Short-term effects of ambient air pollution on emergency room admissions due to cardiovascular causes in Beijing, China

Impact of Indoor Air Pollutants on the Cardiovascular Health Outcomes of Older Adults: Systematic Review

Indoor air pollution accounts for approximately 3.8 million inopportune deaths annually at global level. Due to spending more time indoors, children and older adults are especially susceptible to the health risks of indoor air pollution. This review seeks to summarise existing knowledge on the cardiovascular health effects of three common indoor air pollutants, namely carbon monoxide (CO), particulate matter (PM2.5 and PM10), and Nitrogen dioxide (NO2), focusing on older adults. We systematically reviewed the literature (PROSPERO CRD42024479220) on PubMed, Google Scholar, Scopus, Web of Science and Embase. The search yielded 20,914 records. Two independent reviewers screened the articles using titles, abstracts, and full-length articles written in English. Upon a detailed assessment of all the records, the review considered 38 full-length articles. Several studies reported mortality, myocardial infarction, stroke, increased hospitalisation and increased emergency room visits due to exposure to indoor air pollution. A few studies reported arrhythmias, hypertension and Ischaemic heart disease due to exposure to indoor air pollutants. The increased mortality, morbidity, hospitalization, and emergency rooms visits resulting from indoor air pollution associated CVDs makes indoor air pollution a health risk for older adults. There is, therefore, a need to synthesize information on studies relate d to how the selected indoor air pollutants affected the cardiovascular health of older adults.

Short-term associations of PM10 attributed to biomass burning with respiratory and cardiovascular hospital admissions in Peninsular Malaysia

BACKGROUND

Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events.

METHODS

We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex.

RESULTS

We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions.

CONCLUSIONS

Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.

Air pollution and cancer daily mortality in Hangzhou, China: an ecological research

BACKGROUND

Long-term exposure to air pollution has been linked to cancer incidence. However, the evidence is limited regarding the effect of short-term exposure to air pollution on cancer mortality.

OBJECTIVES

This study aimed to investigate associations between short-term exposure to air pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter <10 mm (PM10) and PM2.5) and cancer daily mortality.

METHODS

This study used air quality, meteorological and daily cancer death data from 2014 to 2019 in Hangzhou, China. Generalised additive models (GAM) with quasi-Poisson regression were used to analyse the associations between air pollutants and cancer mortality with adjustment for confounding factors including time trends, day of week, temperature and humidity. Then, we conducted stratified analyses by sex, age, season and education. In addition, stratified analyses of age, season and education were performed within each sex to determine whether sex difference was modified by such factors.

RESULTS

After adjusting for potential confounders, the GAM results indicated a statistically significant relationship between increased cancer mortality and elevated air pollution concentrations, but only in the female population. For every 10 μg/m3 rise in pollutant concentration, the increased risk of cancer death in females was 6.82% (95% CI 3.63% to 10.10%) for SO2 on lag 03, and 2.02% (95% CI 1.12% to 2.93%) for NO2 on lag 01 and 0.89% (95% CI 0.46% to 1.33%) for PM10 on lag 03 and 1.29% (95% CI 0.64% to 1.95%) for PM2.5 on lag 03. However, no statistically significant association was found among males. Moreover, the differences in effect sizes between males and females were more pronounced during the cold season, among the elderly and among subjects with low levels of education.

CONCLUSIONS

Increased cancer mortality was only observed in females with rising concentrations of air pollutants. Further research is required to confirm this sex difference. Advocate for the reduction of air pollutant emissions to protect vulnerable groups.

Association Between Air Pollution and Cardiovascular Disease Hospitalizations in Lanzhou City, 2013-2020: A Time Series Analysis

Extensive evidence has shown that air pollution increases the risk of cardiovascular disease (CVD) admissions. We aimed to explore the short-term effect of air pollution on CVD admissions in Lanzhou residents and their lag effects. Meteorological data, air pollution data, and a total of 309,561 daily hospitalizations for CVD among urban residents in Lanzhou were collected from 2013 to 2020. Distributed lag non-linear model was used to analyze the relationship between air pollutants and CVD admissions, stratified by gender, age, and season. PM2.5, NO2, and CO have the strongest harmful effects at lag03, while SO2 at lag3. The relative risks of CVD admissions were 1.0013(95% CI: 1.0003, 1.0023), 1.0032(95% CI: 1.0008, 1.0056), and 1.0040(95% CI: 1.0024, 1.0057) when PM2.5, SO2, and NO2 concentrations were increased by 10 μg/m³, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of cardiovascular hospitalization of risk was 1.0909(95% CI: 1.0367, 1.1479). We observed a relative risk of 0.9981(95% CI: 0.9972, 0.9991) for each 10 μg/m³ increase in O3 for CVD admissions at lag06. We found a significant lag effects of air pollutants on CVD admissions. NO2 and CO pose a greater risk of hospitalization for women, while PM2.5 and SO2 have a greater impact on men. PM2.5, NO2, and CO have a greater impact on CVD admissions in individuals aged <65 years, whereas SO2 affects those aged ≥65 years. Our research indicates a possible short-term impact of air pollution on CVD. Local public health and environmental policies should take these preliminary findings into account.

Ambient carbon monoxide and relative risk of daily hospital outpatient visits for respiratory diseases in Lanzhou, China

At present, evidence of the associations between carbon monoxide (CO) and respiratory diseases (RD) in Northwest China is limited and controversial. The aim of this study is to evaluate the impact of ambient CO on outpatient visits for RD in Lanzhou, China. The daily amount of outpatient visits for total and cause-specific RD, air pollutant, and weather variables were collected in Lanzhou, China from 1st January 2013 to 31st December 2019. A generalized additive model and distributed lag nonlinear model were used to assess associations between CO and outpatient visits for RD. During the study period, a total of 1,623,361 RD outpatient visits were recorded. For each interquartile range (IQR) (0.77 mg/m3) increase in CO, the relative risk (RR) was 1.163 (95% CI: 1.138, 1.188) for total RD at lag07, 1.153 (95% CI: 1.128,1.179) for upper respiratory tract infection (URTI) at lag07, 1.379 (95% CI: 1.338,1.422) for pneumonia at lag07, 1.029 (95% CI: 0.997,1.062) for chronic obstructive pulmonary disease (COPD) lag04, 1.068 (95% CI: 1.028,1.110) for asthma lag03, and 1.212 (95% CI: 1.178,1.247) for bronchitis lag07, respectively. In the subgroup analyses, the impacts of CO were more pronounced on total RD, pneumonia, COPD, and bronchitis in males than females, while the opposite was true in URTI and asthma. The impact of CO on RD was the strongest for children under 15 years-of-age. We also found significantly stronger effects during cold seasons compared to warm seasons. In addition, we observed a roughly linear exposure-response curve between CO and RD with no threshold effect. This study in Lanzhou revealed a remarkable association between CO level and an elevated risk of total and cause-specific RD outpatient visits, especially for pneumonia.

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.

Effects of the lockdown measure amid COVID-19 pandemic on outpatient department visits associated with air pollution reduction in Thailand

We investigated the effects of COVID-19 lockdown on air quality and its consequences health and economic benefits in Thailand. The conditional Poisson regression model was applied to examine the association between air pollution and outpatient department (OPD) visits in each province and pooled the province-specific estimates using the random-effects meta-analysis to derive the national estimates. We then applied a random forest model with meteorological normalization approach to predict the concentration of air pollutants by means of business as usual during the lockdown period (April 3-May 3) in 2020 and further calculated the changes in the number of OPD visits and their consequent expenditure attributable to air pollution reduction using the obtained risk function performed earlier. The number of cardiovascular OPD visits attributed to PM10, PM2.5 and NO2 decreased by 4,414 (95% CI 982, 8,401), 4,040 (95% CI 326, 7,770), and 13,917 (95% CI 1,675, 27,278) cases, respectively, leading to reduced medical expenditure by 14,7180.21, 13,4708.31, and 46,4025.04 USD, respectively. The number of respiratory OPD visits attributed to PM10, PM2.5, NO2, and O3 reduction decreased by 2,298 (95% CI 1,223, 3,375), 2,056 (95% CI 740, 3,252), 3,326 (95% CI 542, 6,295), and 1,160 (95% CI 5,26, 1,804) cases, respectively, where the consequent medical expenditure was reduced by 76,618.48, 68,566.36, 11,0908.31, and 38,685.50 USD, respectively. Finding from this study showed that air quality during the lockdown period in Thailand was improved, contributing to the reduction of cardiovascular and respiratory OPD visits, and consequent medical service costs attributable to air pollution.

Ambient carbon monoxide and the risk of cardiovascular disease emergency room visits: a time-series study in Lanzhou, China

Until now, the epidemiological evidence on the association between short-term exposure to ambient carbon monoxide (CO) and cardiovascular diseases (CVDs) is relatively lacking and controversial. This study aims to examine the relationship between ambient CO and daily emergency room visits (ERVs) for total and cause-specific CVD in Lanzhou, China. A distributed lag nonlinear model was used to examine the association. For every 1 mg/m3 increase in the CO concentration, the relative risks of daily ERVs were 1.041 (95% CI: 1.017, 1.065) for total CVD, 1.065 (95% CI: 1.018, 1.114) for ischemic heart disease (IHD), 1.083 (95% CI: 1.020, 1.149) for heart rhythm disturbances (HRD), 1.062 (95% CI: 1.011, 1.115) for heart failure (HF), and 1.057 (95% CI: 1.017, 1.098) for cerebrovascular diseases (CD). For the two different gender subgroups, the short-term impact of CO on total CVD, IHD, and CD was relatively stronger for the females than for the males, while the opposite was true for HRD and HF. In the age subgroup analyses, the effect of ambient CO on total CVD and IHD appeared to be greater for the age ≥ 65 years group, while the opposite was true for HRD, HF, and CD. The associations for all disease categories were stronger in cold seasons than in warm seasons. We also observed a nearly linear correlation between CO and CVD ERVs. In conclusion, the study showed that exposure to ambient CO may increase the risks of ERVs for total and cause-specific CVD. Besides, CO-ERVs associations may vary by gender and age.

Association of genetic polymorphisms with mercapturic acids in the urine of young healthy subjects before and after exposure to outdoor air pollution

We aimed to identify the relationship between variations in metabolic genes and human urinary changes in mercapturic acids (MAs), including CEMA, HMPMA, SPMA, HPMA and HEMA, before and after air pollution exposure. Genotype detection for 47 relevant single nucleotide polymorphisms (SNPs) collected by literature research was performed. Five MAs expression levels in the urinary samples of 50 young healthy individuals with short-term exposure to clean, polluted and purified air at five time points were detected by targeted online solid-phase extraction liquid chromatography tandem mass spectrometry (SPE-LC-MS/MS), followed with associations of SNPs with MAs changes. Difference in MAs between polluted and clean/purified air was significantly associated with 21 SNPs mapped into 9 genes. Five SNPs in GSTP1 showed the most prominent association with the changes in SPMA expression, indicating that those SNPs in GSTP1 and SPMA might serve as biomarkers for susceptibility and the prognosis of lung cancer.

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

Objectives

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

Methods

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

Results

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

Conclusions

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

Meandered and muddled: a systematic review on the impact of air pollution on ocular health

From the years 1970-2023, a systematic overview of the diverse consequences of particulate matter on eye health and a disease classification according to acute, chronic, and genetic are presented using the PubMed, Research Gate, Google Scholar, and Science Direct databases. Various studies on medical aspects correlate with the eye and health. However, from an application perspective, there is limited research on the ocular surface and air pollution. The main objective of the study is to uncover the relationship between eye health and air pollution, particularly particulate matter, along with other external factors acting as aggravators. The secondary goal of the work is to examine the existing models for mimicking human eyes. The study is followed by a questionnaire survey in a workshop, in which the exposure-based investigation was tagged based on their activity. This paper establishes a relationship between particulate matter and its influence on human health, leading to numerous eye diseases like dry eyes, conjunctivitis, myopia, glaucoma, and trachoma. The results of the questionnaire survey indicate that about 68% of the people working in the workshop are symptomatic with tears, blurred vision, and mood swings, while 32% of the people were asymptomatic. Although there are approaches for conducting experiments, the evaluation is not well defined; empirical and numerical solutions for particle deposition on the eye are needed. There prevails a broad gap in the arena of ocular deposition modeling.

Ambient nitrogen dioxide and cardiovascular diseases in rural regions: a time-series analyses using data from the new rural cooperative medical scheme in Fuyang, East China

Most of studies relating ambient nitrogen dioxide (NO₂) exposure to hospital admissions for cardiovascular diseases (CVDs) were conducted among urban population. Whether and to what extent these results could be generalizable to rural population remains unknown. We addressed this question using data from the New Rural Cooperative Medical Scheme (NRCMS) in Fuyang, Anhui, China. Daily hospital admissions for total CVDs, ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke in rural regions of Fuyang, China, were extracted from NRCMS between January 2015 and June 2017. A two-stage time-series analysis method was used to assess the associations between NO₂ and CVD hospital admissions and the disease burden fractions attributable to NO₂. In our study period, the average number (standard deviation) of hospital admissions per day were 488.2 (117.1) for total CVDs, 179.8 (45.6) for ischaemic heart disease, 7.0 (3.3) for heart rhythm disturbances, 13.2 (7.2) for heart failure, 267.9 (67.7) for ischaemic stroke, and 20.2 (6.4) for haemorrhagic stroke. The 10-μg/m³ increase of NO₂ was related to an elevated risk of 1.9% (RR: 1.019, 95% CI: 1.005 to 1.032) for hospital admissions of total CVDs at lag0-2 days, 2.1% (1.021, 1.006 to 1.036) for ischaemic heart disease, and 2.1% (1.021, 1.006 to 1.035) for ischaemic stroke, respectively, while no significant association was observed between NO₂ and hospital admissions for heart rhythm disturbances, heart failure, and haemorrhagic stroke. The attributable fractions of total CVDs, ischaemic heart disease, and ischaemic stroke to NO₂ were 6.52% (1.87 to 10.94%), 7.31% (2.19 to 12.17%), and 7.12% (2.14 to 11.85%), respectively. Our findings suggest that CVD burdens in rural population are also partly attributed to short-term exposure to NO₂. More studies across rural regions are required to replicate our findings.

Health and economic impacts of ambient air pollution on hospital admissions for overall and specific cardiovascular diseases in Panzhihua, Southwestern China

Background

The associations of ambient air pollution with hospital admissions (HAs) for overall and specific causes of cardiovascular diseases (CVDs), as well as related morbidity and economic burdens remain understudied, especially in low-pollution areas of low- and middle-income countries (LMICs). We evaluated the short-term effects of exposure to PM_2.5 (particles with an aerodynamic diameter ≤2.5 μm), PM₁₀ (particles with an aerodynamic diameter ≤10 μm), and SO₂ (sulfur dioxide) on HAs for CVDs in Panzhihua, China, during 2016-2020, and calculated corresponding attributable risks and economic burden.

Methods

We used a generalized additive model (GAM) while controlling for time trends, meteorological conditions, holidays, and days of the week to estimate the associations. The cost of illness (COI) method was adopted to further assess corresponding hospitalization costs and productivity losses.

Results

A total of 27 660 HAs for CVDs were included in this study. PM₁₀ and SO₂ were significantly associated with elevated risks of CVDs hospitalizations. Each 10 μg/m³ increase in PM₁₀ and SO₂ at lag06 corresponded to an increase of 2.48% (95% confidence interval (CI) = 0.92%-4.06%), and 5.50% (95% CI = 3.09%-7.97%) in risk of HAs for CVDs, respectively. The risk estimates of PM₁₀ and SO₂ on CVD hospitalizations were generally robust after adjustment for other pollutants in two-pollutant models. We found stronger associations between air pollution (PM₁₀ and SO₂) and CVDs in cool seasons than in warm seasons. For specific causes of CVDs, significant associations of PM₁₀ and SO₂ exposure with cerebrovascular disease and ischaemic heart disease were observed. Using 0 μg/m³ as the reference concentrations, 11.91% (95%CI = 4.64%-18.56%) and 15.71% (95%CI = 9.30%-21.60%) of HAs for CVDs could be attributable to PM₁₀ and SO₂, respectively. During the study period, PM₁₀ and SO₂ brought 144.34 million Yuan economic losses for overall CVDs, accounting for 0.028% of local GDP.

Conclusions

Our results suggest that PM₁₀ and SO₂ exposure might be an important trigger of HAs for CVDs and accounted for substantial morbidity and economic burden.

Indoor Solid Fuel Use and Non-Neoplastic Digestive System Diseases: A Population-Based Cohort Study Among Chinese Middle-Aged and Older Population

Objectives: We tended to explore the association of indoor air pollution (IAP) and non-neoplastic digestive system diseases (NNDSD) among the Chinese middle-aged and older population. Methods: From 2011 to 2018, we included 7884 NNDSD-free adults from the China Health and Retirement Longitudinal Study (CHARLS). Physician-diagnosed NNDSD was obtained by self-reported information at baseline and updated across follow-up surveys. We investigated the associations between baseline exposure of solid fuel use for cooking and/or heating and NNDSD diagnosed during follow-up through Cox proportional hazard models. Furthermore, we examined the relationship between cooking fuel switching and NNDSD diagnosed during follow-up. Results: Solid fuel use for cooking and/or heating was positively associated with NNDSD after adjusting for potential confounders. The risk of NNDSD among subjects who always use solid fuel for cooking (adjusted hazard ratio [aHR]: 1.42; 95% confidence interval [CI]: 1.09, 1.84) was higher than those with always clean fuels. Moreover, we found a lower NNDSD risk among participants who switched from solid to clean cooking fuel (aHR: 0.65; 95% CI: 0.49, 0.87) than those with always solid fuels. Conclusion: Our present study shows that indoor solid fuel use is a dependent risk factor for NNDSD. Moreover, switching to clean fuel may contribute to the prevention of digestive system illnesses.

Ambient Air Quality and Emergency Hospital Admissions in Singapore: A Time-Series Analysis

Air pollution exposure may increase the demand for emergency healthcare services, particularly in South-East Asia, where the burden of air-pollution-related health impacts is high. This article aims to investigate the association between air quality and emergency hospital admissions in Singapore. Quasi-Poisson regression was applied with a distributed lag non-linear model (DLNM) to assess the short-term associations between air quality variations and all-cause, emergency admissions from a major hospital in Singapore, between 2009 and 2017. Higher concentrations of SO₂, PM_2.5, PM₁₀, NO₂, and CO were positively associated with an increased risk of (i) all-cause, (ii) cardiovascular-related, and (iii) respiratory-related emergency admissions over 7 days. O₃ concentration increases were associated with a non-linear decrease in emergency admissions. Females experienced a higher risk of emergency admissions associated with PM_2.5, PM₁₀, and CO exposure, and a lower risk of admissions with NO₂ exposure, compared to males. The older adults (≥65 years) experienced a higher risk of emergency admissions associated with SO₂ and O₃ exposure compared to the non-elderly group. We found significant positive associations between respiratory disease- and cardiovascular disease-related emergency hospital admissions and ambient SO₂, PM_2.5, PM₁₀, NO₂, and CO concentrations. Age and gender were identified as effect modifiers of all-cause admissions.

More obvious association between short-term ambient nitrogen dioxide and atrial fibrillation outpatient visits in cool seasons: A hospital-based study in northwestern China

Atrial fibrillation (AF) is the most common sustained heart rhythm disorder associated with high mortality and morbidity. Limited studies have been conducted to assess the relationship between short-term exposure to ambient air pollution and AF attacks. This study aimed to explore the association between short-term ambient nitrogen dioxide (NO₂) exposure and outpatient visits for AF in Xi'an, China. Data on daily AF outpatient visits and air pollutants from 2013 to 2019 (2555 days) were obtained. A time-series approach using over-dispersed Poisson generalized additive model (GAM) was employed, and stratified analyses were performed to investigate the potential modifying effects by season, age, and gender. A total of 8307 outpatient visits for AF were recorded. Increased levels of NO₂ were associated with increased AF outpatient visits, and the most significant effect estimates were observed at lag 03: A 10 μg/m³ increase of NO₂ at lag 03 was related to an elevation of 5.59% (95% CI: 2.67%, 8.51%) in daily outpatient visits for AF. Stratified analyses showed that there were no gender and age difference in the effect of NO₂, while more obvious association was observed in cool seasons (October to March) than in warm seasons (April to September). In summary, short-term ambient NO₂ exposure can be positively associated with daily outpatient visits for AF, especially in cool seasons. This work provided novel data that the association between air pollutants and AF can vary by seasons, further supporting that the prevention of cardiovascular health effects should be strengthened in winter.

Potential urinary biomarkers in young adults with short-term exposure to particulate matter and bioaerosols identified using an unbiased metabolomic approach

Numerous epidemiological studies have shown a close relationship between outdoor air pollution and increased risks for cancer, infection, and cardiopulmonary diseases. However, very few studies have investigated the potential health effects of coexposure to airborne particulate matter (PM) and bioaerosols through the transmission of infectious agents, particularly under the current circumstances of the coronavirus disease 2019 pandemic. In this study, we aimed to identify urinary metabolite biomarkers that might serve as clinically predictive or diagnostic standards for relevant diseases in a real-time manner. We performed an unbiased gas/liquid chromatography-mass spectroscopy (GC/LC-MS) approach to detect urinary metabolites in 92 samples from young healthy individuals collected at three different time points after exposure to clean air, polluted ambient, or purified air, as well as two additional time points after air repollution or repurification. Subsequently, we compared the metabolomic profiles between the two time points using an integrated analysis, along with Kyoto Encyclopedia of Genes and Genomes-enriched pathway and time-series analysis. We identified 33 and 155 differential metabolites (DMs) associated with PM and bioaerosol exposure using GC/LC-MS and follow-up analyses, respectively. Our findings suggest that 16-dehydroprogesterone and 4-hydroxyphenylethanol in urine samples may serve as potential biomarkers to predict or diagnose PM- or bioaerosol-related diseases, respectively. The results indicated apparent differences between PM- and bioaerosol-associated DMs at five different time points and revealed dynamic alterations in the urinary metabolic profiles of young healthy humans with cyclic exposure to clean and polluted air environments. Our findings will help in investigating the detrimental health effects of short-term coexposure to airborne PM and bioaerosols in a real-time manner and improve clinically predictive or diagnostic strategies for preventing air pollution-related diseases.

Short term exposure to ambient air pollutants and cardiovascular emergency department visits in Mexico city

Available data on the acute cardiovascular effect of ambient air pollution (AAP) in Latin America is limited considering that over 80% of its 1 billion inhabitants live in urban settlements with poor air quality. The study aim was to evaluate the association between Cardiovascular Emergency Department Visits (CEDVs) and AAP in Mexico City from 2016 to 2019 using generalized additive models with distributed lags to examine the percentage change of CEDVs and a backward approach of time-series model to calculate attributable fractions. A total of 48,891 CEDVs were recorded in a period of 1019 days. We estimated a significant percentage increase for each 10 μg/m³ of PM₁₀ at Lag0-5 (2.8%, 95%CI 0.6-5.0), PM_2.5 at Lag0-6 (3.7%, 95%CI 0.1-7.6), O₃ at Lag0-5 (1.1%, 95%CI 0.2-2.0), NO₂ at Lag0-4 (2.5%, 95%CI 0.3-4.7) and for each 1 mg/m³ of CO at Lag0 (6.6%, 95%CI 0.3-13.2). Overall, 10.3% of CEDVs in Mexico City may be related to PM¹⁰ exposure, 9.5% to PM_2.5, 10.3% to O₃, 11% to NO₂ and 5.7% to CO. AAP significantly increase cardiovascular morbidity impacting on emergency medical services.

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.

Synergistic effects of gaseous pollutants on hospital admissions for cardiovascular disease in Liuzhou, China

Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People's Republic of China, including NO₂, SO₂, and O₃. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO₂ and SO₂ increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO₂ was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O₃ were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O₃ was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO₂ and SO₂ for CVD, as well as between SO₂ and O₃. The synergistic effects of NO₂ and SO₂ on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO₂-O₃ and NO₂-O₃. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO₂ and SO₂ was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.

Association between air pollution and hospital admissions for hypertension in Lanzhou, China

Air pollution has been accepted as an important risk factor for hypertension. However, little is known about the association between air pollution and hospitalization for hypertension. In this study, we explored the association between six criteria air pollutants and hypertension hospitalization in Lanzhou, China. An over-dispersed Poisson regression model combined with a distributed lag nonlinear model (DLNM) was used. In addition, we investigated the effect of modification by sex, age, and season. A total of 30,197 hospitalization cases were identified during the study period. A 10μg/m³ increase in PM_2.5, PM₁₀, SO₂, and NO₂ concentrations or 1 mg/m³ increment in CO was significantly associated with relative risks (RRs) of hospital admissions due to hypertension 1.026 [95% confidence interval (CI): 1.010, 1.043], 1.010 (95%CI: 1.005, 1.015), 1.042 (95%CI: 1.001, 1.085), 1.028 (95%CI: 1.003, 1.052), and 1.106 (95%CI: 1.031, 1.186), respectively. No significant influence of O₃8h was found on hypertension hospital admissions. The associations differed by individual characteristics; the elderly (≥ 65 years) and females were highly vulnerable. The effects of PM_2.5, SO₂, and CO were more evident in the cool season than in the warm season. From exposure-response curves, we observe a nearly linear relationship for PM_2.5, PM₁₀, SO₂, NO₂, and CO. This study suggests that exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO is associated with hypertension morbidity.

Constituents of fine particulate matter and asthma in six low- and middle-income countries

BACKGROUND

Evidence concerning the effects of different chemical components of PM_2.5 on asthma is limited, and the methodology to compare the relative importance of different PM_2.5 components is lacking.

OBJECTIVES

To examine the associations between PM_2.5 components and asthma, and investigate which constituent of PM_2.5 possessed the most harmful effect on asthma.

METHODS

A total of 45,690 subjects were surveyed in six countries from 2007 to 2010. We geo-coded the residential community address of the participants, and used satellite remote sensing and chemical transport modeling to estimate their annual average concentrations. Mixed-effects generalized additive models were utilized to examine the associations between PM_2.5 constituents and prevalence of asthma. We further used counterfactual analyses to determine the potential number of asthma cases.

RESULTS

We identified 6,178 asthma cases among the participants, producing a prevalence of 13.5%. The odds ratio (OR) for asthma associated with per standard deviation (SD) increment was 1.12 for PM_2.5 mass, 1.12 for organic carbon (OC), 1.18 for black carbon (BC), 1.19 for sulfate, 1.28 for ammonium, and 1.21 for nitrate after controlling for potential confounders. Our counterfactual analyses suggested that ammonium was responsible for a substantial decline in asthma cases (1382, corresponding to 22.37% of overall cases) if the concentration was reduced to the 5th percentile of the current level.

CONCLUSIONS

Our study suggests that some chemical components (including BC, OC, sulfate, ammonium, and nitrate) of PM_2.5 might be hazardous constituents contributing to the prevalence of asthma, among them, ammonium might be responsible for substantial proportion of asthma cases if reduced to a certain level.

Associations of mixture of air pollutants with estimated 10-year atherosclerotic cardiovascular disease risk modified by socio-economic status: The Henan Rural Cohort Study

BACKGROUND

Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear.

METHODS

A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM₁), ≤2.5 μm (PM_2.5) or ≤10 μm (PM₁₀), nitrogen dioxide (NO₂)) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots.

RESULTS

Exposure to single air pollutant (PM₁, PM_2.5, PM₁₀ or NO₂) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed.

CONCLUSION

Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect.

Acute effects of short-term exposure to ambient air pollution on reproductive hormones in young males of the MARHCS study in China

Air pollution, which is associated with male reproductive health. However, it is unknown the acute effects of ambient air pollutants exposure on male reproductive hormones. The current study, we measured serum levels of reproductive hormone in 2030 blood samples gathered from The Male Reproductive Health in Chongqing College Students (MARHCS) cohort study. We derived a full coverage of ambient air pollutant (PM₁₀, PM_2.5, SO₂, NO₂, CO and O₃) concentrations by employing machine learning algorithms, and used a mixed-effect model to estimate single-day and cumulative effects of air pollutants exposure on serum reproductive hormones. Our results showed that (1) PM₁₀ and PM_2.5 concentrations were positively associated with estradiol (E₂) in both single and cumulative lag days, but were negatively associated with the ratio of Testosterone/E₂ (the T/E₂ ratio). NO₂ was positively associated with estradiol at lag day 2 (95% CI: 0.290, 0.881; corrected P = 0.048) and lag 0-2 days (95% CI: 0.523, 1.337; corrected P = 0.003), with progesterone (P) at lag day 2 and lag day 3 (corrected P < 0.05). There was also a positive association between CO exposure and progesterone at lag day 2. (2) SO₂ was inversely associated with E₂ at lag day 3, 4 and lag 0-4 days, and progesterone at lag day 0, 1, 2 and lag 0-1, 0-2, 0-4 days, but positively associated with the T/E₂ ratio at lag day 3, 4 and lag 0-4 days (corrected P < 0.05). O₃ exposure was negatively associated with E₂ at lag day 3 (95% CI: -0.216, -0.074, corrected P = 0.03). (3) No significant associations were found between the cumulative daily average air pollutant exposure of CO, O₃ and hormone outcomes. This study suggests that short-term exposure to air pollutants may thus alter reproductive hormone levels, especially on serum estradiol, progesterone levels and the T/E₂ ratio.

The short-term association of ambient fine particulate air pollution with hypertension clinic visits: A multi-community study in Guangzhou, China

BACKGROUND

The association of ambient fine particulate pollution with daily outpatient clinic visits (OCV) for hypertension in China remains to be investigated.

OBJECTIVES

This study aimed to examine short-term impacts of exposure to fine particulate matter of aerodynamic diameter < 2.5μm (PM_2.5) on daily OCV for hypertension, using a large-scale multi-center community database in Guangzhou, one of the most densely-populated cities in Southern China.

METHODS

We collected a total of 28,548 individual records of OCV from 22 community healthcare facilities in Guangzhou from January 1st to May 7th 2020. Hourly data on air pollutants and daily information on meteorological factors were obtained. According to the World Health Organization air-quality guidelines, daily excessive concentration hours (DECH) was calculated. PM_2.5 daily mean, hourly-peak concentration and DECH were used as the exposure variables. Based on a case-time-control design, the Cox regression model was applied to evaluate the short-term relative risks (RR) of daily OCV for hypertension. Sensitivity analyses were conducted, with nitrogen dioxide, sulfur dioxide, carbon monoxide, and ozone being adjusted.

RESULTS

Daily mean and hourly-peak of PM_2.5 were significantly associated with daily OCV for hypertension, while weaker associations were observed for DECH. The estimated RRs at lag day 0 were 1.039 (95% confidence interval [CI]: 1.037, 1.040), 1.851 (95%CI: 1.814, 1.888), and 1.287 (95%CI: 1.276, 1.298), respectively, in association with a 1-unit increase in DECH, daily mean, and hourly-peak concentration of PM_2.5. For the lagged effect, lag₄ models estimated the greatest RRs for PM_2.5 DECH and hourly-peak, whereas a lag₂ model produced the highest for PM_2.5 daily mean.

DISCUSSION

This study consolidates the evidence for a positive correlation between ambient PM_2.5 exposure and risks of hypertensive OCV. It also provides profound insight regarding planning for health services needs and establishing early environmental responses to the worsening air pollution in the communities.

Association between PM10 and specific circulatory system diseases in China

Particulate matter (PM) has been proved to be a risk factor for the development of circulatory system diseases (CSDs) around the world. In this study, we collected daily air pollutants, emergency room (ER) visits for CSDs, and meteorological data from 2009 to 2012 in Beijing, China. After controlling for the long-term trend and eliminating the influence of confounding factors, the generalized additive model (GAM) was used to evaluate the short-term effects of PM10 on CSDs and cause-specific diseases. The results showed that for every 10 μg/m3 increase in PM10, the largest effect estimates in ER visits of total CSDs, arrhythmia, cerebrovascular diseases, high blood pressure, ischemic heart disease and other related diseases were 0.14% (95% CI: 0.06-0.23%), 0.37% (95% CI: - 0.23 to 0.97%), 0.20% (95% CI: 0.00-0.40%), 0.15% (95% CI: 0.02-0.27%), 0.18% (95% CI: 0.02-0.35%) and 0.35% (95% CI: - 0.04 to 0.79%), respectively. When NO2 or SO2 was added into the model, the effect estimates of PM10 were mostly attenuated, while in those models with PM2.5 added, the effect estimates of PM10 were mostly increased. Stratified analysis indicated that PM10 had a greater effect on males and the elderly.

Particulate matter (PM10) as a newly identified environmental risk factor for acute gout flares: A time-series study

OBJECTIVES

This study aimed to investigate the effect of short-term exposure to ambient particulate matter less than 10μm in diameter (PM₁₀) on occurrence of acute gout flares in the general population and identify susceptible groups accordingly.

METHODS

The data of emergency department (ED) cases with acute gout flare in Incheon city, Korea between January 1st 2008 and December 31st 2015 were collected from the National Health Insurance Service claims data. The levels of PM₁₀ and meterological measurements were provided by the Ministry of Environment and the National Meterological Office, respectively. To estimate the risk of daily ED visits due to acute gout flare, these time-series data set were analyzed using generalized additive models with Poisson distribution, including daily average PM₁₀ level, temperature, relative humidity, day of the week, national holiday, season, and date.

RESULTS

The risk of daily ED visits for acute gout flares per interquartile range increment of the average daily PM₁₀ levels significantly increased in the cumulative lag 0-7 model (relative risk, 1.018; 95% confidence interval, 1.008-1.027, P<0.001). In particular, men aged≥40 years and those with a history of diabetes mellitus or gout were significantly at a high risk of acute gout flares by subgroup analysis.

CONCLUSIONS

Our time-series study demonstrated a modest, but significant effect of short-term exposure to PM₁₀ on ED visits for acute gout flares. Ambient PM₁₀ may be a newly identified environmental risk factor for acute gout flares.

Acute effects of ambient air pollution on hospital outpatients with chronic pharyngitis in Xinxiang, China

We present results on a time-series study that analyzed the acute effects of six criteria air pollutants on hospital outpatient with chronic pharyngitis (CP) in Xinxiang, China. Data on the concentration of air pollutants and CP outpatient records were collected daily in Xinxiang, China, from January 1, 2015 to December 31, 2018. This study identified 62,823 outpatients with CP. The annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ are 75.7, 132.1, 33.2, 48.4, 1377, and 59.4 μg/m³, respectively. Further, a 10 μg/m³ increment in the concentration of PM₁₀, SO₂, NO₂, and CO corresponds to an increase of 0.28% (95% confidence interval (CI): 0.03-0.53%), 1.10% (95% CI: 0.09-2.11%), 1.82% (95% CI: 0.84-2.80%), and 0.03% (95% CI: 0.01-0.06%) in daily CP hospital outpatients, respectively. Furthermore, results indicated that outpatients under the age of 15 are more susceptible to the air pollutants, excluding O₃. Meanwhile, males might be more susceptible, and effect estimates appear slightly stronger in the cool season. Therefore, we should implement effective measures to manage air pollutants and reinforce protection of the high-risk population.

The Interactive Effects between Particulate Matter and Heat Waves on Circulatory Mortality in Fuzhou, China

The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32–16.72) and 3.84% (95% CI: 0.28–7.54) per 10 μg/m³ increase of PM_2.5 and PM₁₀, respectively, compared to non-heat waves. Compared with low-level PM_2.5 concentration on non-heat waves layer, the high level of PM_2.5 concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37–106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.

The short-term effects of air pollution on respiratory disease hospitalizations in 5 cities in Poland: comparison of time-series and case-crossover analyses

Very few publications have compared different study designs investigating the short-term effects of air pollutants on healthcare visits and hospitalizations for respiratory tract diseases. This study describes, using two different study designs (a case-crossover design and a time-series analysis), the association of air pollutants and respiratory disease hospitalizations. The study has been conducted on 5 cities in Poland on a timeline of almost 4 years. DLNM and regression models were both used for the assessment of the short-term effects of air pollution peaks on respiratory hospitalizations. Both case-crossover and time-series studies equally revealed a positive association between air pollution peaks and hospitalization occurrences. Results were provided in the form of percentage increase of a respiratory visit/hospitalization, for each 10-μg/m3 increment in single pollutant level for both study designs. The most significant estimated % increases of hospitalizations linked to increase of 10 μg/m3 of pollutant have been recorded in general with particulate matter, with highest values for 24 h PM2.5 in Warsaw (6.4%, case-crossover; 4.5%, time series, respectively) and in Białystok (5.6%, case-crossover; 4.5%, time series, respectively). The case-crossover analysis results have shown a larger CI in comparison to the results of the time-series analysis, while the lag days were easier to identify with the case-crossover design. The trends and the overlap of the results occurring from both methods are good and show applicability of both study designs to air pollution effects on short-term hospitalizations.

Relationship between different particle size fractions and all-cause and cause-specific emergency ambulance dispatches

BACKGROUND

Evidence on the relationship between different particle size fractions and emergency ambulance dispatches (EAD) remains limited and sparse.

METHODS

We collected daily data of EAD, ambient air pollution and meteorological data from 2014 to 2018 in Guangzhou, China. We used a generalized additive model with covariate adjustments to estimate the associations between different particle size fractions and EAD related to all-cause, cardiovascular diseases, and respiratory diseases. Several subgroup and sensitivity analyses were also performed.

RESULTS

Significant associations were observed between PM_2.5, PM_2.5-10, PM₁₀ and EADs. A 10 μg/m³ increase of PM_2.5, PM_2.5-10, and PM₁₀ was associated with an increase of 0.98% (95% CI: 0.67, 1.28%), 2.06% (95% CI: 1.44, 2.68%), and 0.75% (95%CI: 0.53, 0.96%) in all-cause EAD, with an increase of 0.69% (95% CI: 0.00, 1.39%), 2.04% (95% CI: 0.64, 3.45%), and 0.60% (95%CI: 0.11,1.10%) in cardiovascular-related EAD, and an increase of 1.14% (95% CI: 0.25, 2.04%), 2.52% (95% CI: 0.72, 4.35%), and 0.89% (95%CI: 0.25,1.52%) in respiratory-related EAD at lag03, respectively. The results were robust in subgroup and sensitivity analyses.

CONCLUSIONS

This study revealed that PM_2.5, PM_2.5-10 and PM₁₀ were significantly related with risks of all-cause and cause-specific EAD. More evidence of high quality may be needed to further support our results in this ecological study.

Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure

Background

Accumulating evidence has linked environmental exposure, such as ambient air pollution and meteorological factors, to the development and severity of cardiovascular diseases (CVDs), resulting in increased healthcare demand. Effective prediction of demand for healthcare services, particularly those associated with peak events of CVDs, can be useful in optimizing the allocation of medical resources. However, few studies have attempted to adopt machine learning approaches with excellent predictive abilities to forecast the healthcare demand for CVDs. This study aims to develop and compare several machine learning models in predicting the peak demand days of CVDs admissions using the hospital admissions data, air quality data and meteorological data in Chengdu, China from 2015 to 2017.

Methods

Six machine learning algorithms, including logistic regression (LR), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) were applied to build the predictive models with a unique feature set. The area under a receiver operating characteristic curve (AUC), logarithmic loss function, accuracy, sensitivity, specificity, precision, and F1 score were used to evaluate the predictive performances of the six models.

Results

The LightGBM model exhibited the highest AUC (0.940, 95% CI: 0.900–0.980), which was significantly higher than that of LR (0.842, 95% CI: 0.783–0.901), SVM (0.834, 95% CI: 0.774–0.894) and ANN (0.890, 95% CI: 0.836–0.944), but did not differ significantly from that of RF (0.926, 95% CI: 0.879–0.974) and XGBoost (0.930, 95% CI: 0.878–0.982). In addition, the LightGBM has the optimal logarithmic loss function (0.218), accuracy (91.3%), specificity (94.1%), precision (0.695), and F1 score (0.725). Feature importance identification indicated that the contribution rate of meteorological conditions and air pollutants for the prediction was 32 and 43%, respectively.

Conclusion

This study suggests that ensemble learning models, especially the LightGBM model, can be used to effectively predict the peak events of CVDs admissions, and therefore could be a very useful decision-making tool for medical resource management.

Short-term effects of particulate matter exposure on emergency room visits for cardiovascular disease in Lanzhou, China: a time series analysis

Cardiovascular disease (CVD) has been the leading cause of death in China. Identifying the relationship between particulate matter (PM) and CVD in China is a significant challenge. In this study, daily CVD emergency room visit, environmental monitoring, and weather data from January 1, 2017, to December 31, 2018, in Lanzhou were collected. Generalized additive models (GAMs) were constructed to estimate the short-term effects of daily PM_2.5, PM_C, and PM₁₀ concentrations on CVD emergency room visits with different lag structures after controlling for the influence of meteorological elements and gaseous pollutants. Stratified analyses were conducted according to age (≥ 65 years and < 65 years), sex (male and female), cold season (from November to April), and warm season (from May to October). The results showed that each 10 μg/m³ increase in PM_2.5 was associated with a 1.93% (95% CI 0.12-3.78%) increase in CVD emergency room visits at lag03, and no single lag model was statistically significant. The excess relative risks (ERRs) of PM₁₀ and PM_C were not statistically significant at any lag pattern. The exposure-response curves demonstrated a nonlinear upward trend for these three PM pollutants. When adjusting for other gaseous pollutants, such as NO₂, SO₂, CO, and O₃, in the two-pollutant models, the associations between PM₁₀ and PM_C and CVD emergency room visits did not change compared with the single-pollutant models. The ERRs of PM_2.5 were 1.67% (95% CI 0.03-3.34%) at lag02 after adjustment for NO₂ and 1.65% (95% CI 0.02-3.30%) at lag02 after adjustment for SO₂. The ERRs of PM_2.5 were still statistically significant at lag03 when we adjusted for any one of the gaseous pollutants. Susceptibility to PM_2.5 was increased in people aged < 65 years, in males, and in the warm season. The findings are very important for local governments to develop environmental policies and strategies to reduce ambient PM_2.5 levels.

Short-term impacts of ambient fine particulate matter on emergency department visits: Comparative analysis of three exposure metrics

BACKGROUND

Research argued that daily excessive concentration hours (DECH) could be more informative through accounting for within-day variations, when assessing population-level exposure to ambient fine particle (PM_2.5). However, few studies have comparatively investigated PM_2.5-associated risks using DECH and two common metrics of daily mean and hourly peak concentration.

METHODS

We collected daily records of all-cause emergency department visits (EDVs) and hourly data on air pollutants and meteorological factors from Shenzhen, China, 2015-2018. According to guidelines proposed by the World Health Organization, DECH was calculated by summing up daily concentrations exceeding 25 μg/m³. Based on time-stratified case-crossover design, we adopted conditional logistic regression models to assess short-term attributable risks of EDVs associated with PM_2.5 using three exposure metrics.

RESULTS

DECH and daily average of PM_2.5 strongly elevated risks of EDVs, while less evident associations were observed using hourly peak metric. Estimated excess relative risks at lag 0 day were 0.56% (95% confidence interval [CI]: 0.21 to 0.91), 0.69% (95% CI: 0.25 to 1.13) and 0.37% (95% CI: 0.02 to 0.76), respectively, associated with an interquartile range increase in DECH (420.2 μg/m³), 24-h average (24.9 μg/m³) and hourly peak concentration (38 μg/m³). More emergency visits could be attributed to DECH than daily mean PM_2.5, with attributable fractions of 2.02% (95% CI: 1.42 to 2.61) and 1.09% (95% CI: 0.69 to 1.49), respectively.

CONCLUSIONS

This study added evidence for increased risk of EDVs associated with exposure to ambient PM_2.5. DECH was a potential alternative exposure metric for PM_2.5 assessment, which may have implications for future revision of air quality standards.

Study on the association between ambient air pollution and daily cardiovascular death in Hefei, China

Cardiovascular disease has always been the most serious public health problem in China. Although many studies have found that the risk of death caused by cardiovascular disease is related to air pollutants, the existing results are still inconsistent. The aim of this study was to investigate the effects of air pollutants on the risk of daily cardiovascular deaths in Hefei, China. Daily data on cardiovascular deaths, daily air pollutants, and meteorological factors from 2007 to 2016 were collected in this study. A time-series study design using a distributed lag nonlinear model was employed to evaluate the association between air pollutants and cardiovascular deaths. First, a single air pollutant model was established based on the minimum value of Akaike information criterion (AIC), and the single day lag effects and multi-day lag effects were discussed separately. Then, two-pollutant models were fitted. Subgroup analyses were conducted by gender (male and female), age (< 65 age and ≥ 65 age), and disease type (ischemic heart disease and cerebral vascular disease). There were 34,500 cases of cardiovascular deaths during the period 2007-2016, and the average concentrations of air pollutants (PM₁₀, SO₂, NO₂, PM_2.5, CO, O₃) were 106.11, 20.34, 30.49, 72.59, 958.7, and 67.88 μg/m³, respectively. An increase of interquartile range (IQR) in PM₁₀, SO₂, NO₂, PM_2.5, CO, and O₃ were associated with an increase of 4.34% (95%CI 1.54~7.23%) at lag 0-6, 5.79% (95%CI 2.43~9.27%) at lag 0-5, 4.47% (95%CI 1.64~7.37%) at lag 0-5, 3.14% (95%CI 0.03~6.36%) at lag 0-4, 3.11% (95%CI 0.21~6.10%) at lag 0-3, and 8.17% (95%CI 1.89~14.84%) at lag 0-5 in cardiovascular deaths, respectively. Females, older group (≥ 65 years) and deaths from cerebral vascular disease were more vulnerable to air pollution than males, younger individuals (< 65 years) and deaths from ischemic heart disease. Our results suggest that air pollution increased the risk of cardiovascular deaths in Hefei. These findings can provide evidence for effective air quality interventions in Hefei.

A Study of the Socioeconomic Forces Driving Air Pollution Based on a DPSIR Model in Henan Province, China

The 3D spatiotemporal distribution (spatial and annual-month-daily temporal) features of the air quality index (AQI), air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3-8h), and air pollution risks (R) from 2003 to 2018 were investigated to understand the severity of air pollution in Henan province. The multiyear ascending trends for AQI and R values, with a peak in 2015, were observed in 2003 to 2018 since the annual population-weighted average concentrations of PM2.5, PM10, NO2, and O3-8h were always higher than the CAAQs II from 2013 to 2017 in Henan province. Changes in the monthly moving average AQI values in Henan province conformed to a U-shaped pattern, with the highest values in the winter (from December to February) and the lowest in the summer (from June to August). Triple peaks for AQI values of 8:00‒10:00 a.m., 6:00‒8:00 p.m., and 2:00‒4:00 p.m. in the representative municipalities corresponded with the morning and evening traffic tendencies and photochemical process. A spatial analysis indicated that there were decreasing trends for air pollution from northwest to southeast in Henan province. Data on 48 concrete parameters were collected from 2003 to 2017 to construct a driving force‒pressure‒state‒influence‒response (DPSIR) model for assessing the socioeconomic forces driving air pollution in this province. It was the too-rapid growth of the driving force index (DFI), induced by urban development and population growth (UDPG), economic growth and change of industrial structure (EGCIS), and energy consumption growth and structure change (ECGSC), that led to a direct increase in the atmospheric pollution burden, i.e., total emissions from air pollution and industrial emissions, which are linearly correlated to values of UDPG and ECGSC, respectively (p < 0.05). Furthermore, the prediction models for AQI and R values in Henan province, with the growth rates being 4.251 DFI−1 and 0.0816 DFI−1, respectively, were simulated by multiple linear regression analysis. Therefore, the integrated risks of air pollution in Henan province were originally driven by DFI.

Short-term association between ambient air pollution and lung cancer mortality

RATIONALE

Long-term exposure to air pollution has been associated with increased lung cancer incidence and mortality. However, the short-term association between air pollution and lung cancer mortality (LCM) remains largely unknown.

METHODS

We collected daily data on particulate matter with diameter <2.5 μm (PM_2.5), particulate matter with diameter < 10 μm (PM₁₀), sulfur dioxide (SO₂), and ozone (O₃), and LCM in three of the biggest cities in China, i.e. Beijing, Chongqing, and Guangzhou, from 2013 to 2015. We first estimated city-specific relationships between air pollutants and LCM using time-series generalized linear models, adjusting for potential confounders. A classification and regression tree (CART) model was used to stratify LCM risk based on combinations of air pollutants and meteorological factors in each city. Then we pooled the city-specific associations using random-effects meta-analysis. Meta regression was used to explore if city-specific characteristics modified the air pollution-LCM association. Finally, we stratified the analyses by season, age, and sex.

RESULTS

Over the entire period, the current-day concentrations of PM_2.5 and PM₁₀ in Chongqing and PM_2.5, PM₁₀, and SO₂ in Guangzhou were positively associated with LCM (Excess risk ranged from 0.72% (95% CI 0.27%-1.17%) to 6.06% (95% CI 0.76%-11.64%) with each 10 μg/m³ increment in different pollutants), but the association between current-day air pollution and LCM in Beijing was not significant (P > 0.05). When considering the environmental and weather factors simultaneously, current-day PM_2.5, relative humidity, and PM₁₀ were the most important factors associated with LCM in Beijing, Chongqing, and Guangzhou, respectively. LCM risk related with daily PM_2.5, PM₁₀, and SO₂ significantly increased with the increasing annual mean temperature and humidity of the city, while LCM risk related with daily O₃ significantly increased with the increases of latitude, annual mean O₃ concentration, and socioeconomic level. After stratification, the current-day PM_2.5, PM₁₀, and O₃ during the warm season in Beijing and PM_2.5, PM₁₀, and SO₂ during the cool season in Chongqing and Guangzhou were positively associated with LCM (Excess risk ranged from 0.93% (95% CI 0.42%-1.45%) to 7.16% (95% CI 0.64%-14.09%) with each 10 μg/m³ increment in different pollutants). Male and the elderly lung cancer patients were more sensitive to the short-term effect of air pollution.

CONCLUSIONS

Lung cancer patients should enhance protection measures against air pollution. More attentions should be paid for the high PM_2.5, PM₁₀, and O₃ during the warm season in Beijing, and high PM_2.5, PM₁₀, and SO₂ during the cool season in Chongqing and Guangzhou.

An Azure ACES Early Warning System for Air Quality Index Deteriorating

With the development of industrialization and urbanization, air pollution in many countries has become more serious and has affected people's health. The air quality has been continuously concerned by environmental managers and the public. Therefore, accurate air quality deterioration warning system can avoid health hazards. In this study, an air quality index (AQI) warning system based on Azure cloud computing platform is proposed. The prediction model is based on DFR (Decision Forest Regression), NNR (Neural Network Regression), and LR (Linear Regression) machine learning algorithms. The best algorithm was selected to calculate the 6 pollutants required for the AQI calculation of the air quality monitoring in real time. The experimental results show that the LR algorithm has the best performance, and the method of this study has a good prediction on the AQI index warning for the next one to three hours. Based on the ACES system proposed, it is hoped that it can prevent personal health hazards and help to reduce medical costs in public.

Joint effect of multiple air pollutants on daily emergency department visits in Chengdu, China

Existing studies have typically investigated only the association between single pollutants and health outcomes. However, in the real world, people are exposed to multiple air pollutants simultaneously. The effect of air pollutants on emergency department (ED) visits has not been previously studied in the Sichuan Basin, which is one of the most polluted areas. We collected nonaccidental, respiratory and cardiovascular daily ED visits and daily concentrations of PM_2.5, PM_c, CO, SO₂, NO₂ and O₃ in Chengdu, China, from 2014 to 2016. A weighted variable for the combination of multiple air pollutants was constructed to assess the joint adverse health effects. Each air pollutant was assigned a health-related weight, which indicated the pollutant's relative contribution to the joint effect. The effects on specific subpopulations (males and females; 15-65 years old and >65 years old) were also examined. With an increase of 10 μg/m³ of the combined multiple air pollutants, the daily ED visits for nonaccidental, respiratory and cardiovascular causes increased by 0.96% (95% CI: 0.51%-1.39%), 1.19% (95% CI: 0.53%, 1.85%) and 4.36% (95% CI: 1.06%, 7.76%) at lag 1, respectively. Males presented more pronounced effects, except for cardiovascular disease, than females. Elderly individuals were found to be more sensitive than young individuals. For nonaccidental and respiratory diseases, the contributions of particulate matter (PM) were dominant among the air pollutants, whereas cardiovascular disease was mainly affected by gaseous air pollutants. The combination of multiple air pollutants was significantly associated with ED visits in the Sichuan Basin, China. The joint effect of the combination of multiple air pollutants was highest for cardiovascular disease at lag 1. The relative contributions of individual pollutants varied by disease and subpopulation. These findings suggest that under different pollution scenarios, preventive strategies should target those with different diseases and different subpopulations.

Acute effects of fine particulate matter (PM2.5) on hospital admissions for cardiovascular disease in Beijing, China: a time-series study

BACKGROUND

Air pollution and cardiovascular disease are increasing problems in China. However, the short-term association between fine particulate matter (PM_2.5) and cardiovascular disease (CVD) is not well documented. The purpose of this study is to estimate the short-term effects of PM_2.5 on CVD admissions in Beijing, China.

METHODS

In total, 460,938 electronic hospitalization summary reports for CVD between 2013 and 2017 were obtained. A generalized additive model using a quasi-Poisson distribution was used to investigate the association between exposure to PM_2.5 and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) after controlling for the season, the day of the week, public holidays, and weather conditions. A stratified analysis was also conducted for age (18-64 and ≥ 65 years), sex and season.

RESULTS

For every 10 μg/m³ increase in the PM_2.5 concentration from the previous day to the current (lag 0-1) there was a significant increase in total CVD admissions (0.30, 95% CI: 0.20, 0.39%), with a strong association for older adults (aged ≥65 years), CHD (0.34, 95% CI: 0.22 to 0.45%) and AF (0.29, 95% CI, 0.03 to 0.55%). However, the observed increased risk was not statistically significant for HF hospitalizations. The associations in the single-pollutant models were robust to the inclusion of other pollutants in a two-pollutant model. No differences were found after stratification by sex and season.

CONCLUSIONS

Exposure to PM_2.5 increased the risk of hospitalizations from CVD, especially for CHD, and appeared to have more influence in the elderly. Precautions and protective measures and efforts to reduce exposure to PM_2.5 should be strengthened, especially for the elderly.

Short-term PM10 and emergency department admissions for selective cardiovascular and respiratory diseases in Beijing, China

BACKGROUND

Few studies have explored PM₁₀'s connection with specific respiratory and cardiovascular emergency department admissions (EDAs). This study aimed to examine the overall effects of PM₁₀ on EDAs for cardiovascular and respiratory diseases, including specifically, cerebrovascular events (CVE), ischemic heart disease (IHD), arrhythmia, heart failure (HF), upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), chronic obstructive pulmonary disease (COPD) and asthma.

METHODS

We collected daily data for EDAs from the 10 largest hospitals in Beijing, between January 2013 and December 2013 as well as daily measurements of PM₁₀ from 17 stations in Beijing. The generalized-additive model was utilized to evaluate the associations between daily PM₁₀ and cardio-pulmonary disease admissions. Differences in gender, age, and season groups were also examined by models. Relative risks (RR) with 95% confidence interval (CI) were calculated based on subtype, age, gender and seasonal groups. In all, there were approximately 56,212 cardiovascular and 92,464 respiratory emergency admissions presented in this study.

RESULTS

The largest estimate effects in EDAs of total cardiovascular disease, CVE, IHD, total respiratory diseases, URTI, LRTI and COPD were found for PM₁₀ at day 4 (accumulative) moving average, were 0.29% (95% CI:0.12%, 0.46%), 0.36% (95% CI:0.11%, 0.61%), 0.68% (95% CI:0.25%, 1.10%), 0.34% (95% CI:0.22%, 0.47%), 0.35% (95% CI:0.18%, 0.51%), 0.34% (95% CI:0.14%, 0.55%), 2.75% (95% CI:1.38%, 4.12%) respectively. In two-pollutant models and full-pollutant model modified confounding factors, the positive correlation remained unchanged. The elderly (age ≥ 65 years) and male subjects were more susceptible to specific respiratory diseases. PM₁₀'s impact on EDAs for HF was found higher during the hot season however, EDAs for COPD peaked during the cold season.

CONCLUSION

The study markedly informed that PM₁₀ pollution was strongly associated with EDAs for cardio-pulmonary diseases. The effects of PM₁₀ pollution on COPD and heart failure EDAs were clearly determined by seasonal-temperatures.

Effects of ambient air pollution on daily hospital admissions for respiratory and cardiovascular diseases in Bangkok, Thailand

BACKGROUND

Although health effects of air pollutants are well documented in many countries especially in North America and Western Europe, few studies have been conducted in Thailand where pollution mix, weather conditions, and demographic characteristics are different. The present study aimed to investigate the effects of ambient air pollution on hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand.

METHODS

We obtained daily air pollution concentration (O₃, NO₂, SO₂, PM₁₀, and CO) and weather variable monitored in Bangkok from January 2006 to December 2014. Daily hospital admissions for cardiovascular and respiratory diseases were obtained from the National Health Security Office during the study period. A time-series analysis with generalized linear model was used to examine the effects of air pollution on hospital admissions by controlling for long-term trend and other potential confounders. The effect modification by age (0-14 years, 15-64 years, ≥65 years) and gender was also examined.

RESULTS

An increase of 10 μg/m³ in O₃, NO₂, SO₂, PM₁₀, and 1 mg/m³ in CO at lag 0-1 day was associated with a 0.14% (95% CI: -0.34 to 0.63), 1.28% (0.87 to 1.69), 8.42% (6.16 to 10.74), 1.04% (0.68 to 1.41) and 6.69% (4.33 to 9.11) increase in cardiovascular admission, respectively; and 0.69% (95% CI: 0.18 to 1.21), 1.42% (0.98 to 1.85), 4.49% (2.22 to 6.80), 1.18% (0.79 to 1.57) and 7.69% (5.20 to 10.23) increase in respiratory admission, respectively. The elderly (≥65 years) seemed to be the most susceptible group to the effect of air pollution, whereas the effect estimate for male and female was not significantly different.

CONCLUSIONS

Results from this study contributed the evidence to support the effects of air pollution (O₃, NO₂, SO₂, PM₁₀, and CO) on hospital admissions for cardiovascular and respiratory diseases, which might be useful for public health intervention in Thailand.

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.

Short-Term Effects of Ambient Air Pollution on Hospitalization for Respiratory Disease in Taiyuan, China: A Time-Series Analysis

In this study, we estimated the short-term effects of ambient air pollution on respiratory disease hospitalization in Taiyuan, China. Daily data of respiratory disease hospitalization, daily concentration of ambient air pollutants and meteorological factors from 1 October 2014 to 30 September 2017 in Taiyuan were included in our study. We conducted a time-series study design and applied a generalized additive model to evaluate the association between every 10-μg/m³ increment of air pollutants and percent increase of respiratory disease hospitalization. A total of 127,565 respiratory disease hospitalization cases were included in this study during the present period. In single-pollutant models, the effect values in multi-day lags were greater than those in single-day lags. PM_2.5 at lag02 days, SO₂ at lag03 days, PM₁₀ and NO₂ at lag05 days were observed to be strongly and significantly associated with respiratory disease hospitalization. No significant association was found between O₃ and respiratory disease hospitalization. SO₂ and NO₂ were still significantly associated with hospitalization after adjusting for PM_2.5 or PM₁₀ into two-pollutant models. Females and younger population for respiratory disease were more vulnerable to air pollution than males and older groups. Therefore, some effective measures should be taken to strengthen the management of the ambient air pollutants, especially SO₂ and NO₂, and to enhance the protection of the high-risk population from air pollutants, thereby reducing the burden of respiratory disease caused by ambient air pollution.

Research and application of a novel hybrid air quality early-warning system: A case study in China

As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency.

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.