Effects Of Ambient Air Pollution Research Articles

Exposure to ambient particulate matter and ovarian reserve impairment among reproductive age women in China

Ovarian aging, characterized by a decline in ovarian reserve, is a critical concern in female reproductive health. However, the evidence linking ambient air pollution exposure with ovarian reserve impairment remains limited. We aimed to estimate the association between exposure to fine particulate matter (PM2.5) and respirable particulate matter (PM10) and key indicators of ovarian reserve, including antral follicle count (AFC), ovarian volume (OV), anti-Müllerian hormone (AMH), follicle-stimulating hormone (FSH), estradiol (E2), luteinizing hormone (LH), FSH/LH ratio, and inhibin B (INHB). The cohort consisted of women attending an infertility clinic at the Tongji Reproductive and Environmental (TREE) study between 2018 and 2020. We used multivariate linear and Poisson regression models to estimate the association between PM2.5 and PM10 exposure and these ovarian reserve indicators. Our results showed that PM2.5 and PM10 exposure were associated with a reduction in AFC and an increase in E2 levels, highlighting the adverse effects of ambient air pollution on ovarian reserve. Our findings have important public health implications, emphasizing the urgent need for interventions to safeguard female reproductive health and reduce exposure to ambient air pollution.

The Impact of Ambient Air Pollution on Allergic Rhinitis Symptoms: A Prospective Follow-Up Study.

Air pollution has become a serious public health problem and there is evidence that air pollution affects the incidence of allergic rhinitis. To further investigate the effect of ambient air pollutants on the severity of allergic rhinitis symptoms, a prospective follow-up study in patients with allergic rhinitis was conducted. A total of 167 allergic rhinitis patients with a mean age of 35.4 years, who were visiting the hospital, were enrolled. The daily symptom severity of allergic rhinitis and the concentrations of six air pollutants, including PM2.5, PM10, SO2, CO, O3 and NO2, were collected through follow-up investigations. The impact of ambient air pollutants on symptom severity was assessed via multi-pollutant models. Among several typical ambient air pollutants, we observed correlations of allergic rhinitis symptoms with PM2.5, PM10, CO, SO2 and NO2, whereas O3 showed no such correlation. Specifically, PM2.5 and PM10 were significantly associated with sneezing and nasal blockage. NO2 was significantly correlated with symptoms of rhinorrhea, itchy nose and itchy eyes. CO was significantly linked to sneezing and nasal blockage symptoms. These air pollutants not only had a direct impact on allergic rhinitis symptoms but also exhibited a lagging effect. This study indicates that short-term exposure to air pollutants is associated with exacerbation of nasal symptoms in patients with allergic rhinitis, leading to a decline in their quality of life.

Spatial heterogeneity in the acute effects of ambient air pollution and temperature on pediatric seizures and epilepsy across New York

Spatial heterogeneity in the acute effects of ambient air pollution and temperature on pediatric seizures and epilepsy across New York

Ambient air pollutants exposure during gestation and incidence risk of hypertensive disorders of pregnancy or preeclampsia in China

The relationships between the exposure to ambient air pollutants during gestation and the incidence of hypertensive disorders in pregnancy (HDPs) or preeclampsia are contradictory. This prospective cohort study enrolled the participants between January 2020 and December 2021 from the Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology. The exposure to ambient air pollutants and daily temperatures were obtained from the ChinaHighAirPollutants dataset and the Big Earth Data Platform for Three Poles, respectively. Logistic regression models were used as single- and two-pollutant models. Restricted cubic splines were applied to each ambient air pollutant exposure to further evaluate the exposure-response relationships. Quantile G-computation approaches were employed to evaluate the cumulative impact of mixed ambient air pollutants on the incidence risk HDPs and preeclampsia. Among 19,325 participants (median age: 30.2 years), 1669 (8.64%) were diagnosed with HDPs and 180 (0.94%) with preeclampsia. While mostly null risk estimates were observed, exposure to PM1, PM2.5, PM10, and NO2 correlated with a decreased incidence risk for HDPs and preeclampsia during most gestational periods. Additionally, our multi-pollutant model presented that an increase by one quartile in the cumulative effect of ambient air pollutants was associated with a significantly decreased incidence risk for HDPs in the trimester before gestation and in the third trimester during gestation, as well as for preeclampsia in the third trimester during gestation. These findings warrant further investigation into the mechanisms underlying these associations.

Hourly effect of atmospheric reactive nitrogen species on the onset of acute ischemic stroke: Insight from the Shanghai Stroke Service System Database

Acute ischemic stroke (AIS) is one of the most predominant causes of mortality and disability in China. Significant uncertainties in stroke diagnosis and time of onset have resulted in inconsistent evidence on the association between ambient air pollution and the risk of AIS. The present study aimed to evaluate the impact of air pollution on AIS onset based on high time-resolution air pollution data and a stroke-specific registry across the past five years. Hourly concentrations of PM2.5, PM10, O3, SO2, CO, NO2 and nitrous acid (HONO) were monitored from 2017 to 2021, with which a distributed lag non-linear model and conditional logistic regression models coupled with a time-stratified case-crossover design were applied to 106,623 AIS cases recorded in the Shanghai Stroke Service (4S) database during the study period. Results from the conditional logistic regression models indicate that acute exposure to PM2.5, PM10, SO2, NO2 and HONO was found to be associated with AIS onset, respectively. The corresponding cumulative excessive risks of AIS onset were 0.8 %, 1 %, 2.4 %, 2.1 % and 1.8 % for each interquartile range increase in the respective concentration. The longest lag-effect (up to 13 h) was observed for reactive nitrogen species (RNS), such as NO2 and HONO, which remained robust in two-pollutant models. Similar important role of RNS in AIS onset were confirmed by the distributed lag non-linear model. By demonstrating the transient effect of ambient air pollution on AIS, especially the relationships between RNS and AIS for the first time, our study provides stringent evidence for future mitigation strategies for pollution emission and public health.

Association of ambient air pollution and pesticide mixtures on respiratory inflammatory markers in agricultural communities

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (β: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (β:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.

Association of residential greenness with incident allergic rhinitis among adults: A prospective analysis of UK Biobank

BackgroundLimited studies have assessed the impact of residential greenness exposure on allergic rhinitis in adults, and its relationship with ambient air pollutants remains unknown. ObjectiveTo investigate the association of residential greenness with allergic rhinitis incidence and explore the mediation effects of ambient air pollutants in adults using data from a prospective cohort study in UK Biobank. MethodsGreenness was defined as the area-weighted mean of greenness coverage based on the land used data from the Generalized Land Use Database for England (GLUD) 2005 in the UK Biobank. Multiple Cox proportional hazard models and a generalized additive model incorporating restricted cubic splines were used to model the potential nonlinear effect of residential greenness on allergic rhinitis incidence and the potential mediation effect of ambient air pollutants. ResultsAmong the 281,699 subjects included in the analysis, 3260 allergic rhinitis incident cases occurred after a median follow-up of 14 years. With per 10% increase in residential greenness at a 300-m buffer, a 2.5% (95% CI: 1.0%, 4.0%) decreased risk of allergic rhinitis was observed. An L-shaped, non-linear dose-response relationship was indicated with a threshold of 54.9% greenness above which no excess allergic rhinitis risk was seen. PM10 partially mediated the relationship between greenness and allergic rhinitis incidence with a mediation effect of 26.9% (95% CI: 12.6%, 41.2%). A similar pattern of association was found at 1000-m buffer size. ConclusionThis study demonstrates a significant beneficial effect of residential greenness on reducing allergic rhinitis incidence. Greenness may erase air pollutants and mitigate the rhinitis risk from air pollution.

Mixed effects of ambient air pollutants on oocyte-related outcomes: A novel insight from women undergoing assisted reproductive technology

Air pollution is widely acknowledged as a significant risk factor for human health, especially reproductive health. Nevertheless, many studies have disregarded the potentially mixed effects of air pollutants on reproductive outcomes. We performed a retrospective cohort study involving 8048 women with 9445 cycles undergoing In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) in China, from 2017 to 2021. A land-use random forest model was applied to estimate daily residential exposure to air pollutants, including sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and fine particulate matter (PM2.5). Individual and joint associations between air pollutants and oocyte-related outcomes of ART were evaluated. In 90 days prior to oocyte pick-up to oocyte pick-up (period A), NO2, O3 and CO was negatively associated with total oocyte yield. In the 90 days prior to oocyte pick-up to start of gonadotropin medication (Gn start, period B), there was a negative dose-dependent association of exposure to five air pollutants with total oocyte yield and mature oocyte yield. In Qgcomp analysis, increasing the multiple air pollutants mixtures by one quartile was related to reducing the number of oocyte pick-ups by −2.00 % (95 %CI: −2.78 %, −1.22 %) in period A, −2.62 % (95 %CI: −3.40 %, −1.84 %) in period B, and −0.98 % (95 %CI: −1.75 %, −0.21 %) in period C. During period B, a 1-unit increase in the WQS index of multiple air pollutants exposure was associated with fewer number of total oocyte (−1.27 %, 95 %CI: −2.16 %, −0.36 %) and mature oocyte (−1.42 %, 95 %CI: −2.41 %, −0.43 %). O3 and NO2 were major contributors with adverse effects on the mixed associations. Additionally, period B appears to be the susceptible window. Our study implies that exposure to air pollution adversely affects oocyte-related outcomes, which raises concerns about the potential adverse impact of air pollution on women’s reproductive health.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis

Background:As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution. Method:To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018–2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19. Results:We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants. Conclusions:Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

Effects of Ambient Air Pollution on Brain Cortical Thickness and Subcortical Volume: A Longitudinal Neuroimaging Study.

Several cross-sectional studies have shown that long-term exposures to air pollutants are associated with smaller brain cortical volume or thickness. Here, we investigated longitudinal associations of long-term air pollution exposures with cortical thickness and subcortical volume. In this longitudinal study, we included a prospective cohort of 361 adults residing in four cities in the Republic of Korea. Long-term concentrations of particulate matter with aerodynamic diameters of ≤10 μm (PM10) and ≤2.5 μm (PM2.5) and nitrogen dioxide (NO2) at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images at baseline (August 2014 to March 2017) and at the 3-year follow-up (until September 2020). Linear mixed-effects models were used, adjusting for covariates. A 10-μg/m3 increase in PM10 was associated with reduced whole-brain mean (β = -0.45, standard error [SE] = 0.10; p < 0.001), frontal (β = -0.53, SE = 0.11; p < 0.001) and temporal thicknesses (β = -0.37, SE = 0.12; p = 0.002). A 10-ppb increase in NO2 was associated with a decline in the whole-brain mean cortical thickness (β = -0.23, SE = 0.05; p < 0.001), frontal (β = -0.25, SE = 0.05; p < 0.001), parietal (β = -0.12, SE = 0.05; p = 0.025), and temporal thicknesses (β = -0.19, SE = 0.06; p = 0.001). Subcortical structures associated with air pollutants included the thalamus. Long-term exposures to PM10 and NO2 may lead to cortical thinning in adults.

A study on Effect of Ambient Air Pollution from Roadside Traffic on Qualitative and Quantitative Phytochemical Constituents of Solanum tuberosum L.

Solanum tuberosum L. is a useful vegetable crop and a member of the Solanaceae family that yields starch molecules with a high concentration. The analysis of both qualitative and quantitative phytochemical substances was the main focus of the current investigation. We have chosen places with road traffic and without road traffic (control) for the crop comparison analysis. The qualitative phytochemical substances analysed protein, carbohydrate, iodine, phenol, tannin, flavonoids, saponin, glycosides, steroids, terpene, and alkaloids. The complete phenolic content exhibits a total mean value of 0.03712, surpassing the threshold of 0.03176, while the overall flavonoid content shows a total mean value of 0.04696, exceeding the threshold of 0.03764. Crops growing close to busy road traffic had lower phytochemical substances, in terms of quantity and quality. This record demonstrates the detrimental impact of air pollution caused by vehicles on crop vegetation. Crop vegetation differs between control and road traffic sites, according to data on both qualitative and quantitative phytochemical substances.

Short-Term Effects of Ambient Air Pollution on Chronic Obstructive Pulmonary Disease Admissions in Jiuquan, China.

Recent findings indicate that air pollution contributes to the onset and advancement of chronic obstructive pulmonary disease (COPD). Nevertheless, there is insufficient research indicating that air pollution is linked to COPD in the region of inland northwest China. Daily hospital admission records for COPD, air pollutant levels, and meteorological factor information were collected in Jiuquan for this study between 1 January 2018 and 31 December 2019. We employed a distributed lag non-linear model (DLNM) integrated with the generalized additive model (GAM) to assess the association between air pollution and hospital admissions for COPD with single lag days from lag0 to lag7 and multiday moving average lag days from lag01 to lag07. For example, the pollutant concentration on the current day was lag0, and on the prior 7th day was lag7. The present and previous 7-day moving average pollutant concentration was lag07. Gender, age, and season-specific stratified analyses were also carried out. It is noteworthy that the delayed days exhibited a different pattern, and the magnitude of associations varied. For NO2 and CO, obvious associations with hospitalizations for COPD were found at lag1, lag01-lag07, and lag03-lag07, with the biggest associations at lag05 and lag06 [RR = 1.015 (95%CI: 1.008, 1.023) for NO2, RR = 2.049 (95%CI: 1.416, 2.966) for CO], while only SO2 at lag02 was appreciably linked to hospitalizations for COPD [1.167 (95%CI: 1.009, 1.348)]. In contrast, short-term encounters with PM2.5, PM10, and O3 were found to have no significant effects on COPD morbidity. The lag effects of NO2 and CO were stronger than those of PM2.5 and PM10. Males and those aged 65 years or older were more vulnerable to air pollution. When it came to the seasons, the impacts appeared to be more pronounced in the cold season. In conclusion, short-term encounters with NO2 and CO were significantly correlated with COPD hospitalization in males and the elderly (≥65).

Occupational particle exposure and chronic kidney disease: a cohort study in Swedish construction workers

ObjectivesIncreasing epidemiological and experimental evidence suggests that particle exposure is an environmental risk factor for chronic kidney disease (CKD). However, only a few case–control studies have investigated this association in...

Effects of ambient air pollution on the risk of small- and large-for-gestational-age births: an analysis using national birth data in Japan.

Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association. We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), photochemical oxidants, and particulate matter 2.5 (PM2.5). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association. We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO2 level, regardless of the exposure period. Specifically, the risk ratio for average SO2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO2 except for the third trimester. It was suggested that ambient level of SO2 during the pregnancy term is a risk factor for SGA birth in Japan.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Effects of exposure to environmental factors on obesity-related growth parameters and leptin (LEP) methylation in children.

The prevalence of childhood obesity is rapidly increasing. Therefore, gaining more information on the role of environmental parameters is key. With overexpression of leptin (encoded by LEP) in obesity, LEP methylation might be altered by environmental exposures. This study aims to assess effects of ambient air pollution and nearby greenness on obesity-related growth and LEP methylation in early childhood. We monitored 120 mother-child pairs from conception until the age of five. Buccal swabs and anthropometric measurements of the children were taken at six months, one year, and five years old. Buccal DNA was extracted to determine LEP methylation levels. Estimates of air pollution and nearby greenness were calculated using high-resolution models. Effects of air pollution and nearby greenness on growth or LEP methylation were investigated using linear mixed effects models. Positive associations were shown for air pollution between conception and age one on impedance in six-month-olds and one-year-olds in the crude model. PM with aerodynamic diameter ≤10 (PM10) and ≤2.5 μm (PM2.5) positively associated with waist-hip-ratio and waist circumference at age five in the fully adjusted model. In early childhood, closest distance to forest negatively, and urban green and forest positively associated with weight-for-length, body mass index, and fat percentage in five-year-olds in the fully adjusted model. No significant associations for noise, and walkability on growth were seen. Negative associations were shown for smaller green clusters and positive associations for greater green clusters on LEP methylation in one-year-olds. For forest distance, walkability, noise, or all green on LEP methylation, no significant associations were found. Evidence is provided that ambient air pollution might have a significant effect on impedance and waist-hip-ratio, suggesting an increased risk of childhood obesity. Based on LEP methylation, greater green clusters might associate with a decreased risk of childhood obesity, while smaller green clusters showed the opposite.

Effects of ambient air pollution on obesity and ectopic fat deposition: a protocol for a systematic review and meta-analysis

IntroductionGlobally, the prevalence of obesity tripled from 1975 to 2016. There is evidence that air pollution may contribute to the obesity epidemic through an increase in oxidative stress and inflammation...

How multiple air pollutants affect hand, foot, and mouth disease incidence in children: assessing effect modification by geographical context in multicity of Sichuan, southwest China

BackgroundSeveral studies have suggested a significant association of hand, foot, and mouth disease (HFMD) with ambient air pollutants. Existing studies have characterized the role of air pollutants on HFMD using only risk ratio measures while ignoring the attributable burden. And whether the geographical context (i.e., diverse topographic features) could modulate the relationships is unclear.MethodsDaily reported childhood HFMD counts, ambient air pollution, and meteorological data during 2015–2017 were collected for each of 21 cities in Sichuan Province. A multistage analysis was carried out in different populations based on geographical context to assess effect modification by topographic conditions. We first constructed a distributed lag nonlinear model (DLNM) for each city to describe the relationships with risk ratio measures. Then, we applied a multivariate meta-regression to estimate the pooled effects of multiple air pollutants on HFMD from the exposure and lagged dimensions. Finally, attributable risks measures were calculated to quantify HFMD burden by air pollution.ResultsBased on 207554 HFMD cases in Sichuan Province, significant associations of HFMD with ambient air pollutants were observed mainly at relatively high exposure ranges. The effects of ambient air pollutants on HFMD are most pronounced on lag0 or around lag7, with relative risks gradually approaching the reference line thereafter. The attributable risks of O3 were much greater than those of other air pollutants, particularly in basin and mountain regions.ConclusionsThis study revealed significant pooled relationships between multiple air pollutants and HFMD incidence from both exposure and lag dimensions. However, the specific effects, including RRs and ARs, differ depending on the air pollution variable and geographical context. These findings provide local authorities with more evidence to determine key air pollutants and regions for devising and implementing targeted interventions.

Assessing the short-term effects of PM2.5 and O3 on cardiovascular mortality using high-resolution exposure: a time-stratified case cross-over study in Southwestern China.

Air pollution is a major risk factor of cardiovascular disease (CVD). To date, limited studies have estimated the effects of ambient air pollution on CVD mortality using high-resolution exposure assessment, which might fail to capture the spatial variation in exposure and introduce bias in results. Besides, the three-year action plan (TYAP, 2018-2020) was released; thus, the constitution and health effect of air pollutants may have changed. In this study, we estimated the short-term effect exposed to particulate matters with parameter less than 2.5µm (PM2.5) and ozone (O3) with 0.05° × 0.05° resolution on CVD mortality and measured the influence of TYAP in the associations. We used random forest models with spatial weight matrices to attain high-resolution pollutant concentrations and conditional Poisson regression to assess the relationship between air pollution and cardiovascular mortality. With an increase of 10µg/m3 in PM2.5 and O3 during 2018-2021 in the Sichuan Basin (SCB), CVD mortality increased 1.0134 (95% CI 1.0102, 1.0166) and 1.0083 (95% CI 1.0060, 1.0107), respectively, using high-resolution air pollutant concentration, comparing to 1.0070 (95% CI 1.0052, 1.0087) and 1.0057 (95% CI 1.0037, 1.0078) using data from air quality monitoring stations (AQMs). After TYAP, the relative risk (RR) due to PM2.5 rose up to 1.0149 (95% CI 1.0054, 1.0243), and the RR due to O3 rose up to 1.0089 (95% CI 1.0030, 1.0148) in Sichuan Province. We found significantly positive association of cardiovascular mortality and air pollution in Sichuan Province. And using high-resolution exposure would be more accurate to estimate the effect of air pollution on CVD. After TYAP, the cardiovascular mortality risk estimation due to PM2.5 decreased in elderly in SCB, and the risk due to O3 increased in Sichuan Province.

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

The aim of this study was to examine the impacts of short-term exposure to air pollutants on hospitalizations for mental disorders (MDs) in Qingdao, a Chinese coastal city, and to assess the corresponding hospitalization risk and economic cost. Daily data on MD hospitalizations and environmental variables were collected from January 1, 2015, to December 31, 2019. An overdispersed generalized additive model was used to estimate the association between air pollution and MD hospitalizations. The cost of illness method was applied to calculate the corresponding economic burden. With each 10μg/m3 increase in the concentration of fine particulate matter (PM2.5) at lag05, inhalable particulate matter (PM10) at lag0, sulfur dioxide (SO2) at lag06 and ozone (O3) at lag0, the corresponding relative risks (RRs) and 95% confidence intervals (CIs) were 1.0182 (1.0035-1.0332), 1.0063 (1.0001-1.0126), 1.0997 (1.0200-1.1885) and 1.0099 (1.0005-1.0194), respectively. However, no significant effects of nitrogen dioxide (NO2) or carbon monoxide (CO) were found. Stratified analysis showed that males were susceptible to SO2 and O3, while females were susceptible to PM2.5. Older individuals (≥ 45years) were more vulnerable to air pollutants (PM2.5, PM10, SO2 and O3) than younger individuals (< 45years). Taking the Global Air Quality Guidelines 2021 as a reference, 8.71% (2,168 cases) of MD hospitalizations were attributable to air pollutant exposure, with a total economic burden of 154.36 million RMB. Short-term exposure to air pollution was associated with an increased risk of hospitalization for MDs. The economic advantages of further reducing air pollution are enormous.