Associations between Coarse Particulate Matter Air Pollution and Cause-Specific Mortality: A Nationwide Analysis in 272 Chinese Cities

Joint Effect of Short-Term Exposure to Fine Particulate Matter and Ozone on Mortality: A Time Series Study in 272 Chinese Cities

Short-term exposure to PM2.5 or O3 can increase mortality risk; however, limited studies have evaluated their interaction. A multicity time series study was conducted to investigate the synergistic effect of PM2.5 and O3 on mortality in China, using mortality data and high-resolution pollutant predictions from 272 cities in 2013-2015. Generalized additive models were applied to estimate associations of PM2.5 and O3 with mortality. Modification and interaction effects were explored by stratified analyses and synergistic indexes. Deaths attributable to PM2.5 and O3 were evaluated with or without modification of the other pollutant. The risk of total nonaccidental mortality increased by 0.70% for each 10 μg/m3 increase in PM2.5 when O3 levels were high, compared to 0.12% at low O3 levels. The effect of O3 on total nonaccidental mortality at high PM2.5 levels (1.26%) was also significantly higher than that at low PM2.5 levels (0.59%). Similar patterns were observed for cardiovascular or respiratory diseases. The relative excess risk of interaction and synergy index of PM2.5 and O3 on nonaccidental mortality were 0.69% and 1.31 with statistical significance, respectively. Nonaccidental deaths attributable to short-term exposure of PM2.5 or O3 when considering modification of the other pollutant were 28% and 31% higher than those without considering modification, respectively. Our results found synergistic effects of short-term coexposure to PM2.5 and O3 on mortality and suggested underestimations of attributable risks without considering their synergistic effects.

Differential associations of fine and coarse particulate air pollution with cause-specific pneumonia mortality: A nationwide, individual-level, case-crossover study

BACKGROUND

The connections between fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) and daily mortality of viral pneumonia and bacterial pneumonia were unclear.

OBJECTIVES

To distinguish the connections between PM2.5 and PM2.5-10 and daily mortality due to viral pneumonia and bacterial pneumonia.

METHODS

Using a comprehensive national death registry encompassing all areas of mainland China, we conducted a case-crossover investigation from 2013 to 2019 at an individual level. Residential daily particle concentrations were evaluated using satellite-based models with a spatial resolution of 1 km. To analyze the data, we employed the conditional logistic regression model in conjunction with polynomial distributed lag models.

RESULTS

We included 221,507 pneumonia deaths in China. Every interquartile range (IQR) elevation in concentrations of PM2.5 (lag 0-2 d, 37.6 μg/m3) was associated with higher magnitude of mortality for viral pneumonia (3.03%) than bacterial pneumonia (2.14%), whereas the difference was not significant (p-value for difference = 0.38). An IQR increase in concentrations of PM2.5-10 (lag 0-2 d, 28.4 μg/m3) was also linked to higher magnitude of mortality from viral pneumonia (3.06%) compared to bacterial pneumonia (2.31%), whereas the difference was not significant (p-value for difference = 0.52). After controlling for gaseous pollutants, their effects were all stable; however, with mutual adjustment, the associations of PM2.5 remained, and those of PM2.5-10 were no longer statistically significant. Greater magnitude of associations was noted in individuals aged 75 years and above, as well as during the cold season.

CONCLUSION

This nationwide study presents compelling evidence that both PM2.5 and PM2.5-10 exposures could increase pneumonia mortality of viral and bacterial causes, highlighting the more robust effects of PM2.5 and somewhat higher sensitivity of viral pneumonia.

Differentiating the impact of fine and coarse particulate matter on cause-specific cerebrovascular mortality: An individual-level, case-crossover study

BACKGROUND AND OBJECTIVES

Many studies suggested that short-term exposure to fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) was linked to elevated risk of cerebrovascular disease. However, little is known about the potentially differential effects of PM2.5 and PM2.5-10 on various types of cerebrovascular disease.

METHODS

We collected individual cerebrovascular death records for all residents in Shanghai, China from 2005 to 2021. Residential daily air pollution data were predicted from a satellite model. The associations between particulate matters (PM) and cerebrovascular mortality were investigated by an individual-level, time-stratified, case-crossover design. The data was analyzed by the conditional logistic regression combined with the distributed lag model with a maximum lag of 7 days. Furthermore, we explored the effect modifications by sex, age and season.

RESULTS

A total of 388,823 cerebrovascular deaths were included. Monotonous increases were observed for mortality of all cerebrovascular diseases except for hemorrhagic stroke. A 10 μg/m3 rise in PM2.5 was related to rises of 1.35% [95% confidence interval (CI): 1.04%, 1.66%] in mortality of all cerebrovascular diseases, 1.84% (95% CI: 1.25%, 2.44%) in ischemic stroke, 1.53% (95% CI: 1.07%, 1.99%) in cerebrovascular sequelae and 1.56% (95% CI: 1.08%, 2.05%) in ischemic stroke sequelae. The excess risk estimates per each 10 μg/m3 rise in PM2.5-10 were 1.47% (95% CI: 1.10%, 1.84%), 1.53% (95% CI: 0.83%, 2.24%), 1.93% (95% CI: 1.38%, 2.49%) and 2.22% (95% CI: 1.64%, 2.81%), respectively. The associations of both pollutants with all cerebrovascular outcomes were robust after controlling for co-pollutants. The associations were greater in females, individuals > 80 years, and during the warm season.

CONCLUSIONS

Short-term exposures to both PM2.5 and PM2.5-10 may independently increase the mortality risk of cerebrovascular diseases, particularly of ischemic stroke and stroke sequelae.

Projection of Mortality Burden Attributable to Nonoptimum Temperature with High Spatial Resolution in China

The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming.

Effects of ambient air pollution on the hospitalization risk and economic burden of mental disorders in Qingdao, China

OBJECTIVE

The aim of this study was to examine the impacts of short-term exposure to air pollutants on hospitalizations for mental disorders (MDs) in Qingdao, a Chinese coastal city, and to assess the corresponding hospitalization risk and economic cost.

METHODS

Daily data on MD hospitalizations and environmental variables were collected from January 1, 2015, to December 31, 2019. An overdispersed generalized additive model was used to estimate the association between air pollution and MD hospitalizations. The cost of illness method was applied to calculate the corresponding economic burden.

RESULTS

With each 10 μg/m3 increase in the concentration of fine particulate matter (PM2.5) at lag05, inhalable particulate matter (PM10) at lag0, sulfur dioxide (SO2) at lag06 and ozone (O3) at lag0, the corresponding relative risks (RRs) and 95% confidence intervals (CIs) were 1.0182 (1.0035-1.0332), 1.0063 (1.0001-1.0126), 1.0997 (1.0200-1.1885) and 1.0099 (1.0005-1.0194), respectively. However, no significant effects of nitrogen dioxide (NO2) or carbon monoxide (CO) were found. Stratified analysis showed that males were susceptible to SO2 and O3, while females were susceptible to PM2.5. Older individuals (≥ 45 years) were more vulnerable to air pollutants (PM2.5, PM10, SO2 and O3) than younger individuals (< 45 years). Taking the Global Air Quality Guidelines 2021 as a reference, 8.71% (2,168 cases) of MD hospitalizations were attributable to air pollutant exposure, with a total economic burden of 154.36 million RMB.

CONCLUSION

Short-term exposure to air pollution was associated with an increased risk of hospitalization for MDs. The economic advantages of further reducing air pollution are enormous.

Associations between fine particulate air pollution with small-airway inflammation: A nationwide analysis in 122 Chinese cities

Alveolar nitric oxide is a non-invasive indicator of small-airway inflammation, a key pathophysiologic mechanism underlying lower respiratory diseases. However, no epidemiological studies have investigated the impact of fine particulate matter (PM2.5) exposure on the concentration of alveolar nitric oxide (CANO). To explore the associations between PM2.5 exposure in multiple periods and CANO, we conducted a nationwide cross-sectional study in 122 Chinese cities between 2019 and 2021. Utilizing a satellite-based model with a spatial resolution of 1 × 1 km, we matched long-term, mid-term, and short-term PM2.5 exposure for 28,399 individuals based on their home addresses. Multivariable linear regression models were applied to estimate the associations between PM2.5 at multiple exposure windows and CANO. Stratified analyses were also performed to identify potentially vulnerable subgroups. We found that per interquartile range (IQR) unit higher in 1-year average, 1-month average, and 7-day average PM2.5 concentration was significantly associated with increments of 17.78% [95% confidence interval (95%CI): 12.54%, 23.26%], 8.76% (95%CI: 7.35%, 10.19%), and 4.00% (95%CI: 2.81%, 5.20%) increment in CANO, respectively. The exposure-response relationship curves consistently increased with the slope becoming statistically significant beyond 20 μg/m3. Males, children, smokers, individuals with respiratory symptoms or using inhaled corticosteroids, and those living in Southern China were more vulnerable to PM2.5 exposure. In conclusion, our study provided novel evidence that PM2.5 exposure in long-term, mid-term, and short-term periods could significantly elevate small-airway inflammation represented by CANO. Our results highlight the significance of CANO measurement as a non-invasive tool for early screening in the management of PM2.5-related inflammatory respiratory diseases.

Long-term exposure to ambient air pollution with sarcopenia among middle-aged and older adults in China

BACKGROUND

Few studies have examined the role of outdoor air pollution exposure in sarcopenia in Asia. We aimed to investigate the association of outdoor air pollutants exposure with sarcopenia among Chinese adults.

METHODS

This nationally population-representative study used data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015, 11,700 participants at least 45 years old from 125 Chinese cities were included. Sarcopenia status was identified according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Ambient annual average air pollutants including fine particulate matter (PM2.5), inhalable particles (PM10), coarse particulate matter (PMcoarse), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) were estimated by satellite models and ground-based measurements. Multinomial logistic regression models were performed to examine the associations of air pollutants exposure with different status of sarcopenia (including possible sarcopenia and sarcopenia). Stratified analyses were utilized to assess the effect modifiers.

RESULTS

Among the 11,700 participants (52.6% women), the average age was 61.0 years. Each 10 μg/m3 increment of annual PMcoarse was associated with a higher risk of possible sarcopenia (odds ratio (OR) = 1.08, 95% confidence interval (CI) 1.04-1.11). Stratified analyses showed a positive risk of possible sarcopenia in women after exposure to PM10, PMcoarse, and NO2. Ambient NO2 exposure was positively associated with sarcopenia (OR = 1.13, 95% CI 1.04-1.22) in those aged 65 years and older. However, we have not observed differences by sex, age, residence, smoking, and drinking. Robustness results were found for PMcoarse in the sensitivity analyses.

CONCLUSION

This nationwide study suggested that long-term exposure to outdoor air pollution, especially for PMcoarse, was associated with the risk of sarcopenia among Chinese adults. Our findings provide epidemiological implications for protecting healthy ageing by improving air quality.

Inflammatory response in mouse lungs to haze episodes under different backgrounds of particulate matter exposure

Particulate matter (PM) toxicity has mostly been investigated through in vitro exposure or tracheal infusion in animal models. However, given the complexity of ambient conditions, most animal studies do not mimic real-life PM exposure. In this work, we established a novel integrated exposure model to study the dynamic inflammatory response and defense strategies in ambient PM-exposed mice. Three groups of male C57BL/6 mice were kept in three chambers with pre-exposure to filtered air (FA), unfiltered air (UFA), or the air with a low PM concentration (PM2.5 ≤ 75 μg/m3) (LPM), respectively, for 37 days. Then all three groups of mice were exposed to haze challenge for 3 days, followed by exposure in filtered air for 7 days to allow recovery. Our results suggest that following a haze challenge, the defense strategies of mice of filtered air (FA) and low PM (LPM) groups comprised a form of "counterattack", whereas the response of the unfiltered air (UFA) group could be viewed as a "silence". While the latter strategy protected the lung tissues of mice from acute inflammatory damage, it also foreshadowed the development of chronic inflammatory diseases. These findings contribute to explaining previously documented PM-associated pathogenic mechanisms.

Short-Term Exposure to Ambient Air Pollution and Influenza: A Multicity Study in China

BACKGROUND

Air pollution is a major risk factor for planetary health and has long been suspected of predisposing humans to respiratory diseases induced by pathogens like influenza viruses. However, epidemiological evidence remains elusive due to lack of longitudinal data from large cohorts.

OBJECTIVE

Our aim is to quantify the short-term association of influenza incidence with exposure to ambient air pollutants in Chinese cities.

METHODS

Based on air pollutant data and influenza surveillance data from 82 cities in China over a period of 5 years, we applied a two-stage time series analysis to assess the association of daily incidence of reported influenza cases with six common air pollutants [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , SO 2 , CO, and O 3 ], while adjusting for potential confounders including temperature, relative humidity, seasonality, and holiday effects. We built a distributed lag Poisson model for one or multiple pollutants in each individual city in the first stage and conducted a meta-analysis to pool city-specific estimates in the second stage.

RESULTS

A total of 3,735,934 influenza cases were reported in 82 cities from 2015 to 2019, accounting for 72.71% of the overall case number reported in the mainland of China. The time series models for each pollutant alone showed that the daily incidence of reported influenza cases was positively associated with almost all air pollutants except for ozone. The most prominent short-term associations were found for SO 2 and NO 2 with cumulative risk ratios of 1.094 [95% confidence interval (CI): 1.054, 1.136] and 1.093 (95% CI: 1.067, 1.119), respectively, for each 10   μ g / m 3 increase in the concentration at each of the lags of 1-7 d. Only NO 2 showed a significant association with the daily incidence of influenza cases in the multipollutant model that adjusts all six air pollutants together. The impact of air pollutants on influenza was generally found to be greater in children, in subtropical cities, and during cold months.

DISCUSSION

Increased exposure to ambient air pollutants, particularly NO 2 , is associated with a higher risk of influenza-associated illness. Policies on reducing air pollution levels may help alleviate the disease burden due to influenza infection. https://doi.org/10.1289/EHP12146.

Criteria air pollutants and diabetes mortality classified by different subtypes and complications: A nationwide, case-crossover study

The associations between air pollution and diabetes mortality of different subtypes and complications were largely unclear. We performed an individual-level, time-stratified case-crossover study among over 0.9 million diabetes deaths from all administrative regions of Chinese mainland during 2013-2019. Daily concentrations of fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2) and ozone (O3) were obtained for each decedent using high-resolution prediction models. Conditional logistic regression models were utilized to analyze the data. Each interquartile range increment in PM2.5, PM2.5-10, NO2 and O3 concentrations on lag 0-2 d increased the risks of overall diabetes mortality by 2.81 %, 1.92 %, 3.96 % and 2.15 %, respectively. Type 2 diabetes had stronger associations with air pollution than type 1 diabetes. Air pollutants were associated with diabetic ketoacidosis and diabetic nephropathy, but not other complications. The exposure-response curves were approximately linear with a plateau at higher concentrations of PM2.5, PM2.5-10, and NO2, while the associations for O3 appear to be statistically significant beyond 60 μg/m3. This nationwide study reinforces the evidence of higher risks of acute diabetic events following short-term air pollution exposure. We identified differential effects of air pollutants on various subtypes and complications of diabetes, which require further mechanistic investigations.

Residential greenness mitigates mortality risk from short-term airborne particulate exposure: An individual-level case-crossover study

BACKGROUND

Studies suggested that greenness could reduce death risks related to ambient exposure to particulate matter (PM), while the available evidence was mixed across the globe and substantially exiguous in low- and middle-income countries. By conceiving an individual-level case-crossover study in central China, this analysis primarily aimed to quantify PM-mortality associations and examined the modification effect of greenness on the relationship.

METHODS

We investigated a total of 177,058 nonaccidental death cases from 12 counties in central China, 2008-2012. Daily residential exposures to PM2.5 (aerodynamic diameter <2.5 µm), PMc (aerodynamic diameter between 2.5 and 10 µm), and PM10 (aerodynamic diameter <10 µm) were assessed at a 1 × 1-km resolution through satellite-derived machine-learning models. Residential surrounding greenness was assessed using satellite-derived enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) at multiple buffer sizes (250, 500, and 1000 m). To quantify the acute mortality risks associated with short-term exposure to PM2.5, PMc, and PM10, a time-stratified case-crossover design was utilized in conjunction with a conditional logistic regression model in our main analyses. To investigate the effect modification of greenness on PM-mortality associations, we grouped death cases into low, medium, and high greenness levels using cutoffs of 25th and 75th percentiles of NDVI or EVI exposure, and examined potential effect heterogeneity in PM-related mortality risks among these groups.

RESULTS

Mean concentrations (standard deviation) on the day of death were 73.8 (33.4) μg/m3 for PM2.5, 43.9 (17.3) μg/m3 for PMc, and 117.5 (44.9) μg/m3 for PM10. Size-fractional PM exposures were consistently exhibited significant associations with elevated risks of nonaccidental and circulatory mortality. For every increase of 10-μg/m3 in PM exposure, percent excess risks of nonaccidental and circulatory mortality were 0.271 (95% confidence interval [CI]: 0.010, 0.533) and 0.487 (95% CI: 0.125, 0.851) for PM2.5 at lag-01 day, 0.731 (95% CI: 0.108, 1.359) and 1.140 (95% CI: 0.267, 2.019) for PMc at lag-02 day, and 0.271 (95% CI: 0.010, 0.533) and 0.386 (95% CI: 0.111, 0.662) for PM10 at lag-01 day, respectively. Compared to participants in the low-level greenness areas, those being exposed to higher greenness were found to be at lower PM-associated risks of nonaccidental and circulatory mortality. Consistent evidence for alleviated risks in medium or high greenness group was observed in subpopulations of female and younger groups (age <75).

CONCLUSIONS

Short-term exposure to particulate air pollution was associated with elevated risks of nonaccidental and circulatory death, and individuals residing in higher neighborhood greenness possessed lower risk of PM-related mortality. These findings emphasized the potential public health advantages through incorporating green spaces into urban design and planning.

The association between intermediate-term sulfur dioxide exposure and outpatient visits for Parkinson's disease: a time-series study in southwestern China

Parkinson's disease (PD) is the second most common human neurodegenerative disorder, and the pathogenesis of it remains poorly understood. Limited studies have shown that both long- and short-term exposure to air pollutants may be associated with increased risk of PD while lacking evidence on the effects of intermediate-term exposure. In this study, over-dispersed Poisson generalized additive models (GAMs) were applied to explore the association between intermediate-term sulfur dioxide (SO2) exposure and outpatient visits for PD in Chongqing, China, and further stratified analyses were performed by age and gender. A total of 39,984 PD cases from January 1, 2014, to December 31, 2019 (2191 days) were included. The association of intermediate-term SO2 exposure with outpatient visits for PD was statistically significant: per 1 μg/m3 increase of SO2 corresponded to 2.34% (95% CI: 0.88%, 3.80%) elevation in monthly PD outpatient visits at lag 0 (the concurrent month). Stratified analyses showed that the associations between SO2 and PD outpatient visits were stronger in younger (≤ 60 years) and female patients. In conclusion, intermediate-term SO2 exposure can be associated with an increased risk of PD outpatient visits. Our results highlight the importance of recognizing the role of intermediate-term SO2 exposure in the development of PD. In addition to focusing on the effects of long-term or short-term air pollutants, it is necessary to pay more attention to the health effects of intermediate-term exposure time windows of air pollutants, which will facilitate policy formulation and public health interventions for health risks.

Role of different mechanisms in pro-inflammatory responses triggered by traffic-derived particulate matter in human bronchiolar epithelial cells

BACKGROUND

Traffic-derived particles are important contributors to the adverse health effects of ambient particulate matter (PM). In Nordic countries, mineral particles from road pavement and diesel exhaust particles (DEP) are important constituents of traffic-derived PM. In the present study we compared the pro-inflammatory responses of mineral particles and DEP to PM from two road tunnels, and examined the mechanisms involved.

METHODS

The pro-inflammatory potential of 100 µg/mL coarse (PM10-2.5), fine (PM2.5-0.18) and ultrafine PM (PM0.18) sampled in two road tunnels paved with different stone materials was assessed in human bronchial epithelial cells (HBEC3-KT), and compared to DEP and particles derived from the respective stone materials. Release of pro-inflammatory cytokines (CXCL8, IL-1α, IL-1β) was measured by ELISA, while the expression of genes related to inflammation (COX2, CXCL8, IL-1α, IL-1β, TNF-α), redox responses (HO-1) and metabolism (CYP1A1, CYP1B1, PAI-2) was determined by qPCR. The roles of the aryl hydrocarbon receptor (AhR) and reactive oxygen species (ROS) were examined by treatment with the AhR-inhibitor CH223191 and the anti-oxidant N-acetyl cysteine (NAC).

RESULTS

Road tunnel PM caused time-dependent increases in expression of CXCL8, COX2, IL-1α, IL-1β, TNF-α, COX2, PAI-2, CYP1A1, CYP1B1 and HO-1, with fine PM as more potent than coarse PM at early time-points. The stone particle samples and DEP induced lower cytokine release than all size-fractionated PM samples for one tunnel, and versus fine PM for the other tunnel. CH223191 partially reduced release and expression of IL-1α and CXCL8, and expression of COX2, for fine and coarse PM, depending on tunnel, response and time-point. Whereas expression of CYP1A1 was markedly reduced by CH223191, HO-1 expression was not affected. NAC reduced the release and expression of IL-1α and CXCL8, and COX2 expression, but augmented expression of CYP1A1 and HO-1.

CONCLUSIONS

The results indicate that the pro-inflammatory responses of road tunnel PM in HBEC3-KT cells are not attributed to the mineral particles or DEP alone. The pro-inflammatory responses seem to involve AhR-dependent mechanisms, suggesting a role for organic constituents. ROS-mediated mechanisms were also involved, probably through AhR-independent pathways. DEP may be a contributor to the AhR-dependent responses, although other sources may be of importance.

The association between ambient pollutants and influenza transmissibility: A nationwide study involving 30 provinces in China

Background

The impact of exposure to ambient pollutants on influenza transmissibility is poorly understood. We aim to examine the associations of six ambient pollutants with influenza transmissibility in China and assess the effect of the depletion of susceptibles.

Methods

Provincial-level surveillance data on weekly influenza-like illness (ILI) incidence and viral activity were utilized to estimate the instantaneous reproduction number (R_t) using spline functions. Log-linear regression and the distributed lag non-linear model (DLNM) were employed to investigate the effects of ambient pollutants-ozone (O₃), particulate matter ≤2.5 μm (PM_2.5), particulate matter ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO)-on influenza transmissibility across 30 Chinese provinces from 2014 to 2019. Additionally, the potential effects of the depletion of susceptibles and regional characteristics were explored.

Results

There is a significantly positive correlation between influenza transmissibility and five distinct ambient pollutants: PM_2.5, PM₁₀, SO₂, CO, and NO₂. On average, these ambient pollutants explained percentages of the variance in R_t: 0.8%, 0.8%, 1.9%, 1.3%, and 1.4%, respectively. Conversely, O₃ was found to be negatively associated with R_t, explaining 1.5% of the variance in R_t. When controlling for the effect of susceptibles depletion, the effects of all pollutants were more pronounced. The effects of PM_2.5, PM₁₀, CO, and SO₂ were higher in the eastern and southern regions.

Conclusions

Most ambient pollutants may potentially contribute to the facilitation of human-to-human influenza virus transmission in China. This observed association was maintained even after adjusting for variation in the susceptible population.

Effect of short-term exposure to ambient air pollutants on non-accidental mortality in emergency department visits: a time-series study

Objectives

Exposure to air pollution has been linked to an increased risk of premature mortality. However, the acute effects of air pollution on the risk of non-accidental mortality have not been extensively researched in developing countries, and the findings thus far have been inconsistent. Therefore, this study aimed to examine the association between short-term exposure to six pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) and non-accidental mortality in Beijing, China.

Methods

Daily data on non-accidental deaths were gathered from 1 January 2017 to 31 December 2018. Air pollution data for the same period were collected from 35 fixed-site air quality monitoring stations in Beijing. Generalized additive models (GAM) based on Poisson regression were used to investigate the association between non-accidental mortality in emergency department visits and the daily average levels of air pollutants.

Results

There were 8,676 non-accidental deaths recorded during 2017-2018. After sensitivity analysis, short-term exposure to air pollutants, particularly gaseous pollutants, was linked to non-accidental mortality. Specifically, for every 10 μg/m³ increase (5 μg/m³ in SO₂, 0.5 mg/m³ in CO) of SO₂ (lag 04), NO₂ (lag 04), O₃ (lag 05), and CO (lag 04), the relative risk (RR) values were 1.054 (95% CI: 1.009, 1.100), 1.038 (95% CI: 1.013, 1.063), 1.032 (95% CI: 1.011, 1.054), and 1.034 (95% CI: 1.004, 1.066), respectively. In terms of causes of death, short-term exposure to NO₂, SO₂, and O₃ increased the risk of circulatory mortality. Further stratified analysis revealed that the stronger associations were presented in females for O₃ while in males for CO. People aged 65 and over were strongly associated with ambient air pollution.

Conclusions

Our study showed that ambient air pollutants were associated with non-accidental mortality. Our findings suggested that efforts to control gaseous pollution should be stepped up, and vulnerable groups should be the focus of health protection education.

Fine and coarse particulate air pollution and out-of-hospital cardiac arrest onset: a nationwide case-crossover study in China

Out-of-hospital cardiac arrest (OHCA) is a global public health concern. Nationwide studies on the effects of short-term exposure to particulate matter (PM) on OHCA risk are rare in regions with high PM levels, and evidence for coarse PM (PM_2.5-10) is limited and inconsistent. To evaluate the associations between fine PM (PM_2.5) and PM_2.5-10 and OHCA onset, a time-stratified case-crossover study was conducted on 77,261 patients with cardiac OHCA in 26 cities across China in 2020. Daily PM_2.5 and PM_2.5-10 concentrations were assessed with high-resolution and full-coverage PM estimations. Conditional logistic regression models were applied in analyses. Each interquartile range of PM increase in 3-day moving average was associated with an increased risk of cardiac OHCA onset of 2.37% (95% CI, 1.20-3.56%) for PM_2.5 and 2.12% (95% CI, 0.70-3.56%) for PM_2.5-10. Stratified analyses showed higher susceptibility in patients over 75 years for PM_2.5 exposure and with diabetes for PM_2.5-10. This first nationwide study in region with high PM levels and great PM variability found not only PM_2.5 but also PM_2.5-10 were associated with a higher risk of OHCA onset, which could add powerful epidemiological evidence to this field and provide new evidence for the formulation of air quality guidelines.

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.

microRNA-149-5p mediates the PM2.5-induced inflammatory response by targeting TAB2 via MAPK and NF-κB signaling pathways in vivo and in vitro

Epidemiological evidence has shown that fine particulate matter (PM2.5)-triggered inflammatory cascades are pivotal causes of chronic obstructive pulmonary disease (COPD). However, the specific molecular mechanism involved in PM2.5-induced COPD has not been clarified. Herein, we found that PM2.5 significantly downregulated miR-149-5p and activated the mitogen-activated protein kinase (MAPK) and nuclear factor-kappa B (NF-κB) signaling pathways and generated the inflammatory response in COPD mice and in human bronchial epithelial (BEAS-2B) cells. We determined that increased expression of interleukin-1β (IL-1β), IL-6, IL-8, and tumor necrosis factor-α (TNF-α) induced by PM2.5 was associated with decreased expression of miR-149-5p. The loss- and gain-of-function approach further confirmed that miR-149-5p could inhibit PM2.5-induced cell inflammation in BEAS-2B cells. The double luciferase reporter assay showed that miR-149-5p directly targeted TGF-beta-activated kinase 1 binding protein 2 (TAB2), which regulates the MAPK and NF-κB signaling pathways. We showed that miR-149-5p mediated the inflammatory response by targeting the 3'-UTR sequence of TAB2 and that it subsequently weakened the TAB2 promotor effect via the MAPK and NF-κB signaling pathways in BEAS-2B cells exposed to PM2.5. Thus, miR-149-5p may be a key factor in PM2.5-induced COPD. This study improves our understanding of the molecular mechanism of COPD.

Association between ambient air pollution and daily hospital visits for cardiovascular diseases in Wuhan, China: a time-series analysis based on medical insurance data

Although evidence showed the adverse effects of air pollution on cardiovascular disease (CVDs), few studies were based on medically insured populations. We applied a generalized additive Poisson model (GAM) to estimate the short-term effects of ambient air pollution on a group of medically insured population in Wuhan, China. We extracted daily air pollution data, meteorological data, and daily hospital visits for CVDs. We found that the ambient air pollutants sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ground-level ozone (O₃) particulate matter (PM) with an aerodynamic diameter ≤10 μm (PM₁₀), and those ≤2.5 μm (PM_2.5) all increased the risk of daily hospital visits for CVDs. We also found that the effect of air pollution on daily hospital visits for CVDs is greater in the cold season than in the warm season. Our findings can be used as evidence that supports the formulation of policies for air pollution and CVDs.

A stronger advance of urban spring vegetation phenology narrows vegetation productivity difference between urban settings and natural environments

Climate change is posing dramatic effects on terrestrial vegetation dynamics. The links between vegetation phenology or vegetation activity (growth) and climate change have been widely reported, yet, less is known about the impacts of phenological shifts on vegetation growth. Urban settings characterized by urban heat island and CO₂ dome are often used as ideal natural laboratories to understand how vegetation responds to global climate change. Here we assessed the impacts of phenology changes on vegetation growth in China using satellite phenology metrics and gross primary production (GPP) data from 2003 to 2018 and urban-natural contrast analysis. Compared with natural environments, phenological metrics (e.g., start/end of growing season (SOS/EOS), and the length of growing season (GSL), etc.) were observed to change more dramatically in urban environments. Furthermore, we found that GPP in both settings increased over time but with a higher increment in the urban environments, and the urban-natural vegetation productivity gap had been diminishing at a rate of 16.9 ± 6.76 g C m^-2 y^-1. The narrowing of the urban-natural GPP difference over time can be attributed to a more advanced SOS and extended GSL in urban settings than their natural counterparts, particularly SOS shift. These findings suggested that the distinct urban phenological shifts would become increasingly important in offsetting the loss of vegetation productivity induced by urbanization.

Will information interventions affect public preferences and willingness to pay for air quality improvement? An empirical study based on deliberative choice experiment

Environmental information is a prerequisite for public participation in air quality improvement, and the choice of such participation behavior is influenced by the intervention of environmental information. Nonetheless, there has been insufficient analysis of how information interventions affect public preferences and willingness to pay for air quality improvement. The combination of deliberative and choice experiment is used to explore the importance of information interventions for public participation in air quality improvement, and the changes in public preferences and willingness to pay for air quality improvement before and after information interventions are compared to analyze the impact of information interventions on evaluation results of air quality value. The results suggest that information interventions do alter the preferences and willingness of the public to pay for air quality improvement, significantly increasing the choice certainty of respondents and decreasing the protest response. In addition, women and high-income groups showed a stronger willingness to improve air quality after the information interventions, with 35.15 CNY, 44.07 CNY and 46.75 CNY increases in willingness to pay for improved urban green coverage rate, fewer haze days and reduced morbidity. The combination of deliberative information interventions and choice experiment will help improve the effectiveness of air quality value evaluation, stimulate public environmental awareness and willingness to participate, and the results will aid government environmental management.

Association between Air Pollution and Physical Activity and Sedentary Behavior among Adults Aged 60 Years or Older in China: A Cross-Sectional Study

BACKGROUND

Exposure to air pollution is associated with an increased risk of all-cause mortality in older adults. Promoting physical activity (PA) and avoiding sedentary behavior (SB) serve as key strategies to maintain and improve human health. However, ambient air pollution can adversely affect PA and SB, increasing the risks of health problems. This study aimed to visualize national spatial patterns of average AQI concentration, PA, and SB distributions and to examine the associations between air pollution and PA and SB in a national sample of Chinese older adults aged 60 years or older.

METHODS

We analyzed the data of the China Longitudinal Aging Social Survey 2020 (CLASS 2020), which sampled 11,399 older men and women from 30 cities in China. Moderate, vigorous, and light PA and SB were measured using the Chinese version of the International Physical Activity Questionnaire-Short Form (IPAQ-C). The environmental measures included the average hourly air quality index (AQI), PM_2.5, PM₁₀, and NO₂ (µg/m³). The data were analyzed using multivariable linear regression.

RESULTS

Increases in the standard deviations (±SD) of AQI, PM_2.5, PM₁₀, and NO₂ concentrations were associated with decreases in MVPA per week of -2.34 (95%CI = -3.36, -1.32), -2.58 (95%CI = -3.61, -1.55), -1.96 (95%CI = -3.05, -0.08), and -1.19 (95%CI = -2.06, -0.31) and decreases in LPA per week of -6.06 (95%CI = -7.15, -4.97), -4.86 (95%CI = -5.88, -3.85), -4.78 (95%CI = -5.89, -3.68), and -4.59 (95%CI = -5.57, -3.61) h/week, respectively. Increases in one SD of AQI, PM_2.5, PM₁₀, and NO₂ were associated with increases in SB per week of 1.32 (95%CI = 0.77, 1.88), 0.62 (95%CI = 0.09, 1.14), 1.03 (95%CI = 0.48, 1.59), and 0.98 (95%CI = 0.46, 1.49) h/week, respectively.

CONCLUSIONS

The spatial distributions of the average AQI concentration, MVPA, LPA, and SB are useful and allow environmental and health policymakers to identify the areas with the highest priority air pollution environmental equality concerns. AQI was positively associated with MVPA and LPA, and it was negatively associated with SB among older adults. AQI, PM_2.5, PM₁₀, and NO₂ were hardly associated with women's average time spent engaged in MVPA. Region-specific and multi-level health policy options are needed to reduce ambient air pollution by taking different types of pollutants into account in order to avoid changes in PA and SB in this population, especially in locations with high air pollution concentrations.

Association between short-term exposure to air pollutants and cause-specific daily mortality in Italy. A nationwide analysis

BACKGROUND/AIM

Daily air pollution has been linked with mortality from urban studies. Associations in rural areas are still unclear and there is growing interest in testing the role that air pollution has on other causes of death. This study aims to evaluate the association between daily air pollution and cause-specific mortality in all 8092 Italian municipalities.

METHODS

Natural, cardiovascular, cardiac, ischemic, cerebrovascular, respiratory, metabolic, diabetes, nervous and psychiatric causes of death occurred in Italy were extracted during 2013-2015. Daily ambient PM₁₀, PM_2.5 and NO₂ concentrations were estimated through machine learning algorithms. The associations between air pollutants and cause-specific mortality were estimated with a time-series approach using a two-stage analytic protocol where area-specific over-dispersed Poisson regression models where fit in the first stage, followed by a meta-analysis in the second. We tested for effect modification by sex, age class and the degree of urbanisation of the municipality.

RESULTS

We estimated a positive association between PM₁₀ and PM_2.5 and the mortality from natural, cardiovascular, cardiac, respiratory and nervous system causes, but not with metabolic or psychiatric causes of death. In particular, mortality from nervous diseases increased by 4.55% (95% CI: 2.51-6.63) and 9.64% (95% CI: 5.76-13.65) for increments of 10 μg/m³ in PM₁₀ and PM_2.5 (lag 0-5 days), respectively. NO₂ was positively associated with respiratory (6.68% (95% CI: 1.04-12.62)) and metabolic (7.30% (95% CI: 1.03-13.95)) mortality for increments of 10 μg/m³ (lag 0-5). Higher associations with natural mortality were found among the elderly, while there were no differential effects between sex or between rural and urban areas.

CONCLUSIONS

Short-term exposure to particulate matter was associated with mortality from nervous diseases. Mortality from metabolic diseases was associated with NO₂ exposure. Other associations are confirmed and updated, including the contribution of lowly urbanised areas. Health effects were also found in suburban and rural areas.

Synergism of cell adhesion regulatory genes and instant air pollutants on blood pressure elevation

Accumulating evidence suggests that an instant exposure to particulate matter (PM) may elevate blood pressure (BP), where cell-adhesion regulatory genes may be involved in the interplay. However, few studies to date critically examined their interaction, and it remained unclear whether these genes modified the association. To assess the association between instant PM exposure and BP, and to examine whether single-nucleotide polymorphisms (SNPs) mapped in four cell adhesion regulatory genes modify the relationship, a cross-sectional study was performed, based on the baseline of an ongoing family-based cohort in Beijing, China. A total of 4418 persons from 2089 families in Northern China were included in the analysis. Four tagged SNPs in cell adhesion regulatory genes were selected among ZFHX3, CXCL12, RASGRP1 and MIR146A. A generalized additive model (GAM) with a Gaussian link was adopted to estimate the change in blood pressure after instant PM_2.5 or PM₁₀ exposure. A cross-product term of PM_2.5/PM₁₀ and genotype was incorporated into the GAM model to test for interaction. The study observed that an instant exposure to either PM_2.5 or PM₁₀ was found to be associated with elevated systolic blood pressure (SBP). On average, a 10 μg/m³ increase in instant exposure to PM_2.5 and PM₁₀ concentration corresponded to 0.140% (95% CI: 0.014%-0.265%, P = 0.029) and 0.173% (95% CI: 0.080%-0.266%, P < 0.001) higher SBP. However, diastolic blood pressure (DBP) was not elevated as the PM_2.5 or PM₁₀ concentration increased (P > 0.05). A synergetic interaction on SBP was observed between SNPs in four cell adhesion regulatory genes (rs2910164 in MIR146A, rs2297630 in CXCL12, rs7403531 in RASGRP1, and rs7193343 in ZFHX3) and instant PM_2.5 exposure (P_{for interaction} <0.05). Briefly, as carriers of risk alleles in each of these four genes increased, an enhanced association was found between instant PM_2.5 exposure and SBP.

Influence of air pollution on influenza-like illness in China: a nationwide time-series analysis

BACKGROUND

Evidence concerning effects of air pollution on influenza-like illness (ILI) from multi-center is limited and little is known about how regional factors might modify this relationship.

METHODS

In this ecological study, ILI cases defined as outpatients with temperature ≥38 °C, accompanied by cough or sore throat, were collected from National Influenza Surveillance Network in China. We adopted generalized additive model with quasi-Poisson to estimate province-specific association between air pollution and ILI in 30 Chinese provinces during 2015-2019, after adjusting for time trend and meteorological factors. We then pooled province-specific association by using random-effect meta-analysis. Potential effect modifications of season and regional characteristics were explored.

FINDINGS

A total of 26, 004, 853 ILI cases and 777, 223, 877 hospital outpatients were collected. In general, effects of air pollutants were acute. An inter-quartile range increase of PM_2.5, SO₂, PM₁₀, NO₂ and CO at lag0, and O₃ at lag0-2 was associated with 3.08% (95% CI: 1.91%, 4.27%), 3.00% (1.86%, 4.16%), 6.46% (4.71%, 8.25%), 7.21% (5.73%, 8.71%), 4.37% (3.05%, 5.70%), and -9.26% (-11.32%, -7.14%) change of ILI at national level, respectively. Associations between air pollutants and ILI varied by season and regions, with higher effect estimates in cold season, eastern and central regions and provinces with more humid condition and larger population.

INTERPRETATION

This study indicated that most air pollutants increased the risk of ILI in China. Our findings might provide implications for the development of policies to protect public health from air pollution and influenza.

FUNDING

National Natural Science Foundation of China and Chongqing Health Commission Program.

Protective effect and mechanism of baicalin on lung inflammatory injury in BALB/cJ mice induced by PM2.5

The public health harms caused by fine particulate matter (PM2.5) have become a global focus, with PM2.5 exposure recognized as a critical risk factor for global morbidity and mortality. Chronic inflammation is the common pathophysiological feature of respiratory diseases induced by PM2.5 and is the most critical cause of all these diseases. However, presently there is a lack of effective preventive and therapeutic approaches for inflammatory lung injuries caused by PM2.5 exposure. Baicalin is a herb-derived effective flavonoid compound with multiple health benefits. This study established a murine lung inflammatory injury model via inhalation of PM2.5 aerosols. The data showed that after baicalin intervention, lung injury pathological score of baicalin (4.16 ± 0.54, 3.33 ± 0.76, 4.00 ± 0.45) and claricid (3.00 ± 0.78) treatments were markedly lower than PM2.5-treated mice (6.17 ± 0.31), and pathological damage was alleviated. Compared to the PM2.5 group, the spleen and lung indexes in the baicalin and claricid groups were significantly reduced. The inflammatory cytokines of TNF-α, IL-18, and IL-1β in serum, alveolar lavage fluid, and lung tissue were significantly decreased in the baicalin and claricid groups. The expressions of inflammatory pathway-related genes and proteins HMGB1, NLRP3, ASC, and caspase-1 were up-regulated in the PM2.5 group. The expressions of these genes and proteins were significantly decreased following baicalin treatment. The lung function indicators showed that the MV (65.94 ± 8.19 mL), sRaw (1.79 ± 0.08 cm H2O^.s), and FRC (0.52 ± 0.01 mL) in the PM2.5 group were higher than in the control and baicalin groups, and respiratory function was improved by baicalin. PM2.5 exposure markedly altered the bacterial composition at the genus level. The dominant flora relative abundances of uncultured_bacterium_f_Muribaculaceae, Streptococcus, and Lactobacillus, were decreased from the control group (9.20%, 8.53%, 6.21%) to PM2.5 group (6.26%, 5.49%, 4.77%), respectively. Following baicalin intervention, the relative abundances were 9.72%, 6.65%, and 3.57%, respectively. Therefore, baicalin could potentially prevent and improve mice lung inflammatory injury induced by PM2.5 exposure. Baicalin might provide a protective role by balancing oropharyngeal microbiota and affecting the expression of the HMGB1/Caspase1 pathway.

Association and interaction of O3 and NO2 with emergency room visits for respiratory diseases in Beijing, China: a time-series study

BACKGROUND

Ozone (O₃) and nitrogen dioxide (NO₂) are the two main gaseous pollutants in the atmosphere that act as oxidants. Their short-term effects and interaction on emergency room visits (ERVs) for respiratory diseases remain unclear.

METHODS

We conducted a time-series study based on 144,326 ERVs for respiratory diseases of Peking University Third Hospital from 2014 to 2019 in Beijing, China. Generalized additive models with quasi-Poisson regression were performed to analyze the association of O₃, NO₂ and their composite indicators (O_x and O_x^wt) with ERVs for respiratory diseases. An interaction model was further performed to evaluate the interaction between O₃ and NO₂.

RESULTS

Exposure to O₃, NO₂, O_x and O_x^wt was positively associated with ERVs for total respiratory diseases and acute upper respiratory infection (AURI). For instance, a 10 μg/m³ increase in O₃ and NO₂ were associated with 0.93% (95%CI: 0.05%, 1.81%) and 5.87% (95%CI: 3.92%, 7.85%) increase in AURI at lag0-5 days, respectively. Significant linear exposure-response relationships were observed in O_x and O_x^wt over the entire concentration range. In stratification analysis, stronger associations were observed in the group aged < 18 years for both O₃ and NO₂, in the warm season for O₃, but in the cold season for NO₂. In interaction analysis, the effect of O₃ on total respiratory emergency room visits and AURI visits was the strongest at high levels (> 75% quantile) of NO₂ in the < 18 years group.

CONCLUSIONS

Short-term exposure to O₃ and NO₂ was positively associated with ERVs for respiratory diseases, particularly in younger people (< 18 years). This study for the first time demonstrated the synergistic effect of O₃ and NO₂ on respiratory ERVs, and O_x and O_x^wt may be potential proxies.

Short-term effect of air pollution on childhood epilepsy in eastern China: A space-time-stratified case-crossover and pooled analysis

BACKGROUND

Growing studies suggest that air pollution exposure is an emerging driver for neurological diseases, but existing evidence on the association between air pollution and epilepsy is scarce. Here, we aimed to quantitatively estimated the short-term effects of various air pollutants on childhood epilepsy hospitalizations in China.

METHODS

We obtained daily electronic health records on childhood epilepsy hospitalizations and air pollutants (PM_2.5, PM_10-2.5, PM₁₀, SO₂, NO₂, O₃) from 2016 through 2018 in 10 cities of Anhui Province in China. In the first stage, a space-time-stratified case-crossover analysis was employed to evaluate the short-term association of childhood epilepsy hospitalizations with each air pollutant in Anhui Province. In the second stage, short-term effect of air pollution on childhood epilepsy morbidity reported in Anhui Province and in previous studies was pooled with a random-effect meta-analysis model to get the overall effect of different air pollutants in eastern China.

RESULTS

This study included 8,181 childhood epilepsy patients from 10 cities in Anhui province of China. The first stage case-crossover analysis in Anhui province found significant associations between higher concentrations of all air pollutants (except O₃) and increased risk of childhood epilepsy hospitalizations. Each 10 μg/m³ increase in PM_2.5, PM_10-2.5, PM₁₀, SO₂, and NO₂ concentrations was associated with an increase of 1.1 % [95 % confidence interval (CI): 0.1 %-2.1 %], 1.7 % (95 %CI: 0.5 %-2.9 %), 0.8 % (95 %CI: 0.1 %-1.4 %), 8.5 % (95 %CI: 1.5 %-16.0 %), and 4.3 % (95 %CI: 2.3 %-6.3 %) in epilepsy hospitalizations, respectively. We also observed greater effects of particulate matter in cold season. The second stage meta-analysis that additionally included two prior studies with 43,002 patients from other 11 cities found a marginally significant increase in childhood epilepsy attacks associated with PM_2.5, PM₁₀, and NO₂ in eastern China.

CONCLUSIONS

Short-term exposure to both particulate matter and gaseous air pollution was associated with an increased risk of childhood epilepsy exacerbation in eastern China. Our findings suggest that air pollution exposure especially in cold season needs to be considered by children's parents or guardians to prevent epilepsy attacks.

The establishment of Air Quality Health Index in China: A comparative analysis of methodological approaches

BACKGROUND

The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales.

OBJECTIVES

To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales.

METHODS

By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect.

RESULTS

The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants.

CONCLUSIONS

AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.

Acute effect of fine particulate matter and respiratory mortality in Changsha, China: a time-series analysis

Background

Previous studies have confirmed that exposure to fine particulate matter (PM_2.5) is associated with respiratory disease mortality. However, due to the differences in PM_2.5 concentration, composition and population susceptibility within different regions, the estimates of the association between PM_2.5 concentration and mortality are different. Moreover, few studies have examined the potential hazard of excessive PM_2.5 exposure in terms of respiratory disease mortality.

Methods

Daily recorded data on meteorological indices, environmental pollutants, and causes of death data in Changsha from January 2015 to December 2018 were obtained. The potential relationship between PM_2.5 concentrations and respiratory disease mortality was determined using distributed lag nonlinear model (DLNM), which includes the relative risk (RR) and cumulative relative risk (CRR) of the lagged effect. The synergistic effects of other air pollutants were also considered.

Results

A total of 8,825 cases of respiratory disease mortality occurred in Changsha between 2015 and 2018. The acute effect of PM_2.5 concentration was associated with an increased risk of respiratory disease mortality. Regarding the lag specific effect, a 10 μg/m³ increase in PM_2.5 concentration on respiratory disease mortality was statistically significant at lag day 0 and lag day 7 with a relative risk of 1.019 (95% CI 1.007- 1.031) and 1.013(95%CI: 1.002-1.024). As for the cumulative lag effect, a 4-day moving average of PM_2.5 concentrations was significantly associated with a cumulative relative risk of 1.027 (95%CI: 1.011-1.031). The single-day lag effect and cumulative 4-day lag effect for male individuals were more significant than those observed in females. The effect of PM_2.5 concentrations and respiratory disease mortality remained statistically significant in the multi-pollutant models (SO₂, NO₂, and O₃). A higher risk was observed in the cold season than in the warm season.

Conclusions

Our findings show a potential association between exposure to PM_2.5 concentration and respiratory disease mortality in Changsha, with male individuals observed to have particularly higher risk.

Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city

Background

The influences of air pollution exposure and temperature on respiratory diseases have become major global health concerns. This study investigated the relationship between ambient air pollutant concentrations and temperature in cold industrial cities that have the risk of hospitalization for respiratory diseases.

Methods

A time-series study was conducted in Changchun, China, from 2015 to 2019 to analyse the number of daily admissions for respiratory diseases, air pollutant concentrations, and meteorological factors. Time-series decomposition was applied to analyse the trend and characteristics of the number of admissions. Generalized additive models and distributed lag nonlinear models were constructed to explore the effects of air pollutant concentrations and temperature on the number of admissions.

Results

The number of daily admissions showed an increasing trend, and the seasonal fluctuation was obvious, with more daily admissions in winter and spring than in summer and autumn. There were positive and gradually decreasing lag effects of PM10, PM2.5, NO₂, and CO concentrations on the number of admissions, whereas O₃ showed a J-shaped trend. The results showed that within the 7-day lag period, 0.5°C was the temperature associated with the lowest relative risk of admission due to respiratory disease, and extremely low and high temperatures (<-18°C, >27°C, respectively) increased the risk of hospitalization for respiratory diseases by 8.3% and 12.1%, respectively.

Conclusions

From 2015 to 2019, respiratory diseases in Changchun showed an increasing trend with obvious seasonality. The increased concentrations of SO₂, NO₂, CO, PM2.5, O₃ and PM10 lead to an increased risk of hospitalization for respiratory diseases, with a significant lag effect. Both extreme heat and cold could lead to increases in the risk of admission due to respiratory disease.

Association between short-term exposure to ambient PM1 and PM2.5 and forced vital capacity in Chinese children and adolescents

This study aims to examine the association between short-term exposure to ambient PM₁, PM_1-2.5, and PM_2.5 and forced vital capacity (FVC). Population data were obtained from a school-based cross-sectional survey in Shandong in 2014. Distributed lag non-linear models were used to examine the association between exposure to PM₁, PM_1-2.5, and PM_2.5 and FVC at the day of FVC measurement and the previous 6 days (lag 0 to 6 days). A total of 35,334 students aged 9 to 18 years were included in the study, and the mean exposure concentrations of ambient PM₁, PM_1-2.5, and PM_2.5 for them were 47.4 (standard deviation [SD] = 21.3) μg/m³, 32.8 (SD = 32.2) μg/m³, and 80.1 (SD = 47.7) μg/m³, respectively. An inter-quartile range (IQR, 24 μg/m³) increment in exposure to PM₁ was significantly associated with a lower FVC at lag 0 and lag 1 day (β =  - 80 mL, 95% CI =  - 119, - 42, and β =  - 37 mL, 95% CI =  - 59, - 16, respectively), and an IQR (54 μg/m³) increment in exposure to PM_2.5 was significantly associated with a lower FVC at lag 0 and lag 1 day (β =  - 57 mL, 95% CI =  - 89, - 18, and β =  - 34 mL, 95% CI =  - 56, - 12, respectively) after adjustment for gender, age, body mass index category, residence, month of the survey, intake of eggs, intake of milk, physical activity, and screen time. No significant associations were observed for PM_1-2.5. The inverse associations of PM₁ and PM_2.5 with FVC were larger in males, younger children, those overweight or obese, and those with insufficient physical activity levels. Short-term exposure to ambient PM₁ and PM_2.5 was associated with decreased FVC, and PM₁ may be the primary fraction of PM_2.5 causing the adverse pulmonary effects. Our findings emphasize the need to address ambient PM, especially PM₁, pollution for affecting pulmonary health in children and adolescents.

Short-term exposure to six air pollutants and cause-specific cardiovascular mortality of nine counties or districts in Anhui Province, China

Recently, the burden of cardiovascular disease (CVD) has attracted global attention. Meanwhile, CVD has become the leading cause of death in China. Some epidemiological studies have indicated that ambient air pollution may contribute to increased mortality from CVD diseases. Many studies have found a strong association between air pollutants and the risk of CVD deaths in some big cities, but few have focused on the effects of six pollutants in rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on CVD deaths of rural areas in Anhui Province and to further clarify which populations were susceptible to air pollution. First, the generalized additive models were combined with the distributed lag nonlinear models to evaluate the individual effects of air pollution on CVD deaths in each area. Then, random-effects models were used to aggregate the associations between air pollutants and CVD mortality risk in nine regions. Overall, all six pollutants had a statistically significant effect on the risk of CVD deaths on the lag 07 days. The associations between PM_2.5, PM₁₀, and SO₂ and daily CVD deaths were strongest, with maximum cumulative RR (lag 07) of 1.91 (1.64-2.18), 2.27 (1.50-3.05), and 2.13 (1.44-2.82). In general, we found that six air pollutants were the important risk factors for CVD and specific CVD deaths in Anhui Province. The elderly were susceptible to PM_2.5, PM₁₀, and SO₂.

Short-term effects of exposure to ambient PM1, PM2.5, and PM10 on ischemic and hemorrhagic stroke incidence in Shandong Province, China

BACKGROUND

Short-term exposure to ambient PM_2.5 and PM₁₀ is associated with increased risk of mortality and hospital admissions for stroke. However, there is less evidence regarding the effect of exposure to PM₁ on stroke incidence. We estimated the incidence risk of stroke and the attributable fractions related to short-term exposure to ambient PM₁, PM_2.5 and PM₁₀ in China.

METHODS

County-specific incidence of stroke was obtained from health statistics in years 2014-2019. We linked county-level mean daily concentrations of PM₁, PM_2.5 and PM₁₀ with stroke incidence. We used the time stratified case-crossover design to estimate the associations between stroke incidence and exposure to PM₁, PM_2.5 and PM₁₀. We also estimated the disease burden fractions attributable to PM₁, PM_2.5, and PM₁₀.

RESULTS

The study included a total of 2,193,954 stroke, from which 1,861,331 were ischemic and 332,623 were hemorrhagic stroke. PM₁, PM_2.5, and PM₁₀ levels were associated with increased risks of total stroke and ischemic stroke at when assessing the associations in exposure at lag0-4 days. The increase of 10 μg/m³ in PM₁, PM_2.5, and PM₁₀ was associated with total stroke, and the relative risks were 1.012 (95% confidence interval: 1.008, 1.015), 1.006 (1.004, 1.007) and 1.003 (1.002, 1.004), while the associations with ischemic stroke were 1.013 (1.010, 1.017), 1.006 (1.005, 1.008) and 1.003 (1.002, 1.004), respectively. There was no significant association between PM and risk of hemorrhagic stroke. The attributable fractions of total stroke were 6.9% (5.1%, 8.5%), 5.6% (4.2%, 6.8%) and 5.6% (3.9%, 7.1%) for PM₁, PM_2.5, and PM₁₀, respectively.

CONCLUSIONS

PM₁ showed a stronger association with stroke, with a larger attributable fraction of outcomes, than PM_2.5 and PM₁₀. Clean air policies should target the whole scope of PM, including PM₁.

Significant reduction in atmospheric organic and elemental carbon in PM2.5 in 2+26 cities in northern China

To better understand the change characteristics and reduction in organic carbon (OC) and elemental carbon (EC) in particulate matter (PM) with a diameter of ≤2.5 μm (PM_2.5) driven by the most stringent clean air policies and pandemic-related lockdown measures in China, a comprehensive field campaign was performed to measure the carbonaceous components in PM_2.5 on an hourly basis via harmonized analytical methods in the Beijing-Tianjin-Hebei and its surrounding region (including 2 + 26 cities) from January 1 to December 31, 2020. The results indicated that the annual average concentrations of OC and EC reached as low as 6.6 ± 5.7 and 1.8 ± 1.9 μg/m³, respectively, lower than those obtained in previous studies, which could be attributed to the effectiveness of the Clean Air Action Plan and the impact of the COVID-19-related lockdown measures implemented in China. Marked seasonal and diurnal variations in OC and EC were observed in the 2 + 26 cities. Significant correlations (p < 0.001) between OC and EC were found. The annual average secondary OC levels level ranged from 1.8-5.4 μg/m³, accounting for 37.7-73.0% of the OC concentration in the 2 + 26 cities estimated with the minimum R squared method. Based on Interagency Monitoring of Protected Visual Environments (IMPROVE) algorithms, the light extinction contribution of carbonaceous PM to the total amount reached 21.1% and 26.0% on average, suggesting that carbonaceous PM played a less important role in visibility impairment than did the other chemical components in PM_2.5. This study is expected to provide an important real-time dataset and in-depth analysis of the significant reduction in OC and EC in PM_2.5 driven by both the Clean Air Action Plan and COVID-19-related lockdown policies over the past few years, which could represent an insightful comparative case study for other developing countries/regions facing similar carbonaceous PM pollution.

Effect of environment and season on acute decompensated heart failure: data from low-to middle-income country

Objectives

The environmental effect in heart failure (HF) patients is well established. However, the data is limited from low-to middle-income countries like India. This study determined the impact of environment on acute decompensated HF (ADHF) admissions and mortality in India.

Methods

Retrospectively, the data of all HF patients admitted between April 2017 and March 2019 was accessed through electronic hospital records. Simultaneously, the environmental-related data was collected from the central pollution control board.

Results

The study included 4561 patients of ADHF. The peak of monthly ADHF events (admission and mortality) was observed during the chilly month (January) while the lowest rates were observed in summer months (May–June). The most significant factor correlating inversely with the monthly ADHF admission (r = −0.78, p = 0.003) and mortality (r = −0.65, p = 0.004) was the maximum air temperature, and it was found to be the independent predictor for both ADHF mortality [t = −2.78, β = −0.84; 95%CI(-6.0 to −0.6), p = 0.021] and admission [t = −4.83, β = −0.91; 95%CI(-19.8 to −6.9), p = 0.001]. The above correlation was better seen in the elderly subset and male gender. Humidity and the air pollution attributes did not have a significant correlation with ADHF admission or mortality.

Conclusion

In conclusion, even in low-to middle-income country like India, a periodic effect of season was demonstrated for ADHF mortality and admission, with a peak in ADHF events noted during winter months especially in the regions having extremes of seasons. Air pollution could not affect the ADHF outcome for which further studies are needed.

High-Resolution Urban Air Quality Mapping for Multiple Pollutants Based on Dense Monitoring Data and Machine Learning

Spatially explicit urban air quality information is important for urban fine-management and public life. However, existing air quality measurement methods still have some limitations on spatial coverage and system stability. A micro station is an emerging monitoring system with multiple sensors, which can be deployed to provide dense air quality monitoring data. Here, we proposed a method for urban air quality mapping at high-resolution for multiple pollutants. By using the dense air quality monitoring data from 448 micro stations in Lanzhou city, we developed a decision tree model to infer the distribution of citywide air quality at a 500 m × 500 m × 1 h resolution, with a coefficient of determination (R²) value of 0.740 for PM_2.5, 0.754 for CO and 0.716 for SO₂. Meanwhile, we also show that the deployment density of the monitoring stations can have a significant impact on the air quality inference results. Our method is able to show both short-term and long-term distribution of multiple important pollutants in the city, which demonstrates the potential and feasibility of dense monitoring data combined with advanced data science methods to support urban atmospheric environment fine-management, policy making, and public health studies.

The effects of air pollution on the lung cancer mortality in rural areas of eastern China: a multi-region study

Recently, the burden of lung cancer (LC) has attracted global attention. Meanwhile, LC has become the leading cause of death in China. Many studies found a strong link between air pollutants and the risk of LC mortality in some large cities, but the results have been inconsistent, and most studies have only focused on the daily effects of six pollutants in large cities, ignoring their potential cumulative effects. This study was to investigate the weekly effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on LC mortality in rural areas of eastern China and to further clarify which population groups were susceptible to air pollution and seasonal trends. First, a generalized additive model was combined with a distributed lag nonlinear model to evaluate the individual impact of air pollution on LC deaths in each area. The random-effect model was then used to pool the associations between air pollutants and LC mortality risk in ten counties or districts. The results showed that six air pollutants had a statistically significant effect on the risk of LC mortality at different lag weeks. The effects of NO₂, PM₁₀, and CO on weekly LC mortality were strongest at a cumulative lag of 1, 0, and 1 week, respectively, the maximum cumulative risk ratio (RR) of 1.37 (95%CI: 1.23 to 1.52), 1.30 (95%CI: 1.15 to 1.46), and 1.30 (95%CI: 1.17 to 1.43), with interquartile concentrations increasing. In summary, air pollution was an important factor in LC mortality, and the effect was stronger on males, the elderly, and during cold season. It was suggested that relevant departments should formulate air pollution management measures for the elderly, males, and in different seasons in rural areas and reduce the burden of lung cancer caused by air pollution.

Reduction in daily ambient PM2.5 pollution and potential life gain by attaining WHO air quality guidelines in Tehran

BACKGROUND

Fine particulate matter pollution (PM_2.5) is widely considered to be a top-ranked risk factor for premature mortality and years of life lost (YLL). However, evidence regarding the effect of daily air quality improvement on life expectancy is scarce, especially in the Middle East such as Iran. This study aimed to investigate the potential benefits in life expectancy at concentrations meeting the daily PM_2.5 standards during 2012-2016 in Tehran, Iran.

METHODS

We collected daily non-accidental mortality and data on air pollutants and weather conditions from Tehran, Iran, 2012-2016. A quasi-Poisson or Gaussian time-series regression was employed to fit the associations between ambient PM_2.5 and mortality or YLL. Potential gains in life expectancy (PGLE) and attributable fraction (AF) were estimated by assuming that daily PM_2.5 concentrations attained the World Health Organization air quality guidelines (WHO AQG) 2005 (25 μg/m³) and 2021 (15 μg/m³).

RESULTS

During the study period, a total of 221,231 non-accidental deaths were recorded in Tehran, resulting in 3.6 million YLL. The mean concentration of ambient PM_2.5 was 34.7 μg/m³ (standard deviation: 15.3 μg/m³). For a 10-μg/m³ rise in 4-day moving average (lag 03-day) in PM_2.5 concentration, non-accidental mortality and YLL increased by 1.12% (95% confidence interval: 0.60, 1.65) and 20.73 (7.08, 34.39) person years, respectively. A relatively higher effect was observed in males and young adults aged 18-64 years. We estimated that 39830 [AF = 1.1%] and 74284 [AF = 2.1%] YLL could potentially be avoided if daily PM_2.5 concentrations attained the WHO AQG 2005 and 2021, respectively, which corresponded to potential gains in life expectancy of 0.18 (0.06, 0.30) and 0.34 (0.11, 0.56) years for each deceased person. PM_2.5-associated PGLE estimates were largely robust when performing sensitivity analyses.

CONCLUSIONS

Our findings indicated that short-term exposure to PM_2.5 is associated with increased non-accidental YLL and mortality. Prolonged life expectancy could be achieved if the particulate matter air pollution level were kept under a stricter standard.

Hourly Air Pollutants and Acute Coronary Syndrome Onset In 1.29 Million Patients

Background: Short-term exposure to ambient air pollution has been linked with daily hospitalization and mortality of acute coronary syndrome (ACS); however, the associations of sub-daily (hourly) levels of criteria air pollutants with the onset of ACS and its subtypes have rarely been evaluated. Methods: We conducted a time-stratified case-crossover study among 1,292,880 ACS patients from 2,239 hospitals in 318 Chinese cities between January 1, 2015, and September 30, 2020. Hourly concentrations of fine particulate matter (PM_2.5), coarse particulate matter (PM_2.5-10), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃) were collected. Hourly onset data of ACS and its subtypes, including ST-segment-elevation myocardial infarction, non-ST-segment-elevation myocardial infarction, and unstable angina, were also obtained. Conditional logistic regressions combined with polynomial distributed lag models were applied. Results: Acute exposures to PM_2.5, NO₂, SO₂, and CO were each associated with the onset of ACS and its subtype. These associations were strongest in the concurrent hour of exposure and were attenuated thereafter, with the weakest effects observed after 15-29 hours. There were no apparent thresholds in the concentration-response curves. An interquartile range increase in concentrations of PM_2.5 (36.0 μg/m³), NO₂ (29.0 μg/m³), SO₂ (9.0 μg/m³), and CO (0.6 mg/m³) over the 0-24 hours preceding onset was significantly associated with 1.32%, 3.89%, 0.67%, and 1.55% higher risks of ACS onset, respectively. For a given pollutant, the associations were comparable in magnitude across different subtypes of ACS. Generally, NO₂ showed the strongest associations with all three subtypes, followed by PM_2.5, CO, and SO₂. Greater magnitude of associations was observed among patients older than 65, without a history of smoking or chronic cardiorespiratory diseases, and in the cold season. Null associations of exposure to either PM_2.5-10 or O₃ with ACS onset were observed. Conclusions: The results suggest that transient exposure to the air pollutants of PM_2.5, NO₂, SO₂, CO, but not PM_2.5-10 or O₃, may trigger the onset of ACS, even at concentrations below the World Health Organization air-quality guidelines.

New WHO global air quality guidelines help prevent premature deaths in China

The World Health Organization has issued new air quality guidelines (AQG). Based on 2020 data, achieving the new AQG for PM2.5 could prevent an additional 285,000 chronic deaths and 13,000 acute deaths, across China, compared with the previous AQG. The new AQG can better protect health but cannot be achieved without coordinated air-pollution-control and climate-mitigation efforts.

Land Use Quantile Regression Modeling of Fine Particulate Matter in Australia

Small data samples are still a critical challenge for spatial predictions. Land use regression (LUR) is a widely used model for spatial predictions with observations at a limited number of locations. Studies have demonstrated that LUR models can overcome the limitation exhibited by other spatial prediction models which usually require greater spatial densities of observations. However, the prediction accuracy and robustness of LUR models still need to be improved due to the linear regression within the LUR model. To improve LUR models, this study develops a land use quantile regression (LUQR) model for more accurate spatial predictions for small data samples. The LUQR is an integration of the LUR and quantile regression, which both have advantages in predictions with a small data set of samples. In this study, the LUQR model is applied in predicting spatial distributions of annual mean PM2.5concentrations across the Greater Sydney Region, New South Wales, Australia, with observations at 19 valid monitoring stations in 2020. Cross validation shows that the goodness-of-fit can be improved by 25.6–32.1% by LUQR models when compared with LUR, and prediction root mean squared error (RMSE) and mean absolute error (MAE) can be reduced by 10.6–13.4% and 19.4–24.7% by LUQR models, respectively. This study also indicates that LUQR is a more robust model for the spatial prediction with small data samples than LUR. Thus, LUQR has great potentials to be widely applied in spatial issues with a limited number of observations.

Gaseous air pollutants and hospitalizations for mental disorders in 17 Chinese cities: Association, morbidity burden and economic costs

The short-term morbidity effects of gaseous air pollutants on mental disorders (MDs), and the corresponding morbidity and economic burdens have not been well studied. We aimed to explore the associations of ambient sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃) and carbon monoxide (CO) with MDs hospitalizations in 17 Chinese cities during 2015-2018, and estimate the attributable risk and economic costs of MDs hospitalizations associated with gaseous pollutants. City-specific relationships between gaseous pollutants and MDs hospitalizations were evaluated using over-dispersed generalized additive models, then combined to obtain the pooled effect. Concentration-response (C-R) curves of gaseous pollutants with MDs from each city were pooled to allow regional estimates to be derived. The morbidity and economic burdens of MDs hospitalizations attributable to gaseous pollutants were further assessed. A total of 171,939 MDs hospitalizations were included. We observed insignificant association of O₃ with MDs. An interquartile range increase in SO₂ at lag0 (9.1 μg/m³), NO₂ at lag0 (16.7 μg/m³) and CO at lag2 (0.4 mg/m³) corresponded to a 3.02% (95%CI: 0.72%, 5.38%), 5.03% (95%CI: 1.84%, 8.32%) and 2.18% (95%CI: 0.40%, 4.00%) increase in daily MDs hospitalizations, respectively. These effects were modified by sex, season and cause-specific MDs. The C-R curves of SO₂ and NO₂ with MDs indicated nonlinearity and the slops were steeper at lower concentrations. Overall, using current standards as reference concentrations, 0.27% (95%CI: 0.07%, 0.48%) and 0.06% (95%CI: 0.02%, 0.10%) of MDs hospitalizations could be attributable to extra SO₂ and NO₂ exposures, and the corresponding economic costs accounted for 0.34% (95%CI: 0.08%, 0.60%) and 0.07% (95%CI: 0.03%, 0.11%) of hospitalization expenses, respectively. Moreover, using threshold values detected from C-R curves as reference concentrations, the above mentioned morbidity and economic burdens increased a lot. These findings suggest more strict emission control regulations are needed to protect mental health from gaseous pollutants.

Oxidative stress-mediated particulate matter affects the risk of relapse in schizophrenia patients: Air purification intervention-based panel study

Particulate matter (PM) exposure increased the risk of hospital admission and was related to symptoms of schizophrenia (SCZ). However, there are limited studies on the relationship between PM exposure and SCZ relapse risk, and the underlying biological mechanisms remain unclear. We designed an air purification intervention study under a 16-day real air purifier scenario and another 16-day sham air purifier scenario, with a 2-day washout period. Twenty-four chronic stable male patients were recruited. The oxidative stress biomarkers were measured including serum catalase (CAT), superoxide dismutase (SOD), total antioxidant capacity (T-AOC), malondialdehyde (MDA), and nitric oxide (NO). The relapse risk was evaluated by the early signs scale (ESS). Linear mixed effect models were fitted to establish the associations between PM exposure and ESS and oxidative stress. Mediation model was performed to explore the mediation effect of oxidative stress on the PM-ESS association. Higher concentrations of PM_2.5/PM₁₀ exposure were associated with an elevated risk of relapse of SCZ. For each 10 μg/m³ in PM_2.5 concentration, the scores of ESS and subscales of incipient psychosis (ESS-IP), depression/withdrawal (ESS-N), anxiety/agitation (ESS-A), and excitability/disinhibition (ESS-D) were increased by 4.112 (95% CI: 3.174, 5.050), 1.516 (95%CI: 1.178, 1.853), 1.143 (95%CI: 0.598, 1.689), 1.176 (95%CI: 0.727, 1.625) and 0.238 (95%CI: 0.013, 0.464), while logCAT, SOD and T-AOC were reduced by 0.039 U/ml (95% CI: 0.017, 0.060), 1.258 U/ml (95% CI: 0.541, 1.975), and 0.076 mmol/l (95% CI: 0.026, 0.126). In addition, pathways of "PM_2.5→T-AOC→ESS-A″ and "PM_2.5→T-AOC→ESS-D″ were found, with significant T-AOC mediated effects 15.70% (P = 0.02) and 52.99% (P = 0.04). Our findings suggest that PM may increase the risk of anxiety, depression, excitability, and incipient psychosis behaviors in SCZ patients, while reducing the function of the antioxidant system. The decrease of T-AOC may medicate the PM-ESS association in SCZ.

Cumulative effects of ambient particulate matter pollution on deaths: A multicity analysis of mortality displacement

BACKGROUND

Systematic evaluations of the cumulative effects and mortality displacement of ambient particulate matter (PM) pollution on deaths are lacking. We aimed to discern the cumulative effect profile of PM exposure, and investigate the presence of mortality displacement in a large-scale population.

METHODS

We conducted a time-series analysis with different exposure-lag models on 13 cities in Jiangsu, China, to estimate the effects of PM pollution on non-accidental, cardiovascular, and respiratory mortality (2015-2019). Over-dispersed Poisson generalized additive models were integrated with distributed lag models to estimate cumulative exposure effects, and assess mortality displacement.

RESULTS

Pooled cumulative effect estimates with lags of 0-7 and 0-14 days were substantially larger than those with single-day and 2-day moving average lags. For each 10 μg/m³ increment in PM_2.5 concentration with a cumulative lag of 0-7 days, we estimated an increase of 0.50 % (95 % CI: 0.29, 0.72), 0.63 % (95 % CI: 0.38, 0.88), and 0.50 % (95 % CI: 0.01, 1.01) in pooled estimates of non-accidental, cardiovascular, and respiratory mortality, respectively. Both PM₁₀ and PM_2.5 were associated with significant increases in non-accidental and cardiovascular mortality with a cumulative lag of 0-14 days. We observed mortality displacement within 30 days for non-accidental, cardiovascular, and respiratory deaths.

CONCLUSIONS

Our findings suggest that risk assessment based on single-day or 2-day moving average lag structures may underestimate the adverse effects of PM pollution. The cumulative effects of PM exposure on non-accidental and cardiovascular mortality can last up to 14 days. Evidence of mortality displacement for non-accidental, cardiovascular, and respiratory deaths was found.

Hourly concentrations of fine and coarse particulate matter and dynamic pulmonary function measurements among 4992 adult asthmatic patients in 25 Chinese cities

The short-term associations of fine particulate matter (PM_2.5) and coarse particulate matter (PM_2.5-10) with pulmonary function were inconsistent and rarely evaluated by dynamic measurements. Our study aimed to investigate the associations of PM_2.5 and PM_2.5-10 with real-time pulmonary function. We conducted a longitudinal study based on dynamic pulmonary function measurements among adult asthmatic patients in 25 cities of 19 provincial regions of China from 2017 to 2020. Linear mixed-effects models combined with polynomial distributed lag models were used for statistical analysis. A total of 298,396 records among 4,992 asthmatic patients were evaluated. We found generally inverse associations of PM_2.5 and PM_2.5-10 with 16 pulmonary function indicators that were independent of gaseous pollutants. The associations occurred at lag 1 d, became the strongest at lag 4 d, and vanished a week later. PM_2.5-10 had stronger associations than PM_2.5, especially in southern China. Nationally, an interquartile increase in PM_2.5-10 (28.0 μg/m³) was significantly associated with decreases in forced expiratory volume in 1 s (FEV_1, 41.6 mL), the ratio of FEV₁ in forced vital capacity (1.1%), peak expiratory flow (136.9 mL/s), and forced expiratory flow at 25-75% of forced vital capacity (54.3 mL/s). We observed stronger associations in patients of male, BMI ≥ 25 kg/m², age ≥ 45 years old, and during warm seasons. In conclusion, this study provided robust evidence for impaired pulmonary function by short-term exposure to PM_2.5 and PM_2.5-10 in asthmatic patients using the largest dataset of dynamic monitoring. The associations can last for one week and PM_2.5-10 may be more hazardous.

lncRNA AABR07005593.1 potentiates PM2.5-induced interleukin-6 expression by targeting MCCC1

BACKGROUND

Fine particle pollution, specifically pollution by fine particulate matter (PM_2.5), remains a significant concern in developing countries and plays an important role in the development and progression of respiratory diseases. Increasing evidences have demonstrated that long non-coding RNAs (lncRNAs) may act as vital molecules by binding to specific RNA-binding protein (RBP); however, their relationship with PM_2.5 pollution is largely unexplored.

OBJECTIVE

We investigated the association between lncRNA and respiratory system inflammation caused by PM_2.5.

METHODS

PM_2.5 components were detected by gas chromatography-mass spectrometry (GC-MS), inductively coupled plasma-mass spectrometry (ICP-MS), and ionic chromatography. We established an inflammation model of PM_2.5-induced toxicity in vivo (male and female SD rats, 0, 25, 50 and 100 mg/k PM_2.5, 1, 7 and 14 days, single non-invasive tracheal instillation) and in vitro (rat alveolar macrophage cell line (NR8383), 0, 50, 100, 200, 400 μM PM_2.5 for 24, 48, and 72 h). lncRNA high-throughput sequencing (lncRNA-seq) was used to investigate lncRNA profiles in PM_2.5-treated NR8383 cells, and RNA interference (RNAi) was applied to explore the function of the target lncRNA. The mechanisms associated with specific lncRNAs were explored using comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) and western blot.

RESULTS

PM_2.5-treated NR8383 cells and SD rats exhibited respiratory inflammation. lncRNA AABR07005593.1 was a pro-inflammatory factor that regulated IL-6 levels. Mechanistically, ChIRP-MS and western blot analyses revealed that highly expressed lncRNA AABR07005593.1 interacted with MCCC1 to involve in the activation of NF-κB pathway, and ultimately promoted the expression of IL-6.

CONCLUSION

This study demonstrated that PM_2.5 induced inflammation in vivo and in vitro. Furthermore, lncRNA AABR07005593.1 bound to MCCC1 to potentiated IL-6 expression. Therefore, lncRNA AABR07005593.1 may act as a potential biomarker for PM_2.5 inflammation.

Changes in Air Pollution-Related Behaviour Measured by Google Trends Search Volume Index in Response to Reported Air Quality in Poland

Decreased air quality is connected to an increase in daily mortality rates. Thus, people’s behavioural response to sometimes elevated air pollution levels is vital. We aimed to analyse spatial and seasonal changes in air pollution-related information-seeking behaviour in response to nationwide reported air quality in Poland. Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM₁₀ and PM_2.5 concentrations measured across Poland between 2016 and 2019 as well as locations of monitoring stations were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation Coefficients were used to measure the strength of spatial and seasonal relationships between reported air pollution levels and the popularity of search queries. The highest PM₁₀ and PM_2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air pollution-related keywords. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels. It appears that Poles are socially aware of this issue and that their intensification of the information-seeking behaviour seems to indicate a relevant ad hoc response to variable threat severity levels.

Spatiotemporal variation in residential PM2.5 and PM10 concentrations in China: National on-site survey

BACKGROUND

Significant efforts have been directed toward addressing the adverse health effects of particulate matter, while few data exist to evaluate indoor exposure nationwide in China.

OBJECTIVES

This study aimed to investigate dwellings particulate matter levels in the twelve cities in China and provide large data support for policymakers to accelerate the legislative process.

METHODS

The current study was based on the CIEHS 2018 study and conducted in 12 cities of China. A total of 2128 air samples were collected from 610 residential households during the summer and winter. Both PM₁₀ and PM_2.5 were detected with a light-scattering dust meter in both the living room and bedroom. The Wilcoxon rank-sum test was performed to evaluate the correlations between PM_2.5 and PM₁₀ concentrations and both sampling season and site. Ratios of the living room to bedroom were calculated to evaluate the particulate matter variation between rooms. Hierarchical clustering was used to probe the question of whether the concentration varies between cities throughout China.

RESULTS

The geometric means of the PM_2.5 in living rooms and bedrooms were 39.80 and 36.55 μg/m³ in the summer, and 70.97 and 67.99 μg/m³ in the winter, respectively. In the summer, approximately 70 % of indoor dwelling PM_2.5 exceeded the limit of 25 μg/m³, and for PM₁₀ approximately 60 % of dwellings demonstrated levels higher than 50 μg/m³; the corresponding values were over 90 % and 80 % in winter, respectively. In Shijiazhuang, Lanzhou, Luoyang and Qingdao, the geometric means of the PM_2.5 concentrations were observed to be 1.5 to 4.3 times higher during winter than during summer; similar concentrations in summer and winter were observed in Harbin, Wuxi, and Shenzhen, while the PM_2.5 concentrations in Panjin were approximately 1.5 times higher in summer than in winter. There was no significant difference in particulate matter concentrations between the living rooms and bedrooms. Scatter plots showed that cities with low GDP and a small population had higher concentrations, while Shenzhen, which has a higher GDP and a large permanent population, had a relatively low concentration of particulate matter.

CONCLUSIONS

Our results suggest that indoor air pollution is a severe problem in China. It is necessary to continue monitoring indoor air quality to observe the changing trend under the tremendous effort of the Chinese government.