular mortality to long-term exposure to particulate matter (PM). However, limited evidence from large cohorts in high-exposure areas and the traditional approach of association assessment may cause residual confounding issues. In this study, we aimed to investigate the causal links between cerebrovascular mortality and long-term exposure to PM_2.5, PM₁₀, and PM_2.5-10 in an ongoing cohort study with 580,757 participants in southern China. Using satellite-based estimates of PM concentration at a 1-km² spatial resolution, we assigned exposure levels to each participant and used the marginal structural Cox model to assess the association between PM exposure and cerebrovascular mortality while accounting for time-varying covariates. We also explored the potential modification effects of sociodemographic and behavioral factors on the PM-health associations. Adjusted hazard ratios (HR) for overall cerebrovascular mortality were 1.041 (95% confidence interval (CI): 1.034-1.049) and 1.032 (95% CI: 1.026-1.038) for each 1 μg/m³ increase in PM_2.5, and PM₁₀, respectively. Similar trends were observed in the mortality risk from stroke and ischemic stroke, with HRs ranging from 1.040 to 1.069 and 1.025 to 1.052, respectively, across 2 p.m. exposures. The impact of PM exposure was generally more apparent among women, participants with primary school diplomas and below, and the subgroup under low-exposure. Multiple sensitivity analyses confirmed the robustness of the results. In conclusion, this sizable prospective cohort study hypothesizes causal links between long-term PM exposure and cerebrovascular mortality, particularly among vulnerable participants, supporting the rationale for reducing PM concentration in China to reduce cerebrovascular mortality.

The causal links between long-term exposure to major PM2.5 components and the burden of tuberculosis in China

BACKGROUND

We aimed to estimate the causal impacts of long-term exposure to major PM_2.5 components - including black carbon, organic matter, sulfate, nitrate, and ammonium - on the incidence and mortality of tuberculosis in China.

METHODS

We collected annual and provincial-level tuberculosis incidence and mortality, concentrations of PM_2.5 components, and socioeconomic indicators from between 2004 and 2018 in mainland China. We used the difference-in-differences (DID) causal inference approach with a generalized weighted quantile sum (gWQS) regression model to estimate the long-term effects and relative contributions of PM_2.5 components' exposure on tuberculosis incidence and mortality.

RESULTS

We found that long-term multi-components exposure was significantly associated with tuberculosis incidence (WQS index IR%:8.34 %, 95 % CI:4.54 %-12.27 %) and mortality (WQS index IR%:19.49 %, 95 % CI: 9.72 %-30.13 %). Primary pollutants, black carbon and organic matter, contributed most of the overall mixture effect (over 85 %). Nitrate showed a critical role in tuberculosis burden in not-aging provinces and in regions at the Q3 stratum (i.e., the 3rd quartile) of GDP per capita and urbanization rate. Meanwhile the contribution of sulfate to tuberculosis burden in regions at the Q1 stratum of GDP per capita and urbanization rate was the largest among the effect of secondary pollutants (i.e., sulfate, nitrate, and ammonium).

CONCLUSION

The mitigation of black carbon and organic matter pollution may significantly reduce the tuberculosis burden in China. Controlling nitrate emissions and increasing clean energy (i.e., energy sources with limited pollution emissions, such as natural gas and clean coal) may also be effective in certain regions.

Estimating the effect of increasing ambient temperature on antimicrobial resistance in China: A nationwide ecological study with the difference-in-differences approach

Antimicrobial resistance (AMR) and the possible consequences of rising ambient temperatures brought on by global warming have been extensively discussed. However, the epidemiological evidence on the effects of temperature on AMR is rare and little is known about the role of socioeconomic inequities. This ecological study obtained 31 provinces AMR data of Escherichia Coli (E. coli) from the China Antimicrobial Resistance Surveillance System (CARSS) over the period from 2014 to 2020, which were linked to the meteorological and socioeconomic data published in the China Statistical Yearbook. Modified difference-in-differences (DID) analyses were performed to estimate the effect of ambient temperature on AMR of E. coli to third-generation cephalosporins (ceftriaxone and cefotaxime), carbapenems, and quinolones, adjusting for variations in meteorological and socioeconomic factors. We estimated that every 1 °C increase in average ambient temperature was associated with 2.71 % (95 % confidence interval [CI]: 1.20-4.24), 32.92 % (95 % CI: 15.62-52.81), and 1.81 % (95 % CI: 0.47-3.16) increase in the prevalence of E. coli resistance to third-generation cephalosporins (ceftriaxone and cefotaxime), carbapenems and quinolones, respectively. The link was more profound in the regions with lower temperature and a median level of average humidity, and the regions with lower income, lower expenditure (in economics), lower health resources, and lower hospital admissions. Neither the replacement of the temperature variable nor the alternative approaches for confounding adjustment changed the positive association between ambient temperature and AMR. In general, there exists a positive association between ambient temperature and AMR, although the strength of such an association varies by socioeconomic and health services factors. The association is possibly nonlinear, especially for E. coli resistance to third-generation cephalosporins. The findings suggest that AMR control programs should explicitly incorporate weather patterns to increase their effectiveness.

Association between exposure to ambient PM2.5 and the health status in the mobile population from 338 cities in China

There are limited studies investigating the relationship between exposure to PM_2.5 and the health status among the mobile population. A cross-sectional analysis was performed in a nationally representative sample (2017 China Migrants Dynamic Survey data) consisting of 169,469 mobile population. The ordered logistic regression model was used to examine the association between PM_2.5 and the health status in mobile population. Stratified analyses were performed to identify whether the association varied across gender, age group, and regions in China. Overall, every 10 μg/m³ increment in annual average PM_2.5 was associated with increased risk of poor self-reported health (OR = 1.021, 95% CI: 1.012-1.030). Mobile population aged 31-49 years and living in the central region suffers the highest PM_2.5-associated health risk (OR = 1.030, 95% CI: 1.019-1.042; OR = 1.095, 95% CI: 1.075-1.116). Our study suggests that PM_2.5 exposure was associated with an increased risk of poor self-reported health in mobile population, particularly among the population aged 31-49 years and people living in the central region of China. Policymakers should pay more attention to the vulnerable mobile population to tackle the health burden of ambient air pollution.

Long-term exposure to fine particulate matter and site-specific cancer mortality: A difference-in-differences analysis in Jiangsu province, China

BACKGROUND

Accumulating studies have reported that chronic exposure to ambient fine particulate matter (PM_2.5) can lead to adverse effects on lung cancer mortality; however, such chronic effects are less clear for mortality from other site-specific cancers.

OBJECTIVE

To explore the causal effect of long-term PM_2.5 exposure on mortality from all-site and a variety of site-specific cancers in Jiangsu province, China during 2015-2020 using a difference-in-differences analysis.

METHODS

For each of 53 county-based spatial units in Jiangsu province, we calculated annual death counts for all-site cancer and 23 site-specific cancers. Using a validated high-resolution PM_2.5 grid dataset, long-term PM_2.5 exposure of a spatial unit within a given year was evaluated as the average of population-weighted annual concentrations during recent 10 years. Conditional Poisson regression models were employed to evaluate exposure-response associations adjusting for spatial and temporal variables, seasonal temperatures, relative humidity, and gross domestic product (GDP).

RESULTS

During the study period, we identified 947,337 adult cancer deaths in Jiangsu province. Each 1 μg/m³ increment in PM_2.5 exposure was significantly associated with a 2.7% increase in the risk of all-site cancer mortality. PM_2.5-mortality associations were also observed in cancer of lip, oral cavity and pharynx, stomach, colorectum, pancreas, lung, bone and joints, ovary, prostate, and lymphoma (all adjusted P < 0.05), with the relative risks ranging from 1.028 (95% confidence interval [CI]: 1.011, 1.046) for stomach cancer to 1.201 (95% CI: 1.120, 1.308) for bone and joints cancers. Exposure-response curves showed that these associations were close to linearity, though most of them had increasing slopes at high exposure levels. Overall, women and subjects in low GDP regions were more vulnerable to PM_2.5 exposures.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 contributes to a higher risk of mortality from multiple site-specific cancers.

Influence of Urbanization on the Spatial Distribution of Associations Between Air Pollution and Mortality in Beijing, China

This study investigated the influence of urbanization on the intra-city spatial distribution of associations between air pollution and mortality in Beijing, China. First, we utilized the generalized additive model to establish the exposure-response associations of PM_2.5, O₃, with nonaccidental and cardiorespiratory mortality between urban and suburban areas. Second, we assessed district-specific air pollution-related mortality and analyzed how these associations were affected by the degree of urbanization. Finally, we analyzed the changes in air pollution-related mortality before and after the enforcement of the Air Pollution Prevention and Control Action Plan (referred to as the Action Plan). The effect estimates of PM_2.5 for nonaccidental mortality were 0.20% (95% CI: 0.12-0.28) in urban areas and 0.46% (95% CI: 0.35-0.58) in suburban areas per 10 μg/m³ increase in PM_2.5 concentrations. The corresponding estimates of O₃ were 0.13% (95% CI: -0.04-0.29) in urban areas and 0.34% (95% CI: 0.12-0.56) in suburban areas per 10 μg/m³ increase in O₃ concentrations; however, the difference between the estimates of O₃ in urban and suburban areas was not statistically significant. The district-specific results suggested that the estimated risks increased along with urban vulnerability levels for the effects of PM_2.5. Implementing the Action Plan reduced the mortality risks of PM_2.5, but the risks of O₃ increased in some districts. However, the difference in the estimates between the pre- and post-emission reductions was not statistically significant. Our study indicated that populations living in less urbanized areas are more vulnerable to the adverse effects of air pollution in Beijing, particularly for PM_2.5.

Exposure to wildfire-related PM2.5 and site-specific cancer mortality in Brazil from 2010 to 2016: A retrospective study

BACKGROUND

Long-term exposure to fine particles ≤2.5 μm in diameter (PM2.5) has been linked to cancer mortality. However, the effect of wildfire-related PM2.5 exposure on cancer mortality risk is unknown. This study evaluates the association between wildfire-related PM2.5 and site-specific cancer mortality in Brazil, from 2010 to 2016.

METHODS AND FINDINGS

Nationwide cancer death records were collected during 2010-2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM2.5 concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM2.5 concentration was 2.38 μg/m3, and the annual non-wildfire-related PM2.5 concentration was 8.20 μg/m3. The RR for mortality from all cancers was 1.02 (95% CI 1.01-1.03, p < 0.001) per 1-μg/m3 increase of wildfire-related PM2.5 concentration, which was higher than the RR per 1-μg/m3 increase of non-wildfire-related PM2.5 (1.01 [95% CI 1.00-1.01], p = 0.007, with p for difference = 0.003). Wildfire-related PM2.5 was associated with mortality from cancers of the nasopharynx (1.10 [95% CI 1.04-1.16], p = 0.002), esophagus (1.05 [95% CI 1.01-1.08], p = 0.012), stomach (1.03 [95% CI 1.01-1.06], p = 0.017), colon/rectum (1.08 [95% CI 1.05-1.11], p < 0.001), larynx (1.06 [95% CI 1.02-1.11], p = 0.003), skin (1.06 [95% CI 1.00-1.12], p = 0.003), breast (1.04 [95% CI 1.01-1.06], p = 0.007), prostate (1.03 [95% CI 1.01-1.06], p = 0.019), and testis (1.10 [95% CI 1.03-1.17], p = 0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders.

CONCLUSIONS

Exposure to wildfire-related PM2.5 can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM2.5 was higher than for PM2.5 from non-wildfire sources.

Loss of life expectancy from PM2.5 in Brazil: A national study from 2010 to 2018

BACKGROUND

Long-term exposure to PM2.5 is proved to be linked with mortality. However, limited studies have estimated the PM2.5 related loss of life expectancy (LLE) and its changing trends. How much life expectancy would be improved if PM2.5 pollution is reduced to the new WHO air quality guideline (AQG) level is unclear.

METHODS

Data on deaths from all-causes, cancer, cardiovascular and respiratory diseases were collected from 5,565 Brazilian municipalities during 2010-2018. A difference-in-differences approach with quasi-Poisson regression was applied to examine the PM2.5-years of life lost (YLL) associations and PM2.5 associated LLE.

RESULTS

The annual PM2.5 concentration in each municipality from 2010 to 2018 was 7.7 µg/m3 in Brazil. Nationally, with each 10 μg/m3 increase in five-year-average (current and previous four years) concentrations of PM2.5, the relative risks (RRs) were 1.18 (95% CI: 1.15-1.21) for YLL from all-causes, 1.22 (1.16-1.28) from cancer, 1.12 (1.08-1.17) from cardiovascular and 1.17 (1.10-1.25) from respiratory diseases. Life expectancy could be improved by 1.09 (95% CI: 0.92-1.25) years by limiting PM2.5 concentration to the national lowest level (2.9 µg/m3), specifically, 0.20 (0.15-0.24) years for cancer, 0.16 (0.11-0.22) years for cardiovascular and 0.09 (0.05-0.13) years for respiratory diseases, with significant disparities across regions and municipalities. Life expectancy would be improved by 0.78 (0.66-0.90) years by setting the new WHO AQG PM2.5 concentration level of 5 μg/m3 as an acceptable threshold.

CONCLUSIONS

Using nationwide death records in Brazil, we found that long-term exposure to PM2.5 was associated with reduced life expectancy from all-causes, cancer, cardiovascular and respiratory diseases with regional inequalities and different trends. PM2.5 pollution abatement to below the WHO AQG level would improve this loss of life expectancy in Brazil.

Mortality burden due to long-term exposure to ambient PM2.5 above the new WHO air quality guideline based on 296 cities in China

OBJECTIVE

Quantifying the spatial and socioeconomic variation of mortality burden attributable to particulate matters with aerodynamic diameter ≤ 2.5 µm (PM2.5) has important implications for pollution control policy. This study aims to examine the regional and socioeconomic disparities in the mortality burden attributable to long-term exposure to ambient PM2.5 in China.

METHODS

Using data of 296 cities across China from 2015 to 2019, we estimated all-cause mortality (people aged ≥ 16 years) attributable to the long-term exposure to ambient PM2.5 above the new WHO air quality guideline (5 µg/m3). Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) by regional and socioeconomic levels were reported.

RESULTS

Over the period of 2015-2019, 17.0% [95% confidence interval (CI): 7.4-25.2] of all-cause mortality were attributable to long-term exposure to ambient PM2.5, corresponding to 1,425.2 thousand deaths (95% CI: 622.4-2,099.6), 103.5/105 (95% CI: 44.9-153.3) AMR, and 1006.9 billion USD (95% CI: 439.8-1483.4) total VSL per year. The AMR decreased from 120.5/105 (95% CI: 52.9-176.6) to 92.7/105 (95% CI:39.9-138.5) from 2015 to 2019. The highest mortality burden was observed in the north region (annual average AF = 24.2%, 95% CI: 10.8-35.1; annual average AMR = 137.0/105, 95% CI: 60.9-198.5). The highest AD and economic loss were observed in the east region (annual average AD = 390.0 thousand persons, 95% CI: 170.3-574.6; annual total VSL = 275.6 billion USD, 95% CI: 120.3-406.0). Highest AMR was in the cities with middle level of GDP per capita (PGDP)/urbanization. The majority of the top ten cities of AF, AMR and VSL were in high and middle PGDP/urbanization regions.

CONCLUSION

There were significant regional and socioeconomic disparities in PM2.5 attributed mortality burden among Chinese cities, suggesting differential mitigation policies are required for different regions in China.

Associations between long-term exposure to PM2.5 and site-specific cancer mortality: A nationwide study in Brazil between 2010 and 2018

Long-term exposure to PM_2.5 has been linked to lung cancer incidence and mortality, but limited evidence existed for other cancers. This study aimed to assess the association between PM_2.5 on cancer specific mortality. An ecological study based on the cancer mortality data collected from 5,565 Brazilian cities during 2010-2018 using a difference-in-differences approach with quasi-Poisson regression, was applied to examine PM_2.5-cancer mortality associations. Globally gridded annual average surface PM_2.5 concentration was extracted and linked with the residential municipality of participants in this study. Sex, age stratified and exposure-response estimations were also conducted. Totalling 1,768,668 adult cancer deaths records of about 208 million population living across 5,565 municipalities were included in this study. The average PM_2.5 concentration was 7.63 μg/m³ (standard deviation 3.32) with range from 2.95 μg/m³ to 28.5 μg/m³. With each 10 μg/m³ increase in three-year-average (current year and previous two years) concentrations of PM_2.5, the relative risks (RR) of cancer mortality were 1.16 (95% confidence interval [CI]: 1.11-1.20) for all-site cancers. The PM_2.5 exposure was significantly associated with several cancer-specific mortalities including oral, nasopharynx, oesophagus, and stomach, colon rectum, liver, gallbladder, larynx, lung, bone, skin, female breast, cervix, prostate, brain and leukaemia. No safe level of PM_2.5 exposure was observed in the exposure-response curve for all types of cancer. In conclusion, with nationwide cancer death records in Brazil, we found that long-term exposure to ambient PM_2.5 increased risks of mortality for many cancer types. Even low level PM_2.5 concentrations had significant impacts on cancer mortality.

A novel approach for assessing the spatiotemporal trend of health risk from ambient particulate matter components: Case of Hong Kong

The spatiotemporal assessment of health risk due to exposure to particulate matter (PM) components should be well studied because of the different toxicity among PM components. However, this research topic has long been overlooked. This study aimed to examine the spatiotemporal variability in ambient respirable PM (PM₁₀) components associated inhalation carcinogenic and non-carcinogenic risk (ICR and INCR) in Hong Kong over 2015-2019. The land-use regression (LUR) approach was adopted to predict the spatial distribution of PM₁₀ component concentrations for the period of 2015-2019, whereas the ICR and INCR values of PM₁₀ components were also estimated using the classic health risk assessment method. Both concentration of PM₁₀ and INCR of PM₁₀ components showed a general decreasing trend, while ICR of PM₁₀ components increased slightly over the study period. LUR-model-based spatial maps at 500 m × 500 m resolution revealed the important spatial variability in PM₁₀ and its eleven components, and their associated ICR and INCR values. High pollution levels and high ICR and INCR of studied PM₁₀ components were generally found in developed urban areas and along the road network. Despite the fact that the PM₁₀ concentrations met the Hong Kong annual PM₁₀ air quality objective of 50 μg/m³, there was still significant potential health risk from the studied PM₁₀ components. This study highlights the importance of taking PM component concentrations and associated inhalation health risk as well as PM mass concentrations into account for the perspective of air quality management and protecting public health.

Toxicology of respiratory system: Profiling chemicals in PM10 for molecular targets and adverse outcomes

Numerous studies have shown that the increasing trend of respiratory diseases have been closely associated with the endogenous toxic chemicals (polycyclic aromatic hydrocarbons, heavy metal ions, etc.) in PM₁₀. In the present study, we aim to determine the strong correlations between the chemicals in PM₁₀ and the adverse consequences. We used the ChemView DB, the ToxRef DB and a comprehensive literature analysis to collect, identify, and evaluate the chemicals in PM₁₀ and their adverse effects on respiratory system, and then used the ToxCast DB to analyze their bioactivity and key targets through 1192 molecular targets and cell characteristic endpoints. Meanwhile, the bioinformatics analysis were carried out on the molecular targets to screen out prevention and treatment targets. A total of 310 chemicals related to the respiratory system were identified. An unsupervised two-directional heatmap was constructed based on hierarchical clustering of 227 chemicals by their effect scores. A subset of 253 chemicals with respiratory system toxicity had in vitro bioactivity on 318 molecular targets that could be described, clustered and annotated in the heatmap and bipartite network, which were analyzed based on the protein information in UniProt KB database and the software of GO, STRING, and KEGG. These results showed that the chemicals in PM₁₀ have strong correlation with different types of respiratory system injury. The main pathways of respiratory system injury caused by PM₁₀ are the Calcium signaling pathway, MAPK signaling pathway, and PI3K-AKT signaling pathway, and the core proteins in which are likely to be the molecular targets for the prevention and treatment of damage caused by PM₁₀.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality

BACKGROUND

Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course.

OBJECTIVES

We aimed to assess the underlying effect of long-term exposure to NO₂ and PM₁₀ on the severity and mortality of COVID-19.

METHODS

A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO₂ and PM₁₀ and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated.

RESULTS

We found that the long-term exposure to PM₁₀ is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM₁₀ showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM₁₀ (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m³ in PM₁₀ concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths.

DISCUSSION

These results demonstrate that long-term PM₁₀ burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Age-specific effects of ozone on pneumonia in Korean children and adolescents: A nationwide time-series study

OBJECTIVES

The aim of this study was to estimate the age-specific effects of 8-hour maximum ozone levels on pneumonia in children and adolescents.

METHODS

We performed quasi-Poisson regression analyses for individuals of 0-4 years, 5-9 years, 10-14 years, and 15-19 years of age using nationwide time-series data from the Korea (2011-2015). We constructed distributed lag linear models employing a generalized difference-in-differences method and controlling for other air pollutants.

RESULTS

A 10.0-parts per billion increase in 8-hour maximum ozone levels was associated with a higher risk of hospital admissions due to pneumonia at 0-4 (relative risk [RR], 1.02; 95% confidence interval [CI], 1.01 to 1.03) and 5-9 years of age (RR, 1.06; 95% CI, 1.04 to 1.08), but not at 10-14 (RR, 1.01; 95% CI, 0.98 to 1.04) or 15-19 years of age (RR, 1.01; 95% CI, 0.97 to 1.06). The association between ozone and hospital admissions due to pneumonia was stronger in cool seasons (from November to April) than in warm seasons (from May to October), but was similar between boys and girls.

CONCLUSIONS

Short-term exposure to ozone was associated with a higher risk of pneumonia at 0-4 years and 5-9 years of age, but not at 10-14 years or 15-19 years of age. Our findings can help identify vulnerable periods, determine the target populations for public health interventions, and establish air pollution standards.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

Air pollution control efficacy and health impacts: A global observational study from 2000 to 2016

Particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5) concentrations vary between countries with similar carbon dioxide (CO₂) emissions, which can be partially explained by differences in air pollution control efficacy. However, no indicator of air pollution control efficacy has yet been developed. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics. A novel indicator, ambient population-weighted average PM_2.5 concentration per unit per capita CO₂ emission (PM_2.5/CO₂), was developed to assess country-specific air pollution control efficacy (abbreviated as APCI). We estimated and mapped the global average distribution of APCI and its changes during 2000-2016 across 196 countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between APCI and health metrics. APCI varied by country with an inverse association with economic development. APCI showed an almost stable trend globally from 2000 to 2016, with the low-income groups increased and several countries (China, India, Bangladesh) decreased. The Pearson correlation coefficients between APCI and life expectancy at birth (LE), infant-mortality rate (IMR), under-five year of age mortality rate (U5MR) and logarithm of per capita GDP (LPGDP) were -0.57, 0.65, 0.66, -0.59 respectively (all P values < 0.001). APCI could explain international variation of LE, IMR and U5MR. The associations between APCI and LE, IMR, U5MR were independent of per capita GDP and climatic factors. We consider APCI to be a good indicator for air pollution control efficacy given its relation to important population health indicators. Our findings provide a new metric to interpret health inequity across the globe from the point of climate change and air pollution control efficacy.

The impacts of long-term exposure to PM2.5 on cancer hospitalizations in Brazil

BACKGROUND

Long-term exposure to PM_2.5 has been linked to cancer incidence and mortality. However, it was unknown whether there was an association with cancer hospitalizations.

METHODS

Data on cancer hospitalizations and annual PM_2.5 concentrations were collected from 1,814 Brazilian cities during 2002-2015. A difference-in-difference approach with quasi-Poisson regression was applied to examine State-specific associations. The State-specific associations were pooled at a national level using random-effect meta-analyses. PM_2.5 attributable burden were estimated for cancer hospitalization admissions, inpatient days and costs.

RESULTS

We included 5,102,358 cancer hospitalizations (53.8% female). The mean annual concentration of PM_2.5 was 7.0 μg/m³ (standard deviation: 4.0 μg/m³). With each 1 μg/m³ increase in two-year-average (current year and previous one year) concentrations of PM_2.5, the relative risks (RR) of hospitalization were 1.04 (95% confidence interval [CI]: 1.02 to 1.07) for all-site cancers from 2002 to 2015 without sex and age differences. We estimated that 33.82% (95%CI: 14.97% to 47.84%) of total cancer hospitalizations could be attributed to PM_2.5 exposure in Brazil during the study time. For every 100,000 population, 1,190 (95%CI: 527 to 1,836) cancer hospitalizations, 8,191 (95%CI: 3,627 to 11,587) inpatient days and US$788,775 (95%CI: $349,272 to $1,115,825) cost were attributable to PM_2.5 exposure.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 was positively associated with hospitalization for many cancer types in Brazil. Inpatient days and cost would be saved if the annual PM_2.5 exposure was reduced.

Association between short-term exposure to ambient fine particulate matter and myocardial injury in the CATHGEN cohort

Exposure to fine particulate matter (PM_2.5) has been associated with a higher risk for coronary events. Elevated circulating cardiac troponins (cTn) are suggestive of myocardial injury in both ischemic and non-ischemic conditions. However, little is known about the association between PM_2.5 and cTn. In this study, we investigated short-term PM_2.5 effects on cardiac troponin T (cTnT), as well as N-terminal-pro brain natriuretic peptide (NT-pro BNP) and inflammatory biomarkers among cardiac catheterized participants. We analyzed 7444 plasma cTnT measurements in 2732 participants who presented to Duke University Hospital with myocardial infarction symptoms between 2001 and 2012, partly along with measurements of NT-pro BNP and inflammatory biomarkers. Daily PM_2.5 concentrations were predicted by a neural network-based hybrid model and were assigned to participants' residential addresses. We applied generalized estimating equations to assess associations of PM_2.5 with biomarker levels and the risk of a positive cTnT test (cTnT > 0.1 ng/mL). The median plasma cTnT concentration at presentation was 0.05 ng/mL and the prevalence of a positive cTnT test was 35.4%. For an interquartile range (7.6 μg/m³) increase in PM_2.5 on the previous day, cTnT concentrations increased by 7.7% (95% CI: 3.4-12.3) and the odds ratio of a positive cTnT test was 1.08 (1.01-1.16). Participants under 60 years (effect estimate: 15.2%; 95% CI: 7.4-23.5) or living in rural areas (12.3%; 95% CI: 4.8-20.3) were more susceptible. There was evidence for increases in fibrinogen and NT-pro BNP associated with elevated PM_2.5 on the concurrent and previous two days. Our study suggests that acute PM_2.5 exposure may elevate indicators of myocardial tissue damage. This finding substantiates the association of air pollution exposure with adverse cardiovascular events.

Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties

BACKGROUND

Although the association between long-term exposure to PM_2.5 and mortality has been evaluated intensively, little is known about the socioeconomic disparity in the association.

METHODS

We collected data on annual all-cause mortality, PM_2.5 concentration, socioeconomic and demographic characteristics of 2640 counties from the two most recent Chinese censuses in 2000 and 2010. We applied the difference-in-differences (DID) method to estimate PM_2.5-mortality association for counties at different quartiles of literacy rate, college rate, urbanization rate and GDP per capita, respectively.

RESULTS

Overall, every 10 µg/m³ increase in annual average PM_2.5 was associated with 3.8% (95% confidence interval [CI]: 3.0-5.0) increase of all-cause mortality. The stratified analysis suggested higher health impact of exposure in counties with lower socioeconomic status. For counties of the lowest quartile (Q₁) of literacy rate, college rate, urbanization rate and GDP per capita, the effect estimates were 6.0% (95% CI: 4.2-7.7), 4.4% (95% CI: 2.8-6.0), 3.5% (95% CI: 2.0-5.1) and 4.9% (95% CI: 2.7-7.1), respectively. There was strong evidence for elevated risk in mortality associated with PM_2.5 of all socioeconomic factors in the lowest quartile (Q₁) compared with the highest quartile counties (Q₄) (p-value for difference < 0.05).

CONCLUSIONS

There was socioeconomic disparity in the PM_2.5-mortality association in China. Dwellers living in less developed counties are more vulnerable to long-term exposure to ambient PM_2.5 than those living in developed counties.

Effects of short-term fine particulate matter exposure on acute respiratory infection in children

BACKGROUND

Previous studies on the association between fine particulate matter (PM_2.5) exposure and acute respiratory infection in children are scarce and present inconsistent results. We estimated the association between short-term PM_2.5 exposure and acute respiratory infection among children aged 0-4 years using a difference-in-differences approach.

METHODS

We used data on the daily PM_2.5 concentrations, hospital admissions for acute respiratory infection, and meteorological factors of the 15 regions in the Republic of Korea (2013-2015). To estimate the cumulative effects, we used a difference-in-differences approach generalized to multiple spatial units (regions) and time periods (day) with distributed lag non-linear models.

RESULTS

With PM_2.5 levels of 20.0 μg/m³ as a reference, PM_2.5 levels of 30.0 μg/m³ were positively associated with the risk of acute upper respiratory infection (relative risk (RR) = 1.048, 95% confidence interval (CI): 1.028, 1.069) and bronchitis or bronchiolitis (RR = 1.060, 95% CI: 1.038, 1.082) but not with the risk of acute lower respiratory infection and pneumonia. PM_2.5 levels of 40.0 μg/m³ were also positively associated with the risk of acute upper respiratory infection (RR = 1.083, 95% CI: 1.046, 1.122) and bronchitis or bronchiolitis (RR = 1.094, 95% CI: 1.054, 1.136).

CONCLUSIONS

We found the associations of short-term PM_2.5 exposure with acute upper respiratory infection and bronchitis or bronchiolitis among children aged 0-4 years. As causal inference methods can provide more convincing evidence of the effects of PM_2.5 levels on respiratory infections, public health policies and guidelines regarding PM_2.5 need to be strengthened accordingly.

The association between long-term exposure to low-level PM2.5 and mortality in the state of Queensland, Australia: A modelling study with the difference-in-differences approach

BACKGROUND

To date, few studies have investigated the causal relationship between mortality and long-term exposure to a low level of fine particulate matter (PM2.5) concentrations.

METHODS AND FINDINGS

We studied 242,320 registered deaths in Queensland between January 1, 1998, and December 31, 2013, with satellite-retrieved annual average PM2.5 concentrations to each postcode. A variant of difference-in-differences (DID) approach was used to investigate the association of long-term PM2.5 exposure with total mortality and cause-specific (cardiovascular, respiratory, and non-accidental) mortality. We observed 217,510 non-accidental deaths, 133,661 cardiovascular deaths, and 30,748 respiratory deaths in Queensland during the study period. The annual average PM2.5 concentrations ranged from 1.6 to 9.0 μg/m3, which were well below the current World Health Organization (WHO) annual standard (10 μg/m3). Long-term exposure to PM2.5 was associated with increased total mortality and cause-specific mortality. For each 1 μg/m3 increase in annual PM2.5, we found a 2.02% (95% CI 1.41%-2.63%; p < 0.01) increase in total mortality. Higher effect estimates were observed in Brisbane than those in Queensland for all types of mortality. A major limitation of our study is that the DID design is under the assumption that no predictors other than seasonal temperature exhibit different spatial-temporal variations in relation to PM2.5 exposure. However, if this assumption is violated (e.g., socioeconomic status [SES] and outdoor physical activities), the DID design is still subject to confounding.

CONCLUSIONS

Long-term exposure to PM2.5 was associated with total, non-accidental, cardiovascular, and respiratory mortality in Queensland, Australia, where PM2.5 levels were measured well below the WHO air quality standard.