Public Health and Air Pollution in Asia (PAPA): a multicity study of short-term effects of air pollution on mortality

Reducing Indoor Particulate Air Pollution Improves Student Test Scores: A Randomized Double-Blind Crossover Study

Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" method─randomized, double-blind crossover─to assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Exploring the adverse effect of fine particulate matter (PM2.5) on wildland firefighters' pulmonary function and DNA damage

Chiang Mai encounters severe pollution during the wildfire season. Wildland firefighters encounter various hazards while engaged in fire suppression operations, which encompass significant exposure to elevated concentrations of air pollutants resulting from combustion, especially particulate matter. The adverse effects of wildfire smoke on respiratory health are a significant concern. The objective of this study was to examine the potential adverse effects of PM2.5 exposure on the respiratory function and DNA damage of wildland firefighters. This prospective cohort study conducted in Chiang Mai from January to May 2022 planned to evaluate the health status of wildland firefighters during the pre-peak, peak, and post-peak ambient air pollution seasons. The measurement of PM2.5 was done at every forest fire station, as well as utilizing data from the Pollution Control Department. Participants received general health examinations, spirometry evaluations, and blood tests for DNA damage analysis. Pair t-tests and multiple regression models were used to examine the connection between pulmonary function parameters (FVC, FEV1) and PM2.5 concentration, with a significance level of P < 0.05. Thirty-three peak-season and twenty-one post-peak-season participants were enrolled. Four pre-peak-season wildland firefighters had FVC and FEV1 declines of > 15%. Multiple regression analysis showed a negative association between PM2.5 exposure and FVC% predicted (- 2.81%, 95% CI - 5.27 to - 0.34%, P = 0.027) and a marginally significant negative correlation with FVC (- 114.38 ml, 95% CI - 230.36 to 1.59 ml, P = 0.053). The remaining pulmonary measures showed a statistically insignificant decline. There were no significant changes in DNA damage detected. Wildland firefighters suffered a significant decline in pulmonary function associated with PM2.5 exposure. Spirometry is crucial for monitoring and promptly identifying respiratory issues that occur during wildfire seasons. Further research is recommended to explore DNA damage alterations and their potential association with PM2.5.

An observed nocturnal ozone transport event in the Sichuan Basin, Southwestern China

The ozone (O3) pollution in China drew lots of attention in recent years, and the Sichuan Basin (SCB) was one of the regions confronting worsening O3 pollution problem. Many previous studies have shown that regional transport is an important contributor to O3 pollution. However, very few features of the O3 profile during transport have been reported, especially in the border regions between different administrative divisions. In this study, we conducted tethered balloon soundings in SCB during the summer of 2020 and captured a nocturnal O3 transport event during the campaign. Vertically, the O3 transport occurred in the bottom of the residual layer, between 200 and 500 m above ground level. Horizontally, the transport pathway was directed from southeast to northwest based on the analysis of the wind field and air mass trajectories. The effect of transport in the residual layer on the surface O3 concentration was related to the spatial distribution of O3. For cities with high O3 concentrations in the upwind region, the transport process would bring clean air masses and abate pollution. For downwind lightly polluted cities, the transport process would slow down the decreasing or even increase the surface O3 concentration during the night. We provided observational facts on the profile features of a transboundary O3 transport event between two provincial administrative divisions, which implicated the importance of joint prevention and control measures. However, the sounding parameters were limited and the quantitative analysis was preliminary, more integrated, and thorough studies of this topic were called for in the future.

Exposure to Concurrent Heatwaves and Ozone Pollution and Associations with Mortality Risk: A Nationwide Study in China

BACKGROUND

Concurrent extreme events are projected to occur more frequently under a changing climate. Understanding the mortality risk and burden of the concurrent heatwaves and ozone (O 3 ) pollution may support the formulation of adaptation strategies and early warning systems for concurrent events in the context of climate change.

OBJECTIVES

We aimed to estimate the mortality risk and excess deaths of concurrent heatwaves and O 3 pollution across 250 counties in China.

METHODS

We collected daily mortality, meteorological, and air pollution data for the summer (1 June to 30 September) during 2013-2018. We defined heatwaves and high O 3 pollution days, then we divided the identified days into three categories: a) days with only heatwaves (heatwave-only event), b) days with only high O 3 pollution (high O 3 pollution-only event), and c) days with concurrent heatwaves and high O 3 pollution (concurrent event). A generalized linear model with a quasi-Poisson regression was used to estimate the risk of mortality associated with extreme events for each county. Then we conducted a random-effects meta-analysis to pool the county-specific estimates to derive the overall effect estimates. We used mixed-effects meta-regression to identify the drivers of the heterogeneity. Finally, we estimated the excess death attributable to extreme events (heatwave-only, high O 3 pollution-only, and concurrent events) from 2013 to 2020.

RESULTS

A higher all-cause mortality risk was associated with exposure to the concurrent heatwaves and high O 3 pollution than exposure to a heatwave-only or a high O 3 pollution-only event. The effects of a concurrent event on circulatory and respiratory mortality were higher than all-cause and nonaccidental mortality. Sex and age significantly impacted the association of concurrent events and heatwave-only events with all-cause mortality. We estimated that annual average excess deaths attributed to the concurrent events were 6,249 in China from 2017 to 2020, 5.7 times higher than the annual average excess deaths attributed to the concurrent events from 2013 to 2016. The annual average proportion of excess deaths attributed to the concurrent events in the total excess deaths caused by three types of events (heatwave-only events, high O 3 pollution-only events, and concurrent events) increased significantly in 2017-2020 (31.50%; 95% CI: 26.73%, 35.53%) compared with 2013-2016 (9.65%; 95% CI: 5.67%, 10.81%). Relative excess risk due to interaction revealed positive additive interaction considering the concurrent effect of heatwaves and high O 3 pollution.

DISCUSSION

Our findings may provide scientific basis for establishing a concurrent event early warning system to reduce the adverse health impact of the concurrent heatwaves and high O 3 pollution. https://doi.org/10.1289/EHP13790.

Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis

BACKGROUND

Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide.

OBJECTIVES

We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk.

METHODS

We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction].

RESULTS

We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults.

DISCUSSION

Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.

Particulate air pollution and cardiovascular disease mortality in Jiangsu Province, China: a time-series analysis between 2015 and 2021

Introduction

Previous time-series studies have revealed a positive association between particulate matter (PM) and acute cardiovascular effects. However, the evidence mostly comes from developed countries and regions, while the majority of air-pollution-related deaths occur in developing countries. To assess the effect of short-term exposure to PM on daily cause-specific cardiovascular disease (CVD) mortality in Jiangsu Province, China, we investigated 1,417,773 CVD deaths from 2015 to 2021 in Jiangsu.

Methods

The city-specific association was estimated using generalized additive models with quasi-Poisson regression, and then, random effects meta-analysis was performed to estimate the pooled provincial-average associations between acute exposure to PM2.5 and PM10 and cardiovascular disease mortality. To test the independence of PM from gaseous pollutants, we fitted two-pollutant models. Mortality data were also stratified by sex, age, and region to investigate the modification of associations. The exposure-response (E-R) curve from each city was combined using meta-analysis to drive the provincial-level E-R curve.

Results

The results showed that each 10-μg/m3 increase in the PM2.5 concentration was associated with a 0.723% [95% confidence interval (CI): 0.512, 0.935] increase in daily total CVD mortality, a 0.669% (95% CI: 0.461, 0.878) increase in CHD mortality, a 0.758% (95% CI: 0.584, 0.931) increase in stroke mortality, a 0.512% (95% CI: 0.245, 0.780) increase in ICH mortality, and a 0.876% (95% CI: 0.637, 1.116) increase in CI mortality. The corresponding increases in daily mortality rates for the same increase in the PM10 concentration were 0.424% (95% CI: 0.293, 0.556), 0.415% (95% CI: 0.228, 0.602), 0.444% (95% CI: 0.330, 0.559), 0.276% (95% CI: 0.026, 0.526), and 0.510% (95% CI: 0.353, 0.667), respectively. The association between PM and total CVD mortality remained significant after adjusting for gaseous pollutants. Females, older adults and districts with lower average PM levels are more sensitive, especially for PM10. The E-R curve for PM on CVD mortality is steeper at lower concentrations and flattens out at higher concentrations. The estimates remained generally consistent in sensitivity analyses when excluding the data during the COVID-19 pandemic period.

Discussion

Our time-series study provides evidence of positive associations between acute exposure to PM2.5 and PM10 and total and cause-specific cardiovascular disease mortality in developing countries.

The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China

Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States

Background

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health.

Methods

We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season.

Results

Short-term exposure increases of 1 μg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)].

Conclusions

Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods.

Classification

environmental public health, fine particulate matter air pollution, respiratory infections.

Effects of air pollution on emergency visits for acute otitis media among children: a case-crossover study in Chongqing, China

Background

Many epidemiological studies have demonstrated the short-term effects of air pollution on acute otitis media (AOM) in children, but few studies have explored the association between AOM and air pollution in Chinese children. This study aimed to analyze the effects of air pollution on emergency visits for AOM among children through a time-stratified case-crossover design in Chongqing, China.

Methods

The outpatient medical records of children from nine main urban districts who presented with AOM between December 22, 2018 and December 21, 2021 were collected from the Children's Hospital of Chongqing Medical University. Data for air pollution variables, including the air quality index (AQI), particulate matter ≤ 10 μm (PM10), PM2.5, SO2, CO, NO2 and O3 from 17 monitoring sites were collected. Data for meteorological factors as confounding variables also were collected. Conditional logistic regression was used to analyze the data with single-pollutant models, multi-pollutant models, and stratified analyses.

Results

Increases in AQI, PM10, PM2.5, SO2, CO and NO2 were positively associated with emergency visits for AOM among children in single-pollutant models and stratified analyses. Increases in PM10, SO2, CO and NO2 were positively associated with emergency visits for AOM among children in multi-pollutant models. NO2 had the most statistically significant OR values in all models, whereas significant effects of O3 were observed only in seasonal stratification. In single-pollutant models, we found that the best lag periods were lag 0-7 for air pollution variables except for O3 and the largest OR values were 1.185 (95%CI: 1.129-1.245) for SO2 in single-pollutant models. In stratified analyses, there were no difference between groups in these statistically significant OR values through gender and age stratification, while the differences between seasons in these OR values of PM10, SO2, CO, NO2 and O3 were statistically significant. Children aged 0 years and 3-5 years represented the most susceptible population, and among the seasons, susceptibility was greater during Winter and Spring.

Conclusion

Short-term exposure to air pollution can increase emergency visits for AOM among children in Chongqing, China.

Using a novel strategy to investigate the spatially autocorrelated and clustered associations between short-term exposure to PM2.5 and mortality and the attributable burden: A case study in the Sichuan Basin, China

Due to the lack of statistical methods, few studies have investigated the spatial autocorrelated distribution in the association between short-term exposure to PM2.5 and mortality and used a statistical manner to explore the association-clustered regions, which play important roles in identifying high-sensitivity/susceptibility regions. The Sichuan Basin (SCB) is one of the most PM2.5-polluted areas, and the extreme economic imbalance may cause considerable spatial heterogeneity and clustering in PM2.5-mortality association. In this work, we used a recently proposed strategy by us to investigate the spatially autocorrelated and clustered association between daily PM2.5 and cardiorespiratory mortality from 2015 to 2019 in 130 counties of the SCB. First, generalized additive models were independently constructed to obtain the county-level association estimations. Then, an estimation-error-based spatial scan statistic was used to detect the association-clustered regions. Third, multivariate conditional meta autoregression was used to obtain the spatially autocorrelated association distribution, based on which the attributable deaths were mapped and their inequality was evaluated using the Gini coefficient and Lorenz curve. Results showed that two significantly association-clustered regions were detected. One is mainly located in the megacity Chengdu where PM2.5 presented a significantly stronger association with no threshold effect at low-level PM2.5 but a threshold at high-level PM2.5. In the other cluster, a threshold effect at low-level PM2.5 but no threshold at high-level PM2.5 were found. The mortality risk at low/middle-level PM2.5 decreased from Chengdu as the center to the surrounding areas. A total of 29,129 (2.0 %) deaths were attributable to the excess PM2.5 exposure. The attributable deaths also decreased from Chengdu as the center to the surrounding areas with Gini coefficients of 0.43 and 0.3 for absolute and relative attributable deaths, respectively. This novel strategy provided a new epidemiological perspective regarding the association and implicated that Chengdu is significantly deserving of more attention regarding PM2.5-related health loss.

A longitudinal study on the effect of extreme temperature on non-accidental deaths in Hulunbuir City based on DLNM model

OBJECTIVE

To explore the frequency and effect of extreme temperature on the non-accidental death rate in Hulunbuir, a Chinese ice city.

METHODS

From 2014 to 2018, mortality data of residents residing in Hulunbuir City were collected. The lag and cumulative effects of extreme temperature conditions on non-accidental death and respiratory and circulatory diseases were analyzed by distributed lag non-linear models (DLNM).

RESULTS

The risk of death was the highest during high-temperature conditions, the RR value was 1.111 (95% CI 1.031 ~ 1.198). The effect was severe and acute. The risk of death during extreme low-temperature conditions peaked on the fifth day, (RR 1.057; 95% CI 1.012 ~ 1.112), then decreased and was maintained for 12 days. The cumulative RR value was 1.289 (95% CI 1.045 ~ 1.589). Heat significantly influenced the incidence of non-accidental death in both men (RR 1.187; 95% CI 1.059-1.331) and women (RR 1.252; 95% CI 1.085-1.445).

CONCLUSIONS

Regardless of the temperature effect, the risk of death in the elderly group (≥ 65 years) was significantly higher than that of the young group (0-64 years). High-temperature and low-temperature conditions can contribute to the increased number of deaths in Hulunbei. While high-temperature has an acute effect, low-temperature has a lagging effect. Elderly and women, as well as people with circulatory diseases, are more sensitive to extreme temperatures.

Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men

Background

Air pollution may impair male fertility, but it remains controversial whether air pollution affects semen quality until now.

Objectives

We undertake a meta-analysis to explore potential impacts of six pollutants exposure during the entire window (0-90 days prior to ejaculation) and critical windows (0-9, 10-14, and 70-90 days prior to ejaculation) on semen quality.

Methods

Seven databases were retrieved for original studies on the effects of six pollutants exposure for 90 days prior to ejaculation on semen quality. The search process does not limit the language and search date. We only included original studies that reported regression coefficients (β) with 95% confidence intervals (CIs). The β and 95% CIs were pooled using the DerSimonian-Laird random effect models.

Results

PM2.5 exposure was related with decreased total sperm number (10-14 lag days) and total motility (10-14, 70-90, and 0-90 lag days). PM10 exposure was related with reduced total sperm number (70-90 and 0-90 lag days) and total motility (0-90 lag days). NO2 exposure was related with reduced total sperm number (70-90 and 0-90 lag days). SO2 exposure was related with declined total motility (0-9, 10-14, 0-90 lag days) and total sperm number (0-90 lag days).

Conclusion

Air pollution affects semen quality making it necessary to limit exposure to air pollution for Chinese men. When implementing protective measures, it is necessary to consider the key period of sperm development.

Long-term ambient air pollution exposure and cardio-respiratory disease in China: findings from a prospective cohort study

BACKGROUND

Existing evidence on long-term ambient air pollution (AAP) exposure and risk of cardio-respiratory diseases in China is mainly on mortality, and based on area average concentrations from fixed-site monitors for individual exposures. Substantial uncertainty persists, therefore, about the shape and strength of the relationship when assessed using more personalised individual exposure data. We aimed to examine the relationships between AAP exposure and risk of cardio-respiratory diseases using predicted local levels of AAP.

METHODS

A prospective study included 50,407 participants aged 30-79 years from Suzhou, China, with concentrations of nitrogen dioxide (NO2), sulphur dioxide (SO2), fine (PM2.5), and inhalable (PM10) particulate matter, ozone (O3) and carbon monoxide (CO) and incident cases of cardiovascular disease (CVD) (n = 2,563) and respiratory disease (n = 1,764) recorded during 2013-2015. Cox regression models with time-dependent covariates were used to estimate adjusted hazard ratios (HRs) for diseases associated with local-level concentrations of AAP exposure, estimated using Bayesian spatio-temporal modelling.

RESULTS

The study period of 2013-2015 included a total of 135,199 person-years of follow-up for CVD. There was a positive association of AAP, particularly SO2 and O3, with risk of major cardiovascular and respiratory diseases. Each 10 µg/m3 increase in SO2 was associated with adjusted hazard ratios (HRs) of 1.07 (95% CI: 1.02, 1.12) for CVD, 1.25 (1.08, 1.44) for COPD and 1.12 (1.02, 1.23) for pneumonia. Similarly, each 10 µg/m3 increase in O3 was associated with adjusted HR of 1.02 (1.01, 1.03) for CVD, 1.03 (1.02, 1.05) for all stroke, and 1.04 (1.02, 1.06) for pneumonia.

CONCLUSIONS

Among adults in urban China, long-term exposure to ambient air pollution is associated with a higher risk of cardio-respiratory disease.

Local Fiscal Pressure and Public Health: Evidence from China

Under the dual challenges of global downward economic pressure and the COVID-19 pandemic, studying the impact of local government fiscal pressure on public health is a meaningful endeavor. First, this paper analyzes the impact of local government fiscal pressure on public health and clarifies its impact mechanisms. Second, by utilizing panel data of 31 Chinese provinces from 2000 to 2020, two-way fixed-effects and mediating-effects models are developed to identify the effects and impact mechanisms of local government fiscal pressure on public health. The results show that local government fiscal pressure can be detrimental to public health through three main mechanisms: reducing public health fiscal expenditures, hindering industrial structure upgrading, and exacerbating environmental pollution. Heterogeneity analysis finds that the negative effects of local government fiscal pressure on public health mainly exist in Central and Western China. Accordingly, three policy implications are proposed: optimizing the fiscal system, accelerating industrial upgrading, and improving the appraisal system of local officers.

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

BACKGROUND AND AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Comparison of the association between different ozone indicators and daily respiratory hospitalization in Guangzhou, China

Background

Epidemiological studies have widely proven the impact of ozone (O₃) on respiratory mortality, while only a few studies compared the association between different O₃ indicators and health.

Methods

This study explores the relationship between daily respiratory hospitalization and multiple ozone indicators in Guangzhou, China, from 2014 to 2018. It uses a time-stratified case-crossover design. Sensitivities of different age and gender groups were analyzed for the whole year, the warm and the cold periods. We compared the results from the single-day lag model and the moving average lag model.

Results

The results showed that the maximum daily 8 h average ozone concentration (MDA8 O₃) had a significant effect on the daily respiratory hospitalization. This effect was stronger than for the maximum daily 1 h average ozone concentration (MDA1 O₃). The results further showed that O₃ was positively associated with daily respiratory hospitalization in the warm season, while there was a significantly negative association in the cold season. Specifically, in the warm season, O₃ has the most significant effect at lag 4 day, with the odds ratio (OR) equal to 1.0096 [95% confidence intervals (CI): 1.0032, 1.0161]. Moreover, at the lag 5 day, the effect of O₃ on the 15-60 age group was less than that on people older than 60 years, with the OR value of 1.0135 (95% CI: 1.0041, 1.0231) for the 60+ age group; women were more sensitive than men to O₃ exposure, with an OR value equal to 1.0094 (95% CI: 0.9992, 1.0196) for the female group.

Conclusion

These results show that different O₃ indicators measure different impacts on respiratory hospitalization admission. Their comparative analysis provided a more comprehensive insight into exploring associations between O₃ exposure and respiratory health.

Mining biomarkers from routine laboratory tests in clinical records associated with air pollution health risk assessment

Clinical laboratory in hospital can produce amounts of health data every day. The purpose of this study was to mine biomarkers from clinical laboratory big data associated with the air pollution health risk assessment using clinical records. 13, 045, 629 clinical records of all 27 routine laboratory tests in Changsha Central Hospital, including ALB, TBIL, ALT, DBIL, AST, TP, UREA, UA, CREA, GLU, CK, CKMB, LDL-C, TG, TC, HDL-C, CRP, WBC, Na, K, Ca, Cl, APTT, PT, FIB, TT, RBC and those daily air pollutants concentration monitoring data of Changsha, including PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ from 2014 to 2016, were retrieved. The moving average method was used to the biological reference interval was established. The tests results were converted into daily abnormal rate. After data cleaning, GAM statistical model construction and data analysis, a concentration-response relationship between air pollutants and daily abnormal rate of routine laboratory tests was observed. Our study found that PM_2.5 had a stable association with TP (lag07), ALB (lag07), ALT (lag07), AST (lag07), TBIL (lag07), DBIL (lag07), UREA (lag07), CREA (lag07), UA (lag07), CK (lag 06), GLU (lag07), WBC (lag07), Cl (lag07) and Ca (lag07), (P < 0.05); O₃ had a stable association with AST (lag01), CKMB (lag06), TG (lag07), TC (lag05), HDL-C (lag07), K (lag05) and RBC (lag07) (P < 0.05); CO had a stable association with UREA (lag07), Na (lag7) and PT (lag07) (P < 0.05); SO₂ had a stable association with TP (lag07) and LDL-C (lag0) (P < 0.05); NO₂ had a stable association with APTT (lag7) (P < 0.05). These results showed that different air pollutants affected different routine laboratory tests and presented different pedigrees. Therefore, biomarkers mined from routine laboratory tests may potentially be used to low-cost assess the health risks associated with air pollutants.

Analysis and forecasting of air quality index based on satellite data

OBJECTIVE

The air quality index (AQI) forecasts are one of the most important aspects of improving urban public health and enabling society to remain sustainable despite the effects of air pollution. Pollution control organizations deploy ground stations to collect information about air pollutants. Establishing a ground station all-around is not feasible due to the cost involved. As an alternative, satellite-captured data can be utilized for AQI assessment. This study explores the changes in AQI during various COVID-19 lockdowns in India utilizing satellite data. Furthermore, it addresses the effectiveness of state-of-the-art deep learning and statistical approaches for forecasting short-term AQI.

MATERIALS AND METHODS

Google Earth Engine (GEE) has been utilized to capture the data for the study. The satellite data has been authenticated against ground station data utilizing the beta distribution test before being incorporated into the study. The AQI forecasting has been explored using state-of-the-art statistical and deep learning approaches like VAR, Holt-Winter, and LSTM variants (stacked, bi-directional, and vanilla).

RESULTS

AQI ranged from 100 to 300, from moderately polluted to very poor during the study period. The maximum reduction was recorded during the complete lockdown period in the year 2020. Short-term AQI forecasting with Holt-Winter was more accurate than other models with the lowest MAPE scores.

CONCLUSIONS

Based on our findings, air pollution is clearly a threat in the studied locations, and it is important for all stakeholders to work together to reduce it. The level of air pollutants dropped substantially during the different lockdowns.

Short-term exposure to fine particulate matter constituents and mortality: case-crossover evidence from 32 counties in China

A growing number of studies associated increased mortality with exposures to specific fine particulate (PM_2.5) constituents, while great heterogeneity exists between locations. In China, evidence linking PM_2.5 constituents and mortality was extensively sparse. This study primarily aimed to quantify short-term associations between PM_2.5 constituents and non-accidental mortality among the Chinese population. We collected daily mortality records from 32 counties in China between January 1, 2011, and December 31, 2013. Daily concentrations of main PM_2.5 constituents (organic carbon (OC), elemental carbon (EC), nitrate (NO₃^-), sulfate (SO₄^2-), and ammonium (NH₄⁺)) were estimated using the modified Community Multiscale Air Quality model. Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM_2.5 mass and its constituents. Stratification analyses were done by sex, age, and season. A total of 116,959 non-accidental deaths were investigated. PM_2.5 concentrations on the day of death were averaged at 75.7 µg m^-3 (control day: 75.6 µg m^-3), with an interquartile range (IQR) of 65.2 µg m^-3. Per IQR rise in PM_2.5, EC, OC, NO₃^-, SO₄^2-, and NH₄⁺ at lag-04 day was associated with an increase in non-accidental mortality of 2.4% (95% confidence interval, (1.0-3.7), 1.7% (0.8-2.7), 2.9% (1.6-4.3), 2.1% (0.4-3.9), 1.0% (0.2-1.9), and 1.6% (0.3-2.9), respectively. Both PM_2.5 mass and its constituents were strongly associated with elevated cardiovascular mortality risks, but only PM_2.5, EC, and OC were positively associated with respiratory mortality at lag-3 day. PM_2.5 mass and its constituents associated effects on mortality varied among sex- and age-specific subpopulations. Differences in the seasonal pattern of associations exist among PM_2.5 constituents, with stronger effects related to EC and NO₃^- in warm months but SO₄^2- and NH₄⁺ in cold months. Short-term exposures to PM_2.5 compositions were positively associated with increased risks of mortality, particularly those constituents from combustion-related sources.

Short-term health impacts related to ozone in China before and after implementation of policy measures: A systematic review and meta-analysis

This paper presents a meta-analysis of the impacts of short-term exposure to ozone (O₃) on three health endpoints: all-cause, cardiovascular, and respiratory mortality in China. All relevant studies from January 1990 to December 2021 were searched from four databases. After screening, 30 studies were included for the meta-analysis. The results showed that a significant rise of 0.41 % (95 % confidence interval (CI): 0.35 %-0.48 %) in all-cause, 0.60 % (95 % CI: 0.51 %-0.68 %) in cardiovascular and 0.45 % (95 % CI: 0.28 %-0.62 %) in respiratory mortality for each 10 μg m^-3 increase in the maximum daily 8 h average O₃ concentration (MDA8 O₃). Moreover, results stratified by heterogeneous time periods before and after implementing a policy measure in 2013, showed that the pooled effects for all-cause and respiratory mortality before were greater than those after, while the pooled effects for cardiovascular mortality before 2013 were slightly smaller than those after. The finding that short-term exposure to O₃ was positively related to the three health endpoints was validated by means of a sensitivity analysis. Furthermore, we did not observe any publication bias. Our results present an updated and better understanding of the relationship between short-term exposure to O₃ and the three health endpoints, while providing a reference for further assessment of the impact of short-term O₃ exposure on human health.

Environmental variable importance for under-five mortality in Malaysia: A random forest approach

BACKGROUND

Environmental factors have been associated with adverse health effects in epidemiological studies. The main exposure variable is usually determined via prior knowledge or statistical methods. It may be challenging when evidence is scarce to support prior knowledge, or to address collinearity issues using statistical methods. This study aimed to investigate the importance level of environmental variables for the under-five mortality in Malaysia via random forest approach.

METHOD

We applied a conditional permutation importance via a random forest (CPI-RF) approach to evaluate the relative importance of the weather- and air pollution-related environmental factors on daily under-five mortality in Malaysia. This study spanned from January 1, 2014 to December 31, 2016. In data preparation, deviation mortality counts were derived through a generalized additive model, adjusting for long-term trend and seasonality. Analyses were conducted considering mortality causes (all-cause, natural-cause, or external-cause) and data structures (continuous, categorical, or all types [i.e., include all variables of continuous type and all variables of categorical type]). The main analysis comprised of two stages. In Stage 1, Boruta selection was applied for preliminary screening to remove highly unimportant variables. In Stage 2, the retained variables from Boruta were used in the CPI-RF analysis. The final importance value was obtained as an average value from a 10-fold cross-validation.

RESULT

Some heat-related variables (maximum temperature, heat wave), temperature variability, and haze-related variables (PM10, PM10-derived haze index, PM10- and fire-derived haze index, fire hotspot) were among the prominent variables associated with under-five mortality in Malaysia. The important variables were consistent for all- and natural-cause mortality and sensitivity analyses. However, different most important variables were observed between natural- and external-cause under-five mortality.

CONCLUSION

Heat-related variables, temperature variability, and haze-related variables were consistently prominent for all- and natural-cause under-five mortalities, but not for external-cause.

Identification of Health Effects of Complex Air Pollution in China

After the Chinese government introduced a series of policies to strengthen the control of air pollution, the concentration of particulate matter has decreased, but the concentration of ozone has increased, and the problem of complex air pollution still exists, posing a serious threat to public health. Therefore, disentangling the health effect of multi-pollutants has been a long-discussed challenge in China. To evaluate the adverse effects of complex air pollution, a generalized additive model was used to assess the health risks of different pollution types in eight metropolises in different climates in China from 2013 to 2016. Instead of directly introducing multiple pollutant concentrations, we integrated the concentration levels of PM_2.5, NO₂, and O₃ into a set of predictors by grouping methods and divided air pollution into three high single-pollutant types and four high multi-pollutant types to calculate mortality risk in different types. The comprehensive results showed that the impact of high multi-pollutant types on mortality risk was greater than that of high single-pollutant types. Throughout the study period, the high multi-pollutant type with high PM_2.5, NO₂, and O₃ and the high multi-pollutant type with high PM_2.5 and NO₂ were more associated with death, and the highest RRs were 1.129 (1.080, 1.181) and 1.089 (1.066, 1.113), respectively. In addition, the pollution types that most threaten people are different in different cities. These differences may be related to different pollution conditions, pollutant composition, and indoor-outdoor activity patterns in different cities. Seasonally, the risk of complex air pollution is greater in most cities in the warm season than in the cold season. This may be caused by the modifying effects of high temperature on pollutants in addition to different indoor-outdoor activity patterns in different seasons. The results also show that calculating the effect of individual air pollutants separately and adding them together may lead to an overestimation of the combined effect. It further highlights the urgency and need for air pollution health research to move towards a multi-pollutant approach that considers air pollution as a whole in the context of atmospheric abatement and global warming.

Short term exposure to air pollution and mortality in the US: a double negative control analysis

RATIONALE

Studies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models.

OBJECTIVES

To estimate the associations between short-term exposures to fine particulate matter (PM_2.5), ozone (O₃), and nitrogen dioxide (NO₂) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis.

METHODS

We conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000-2015, with over 3 million non-accidental deaths. Daily predictions of PM_2.5, O₃, and NO₂ at 1x1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls.

RESULTS

A 10 μg/m³ increase in PM_2.5 exposure at the moving average of lag 0-2 day was significantly associated with a 0.67% (95%CI: 0.34-1.01%) increase in all-cause mortality. 10 ppb increases in NO₂ or O₃ exposure at lag 0-2 day were marginally associated with and 0.19% (95%CI: -0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM_2.5 persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM_2.5, and mixed results for the gases. PM_2.5 was also significantly associated with respiratory mortality and cardiovascular mortality.

CONCLUSIONS

Short-term exposure to PM_2.5 and possibly O₃ and NO₂ are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible.

Long-term exposure to particulate air pollution and incidence of Parkinson's disease: A nationwide population-based cohort study in South Korea

There has been increasing interest in the neurological impact of particulate matter (PM). However, its association with the incidence of Parkinson's disease (PD) remains unclear. We selected 313,355 participants satisfying inclusion criteria from the National Health Insurance Service-National Sample Cohort based on the nationwide population of South Korea, and followed them up from January 2007 through December 2015. Individual-level long-term PM exposure was assessed as the five time-varying average concentrations estimated for the previous 1, 2, 3, 4 and 5 years on each year (until censored or event occurred) at the district-level residential addresses of participants using a previously validated prediction model. Incident PD was defined as the first diagnosis accompanied by anti-PD medication prescription from 2007 through 2015. Time-varying Cox proportional hazards models were employed to estimate the hazard ratio (HR) of incident PD for long-term PM exposure, adjusting for individual- and area-level covariates. During the 8 years (2,745,389 person-years) of follow-up for a total of 313,355 participants (mean [range] age, 48.9 [19-87] years; 169,571 males [54.1%]), 2621 participants (0.8%) developed PD. The HR of incident PD per interquartile range (3.3 μg/m³) increase in fine PM (PM_2.5) for the previous 1 year was 1.08 (95% confidence interval: 1.01-1.19). In subgroup-specific analyses, HRs for PM_2.5 were significant among older participants, males, participants living in metropolitan cities, ibuprofen users, and participants with comorbidities (HR: 1.10-1.20). Long-term exposure to PM_2.5 might play a role in PD development.

Spatiotemporal Correlation Analysis of Hydraulic Fracturing and Stroke in the United States

Hydraulic fracturing or fracking has led to a rapid growth of oil and gas production in the United States, but the impact of fracking on public health is an important but underresearched topic. We designed a methodology to study spatiotemporal correlations between the risk of fracking and stroke mortality. An annualized loss expectancy (ALE) model is applied to quantify the risk of fracking. The geographically and temporally weighted regression (GTWR) model is used to analyze spatiotemporal correlations of stroke mortality, fracking ALE, and nine other socioeconomic- and health-related factors. The analysis shows that fracking ALE is moderately correlated with stroke mortality at ages over 65 in most states of fracking, in addition to cardiovascular disease and drug overdose being positively correlated with stroke mortality. Furthermore, the correlations between fracking ALE and stroke mortality in men appear to be higher than in women near the Marcellus Shale, including Ohio, Pennsylvania, West Virginia, and Virginia, while stroke mortality among women is concentrated in the Great Plains, including Montana, Wyoming, New Mexico, and Oklahoma. Lastly, within two kilometers of the fracking mining activity, the level of benzene in the air was found to be significantly correlated with the fracking activity in Colorado.

Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006–2015

Background: The health effect of air pollution is rarely quantified in Africa, and this is evident in global systematic reviews and multi-city studies which only includes South Africa. Methods: A time-series analysis was conducted on daily mortality (cardiovascular (CVD) and respiratory diseases (RD)) and air pollution from 2006–2015 for the city of Cape Town. We fitted single- and multi-pollutant models to test the independent effects of particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ozone (O3) from co-pollutants. Results: daily average concentrations per interquartile range (IQR) increase of 16.4 µg/m3 PM10, 10.7 µg/m3 NO2, 6 µg/m3 SO2 and 15.6 µg/m3 O3 lag 0–1 were positively associated with CVD, with an increased risk of 2.4% (95% CI: 0.9–3.9%), 2.2 (95% CI: 0.4–4.1%), 1.4% (95% CI: 0–2.8%) and 2.5% (95% CI: 0.2–4.8%), respectively. For RD, only NO2 showed a significant positive association with a 4.5% (95% CI: 1.4–7.6%) increase per IQR. In multi-pollutant models, associations of NO2 with RD remained unchanged when adjusted for PM10 and SO2 but was weakened for O3. In CVD, O3 estimates were insensitive to other pollutants showing an increased risk. Interestingly, CVD and RD lag structures of PM10, showed significant acute effect with evidence of mortality displacement. Conclusion: The findings suggest that air pollution is associated with mortality, and exposure to PM10 advances the death of frail population.

Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013-2020

Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/), we characterized the spatiotemporal variations in PM_2.5 and O₃ exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM_2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O₃ pollution worsened, with the average April-September O₃ exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM_2.5 concentration. It is also noticed that with smaller PM_2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM_2.5-polluted days with the daily average PM_2.5 higher than 75 μg/m³ and the considerable increase in O₃-polluted days with the daily maximum 8 h average O₃ higher than 160 μg/m³, deaths attributable to the short-term O₃ exposure were greater than those due to PM_2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM_2.5 and O₃ are urgently needed.

A Time-Series Study for Effects of Ozone on Respiratory Mortality and Cardiovascular Mortality in Nanchang, Jiangxi Province, China

Objective

Most evidence comes from studies show that ambient ozone(O₃) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province.

Methods

Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O₃-8h). Besides, analyses were also stratified by season, age and sex.

Results

In the single-pollutant model, for every 10 μg/m³ increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05).

Conclusions

In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.

Extended two-stage designs for environmental research

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Ambient gaseous pollutants and emergency ambulance calls for all-cause and cause-specific diseases in China: a multicity time-series study

Much attention has been paid to the health effects of ambient particulate matter pollution; the effects of gaseous air pollutants have not been well studied. Emergency ambulance calls (EACs) may provide a better indicator of the acute health effects than the widely used health indicators, such as mortality and hospital admission. We estimated the short-term associations between gaseous air pollutants [nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃)] and EACs for all-cause, cardiovascular, and respiratory diseases in seven Chinese cities from 2014 to 2019. We used generalized additive models and random-effects meta-analysis to examine the city-specific and pooled associations. Stratified analyses were conducted by age, sex, and season. A total of 1,626,017 EACs were observed for all-cause EACs, including 230,537 from cardiovascular diseases, and 96,483 from respiratory diseases. Statistically significant associations were observed between NO₂ and EACs for all-cause diseases, while the effects of SO₂ were positive, but not statistically significant in most models. No significant relationship was found between O₃ and EACs. Specifically, each 10 μg/m³ increase in the 2-day moving average concentration of NO₂ was associated with a 1.07% [95% confidence interval (CI): 0.40%, 1.76%], 0.76% (95% CI: 0.19%, 1.34%) and 0.06% (95% CI: -1.57%, 1.73%) increase in EACs due to all-cause, cardiovascular and respiratory diseases, respectively. Stratified analysis showed a larger effect of NO₂ on all-cause EACs in the cold season [excess relative risk (ERR): 0.33% (95% CI: 0.05%, 0.60%) for warm season, ERR: 0.77% (95% CI: 0.31%, 1.23%) for cold season]. Our study indicates that acute exposures to NO₂ might be an important trigger of the emergent occurrence of all-cause, cardiovascular and respiratory diseases, and this effect should be of particular concern in the cold season. Further policy development for controlling gaseous air pollution is warranted to reduce the emergent occurrence of cardiopulmonary diseases.

Modeling mortality rates and environmental degradation in Asia and the Pacific: does income group matter?

This two-dimensional study makes significant incursions into the health-environment literature by interrogating whether non-renewable energy moderates the impact of environmental degradation on mortality rates. It further aligns with the 2030 United Nations Sustainable Development Goals and 11, which aim to ensure healthy lives and promote well-being for all at all ages and make cities and human settlements inclusive, safe, resilient and sustainable. It contributes to the health-environment literature by investigating the intrinsic relationships among mortality rates, carbon emissions (environmental degradation), and non-renewable energy consumption. The study uses an unbalanced sample of 42 Asia and Pacific countries to determine (1) whether carbon emissions exaggerate the incidence of mortality rates and (2) if the interaction of non-renewable energy with carbon emissions enhances or alters the impact of carbon emissions on mortality rates. Consistent findings from the panel spatial correlation consistent least-squares dummy variables (PSCC-LSDV) and two-step system generalized method of moments (GMM) techniques reveal that (i) carbon emissions exacerbate mortality rates; (ii) non-renewable energy consumption exhibit mortality-reducing properties; (iii) non-renewable energy attenuates the impact of carbon emissions on mortality rates, (iv) persistency in mortalities occurs; and (v) the health-environment-energy dynamics differ across income groups. The paper's conjecture is expected to channel a new line of discourse on how non-renewable energy influences the environment and health outcomes.

Does Advanced Human Capital Structure Provide Positive Feedback on Public Health? Evidence From China

This paper explores the relationship of advanced human capital structure with public health applying the panel threshold regression model in China. The empirical results highlight that the advanced human capital structure has a non-linear single threshold effect on population health indicators. The health-promoting effect of advanced human capital structure is significantly weaker when exceeding the threshold. These asymmetric effects are strongly related to the response of China's health policies. The promotion effect of the advanced human capital structure on public health has significant heterogeneity in different regions. There is a single threshold value in the eastern and central regions, but the threshold value and facilitation effect are different. However, the western region has no threshold. The heterogeneity effects are caused by the different levels of advanced human capital structure. Governments should adopt appropriate public health policies according to the development characteristics of different regions.

Smaller particular matter, larger risk of female lung cancer incidence? Evidence from 436 Chinese counties

BACKGROUND

Many studies have reported the effects of PM_2.5 and PM₁₀ on human health, however, it remains unclear whether particular matter with finer particle size has a greater effect.

OBJECTIVES

This work aims to examine the varying associations of the incidence rate of female lung cancer with PM₁, PM_2.5 and PM₁₀ in 436 Chinese cancer registries between 2014 and 2016.

METHODS

The effects of PM₁, PM_2.5 and PM₁₀ were estimated through three regression models, respectively. Mode l only included particular matter, while Model 2 and Model 3 further controlled for time and location factors, and socioeconomic covariates, respectively. Moreover, two sensitivity analyses were performed to investigate the robustness of three particular matte effects. Then, we examined the modifying role of urban-rural division on the effects of PM₁, PM_2.5 and PM₁₀, respectively.

RESULTS

The change in the incidence rate of female lung cancer relative to its mean was 5.98% (95% CI: 3.40, 8.56%) for PM₁, which was larger than the values of PM_2.5 and PM₁₀ at 3.75% (95% CI: 2.33, 5.17%) and 1.57% (95% CI: 0.73, 2.41%), respectively. The effects of three particular matters were not sensitive in the two sensitivity analyses. Moreover, urban-rural division positively modified the associations of the incidence rate of female lung cancer with PM₁, PM_2.5 and PM₁₀.

CONCLUSIONS

The effect on the incidence rate of female lung cancer was greater for PM₁, followed by PM_2.5 and PM₁₀. There were positive modifying roles of urban-rural division on the effects of three particular matters. The finding supports the argument that finer particular matters are more harmful to human health, and also highlights the great significance to develop guidelines for PM₁ control and prevention in Chinese setting.

Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China

Fine particulate matter (PM_2.5) and respirable particulate matter (PM₁₀) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM_2.5 and PM₁₀ hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM_2.5 and PM₁₀ at 38.17 and 59.84 μg/m³, respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m³ increase in PM_2.5 and PM₁₀ in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO₂, O₃, CO, and SO₂ had different significant effects on the number of hospitalizations over the same time period, and PM_2.5 and PM₁₀ still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter.

Assessment of the Factors Influencing Sulfur Dioxide Emissions in Shandong, China

Sulfur dioxide (SO2) is a serious air pollutant emitted from different sources in many developing regions worldwide, where the contribution of different potential influencing factors remains unclear. Using Shandong, a typical industrial province in China as an example, we studied the spatial distribution of SO2 and used geographical detectors to explore its influencing factors. Based on the daily average concentration in Shandong Province from 2014 to 2019, we explored the influence of the diurnal temperature range, secondary production, precipitation, wind speed, soot emission, sunshine duration, and urbanization rate on the SO2 concentration. The results showed that the diurnal temperature range had the largest impact on SO2, with q values of 0.69, followed by secondary production (0.51), precipitation (0.46), and wind speed (0.42). There was no significant difference in the SO2 distribution between pairs of sunshine durations, soot emissions, and urbanization rates. The meteorological factors of precipitation, wind speed, and diurnal temperature range were sensitive to seasonal changes. There were nonlinear enhancement relationships among those meteorological factors to the SO2 pollution. There were obvious geographical differences in the human activity factors of soot emissions, secondary production, and urbanization rates. The amount of SO2 emissions should be adjusted in different seasons considering the varied effect of meteorological factors.

Effect of short-term ambient PM2.5 exposure on fasting blood glucose levels: A longitudinal study among 47,471 people in eastern China

As a common health indicator in physical examinations, fasting blood glucose (FBG) level measurements are widely applied as a diagnostic method for diabetes mellitus. Uncertain conclusions remained regarding the relationship between PM_2.5 exposure and FBG levels. We enrolled 47,471 subjects who participated in annual physical examinations between 2017 and 2019. We collected their general characteristics and FBG levels, and environmental factors simultaneously. We applied the generalized additive model to evaluate the impact of short-term outdoor PM_2.5 exposure on FBG levels. Among the entire population, the single-pollutant models showed that a 10 μg/m³ increase in PM_2.5 significantly contributed to 0.0030, 0.0233, and 0.0325 mmol/L increases in FBG at lag 0-7 days, lag 0-21 days, and lag 0-28 days, respectively. Accordingly, in multipollutant models, when PM_2.5 increased by 10 μg/m³, there was an elevation of 0.0361, 0.0315, 0.0357, and 0.0387 mmol/L in FBG for 8-day, 15-day, 22-day, and 29-day moving averages, respectively. Similarly, we observed a significant positive association between them in the normal population. Moreover, the effects could be modified by age in both the entire and normal populations. Decreasing the ambient PM_2.5 concentrations can alleviate the elevation of FBG, which may significantly impact the burden of diabetes mellitus.

Missing Value Imputation of Time-Series Air-Quality Data via Deep Neural Networks

To prevent severe air pollution, it is important to analyze time-series air quality data, but this is often challenging as the time-series data is usually partially missing, especially when it is collected from multiple locations simultaneously. To solve this problem, various deep-learning-based missing value imputation models have been proposed. However, often they are barely interpretable, which makes it difficult to analyze the imputed data. Thus, we propose a novel deep learning-based imputation model that achieves high interpretability as well as shows great performance in missing value imputation for spatio-temporal data. We verify the effectiveness of our method through quantitative and qualitative results on a publicly available air-quality dataset.

Short-term exposure to ambient air pollution and type 2 diabetes mortality: A population-based time series study

Acute health effects of air pollution on diabetes risk have not been fully studied in developing countries and the results remain inconsistent. This study aimed to investigate the association between short-term exposure to ambient air pollution and Type 2 diabetes mellitus (T2DM) mortality in China. Data on T2DM mortality from 2013 to 2019 were obtained from the Cause of Death Reporting System (CDRS) of Wuhan Center for Disease Control and Prevention. Air pollution data for the same period were collected from 10 national air quality monitoring stations of Wuhan Ecology and Environment Institute, including daily average PM_2.5, PM₁₀, SO₂, and NO₂. Meteorological data including daily average temperature and relative humidity were collected from Wuhan Meteorological Bureau. Generalized additive models (GAM) based on quasi-Poisson distribution were applied to evaluate the association between short-term exposure to air pollution and daily T2DM deaths. A total of 9837 T2DM deaths were recorded during the study period in Wuhan. We found that short-term exposure to PM_2.5, PM₁₀, SO₂, and NO₂ were positively associated with T2DM mortality, and gaseous pollutants appeared to have greater effects than particulate matter (PM). For the largest effect, per 10 μg/m³ increment in PM_2.5 (lag 02), PM₁₀ (lag 02), SO₂ (lag 03), and NO₂ (lag 02) were significantly associated with 1.099% (95% CI: 0.451, 1.747), 1.016% (95% CI: 0.517, 1.514), 3.835% (95% CI: 1.480, 6.189), and 1.587% (95% CI: 0.646, 2.528) increase of daily T2DM deaths, respectively. Stratified analysis showed that females or elderly population aged 65 and above were more susceptible to air pollution exposure. In conclusion, short-term exposure to air pollution was significantly associated with a higher risk of T2DM mortality. Further research is required to verify our findings and elucidate the underlying mechanisms.

Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO₂), is related to adverse health effects and mortality.

METHODS

We conducted a systematic review of short-term NO₂ and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias.

RESULTS

We included 87 articles in our quantitative analysis. NO₂ and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO₂ was associated with a 1.58% (95%CI 1.28%-1.88%, I² = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO₂ was associated with a 1.72% (95%CI 1.41%-2.04%, I² = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I² = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification.

CONCLUSIONS

This study provides evidence of an association between short-term exposure to NO₂, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.

Ambient Ozone, PM1 and Female Lung Cancer Incidence in 436 Chinese Counties

Ozone air pollution has been increasingly severe and has become another major air pollutant in Chinese cities, while PM₁ is more harmful to human health than coarser PMs. However, nationwide studies estimating the effects of ozone and PM₁ are quite limited in China. This study aims to assess the spatial associations between ozone (and PM₁) and the incidence rate of female lung cancer in 436 Chinese cancer registries (counties/districts). The effects of ozone and PM₁ were estimated, respectively, using statistical models controlling for time, location and socioeconomic covariates. Then, three sensitivity analyses including the adjustments of smoking covariates and co-pollutant (SO₂) and the estimates of ozone, PM1 and SO₂ effects in the same model, were conducted to test the robustness of the effects of the two air pollutants. Further still, we investigated the modifying role of urban-rural division on the effects of ozone and PM₁. According to the results, a 10 μg/m³ increase in ozone and PM₁ was associated with a 4.57% (95% CI: 4.32%, 16.16%) and 4.89% (95% CI: 4.37%, 17.56%) increase in the incidence rate of female lung cancer relative to its mean, respectively. Such ozone and PM₁ effects were still significant in three sensitivity analyses. Regarding the modifying role of urban-rural division, the effect of PM₁ was greater by 2.98% (95% CI: 1.01%, 4.96%) in urban than in rural areas when PM1 changed by 10 μg/m³. However, there was no modification effect of urban-rural division for ozone. In conclusion, there were positive associations between ozone (and PM₁) and the incidence rate of female lung cancer in China. Urban-rural division may modify the effect of PM₁ on the incidence rate of female lung cancer, which is seldom reported. Continuous and further prevention and control measures should be developed to alleviate the situation of the two air pollutants.

Valuation of Local Demand for Improved Air Quality: The Case of the Mae Moh Coal Mine Site in Thailand

While the district of Mae Moh, Thailand has been well known for its atmospheric pollution associated with coal power production, economic assessment of demand for improved air quality has not been conducted to date. This study estimated local residents’ individual and aggregate willingness to pay (WTP) for mitigation of atmospheric pollution in Mae Moh using the contingent valuation method (CVM), and analyzed the factors associated with the individual WTP using the bivariate tobit and double-hurdle regression techniques. Primary data were collected through face-to-face interviews with a stratified sample of 200 residents. The hypothetical scenarios used in the CVM module were 50% and 80% mitigation of atmospheric concentrations of major pollutants. The weighted average WTP was found to be THB 251.3 and 307.9 per annum (USD 8.4 and 10.3) for the 50% and 80% reduction scenarios, respectively. The aggregate WTP for the entire population of Mae Moh was THB 10,008,733 and 12,264,761 per annum (USD 336,294 and 412,096), respectively. Education, occupation type, income, expenses, satisfaction with ambient quality, and perceived sources of pollution had significant associations with the individual WTP. The paper concludes by discussing policy implications for atmospheric pollution management and avenues for future research.

The short-term associations of particular matters on non-accidental mortality and causes of death in Chiang Mai, Thailand: a time series analysis study between 2016-2018

Open burnings, agricultural and forest fires, are the major sources of particulate matters (PM) in Chiang Mai during dry season. We aim to determine the association of an increased daily PM (PM₁₀, PM_2.5) and daily non-accidental mortality and causes of death in Chiang Mai. The association between PM and daily non-accidental mortality including causes of death were analyzed using a generalized linear model with Poisson distribution. The results showed that PM₁₀ and PM_2.5 were associated with daily non-accidental mortality on different lag days (adjusted RR range from 1.009-1.018 and 1.016 for each 10 µg/m³ increment of PM₁₀ and PM_2.5, respectively). The causes of death associated with PM₁₀, PM_2.5 found on different lag days were chronic obstructive pulmonary disease (COPD), coronary artery disease (CAD), and sepsis. We concluded that PM₁₀ and PM_2.5 are associated with daily non-accidental mortality and causes of death were COPD, CAD, and sepsis.

Exposure to ambient particulate matter and biomass burning during pregnancy: associations with birth weight in Thailand

BACKGROUND

There is a growing evidence that exposure to ambient particulate air pollution during pregnancy is associated with adverse birth outcomes, including reduced birth weight (BW). The objective of this study was to quantify associations between BW and exposure to particulate matter (PM) and biomass burning during pregnancy in Thailand.

METHODS

We collected hourly ambient air pollutant data from ground-based monitors (PM with diameter of <10 µm [PM₁₀], Ozone [O₃], and nitrogen dioxide [NO₂]), biomass burning from satellite remote sensing data, and individual birth weight data during 2015-2018. We performed a semi-ecological analysis to evaluate the association between mean trimester exposure to air pollutants and biomass burning with BW and low-birth weight (LBW) (<2500 g), adjusting for gestation age, sex, previous pregnancies, mother's age, heat index, season, year, gaseous pollutant concentrations, and province. We examined potential effect modification of PM₁₀ and biomass burning exposures by sex.

RESULTS

There were 83,931 eligible births with a mean pregnancy PM₁₀ exposure of 39.7 µg/m³ (standard deviation [SD] = 7.7). The entire pregnancy exposure was associated with reduced BW both for PM₁₀ (-6.81 g per 10 µg/m³ increase in PM₁₀ [95% CI = -12.52 to -1.10]) and biomass burning (-6.34 g per 1 SD increase in fires/km² [95% CI = -11.35 to -1.34]) only after adjustment for NO₂. In contrast with these findings, a reduced odds ratio (OR) of LBW was associated with PM₁₀ exposure only in trimesters one and two, with no relationship across the entire pregnancy period. Associations with biomass burning were limited to increased ORs of LBW with exposure in trimester three, but only for male births.

CONCLUSION

Based on our results, we encourage further investigation of air pollution, biomass burning and BW in Thailand and other low-income and middle-income countries.

Impact of Ambient Air Quality Standards revision on the exposure-response of air pollution in Tianjin, China

To improve air quality, China issued a new version of Ambient Air Quality Standards in 2012, and Tianjin officially implemented these new standards in 2013. In order to observe whether the atmospheric quality and health had been improved after the release of the new standards, this study compared the exposure-response relationships between pollutant concentrations and daily deaths (and years of life lost, YLL) in the six central districts of Tianjin in 2007-2010 and 2014-2017, which were the two periods around the release of the new standards. The exposure-response coefficients were calculated by using the generalized additive model with the time series data. The results showed that the effects of PM₁₀ and NO₂ during 2014-2017 were lower than those during 2007-2010 (PM₁₀: 0.10<0.30, 2.07<4.52; NO2: 0.24<0.87, 6.39<11.98), while the results of SO₂ were opposite (SO₂: 0.61>0.31, 10.31>1.64). And the excess deaths and YLL caused by the portion of the pollutants that exceeded the new standards also declined (PM₁₀: 156<206 persons, 3493<3913 person-years; NO₂: 64<136 persons, 1844<2895 person-years; SO₂ did not exceed the new standards). The results proved that the new standards had a certain protective effect on the health of the population in the central districts of Tianjin. These findings may provide evidence for the formulation of public health policies and further improvement and development of the Ambient Air Quality Standards.

Human health risk associated to particulate matter and polycyclic aromatic hydrocarbon levels and their relation with preponderant sources in Gran La Plata, Argentina

Levels of suspended particulate matter (PM) of both fractions PM₁₀ and PM_2.5 in ambient air were monitored in three areas of Gran La Plata: industrial, urban, and residential (2017-2019). Associated polycyclic aromatic hydrocarbons (PAHs) and nitropolycyclic aromatic hydrocarbons (NPAHs) to PM were also determined and possible emission sources were identified. Assessment of health risk to PM exposure and associated compounds was realized. Results showed a decrease in levels of PM₁₀ in each area along the period studied, especially in the industrial area. Decreases in PM_2.5 levels were also observed in urban and residential areas over the years, although the trend is not as marked as with PM₁₀ levels. Then, PM_2.5 levels in the industrial area have remained practically constant. The 89% of both PM₁₀ and PM_2.5 annual mean exceeds the WHO reference values. The presence of most of the 16 US EPA priority PAHs studied was found with a detection frequency greater than 60% and it was possible to identify the importance of the contributions of vehicular emissions as predominant sources of PAH emission. From the calculations of the risk of contracting cancer throughout life (LCR), in the case of adults, the US EPA limits were not complied in the industrial and urban areas and in both fractions of PM. From the evaluation of the burden of disease (EBD), the calculated relative risks of mortality were very similar for the studied districts, being the relative risk in La Plata slightly lower, about 3-5%, than those in Berisso and Ensenada.

Monitoring the Impact of COVID-19 Lockdown on the Production of Nitrogen Dioxide (NO2) Pollutants Using Satellite Imagery: A Case Study of South Asia

Among the numerous anthropogenic pollutants, nitrogen dioxide (NO2) is one of the leading contaminants mainly released by burning fossil fuels in industrial and transport sectors. This study evaluates the impact of COVID-19 lockdown on the growing trend of NO2 emissions in South Asia. Satellite imagery data of Sentinel-5 Precursor with Tropomi instrument was employed in this study. The analysis was performed using time series data from February–May 2019 and February–May 2020. The time frame from February–May 2020 was further divided into two sub-time-frames, i.e., from 1 February–20 March (pre-lockdown) and from 21 March–May 2020 (lockdown). Results show the concentration of NO2 pollutants over the region declined by 6.41% from February–May 2019 to February–May 2020. Interestingly, an increasing trend of NO2 concentration by 6.58% occurred during the pre-lockdown phase in 2020 (1 February–20 March) compared to 2019 (February–May). However, the concentration of NO2 pollutants reduced considerably by 21.10% during the lockdown phase (21 March–10 May) compared to the pre-lockdown phase in 2020. Furthermore, the country-specific detailed analysis demonstrates the significant impact of COVID-19-attributed lockdown on NO2 concentration in South Asia.

Short-term effects of air pollution on daily asthma-related emergency department visits in an industrial city

BACKGROUND

Epidemiological studies from Europe and North America have provided evidence that exposure to air pollution can aggravate symptoms in asthmatic patients.

METHODS

Daily number of AEDv, air pollution levels (PM10, PM2.5, SO2, NO2 and CO) and meteorological variables was obtained from Jubail Industrial City, Saudi Arabia, for the period of 2007-11. Data were analyzed using a time-series approach. Relative risks (RRs) were estimated using Poisson regression.

RESULTS

The associations between AEDv and PM10, PM2.5, SO2 and NO2 remained positive and statistically significant after mutual adjustment in the multi-pollutant model.The RR of AEDv increased by 5.4, 4.4, 3.4 and 2.2% per an inter-quartile range increase in SO2 (2.0 ppb), PM2.5 (36 μg/m3), NO2 (7.6 ppb) and PM10 (140 μg/m3), respectively. No significant associations between AEDv and CO were found.

CONCLUSIONS

Current levels of ambient air pollution are associated with AEDv in this industrial setting in the Middle East. Greater awareness of environmental health protection and the implementation of effective measures to improve the quality of air in such settings would be beneficial to public health.

Spatiotemporal assessment of health burden and economic losses attributable to short-term exposure to ground-level ozone during 2015-2018 in China

BACKGROUND

Ground-level ozone (O3) pollution is currently the one of the severe environmental problems in China. Although existing studies have quantified the O3-related health impact and economic loss, few have focused on the acute health effects of short-term exposure to O3 and have been limited to a single temporal and spatial dimension.

METHODS

Based on the O3 concentration obtained from ground monitoring networks in 334 Chinese cities in 2015-2018, this study used a two-stage exposure parameter weighted Log-linear exposure-response function to estimate the cause-specific mortality for short-term exposure to O3.

RESULTS

The value of statistical life (VSL) method that were used to calculate the economic loss at the city-level. Our results show that in China, the national all-cause mortality attributed to O3 was 0.27(95% CI: 0.14-0.55) to 0.39 (95% CI: 0.20-0.67) million across 2015-2018. The estimated economic loss caused by O3 was 387.76 (95% CI: 195.99-904.50) to 594.08 (95% CI: 303.34-1140.65) billion CNY, accounting for 0.52 to 0.69% of total reported GDP. Overall, the O3 attributed health and economic burden has begun to decline in China since 2017. However, highly polluted areas still face severe burden, and undeveloped areas suffer from high GDP losses.

CONCLUSIONS

There are substantial health impacts and economic losses related to short-term O3 exposure in China. The government should pay attention to the emerging ozone pollution, and continue to strengthen the intervention in traditional priority areas while solving the pollution problem in non-priority areas.

Ambient air pollution and cerebrovascular disease mortality: an ecological time-series study based on 7-year death records in central China

Most studies of short-term exposure to ambient air pollution and cerebrovascular diseases focused on specific stroke-related outcomes, and results were inconsistent due to data unavailability and limited sample size. It is unclear yet how ambient air pollution contributes to the total cardiovascular mortality in central China. Daily deaths from cerebrovascular diseases were obtained from the Disease Surveillance Point System (DSPs) of Wuhan Center for Disease Control and Prevention during the period from 2013 to 2019. Air pollution data were obtained from Wuhan Ecology and Environment Institute from 10 national air quality monitoring stations, including average daily PM_2.5, PM₁₀, SO₂, NO₂, and O₃. Average daily temperature and relative humidity were obtained from Wuhan Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to examine the association between ambient air pollution and cerebrovascular disease mortality. We observed a total of 84,811 deaths from cerebrovascular diseases from 1 January 2013 to 31 December 2019 in Wuhan. Short-term exposure to PM_2.5, PM₁₀, SO₂, and NO₂ was positively associated with daily deaths from cerebrovascular diseases, and no significant association was found for O₃. The largest effect on cerebrovascular disease mortality was found at lag0 for PM_2.5 (ERR: 0.927, 95% CI: 0.749-1.105 per 10 μg/m3) and lag1 for PM₁₀ (ERR: 0.627, 95% CI: 0.493-0.761 per 10 μg/m³), SO₂ (ERR: 2.518, 95% CI: 1.914, 3.122 per 10 μg/m³), and NO₂ (ERR: 1.090, 95% CI: 0.822-1.358 per 10 μg/m³). The trends across lags were statistically significant. The stratified analysis demonstrated that females were more susceptible to SO₂ and NO₂, while elder individuals aged above 65 years old, compared with younger people, suffered more from air pollution, especially from SO₂. Short-term exposure to PM_2.5, PM₁₀, SO₂, and NO₂ were significantly associated with a higher risk of cerebrovascular disease mortality, and elder females seemed to suffer more from air pollution. Further research is required to reveal the underlying mechanisms.