Time series analysis of ambient air pollution effects on daily mortality

Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium

BACKGROUND

The adverse effect of air pollution on mortality is well documented worldwide but the identification of more vulnerable populations at higher risk of death is still limited. The aim of this study was to evaluate the association between natural mortality (overall and cause-specific) and short-term exposure to five air pollutants (PM2.5, PM10, NO2, O3 and black carbon) and identify potential vulnerable populations in Belgium.

METHODS

We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association.

RESULTS

The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2).

CONCLUSIONS

This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.

Association Between Air Pollution and Coronary Heart Disease Hospitalizations in Lanzhou City, 2013-2020: a Time Series Analysis

Coronary heart disease (CHD) is one of the most serious public health problems. However, few studies have focused on the effects of exposure to particulate matter and gaseous air pollutants on CHD. This study aimed to explore the relationship between air pollutants and the number of hospitalized patients with CHD in Lanzhou, and we collected daily data on the number of hospitalized patients with CHD, daily air pollutants, and meteorological factors from 2013 to 2020. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson regression model was applied to evaluate the relationship between air pollutants and the number of hospitalized patients with CHD. The results indicated that the hysteresis effect of all pollutants except O38h reached its maximum at lag3, and the relative risk of coronary heart disease admission was 1.0014 (95%CI: 1.0004, 1.0023), 1.0003 (95%CI: 1.0000, 1.0006), 1.0020 (95%CI: 1.0004, 1.0035), and 1.0053 (95%CI: 1.0026, 1.0080) when PM2.5, PM10, NO2, and SO2 concentrations were increased by 10 μg/m3, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of coronary heart disease; hospitalization risk was 1.1076 (95%CI: 1.0530, 1.1650). We observed a relative risk of 0.9991 (95%CI: 0.9986, 0.9999) for each 10 μg/m3 increase in O38h for coronary heart disease admission at lag1. Women and elderly were more susceptible to the impact of air pollution, and the impact was greater during cold seasons. Our results indicate that air pollution increased the risk of hospitalization for CHD in a short term. The research findings can provide strategic insights into the impact of current and future air pollution on CHD.

Association between air quality index and effects on emergency department visits for acute respiratory and cardiovascular diseases

BACKGROUND AND OBJECTIVE

Several studies suggest that air pollution, particularly PM2.5, increases morbidity and mortality, Emergency Department (ED) visits, and hospitalizations for acute respiratory and cardiovascular diseases. However, no prior study in Southeastern Asia (SEA) has examined the effects of air pollutants on ED visits and health outcomes. This study focused on the association of the Air Quality Index (AQI) of PM2.5 and other pollutants' effects on ED visits, hospitalization, and unexpected deaths due to acute respiratory disease, acute coronary syndrome (ACS), acute heart failure (AHF), and stroke.

METHODS

We conducted a retrospective study with daily data from ED visits between 2018 and 2019 at Maharaj Nakorn Chiang Mai Hospital, Chiang Mai, Thailand. The AQI of air pollution data was collected from outdoor air quality from the Smoke Haze Integrated Research Unit and the Air Quality Index Visual Map. A distributed lag, non-linear and quasi-Poisson models were used to explore the relationship between air quality parameters and ED visits for each disease.

RESULTS

3,540 ED visits were recorded during the study period. The mean daily AQI of PM2.5 was 89.0 ± 40.2. We observed associations between AQI of PM2.5 and the ED visits due to ACS on the following day (RR = 1.023, 95% confidence interval [CI]: 1.002-1.044) and two days after exposure (RR = 1.026, 95% CI: 1.005-1.047). Also, subgroup analysis revealed the association between AQI of PM2.5 and the ED visits due to pneumonia on the current day (RR = 1.071, 95% CI: 1.025-1.118) and on the following day after exposure (RR = 1.024, 95% CI: 1.003-1.046). AQI of PM2.5 associated with increased mortality resulted from ACS on lag day 3 (OR = 1.36, 95% CI: 1.08-1.73). The AQI of PM10 is also associated with increased ED visits due to COPD/asthma and increased hospitalization in AHF. In addition, the AQI of O3 and AQI of NO2 is associated with increased ICU admissions and mortality in AHF.

CONCLUSION

Short-term PM2.5 exposure escalates ED visits for ACS and pneumonia. PM10's AQI associates with COPD/asthma ED visits and AHF hospitalizations. AQI of O3 and NO2's link to increased ICU admissions and AHF mortality. Urgent action against air pollution is vital to safeguard public health.

Association Between Exposure to Ozone (O3) and the Short-Term Effect on Tuberculosis Outpatient Visits: A Time-Series Study in 16 Cities of Anhui Province, China

Introduction

Evidence has shown that air pollutant exposure plays a vital role in the progression of tuberculosis (TB). The aim of this research was to assess the short-term effects of ozone (O₃) exposure and TB outpatient visits in 16 prefecture-level cities of Anhui, China, 2015-2020.

Methods

Distributed lag nonlinear model (DLNM), Poisson generalized linear regression model and random effects model were applied in this study. The effects of different age and gender on TB were investigated by stratified analysis, and then we performed sensitivity analyses to verify the stability of the results.

Results

A total of 186,623 active TB cases were registered from January 1, 2015 to December 31,2020 in Anhui. The average concentration of ozone is 92.77 ± 42.95 μg/m³. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits was 1.0240 (95% CI: 1.0170-1.0310, lag 28 days) for each 10 µg/m³ increase in O₃ in the single-pollutant model. Estimation for 16 prefecture-level cities indicated that the strong association between O₃ and the risk of TB outpatient visits was in tongling (RR = 1.0555, 95% CI: 1.0089-1.1042), Suzhou (RR = 1.0475, 95% CI: 1.0268-1.0687), wuhu (RR = 1.0358, 95% CI: 1.0023-1.0704). Stratified analysis showed that the health effects of ozone exposure remained significant in male and older adults, and there was no significant association between exposure to ozone in children and adolescents and the risk of tuberculosis.

Discussion

We found that ozone exposure increases the risk of TB infection in outpatient patients, with males and the elderly being more susceptible, and it is necessary for government departments to develop targeted publicity and prevention measures in response to the local air quality conditions.

Long-term exposure to ambient air pollution and greenness in relation to pulmonary tuberculosis in China: A nationwide modelling study

Previous studies have attempted to clarify the relationship between the occurrence of pulmonary tuberculosis (PTB) and exposure to air pollutants. However, evidence from multi-centres, particularly at the national level, is scarce, and no study has examined the modifying effect of greenness on air pollution-TB associations. In this study, we examined the association between long-term exposure to ambient air pollutants (PM₁₀ p.m._2.5, and O₃) and monthly PTB or smear-positive pulmonary tuberculosis (SPPTB) incidence to further evaluate whether these associations were affected by greenness in mainland China using a two-stage analytic procedure. PM_2.5 was positively associated with both PTB and SPPTB incidence, with relative risk (RR) of 1.12 (95% confidence interval [CI]: 1.03, 1.22) and 1.08 (95% CI: 1.02, 1.10) per 10 μg/m³ increase, respectively. Furthermore, PM₁₀ was positively associated with PTB incidence, with RR of 1.07 (95% CI: 1.01, 1.13). However, O₃ was not associated with the monthly incidence of PTB or SPPTB. The normalized difference vegetation index (NDVI) exhibited a modifying effect on the association between PM_2.5 exposure and SPPTB incidence in northern areas, with RR of 1.16 (95% CI: 1.03, 1.31) in lower mean annual NDVI areas than in the higher areas (RR = 0.98, 95% CI: 0.87, 1.09). This nationwide analysis indicated that NDVI could reduce the effect of air pollutants on TB incidence particularly in the northern areas. Long-term exposure to particulate matter (PM) may increase the occurrence of PTB or SPPTB in China, and further studies involving larger numbers of SPPTB cases are required to confirm the effects of PM exposure on SPPTB incidence in the future.

Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution

Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM10), ozone (O3), and nitrogen dioxide (NO2) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021–1.025, per 10 μg/m3 PM10 increase, RR = 1.123 at lag 05, 95% CI: 1.118–1.129, per 10 ppb O3 increase, and RR = 1.110 at lag 05, 95% CI: 1.102–1.119, per 10 ppb NO2 increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015–1.017, per 10 μg/m3 PM10 increase, RR = 1.073 at lag 06, 95% CI: 1.070–1.076, per 10 ppb O3 increase, and RR = 1.046 at lag 06, 95% CI: 1.040–1.051, per 10 ppb NO2 increase). Multi-pollutants modeling analysis identified O3 as a relatively independent risk factor and PM10-NO2 pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control.

Short-term effect of sulfur dioxide (SO2) change on the risk of tuberculosis outpatient visits in 16 cities of Anhui Province, China: the first multi-city study to explore differences in occupational patients

A growing number of biological studies suggest that exogenous sulfur dioxide (SO₂) at a certain concentration may promote human resistance to Mycobacterium tuberculosis. However, the results of most relevant studies are inconsistent, and few studies have explored the relationship between SO₂ exposure and tuberculosis risk at provincial level. In addition, occupational exposure has long been considered to have a certain impact on the human body, so for the first time, we discussed the differences between different occupations in the study on the relationship between air pollutant exposure and tuberculosis risk, and evaluated the impact of occupational exposure. This study aimed to explore the association between short-term SO₂ exposure and the risk of outpatient visits to tuberculosis in Anhui province and 16 prefecture-level cities from 2015 to 2020. We used several models for multi-stage analysis, including distributed lag nonlinear model (DLNM), Poisson generalized linear regression model, and random-effects model. The association was assessed using the 28-day cumulative lag effect RR and 95%CI for each 10-unit increase in SO₂ concentration. We divided all patients into the following six occupations: Worker, Farmer, Retired people, Children and Students, Cadre and Office clerk, and Service staff (catering, business, etc.). Sex, age, and season were analyzed by subgroup. Finally, the robustness of the multi-pollutant model was tested. At provincial level, the overall effect value of SO₂ was RR=0.8191 (95%CI: 07702~0.8712); after grouping all patients by occupation, the association found only among Farmers (RR = 0.7150, 95%CI: 0.6699-0.7632, lag 0-28 days) and Workers (RR = 0.8566, 95%CI: 0.7930-0.9930, lag 0-4 days) was still statistically significant. Estimates for individual cities and using random-effects models to estimate average associations showed that SO₂ exposure was associated with a reduced risk of outpatient TB visits in 14 municipalities, which remained significant when aggregated (RR = 0.9030, 95%CI: 0.8730-0.9340). Analysis of patients grouped by occupation in each municipality showed that statistical significance was again observed only in the Farmer (RR = 0.8880, 95%CI: 0.8610-0.9160) and Worker (RR = 0.8250, 95%CI: 0.7290-0.9340) groups. Stratified analysis of age, sex, and season showed that the effect of SO₂ exposure was greater for middle-aged people (18-64 years old) and males, and less for seasonal changes. In summary, we found that exposure to SO₂ reduces the risk of outpatient visits to tuberculosis, with farmers and workers more susceptible to SO₂. Gender and age had a greater impact on the risk of TB outpatient visits than seasonal variations.

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

There is growing evidence that air pollution plays a role in TB, and most studies have been conducted in the core countries with inconsistent results. Few studies have comprehensively included the six common air pollutants, so they cannot consider whether various pollutants interact with each other. Our objectives were to investigate the association between short-term exposure to six common air pollutants and the risk of tuberculosis outpatient visits in Fuyang, China, 2015-2020. We combined the two models to explore the effects of exposure to six air pollutants on the risk of tuberculosis outpatient visits, including the Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for the season, type of cases, gender, and age. We used the lag-specific relative risks and cumulative relative risk obtained by increasing pollutant concentration by per 10 units to evaluate the connection between six air pollutants and TB; PM_2.5 (RR = 1.0018, 95% CI: 1.0004-1.0032, delay of 12 days) and SO₂ (RR = 1.0169, 95% CI: 1.0007-1.0333, lag 0-16 days) were 0.9549 (95% CI: 0.9389-0.9712, lag 0 day) and 0.8212 (95% CI: 0.7351-0.9173, 0-20-day lag). Stratified analyses showed that seasonal differences had a greater impact on TB, males were more likely to develop TB than females, older people were more likely to develop TB than younger people, and air pollution had a great impact on new cases. Exposure to O₃, CO, PM₁₀, PM_2.5, and NO₂ increases the risk of TB outpatient visits, except SO₂ which reduces the risk. The incidence of TB has seasonal fluctuations. It is necessary for the government to establish a sound environmental monitoring and early warning system to strengthen the monitoring and emission management of pollutants in the atmosphere. Management, prevention, and treatment measures should be developed for high-risk groups (males and older people), reducing the risk of TB by reducing their specific behaviors and changing their lifestyle. We need to pay more attention to the impact of seasonal effects on TB to protect TB patients and avoid a shortage of medical resources, and it is necessary for the government to develop some seasonal preventive measures in the future.

Effect of short-term exposure to air pollution on COVID-19 mortality and morbidity in Iranian cities

PURPOSE

The association between air pollutant (PM_2.5, PM₁₀, NO₂, and O₃) concentrations and daily number of COVID-19 confirmed cases and related deaths were evaluated in three major Iranian cities (Tehran, Mashhad, and Tabriz).

METHODS

Hourly concentrations of air pollutants and daily number of PCR-confirmed cases and deaths of COVID-19 were acquired (February 20^th, 2020 to January 4^th, 2021). A generalized additive model (GAM) assuming a quasi-Poisson distribution was used to model the associations in each city up to lag-day 7 (for mortality) and 14 (for morbidity). Then, the city-specific estimates were meta-analyzed using a fixed effect model to obtain the overall relative risks (RRs).

RESULTS

A total of 114,964 confirmed cases and 21,549 deaths were recorded in these cities. For confirmed cases, exposure to PM_2.5, NO₂, and O₃ for several lag-days showed significant associations. In case of mortality, meta-analysis estimated that the RRs for PM_2.5, PM₁₀, NO₂, and O₃ concentrations were 1.06 (95% CI: 0.99, 1.13), 1.06 (95% CI: 0.93, 1.19), 1.15 (95% CI: 0.93, 1.38), and 1.07 (95% CI: 0.84, 1.31), respectively. Despite several positive associations with all air pollutants over multiple lag-days, COVID-19 mortality was only significantly associated with NO₂ on lag-days 0-1 and 1 with the RRs of 1.35 (95% CI: 1.04, 1.67) and 1.16 (95% CI: 1.02, 1.31), respectively.

CONCLUSION

This study showed that air pollution can be a factor exacerbating COVID-19 infection and clinical outcomes. Actions should be taken to reduce the exposure of the public and particularly patients to ambient air pollutants.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-021-00736-4.

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.

Influence of air pollutants on varicella among adults

Little attention has been paid to the relationship between air pollutants and varicella among adults. We used data collected in Qingdao, China from 2014 to 2019. A combination of quasi-Poisson generalized linear model (GLM) and distributed lag non-linear model (DLNM) was applied to evaluate the association between exposure to air pollutants and varicella. And the effects of exposure to extremely high concentration (at 97.5th percentile) and low concentration (at 2.5th percentile) of air pollutants on varicella were also calculated. The level II of GB3095-2012 was used as the reference. A 10 μg/m³ increase of PM_2.5 was significantly associated with an increased risk of varicella (lag day: 4, 5 and 6). The negative associations were found for NO₂ per 10 μg/m³ increase from lag 15 to 19 day. The high PM_2.5 concentration (135 μg/m³) was significantly associated with the increased risk of varicella (lag day: 6, 7). For NO₂, the negative association was found at high concentration (75 μg/m³) on lag 15 to 20 day; and the positive relationship was shown at low concentration (10 μg/m³) on lag 15 to 20 day. Exposure to PM_2.5 and NO₂ were significantly associated with the risk of varicella among adults.

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.

Association between ambient air pollution and mortality from chronic obstructive pulmonary disease in Wuhan, China: a population-based time-series study

Evidence on the short-term effects of ambient air pollution on chronic obstructive pulmonary disease (COPD) mortality is still not conclusive. The aim of this study was to investigate the relationships between them in Wuhan China. Daily death numbers, concentrations of air pollutants (PM2.5, PM10, SO2, NO2, and O3), and meteorological characteristics in Wuhan from January 1, 2014, to December 31, 2019, were collected. Time-series analysis using generalized additive model was applied. The results showed that a total of 16,150 deaths (7.37 deaths per day) from COPD were observed. The daily average concentrations of PM2.5, PM10, SO2, NO2, and O3 were 59.03, 90.48, 12.91, 48.84, and 91.77 μg/m3, respectively. In single pollutant model, for every increase of 10 μg/m3 in PM10, SO2, and NO2 levels, COPD mortality increased by 0.583% (95% CI: 0.055-1.113%), 4.299% (95% CI: 0.978-7.729%), and 1.816% (95% CI: 0.515-3.313%) at lag03, respectively. No significant associations were found for PM2.5 and O3. Subgroup analysis demonstrated that females were more susceptible to PM2.5, PM10, SO2, and NO2. The concentrations of PM10, SO2, and NO2 were significantly associated with COPD mortality for older adults. The effects of PM2.5 and O3 on COPD mortality were higher in warm period. In two-pollutant models, the significantly positive associations between SO2 and NO2 and COPD mortality remained after adjusting for PM2.5 or O3. In conclusions, short-term exposure to PM10, SO2, and NO2 are significantly associated with a higher risk of COPD mortality. Female or elderly are more susceptible to air pollution. It is urgent to implement the environmental protection policy.

Associations between weekly air pollution exposure and congenital heart disease

BACKGROUND

The topic of congenital heart diseases (CHDs) has attracted more and more attentions. Accumulating evidence suggests that exposure to air pollutants during pregnancy is associated with CHDs, yet the results are inconsistent and study about weekly exposure is few. Our study evaluated the association between weekly air pollution and CHDs in Hefei, China.

MATERIALS AND METHODS

Daily CHDs admission data were obtained from eight hospitals in Hefei from October 2015 to September 2017. Meteorological data and air quality were collected from China Meteorological Data Network. Distributed lag nonlinear model (DLNM) considering both the lag effect of exposure factors and the nonlinear relationship of exposure-reaction was used to assess the effect of weekly air pollutants exposure on CHDs admission.

RESULTS

During the study period, totally 47,046 cases of perinatal infants were recruited, and the incidence of CHDs was 9.71 per thousand. The findings showed PM_2.5, PM₁₀, SO₂ and NO₂ significantly increased the risk of CHDs. Each 10 μg/m³ increase in PM_2.5 during gestational weeks 20-26 increased the risk of CHDs. The susceptibility windows of PM₁₀ (weeks 0-2 and weeks 25-29 of pregnancy), SO₂ (weeks 8-16 and weeks 29-38) and NO₂ (week 40), while the strongest effects of these 4 pollutants on CHDs were observed in week 22 (RR = 1.034, 95% CI: 1.007-1.062), week 0 (RR = 1.081, 95% CI: 1.02-1.146), week 37 (RR = 1.528, 95% CI: 1.085-2.153) and week 40 (RR = 1.171, 95% CI: 1.006-1.364), respectively.

CONCLUSIONS

Air pollutants (SO₂, NO₂, PM₁₀, and PM_2.5) exposure could increase the risk of CHDs, while the most crucial susceptibility windows for the exposure were mainly in the second and third trimesters. Boys seemed to be more sensitive to air pollution. Our study contributes to the knowledge of the association between maternal exposure to air pollution and CHDs, but the associations need to be verified by further studies.

Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis

BACKGROUND

Air pollution is a leading cause of mortality and morbidity worldwide. Short-term exposure (from one hour to days) to selected air pollutants has been associated with human mortality. This systematic review was conducted to analyse the evidence on the effects of short-term exposure to particulate matter with aerodynamic diameters less or equal than 10 and 2.5 µm (PM_10, PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃), on all-cause mortality, and PM₁₀ and PM_2.5 on cardiovascular, respiratory, and cerebrovascular mortality.

METHODS

We included studies on human populations exposed to outdoor air pollution from any source, excluding occupational exposures. Relative risks (RRs) per 10 µg/m³ increase in air pollutants concentrations were used as the effect estimates. Heterogeneity between studies was assessed using 80% prediction intervals. Risk of bias (RoB) in individual studies was analysed using a new domain-based assessment tool, developed by a working group convened by the World Health Organization and designed specifically to evaluate RoB within eligible air pollution studies included in systematic reviews. We conducted subgroup and sensitivity analyses by age, sex, continent, study design, single or multicity studies, time lag, and RoB. The certainty of evidence was assessed for each exposure-outcome combination. The protocol for this review was registered with PROSPERO (CRD42018087749).

RESULTS

We included 196 articles in quantitative analysis. All combinations of pollutants and all-cause and cause-specific mortality were positively associated in the main analysis, and in a wide range of sensitivity analyses. The only exception was NO₂, but when considering a 1-hour maximum exposure. We found positive associations between pollutants and all-cause mortality for PM₁₀ (RR: 1.0041; 95% CI: 1.0034-1.0049), PM_2.5 (RR: 1.0065; 95% CI: 1.0044-1.0086), NO₂ (24-hour average) (RR: 1.0072; 95% CI: 1.0059-1.0085), and O₃ (RR: 1.0043; 95% CI: 1.0034-1.0052). PM₁₀ and PM_2.5 were also positively associated with cardiovascular, respiratory, and cerebrovascular mortality. We found some degree of heterogeneity between studies in three exposure-outcome combinations, and this heterogeneity could not be explained after subgroup analysis. RoB was low or moderate in the majority of articles. The certainty of evidence was judged as high in 10 out of 11 combinations, and moderate in one combination.

CONCLUSIONS

This study found evidence of a positive association between short-term exposure to PM₁₀, PM_2.5, NO₂, and O₃ and all-cause mortality, and between PM₁₀ and PM_2.5 and cardiovascular, respiratory and cerebrovascular mortality. These results were robust through several sensitivity analyses. In general, the level of evidence was high, meaning that we can be confident in the associations found in this study.

A review of multivariate analysis: is there a relationship between airborne particulate matter and meteorological variables?

Among statistical tools for the study of atmospheric pollutants, trajectory regression analysis (TRA), cluster analysis (CA), and principal component analysis (PCA) can be highlighted. Therefore, this article presents a systematic review of such techniques based on (i) air mass influences on particulate matter (PM) and (ii) the study of the relationship between PM and meteorological variables. This article aims to review studies that use TRA and to review studies that adopt CA and/or PCA to identify the associations and relationship between meteorological variables and atmospheric pollutants. Papers published between 2006 and 2018 and indexed by five of the main scientific databases were considered (ScienceDirect, Web of Science, PubMed, SciELO, and Scopus databases). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations supported this systematic review. From the resulting most relevant papers, eight studies analyzed the influence of air mass trajectories on PM using TRA and twenty-one studies searched for the relationship between meteorological variables and PM using CA and/or PCA. A combination of TRA and time series models was identified as the possibility of future works. Besides, studies that simultaneously combine the three techniques to identify both the influence of air masses on PM and its relationship with meteorological variables are a possibility of future papers, because it can lead to a better comprehension of such a phenomenon.

Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution

This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services based on air quality and machine learning. Hemorrhagic stroke, air quality, and meteorological data for 2016-2017 were obtained from the Longquanyi District of China, and the study included 1932 cases. Six machine learning methods were used to forecast the demand for hemorrhagic stroke healthcare services considering seasonality and a lag effect, and the average area under the curve was as high as 0.7971. Our results indicate that (1) the performance of forecasting during the warm season is significantly better than that in the cold season, (2) considering air pollution would improve the performance of forecasting the demand for hemorrhagic stroke healthcare services using machine learning, (3) the association between the demand for hemorrhagic stroke healthcare services and air pollutants is linear to some extent, and (4) it is feasible to use short-term concentrations of air pollutants to forecast the demand for hemorrhagic stroke healthcare services. This practical forecast model could provide an advance warning regarding the potentially high numbers of hemorrhagic stroke admissions to medical institutions, thus allowing time to implement an appropriate response to the increase in patient volumes.

Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

OBJECTIVES

To explore the long-term effect of exposure to ambient air pollution on the risk of active tuberculosis (TB).

METHODS

We constructed a distributed-lag nonlinear model (DLNM) to evaluate the relatively long-term influence of outdoor PM_2.5, PM₁₀, SO₂ and NO₂ exposure on active TB risk in the city of Lianyungang in Jiangsu Province, China.

RESULTS

There were 7,282 TB cases reported in the study area during 2014-2017, with annual median (interquartile range) concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ at 45.86 (34.57-64.14) μg/m³, 85.43 (62.86-116.14) μg/m³, 22.00 (15.71-30.86) μg/m³ and 30.00 (23.29-38.57) μg/m³, respectively. The single-pollutant model showed that for each 10 μg/m³ increase in concentration, the cumulative relative risk of TB was 1.12 (lag 0-24 weeks, 95% CI: 1.03-1.22) for PM_2.5 with reference to 35 μg/m³; 1.11 (lag 0-21 weeks, 95% CI: 1.06-1.17) for PM₁₀ with reference to 70 μg/m³; 1.37 (lag 0-20 weeks, 95% CI: 1.16-1.62) for SO₂ with reference to 60 μg/m³; and 1.29 (lag 0-22 weeks, 95% CI: 1.11-1.49) for NO₂ with reference to 40 μg/m³. In the multipollutant model considering both PM₁₀ and NO₂, the association remained significant.

CONCLUSIONS

Our results revealed a potential association between outdoor exposure to PM_2.5, PM₁₀, SO₂, and NO₂ and active TB. Considering that people from developing countries continue to be exposed to both severe outdoor air pollution and high rates of latent TB infection, the association between worsening air pollution and active TB deserves further attention.

Time series analysis of ambient air pollution effects on dynamic stroke mortality

This study aims to examine the correlations between air pollution and dynamic stroke mortality, which is defined as the daily real-time number of deaths from stroke. Death data were obtained from daily medical records of 7230 incidents from the Center for Disease Control and Prevention in the Longquanyi District of China from 2016 to 2017. Air pollution data were obtained from environmental monitoring stations in the Longquanyi District. Time series analysis using generalized additive Poisson regression models was applied, and single-pollutant and two-pollutant adjusted models were utilized. Furthermore, categories based on gender, age, and meteorological factors were considered in the analysis. The results indicated that PM2.5, PM10, O₃ , and CO had significant effects on dynamic stroke mortality, which were stronger for older people and during the cold season. This study helps hospital managers, patients, and governments seeking to prevent and control the effects of air pollution on the risks of stroke.

Spatial patterns and effects of air pollution and meteorological factors on hospitalization for chronic lung diseases in Beijing, China

Chronic obstructive pulmonary disease (COPD), lung cancer (LC) and tuberculosis (TB) are common chronic lung diseases that generate a large disease burden and significant health care resource use in China. The aim of this study was to quantify spatial patterns and effects of air pollution and meteorological factors on hospitalization of COPD, LC and TB in Beijing. Daily counts of hospitalization for 2010 were obtained from the Beijing Urban Employees Basic Medical Insurance (UEBMI) system. Bayesian hierarchical Poisson regression models were applied to identify spatial patterns of hospitalization for COPD, LC and TB at the district level and explore associations with inhalable particulate matter (aerodynamic diameter <10 μm, PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), mean temperature and relative humidity. There were 18,882, 14,295 and 2,940 counts of hospitalizations for COPD, LC and TB respectively, in Beijing in 2010. Clusters of high relative risk were in different locations for the three diseases. The effect of relative humidity on COPD hospitalization was most significant with a relative risk (RR) of 1.070 (95%CI: 1.054, 1.086) per one percent increase. For lung cancer hospitalization, exposure to ambient SO₂ was associated with a RR of 1.034 (95%CI: 1.011, 1.058) per μg m^-3 increase. For tuberculosis, the effect of mean temperature was significant with a RR of 1.107 (95%CI: 1.038, 1.180) per °C increase. Risk factors and spatial patterns were different for hospitalization of non-infectious and infectious chronic lung disease in Beijing. Even over a short time period (one year), associations were apparent with air pollution and meteorological factors.

Glutathione S-transferase M1 and T1 polymorphisms, and their interactions with smoking on risk of low birth weight: a meta-analysis

Background: Published data regarding the association between glutathione S-transferase M1 (GSTM1) and glutathione S-transferase T1 (GSTT1) gene polymorphisms and risk of low birth weight (LBW) remains inconclusive, and data on the interactions between the two gene polymorphisms and smoking for LBW susceptibility is lacking. To clarify these associations, a meta-analysis was conducted.Methods: A comprehensive literature search was conducted in multiple databases until 11 January 2018. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using fixed or random effects model.Results: Thirty-eight studies from 17 articles concerning maternal and neonatal GSTM1 and GSTT1 gene polymorphism with LBW risk were included in this meta-analysis, and nine studies from five articles provided data of maternal tobacco exposure status during pregnancy. Maternal GSTM1 null genotype was associated with increased LBW risk (OR = 1.27, 95% CI: 1.12-1.45). There was a nonsignificant but positive association (OR = 1.19, 95% CI: 0.97-1.46) between the maternal GSTT1 null genotype and the LBW risk in the overall analysis. There was a null association between neonatal GSTM1 or GSTT1 polymorphism and LBW risk. There were significant associations between the maternal GSTM1 null and GSTT1 null genotype and LBW risk (for the former, OR = 3.85, 95% CI: 1.68-8.81; for the later, OR = 1.88, 95% CI: 1.01-3.50) in individuals with active smoking, respectively.Conclusion: Maternal GSTM1 and GSTT1 null genotypes, but not neonatal genotypes, are suggested to increase LBW susceptibility, and there are interactions between active smoking and these polymorphisms in the development of LBW.

The effects of interaction between particulate matter and temperature on mortality in Beijing, China

BACKGROUND

the effects of interaction between temperature and inhalable particulate matter (aerodynamic diameter < 10 μm, PM₁₀) on mortality have been examined in some previous studies, but the results were inconsistent. This study aims to explore whether the effects of PM₁₀ on daily non-accidental, cardiovascular and respiratory mortality were modified by temperature levels in Beijing from 2006 to 2009.

METHODS

we applied a bivariate response surface model and temperature-stratified model based on time-series Poisson generalized additive models (GAMs) to examine the interactive effects in single- and two-pollutant models. The modification of age and gender was examined in subgroup analyses.

RESULTS

the median of temperature (15.9 °C) and visualized turning point (20 °C) were chosen as cut-offs to define the temperature strata as two levels (low and high). Results showed that the effect estimates of PM₁₀ were stronger at the high temperature level for non-accidental, cardiovascular and respiratory mortality than at the low temperature level. When controlling the moving average lag of temperature for 14 days, the effect estimates per 10 μg m^-3 increase in PM₁₀ for non-accidental, cardiovascular and respiratory mortality increased 0.14% (95% CI: 0.05, 0.22), 0.12% (95% CI: 0.02, 0.23) and 0.14% (95% CI: -0.06, 0.34) when the temperature was low and 0.24% (95% CI: 0.12, 0.35), 0.17% (95% CI: 0.01, 0.34) and 0.45% (95% CI: 0.13, 0.78) at the high temperature level, respectively. In the two-pollutant model, the effects of PM₁₀ were attenuated at both high and low temperatures at all lags after adjusting SO₂ and NO₂. The PM₁₀ effects were stronger at the high temperature level for females and elderly people (≥65 years old).

CONCLUSION

the findings suggest that daily mortality attributed to PM₁₀ might be modified by temperature. The interaction between air pollution and global climate change has potential strategy and policy implications.