The impact of ambient ozone pollution on pneumonia: A nationwide time-series analysis

Interaction between ozone and paternal smoking on fetal congenital heart defects among pregnant women at high risk: a multicenter maternal-fetal medicine study

BACKGROUND

Evidence remains limited on the association between maternal ozone (O3) exposure and congenital heart defects (CHDs) in offspring, and few studies have investigated the interaction and modification of paternal smoking on this association.

METHODS

Using a sample including pregnant women at high risk of fetal CHD (with metabolic disease, first-trimester viral infection, family history of CHD, etc.) from a maternal-fetal medicine study covering 1313 referral hospitals in China during 2013-2021, we examined the associations between maternal O3 exposure during 3-8 weeks of gestational age and fetal CHD in offspring and investigated the interaction and modification of paternal smoking on this association. CHD was diagnosed by fetal echocardiograms, maximum daily 8-hour average O3 exposure data at a 10 km × 10 km spatial resolution came from the Tracking Air Pollution in China dataset, and paternal smoking was collected using questionnaires. Logistic regression models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Among 27,834 pregnant women at high risk of fetal CHD, 17.4% of fetuses were diagnosed with CHD. Each 10 μg/m3 increase in maternal O3 exposure was associated with a 17% increased risk of CHD in offspring (OR = 1.17, 95% CI = 1.14-1.20). Compared with paternal nonsmoking and maternal low O3 exposure, the ORs (95% CI) of CHD for smoking and low O3 exposure, nonsmoking and high O3 exposure, and smoking and high O3 exposure were 1.25 (1.08-1.45), 1.81 (1.56-2.08), and 2.23 (1.84-2.71), respectively. Paternal smoking cessation seemingly mitigated the increased risk of CHD.

CONCLUSIONS

Maternal O3 exposure and paternal smoking were interactively associated with an increased risk of fetal CHD in offspring, which calls for effective measures to decrease maternal exposure to O3 pollution and secondhand smoke for CHD prevention.

Understanding the spatial and seasonal variation of the ground-level ozone in Southeast China with an interpretable machine learning and multi-source remote sensing

Ground-level ozone (O3) pollution poses significant threats to both human health and air quality. This study uses ground observations and satellite retrievals to explore the spatiotemporal characteristics of ground-level O3 in Zhejiang Province, China. We created data-driven machine learning models that include meteorological, geographical and atmospheric parameters from multi-source remote sensing products, achieving good performance (Pearson's r of 0.81) in explaining regional O3 dynamics. Analyses revealed the crucial roles of temperature, relative humidity, total column O3, and the distributions and interactions of precursor (volatile organic compounds and nitrogen oxides) in driving the varied O3 patterns observed in Zhejiang. Furthermore, the interpretable modeling quantified multifactor interactions that sustain high O3 levels in spring and autumn, suppress O3 levels in summer, and inhibit O3 formation in winter. This work demonstrates the value of a combined approach using satellite and machine learning as an effective novel tool for regional air quality assessment and control.

Impacts of short-term low-level exposure to air pollutants on hospital admissions for pulmonary sepsis in elderly patients

BACKGROUND

Acute exposures to high levels of air pollutants are thought to be associated with hospitalization of patients with lung infection, while relatively little is known about the association between air pollutants and HOSPITAL ADMISSIONS FOR pulmonary sepsis.

OBJECTIVES

To assess the correlation between low-level exposure to air pollutants and the hospitalizations for pulmonary sepsis in elderly patients.

METHODS

A total of 249 elderly patients with pulmonary sepsis from January 2018 to December 2020 in Shenzhen people's hospital were included. The data regarding hospitalizations for pulmonary sepsis, meteorological factors, and daily average levels of air pollutants on single-day lags (Lag0 to Lag7) in Shenzhen were collected. Low-level exposure was defined as the annual means of air pollutants below the levels of the Ambient Air Quality Standard (AAQS) in China (NO. GB3095-2012) and/or Global Air Quality Guidelines (AQG). A time-stratified case-crossover study design approach was used to evaluate the associations between exposure to air pollutants and incidence of the disease, univariate and multivariate logistic regression analysis to analyze the association between levels of air pollutants and hospitalizations for pulmonary sepsis in elderly patients.

RESULTS

Exposure to PM1(P = 0.007, Lag 2 day; P = 0.038, Lag6 day), PM2.5(P = 0.046, Lag2 day), PM10(P = 0.048, Lag4 day), and O3(P = 0.044, Lag6 day) was positively correlated with elevated risk of hospitalizations for pulmonary sepsis. In addition, logistic regression analysis revealed that exposure to PM1 (OR = 1.833, 95%CI:1.032 ~ 3.256, Lag6 day) and O3 (OR = 2.091, 95%CI:1.019 ~ 4.289, Lag6 day) were the independent risk factors of pulmonary sepsis in elderly patients.

CONCLUSION

Our results demonstrate that short-term low-level exposure to PM1 and O3 could elevate the risk of hospitalizations for pulmonary sepsis in elderly patients in Shenzhen, providing evidence for developing early warning and screening systems for pulmonary sepsis.

The modification of meteorological factors on the relationship between air pollution and periodontal diseases: an exploration based on different interaction strategies

We aimed to characterize the association between air pollutants exposure and periodontal diseases outpatient visits and to explore the interactions between ambient air pollutants and meteorological factors. The outpatient visits data of several large stomatological and general hospitals in Hefei during 2015-2020 were collected to explore the relationship between daily air pollutants exposure and periodontal diseases by combining Poisson's generalized linear model (GLMs) and distributed lag nonlinear model (DLNMs). Subgroup analysis was performed to identify the vulnerability of different populations to air pollutants exposure. The interaction between air pollutants and meteorological factors was verified in both multiplicative and additive interaction models. An interquartile range (IQR) increased in nitrogen dioxide (NO2) concentration was associated with the greatest lag-specific relative risk (RR) of gingivitis at lag 3 days (RR = 1.087, 95% CI 1.008-1.173). Fine particulate matter (PM2.5) exposure also increased the risk of periodontitis at the day of exposure (RR = 1.049, 95% CI 1.004-1.096). Elderly patients with gingivitis and periodontitis were both vulnerable to PM2.5 exposure. The interaction analyses showed that exposure to high levels of NO2 at low temperatures was related to an increased risk of gingivitis, while exposure to high levels of NO2 and PM2.5 may also increase the risk of gingivitis and periodontitis in the high-humidity environment, respectively. This study supported that NO2 and PM2.5 exposure increased the risk of gingivitis and periodontitis outpatient visits, respectively. Besides, the adverse effects of air pollutants exposure on periodontal diseases may vary depending on ambient temperature and humidity.

Effects of Ambient O3 on Respiratory Mortality, Especially the Combined Effects of PM2.5 and O3

BACKGROUND

In China, the increasing concentration of ozone (O3) has emerged as a significant air pollution issue, leading to adverse effects on public health, particularly the respiratory system. Despite the progress made in managing air pollution in China, it is crucial to address the problem of environmental O3 pollution at present.

METHODS

The connection between O3 exposure and respiratory mortality in Shenyang, China, from 2014 to 2018 was analyzed by a time-series generalized additive regression model (GAM) with quasi-Poisson regression. Additionally, the potential combined effects of fine particulate matter (PM2.5) and O3 were investigated using the synergy index (SI).

RESULTS

Our findings indicate that each 10 μg/m3 increase in O3 at lag 2 days was associated with a maximum relative risk (RR) of 1.0150 (95% CI: 1.0098-1.0202) for respiratory mortality in the total population. For individuals aged ≥55 years, unmarried individuals, those engaged in indoor occupations, and those with low educational attainment, each 10 μg/m3 increase in O3 at lag 07 days was linked to RR values of 1.0301 (95% CI: 1.0187-1.0417), 1.0437 (95% CI: 1.0266-1.0610), 1.0317 (95% CI: 1.0186-1.0450), and 1.0346 (95% CI: 1.0222-1.0471), respectively. Importantly, we discovered a synergistic effect of PM2.5 and O3, resulting in an SI of 2.372 on the occurrence of respiratory mortality.

CONCLUSIONS

This study confirmed a positive association between O3 exposure and respiratory mortality. Furthermore, it highlighted the interaction between O3 and PM2.5 in exacerbating respiratory deaths.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Short-term exposure to ambient fine particulate pollution aggravates ventilator-associated pneumonia in pediatric intensive care patients undergoing cardiovascular surgeries

BACKGROUND

Ambient air pollutants can be hazardous to human health, especially for vulnerable children. The impact of ambient air pollutant exposure before and during intensive care unit (ICU) stays on the development of ventilator-associated pneumonia (VAP) in critically ill children has not been established. We aimed to determine the correlations between short-term exposures to ambient fine particulate matter (PM_2.5) and VAP in pediatric cardiac surgery patients in the ICU, and explore the effect of delayed exposure.

METHODS

The medical record of 1755 child patients requiring artificial ventilation in the ICU between December 2013 to December 2020, were analyzed. The daily average concentrations of particulate matters (PM_2.5 and PM₁₀), sulfur dioxide (SO₂), and ozone (O₃) were calculated from public data. Interactions between these pollutants and VAP were simulated with the distributed lag non-linear model.

RESULTS

Three hundred forty-eight cases (19.829%) of VAP were identified in this study, while the average concentrations of PM_2.5, PM₁₀, O₃ and SO₂ were 58, 118, 98 and 26 μg/m³, respectively. Exposure to increased levels of PM_2.5 two days prior (lag 2-day) to VAP diagnosis is significantly correlated with an enhanced risk for VAP development. Even a slight increase of 10 μg/m³ in PM_2.5 can translate to a 5.4% increase in VAP incidence (95% CI: 1.4%-9.5%) while the VAP incidence increased to 11.1% (95%CI: 4.5-19.5%) when PM_2.5 concentration is well below the National Ambient Air Quality standard (NAAQS) of 50 μg/m³. The association was more pronounced in those aged below 3-months, with low body mass index or suffered from pulmonary arterial hypertension.

CONCLUSION

Short-term PM_2.5 exposure is a significant risk for development of VAP in pediatric patients. This risk is present even with PM_2.5 levels below the NAAQS. Ambient PM_2.5 may represent a previously unrecognized risk factor for pneumonia and the current environmental pollution standards need to be reevaluated to consider susceptible populations.

TRIAL REGISTRATION

The trial was registered with the National Clinical Trial Center: The correlation between ambient air pollution and the complications in ICU underwent cardiac surgery.

TRIAL REGISTRATION NUMBER

ChiCTR2000030507. Date of registration: March 5, 2020. URL of trial registry record: http://www.chictr.org.cn/index.aspx .

Spatial characterization of HCHO and reapportionment of its secondary sources considering photochemical loss in Taiyuan, China

Formaldehyde (HCHO) plays an important role in atmospheric ozone (O₃) formation. To accurately identify the sources of HCHO, carbonyls and volatile organic compounds (VOCs) were measured at three urban sites (Taoyuan, TY-U; Jinyuan, JY-U; Xiaodian, XD-U) and a suburban site (Shanglan, SL-B) in Taiyuan during a high O₃ period (from July 20 to August 3, 2020). The average mixing ratio of HCHO at XD-U (8.1 ± 2.8 ppbv) was comparable to those at TY-U (7.4 ± 2.1 ppbv) and JY-U (7.0 ± 2.3 ppbv) but higher (p < 0.01) than that at SL-B (4.9 ± 2.3 ppbv). HCHO contributed to 54.3-59.9 % of the total ozone formation potentials (OFPs) of non-methane hydrocarbons (NMHCs) at four sites. The diurnal variation of HCHO concentrations reached a peak value at 12:00-15:00, which may be attributed to the strong photochemical reaction. To obtain more accurate source results of HCHO under the condition of photochemical loss, the initial concentrations of NMHCs were estimated based on photochemical age parameterization and incorporated into the positive matrix factorization (PMF) model (termed IC-PMF). According to the IC-PMF results, secondary formation (SF) contributed the most to HCHO at XD-U (35.6 %) and SL-B (25.1 %), whereas solvent usage (SU) (40.9 %) and coking sources (CS) (36.0 %) were the major sources at TY-U and JY-U, respectively. Compared to the IC-PMF, the conventional PMF analysis based on the observed data underestimated the contributions of SU (100.5-154.2 %) and biogenic sources (BS) (28.5-324.7 %). Further reapportionment of secondary HCHO by multiple linear regression indicated that SU dominated the sources of HCHO at SL-B (28.3 %) and TY-U (41.7 %), while industrial emissions (IE) and CS contributed the most to XD-U (26.6 %) and JY-U (43.0 %) in Taiyuan from north to south, respectively.

Estimation of near-surface ozone concentration and analysis of main weather situation in China based on machine learning model and Himawari-8 TOAR data

Ozone (O₃) is an important greenhouse gas in the atmosphere. Stratospheric ozone protects human beings, but high near-surface ozone concentrations threaten environment and human health. Owing to the uneven distribution of ground-monitoring stations and the low time resolution of polar orbiting satellites, it is difficult to accurately evaluate the refinement and synergistic pollution of near-surface ozone in China. Besides, atmospheric circulation patterns also affect ozone concentrations greatly. In this study, a new generation of geostationary satellite is used to estimate the hourly near-surface ozone concentration with a spatial resolution of 0.05°. First, the Pearson correlation coefficient and maximum information coefficient were used to study the correlation between the top of atmospheric radiation (TOAR) of Himawari-8 satellite and O₃ concentration; seven TOAR channels were selected. Second, based on an interpretable deep learning model, the hourly ozone concentration in China from September 2015 to August 2021 was obtained using the TOAR-O₃ model. Finally, the self-organizing map method was used to determine six major summer weather circulation patterns in China. The results showed that (1) the near-surface O₃ concentration can be accurately estimated; the R² (RMSE: μg/m³) values of the daily, monthly, and annual tenfold cross validation results were 0.91 (12.74), 0.97 (5.64), and 0.98 (1.75), respectively. The feature importance of the model showed that the temperature, TOAR, and boundary layer height contributed 38 %, 22 %, and 13 %, respectively. (2) The O₃ concentration showed obvious spatiotemporal difference and gradually increased from 10:00 to 15:00 (Beijing time) every day. In most areas of China, O₃ concentration had increased significantly. (3) The O₃ concentration in northern China was the highest under the circulation pattern of the Meiyu front over the Yangtze River Delta, while in southern China, it was the highest under the circulation pattern of the northeast cold vortex controlling most of China.

Ozone exposure and health risks of different age structures in major urban agglomerations in People's Republic of China from 2013 to 2018

High concentration of surface ozone (O₃) will cause health risks to people. In order to analyze the spatiotemporal characteristics of O₃ and assess O₃ exposure and health risks for different age groups in China, we applied multiple methods including standard deviation ellipse, spatial autocorrelation, and exposure-response functions. Results show that O₃ concentrations increased in 64.5% of areas in China from 2013 to 2018. The central plain urban agglomeration (CPU), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) witnessed the greatest incremental rates of O₃ by 16.7%, 14.3%, and 13.1%. Spatially, the trend of O₃ shows a significant positive autocorrelation, and high trend values primarily in central and east China. The proportion of the total population exposed to high O₃ (above 160 μg/m³) increased annually. Compared to 2013, the proportion of the young, adult, and old populations exposed to high O₃ increased to different extents in 2018 by 26.8%, 29.6%, and 27.2%, respectively. The extent of population exposure risk areas in China expanded in size, particularly in north and east China. The total premature respiratory mortalities attributable to long-term O₃ exposure in six urban agglomerations were about 177,000 in 2018 which has increased by 16.4% compared to that in 2013. Among different age groups, old people are more vulnerable to O₃ pollution, so we need to strengthen their relevant health protection of them.

Global attributed burden of death for air pollution: Demographic decomposition and birth cohort effect

BACKGROUND

To identify the high-risk pollutants and evolving patterns of attributed mortality burden, more detailed evidence is needed to examine the contribution of different air pollutants to death across the disease spectrum, particularly considering population change as well as the context of the era.

METHODS

We explored the evolving patterns of all-cause and disease-specific deaths attributed to overall air pollution and its main subcategories by using the estimated annual percentage change and additionally assessing the contribution of population growth and ageing to death burden using the decomposition method. Age-period-cohort model and Joinpoint analysis were used to evaluate birth cohort effects specific-disease death burden owing to high-risk air pollution subcategories.

FINDINGS

The number of deaths caused by air pollution increased by 2.62 %, which was driven by ambient particulate matter pollution and ambient ozone pollution, whereas household air pollution decreased. Population ageing contributed 28.88 % of the deaths increase change for air pollution. Compared with other subcategories, the age-standardized mortality rate (ASMR) attributed to ambient particulate matter pollution remained the heaviest attributed death burden, comprehensively considering of bivariate burden. In 2019, ischemic heart disease attributed to ambient particulate matter pollution exhibited the highest ASMR, which may be impacted by a rapid increase era from 1950 to 1980 birth cohort in woman and 1970 to 1990 birth cohort in man. Diabetes mellitus attributed to ambient particulate matter pollution showed the largest increase for ASMR, which was driven primarily by men born 1910-1975 and women born 1950-1975.Uzbekistan showed the highest ASMR for ischemic heart disease, with Equatorial Guinea showing the fastest increase for diabetes mellitus.

CONCLUSION

Priority intervention targets for air pollution and health should emphasize the susceptibility of the elderly population as well as the structural factors of the era, in particular sensitive diseases to the ambient particulate matter pollution.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Has the Risk of Outpatient Visits for Allergic Rhinitis, Related to Short-Term Exposure to Air Pollution, Changed over the Past Years in Beijing, China?

A number of studies have found associations between the short-term exposure to ambient air pollution and hospital admissions. However, little is known about the temporal variations in ambient air pollution associated with health exposure, especially in China. We evaluated whether the risks of allergic rhinitis (AR) outpatient visits from short-term exposure to air pollution varied over time (2014-2020) in Beijing, China. A quasi-Poisson generalized additive model was used to evaluate the relative risks (RRs) and 95% confidence intervals (CIs) associated with the pollutant concentrations during the entire study period and three specific periods. We also analyzed the temporal variations of the period-specific associations and tested the trend of change using the Mann-Kendall test. The concentration-response relationships for the specific periods were further investigated. The RRs (95%CI) for an interquartile range (IQR) increased in PM₁₀ (70 μg/m³) and CO (0.5 mg/m³) decreased from period 1 to period 3. However, The RRs (95%CI) of PM_2.5 (55 μg/m³), SO₂ (7 μg/m³) and NO₂ (27 μg/m³) increased from 1.015 (0.978, 1.054), 1.027 (1.009, 1.044) and 1.086 (1.037, 1.137) in period 1 to 1.069 (1.005, 1.135), 1.074 (1.003, 1.149) and 1.214 (1.149, 1.282) in period 3, respectively. A statistically significant temporal change and the stable effects were observed between the NO₂ exposure and AR visits over time. Despite a substantial reduction in ambient air pollution, the short-term effects on AR outpatient visits remained significant. Our findings provide a rationale for continued air pollution control efforts in the future to minimize air pollution and to protect the public.

Ozone modelling and mapping for risk assessment: An overview of different approaches for human and ecosystems health

Tropospheric ozone (O₃) is one of the most concernedair pollutants dueto its widespread impacts on land vegetated ecosystems and human health. Ozone is also the third greenhouse gas for radiative forcing. Consequently, it should be carefully and continuously monitored to estimate its potential adverse impacts especially inthose regions where concentrations are high. Continuous large-scale O₃ concentrations measurement is crucial but may be unfeasible because of economic and practical limitations; therefore, quantifying the real impact of O₃over large areas is currently an open challenge. Thus, one of the final objectives of O₃ modelling is to reproduce maps of continuous concentrations (both spatially and temporally) and risk assessment for human and ecosystem health. We here reviewedthe most relevant approaches used for O₃ modelling and mapping starting from the simplest geo-statistical approaches andincreasing in complexity up to simulations embedded into the global/regional circulation models and pro and cons of each mode are highlighted. The analysis showed that a simpler approach (mostly statistical models) is suitable for mappingO₃concentrationsat the local scale, where enough O₃concentration data are available. The associated error in mapping can be reduced by using more complex methodologies, based on co-variables. The models available at the regional or global level are used depending on the needed resolution and the domain where they are applied to. Increasing the resolution corresponds to an increase in the prediction but only up to a certain limit. However, with any approach, the ensemble models should be preferred.

Spatial variations and social determinants of life expectancy in China, 2005-2020: A population-based spatial panel modelling study

BACKGROUND

Social determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China.

METHODS

Provincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities.

FINDINGS

Nationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors.

INTERPRETATION

Spatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE.

FUNDING

National Key Research & Development Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

Nonlinear effect of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China: A time-series analysis

Many studies have illustrated adverse effects of short-term exposure to air pollution on human health, which usually assumes a linear exposure-response (E-R) function in the delineation of health effects due to air pollution. However, nonlinearity may exist in the association between air pollutant concentrations and health outcomes such as adult pneumonia hospital visits, and there is a research gap in understanding the nonlinearity. Here, we utilized both the distributed lag model (DLM) and nonlinear model (DLNM) to compare the linear and nonlinear impacts of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China. While both models show adverse effects of air pollutants on adult pneumonia hospital visits, the DLNM shows an attenuation of E-R curves at high concentrations. Moreover, the DLNM may reveal delayed health effects that may be missed in the DLM, e.g., ozone exposure and pneumonia hospital visits. With the stratified analysis of air pollutants on adult pneumonia hospital visits, both models consistently reveal that the influence of air pollutants is higher during the cold season than during the warm season. Nevertheless, they may behave differently in terms of other subgroups, such as age, gender and visit types. For instance, while no significant impact due to PM_2.5 in any of the subgroups abovementioned emerges based on DLM, the results from DLNM indicate statistically significant impacts for the subgroups of elderly, female and emergency department (ED) visits. With respect to adjustment by two-pollutants, PM₁₀ effect estimates for pneumonia hospital visits were the most robust in both DLM and DLNM, followed by NO₂ and SO₂ based on the DLNM. Considering the estimated health effects of air pollution relying on the assumed E-R functions, our results demonstrate that the traditional linear association assumptions may overlook some potential health risks.

Associations of air pollutants with pneumonia hospital admissions in Qingdao, China: a prospective cohort study

Studies about the pneumonia morbidity effects of various air pollution exposure are still limited in China. We aimed to explore the short-term effect of air pollutants exposure on pneumonia admission and identify the vulnerable groups in Qingdao, China. From January 2015 to October 2017, a prospective cohort involving 433,032 participants across 3 counties in Qingdao were enrolled in the study. Distributed lag nonlinear model (DLNM) was applied to assess the associations between air pollutants and pneumonia hospitalizations. There were 636 cases of pneumonia, with an annual incidence density of 54.33 per 100,000 person-years (95% CI: 50.11, 58.56). A 10 μg/m³ increment of sulfur dioxide (SO₂) distributed at a 4-week lag in Qingdao was associated with increased pneumonia hospitalizations, with a risk ratio of 2.10 (95% CI: 1.06, 4.13). Subgroup analyses indicate that PM ≤ 2.5 μm in aerodynamic diameter and SO₂ showed stronger effects on pneumonia in females than males, whereas people in urban regions were more vulnerable to nitrogen dioxide and ozone (O₃) than the others. We also observed distinct acute effects and harvesting effects of SO₂ and O₃ on pneumonia in urban areas. Strategies should be taken to further reduce levels of ambient PM_2.5, SO₂, and O₃.

Short-term exposure to ambient air pollution and pneumonia hospital admission among patients with COPD: a time-stratified case-crossover study

Background

Pneumonia is a major contributor to hospital admission for patients with chronic obstructive pulmonary disease (COPD). However, evidence for acute effects of ambient air pollution exposure on pneumonia hospital admission among patients with COPD is scarce. We aimed to examine the association between short-term exposure to ambient air pollution and pneumonia hospital admission among patients with COPD.

Methods

We enrolled COPD cases aged ≥ 60 years old and further filtered those who were admitted into hospitals from pneumonia during 2016–2019 in Guangdong province, China for main analysis. A time-stratified case-crossover design was applied to investigate the association and conditional logistic regression model was used for data analysis. We performed inverse distance weighting method to estimate daily individual-level exposure on particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) based on personal residential addresses.

Results

We included 6473 pneumonia hospital admissions during the study period. Each interquartile range (IQR) increase in PM_2.5 (lag 2; IQR, 22.1 μg/m³), SO₂ (lag 03; IQR, 4.2 μg/m³), NO₂ (lag 03; IQR, 21.4 μg/m³), and O₃ (lag 04; IQR, 57.9 μg/m³) was associated with an odds ratio in pneumonia hospital admission of 1.043 (95% CI: 1.004–1.083), 1.081 (95% CI: 1.026–1.140), 1.045 (95% CI: 1.005–1.088), and 1.080 (95% CI: 1.018–1.147), respectively. Non-linear trends for PM_2.5, PM₁₀, and SO₂ were observed in the study. Sex, age at hospital admission, and season at hospital admission did not modify the associations.

Conclusions

We found significantly positive associations of short-term exposure to PM_2.5, SO₂, NO₂, and O₃ with pneumonia hospital admission among COPD patients. It provides new insight for comprehensive pneumonia prevention and treatment among COPD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-01989-9.

Modeling Air Pollution Health Risk for Environmental Management of an Internationally Important Site: The Salt Range (Kallar Kahar), Pakistan

This study aimed to assess the health effects of emissions released by cement industries and allied activities, such as mining and transportation, in the salt range area of district Chakwal, Pakistan. DISPER was used to estimate dispersion and contribution of source emission by cement industries and allied activities to surface accumulation of selected pollutants (PM2.5, PM10, NOx, and O3). To assess the long-term effects of pollutants on human health within the radius of 500 m to 3 km, Air Q+ software was used, which was designed by the World Health Organization (WHO). One-year average monitoring data of selected pollutants, coordinates, health data, and population data were used as input data for the model. Data was collected on lung cancer mortality among different age groups (25+ and 30+), infant post-neonatal mortality, mortality due to respiratory disease, and all-cause mortality due to PM2.5 and NO2. Results showed that PM2.5 with the year-long concentration of 27.3 µg/m3 contributes a 9.9% attributable proportion (AP) to lung cancer mortality in adults aged 25+, and 13.8% AP in adults age 30+. Baseline incidence is 44.25% per 100,000 population. PM10 with the year-long concentration of 57.4 µg/m3 contributes 16.96% AP to infant post-neonatal mortality and baseline incidence is 53.86% per 1000 live births in the country. NO2 with the year-long concentration of 14.33 µg/m3 contributes 1.73% AP to all-cause mortality. Results obtained by a simulated 10% reduction in pollutant concentration showed that proper mitigation measures for reduction of pollutants’ concentration should be applied to decrease the rate of mortalities and morbidities. Furthermore, the study showed that PM2.5 and PM10 are significantly impacting the human health in the nearby villages, even after mitigation measures were taken by the selected cement industries. The study provides a roadmap to policymakers and stakeholders for environmental and health risk management in the area.

A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology

Estimating ground-level ozone concentrations is crucial to study the adverse health effects of ozone exposure and better understand the impacts of ground-level ozone on biodiversity and vegetation. However, few studies have attempted to use satellite retrieved ozone as an indicator given their low sensitivity in the boundary layer. Using the Troposphere Monitoring Instrument (TROPOMI)'s total ozone column together with the ozone profile information retrieved by the Ozone Monitoring Instrument (OMI), as TROPOMI ozone profile product has not been released, we developed a machine learning model to estimate daily maximum 8-hour average ground-level ozone concentration at 10 km spatial resolution in California. In addition to satellite parameters, we included meteorological fields from the High-Resolution Rapid Refresh (HRRR) system at 3 km resolution and land-use information as predictors. Our model achieved an overall 10-fold cross-validation (CV) R² of 0.84 with root mean square error (RMSE) of 0.0059 ppm, indicating a good agreement between model predictions and observations. Model predictions showed that the suburb of Los Angeles Metropolitan area had the highest ozone levels, while the Bay Area and the Pacific coast had the lowest. High ozone levels are also seen in Southern California and along the east side of the Central Valley. TROPOMI data improved the estimate of extreme values when compared to a similar model without it. Our study demonstrates the feasibility and value of using TROPOMI data in the spatiotemporal characterization of ground-level ozone concentration.

Age-specific effects of ozone on pneumonia in Korean children and adolescents: A nationwide time-series study

OBJECTIVES

The aim of this study was to estimate the age-specific effects of 8-hour maximum ozone levels on pneumonia in children and adolescents.

METHODS

We performed quasi-Poisson regression analyses for individuals of 0-4 years, 5-9 years, 10-14 years, and 15-19 years of age using nationwide time-series data from the Korea (2011-2015). We constructed distributed lag linear models employing a generalized difference-in-differences method and controlling for other air pollutants.

RESULTS

A 10.0-parts per billion increase in 8-hour maximum ozone levels was associated with a higher risk of hospital admissions due to pneumonia at 0-4 (relative risk [RR], 1.02; 95% confidence interval [CI], 1.01 to 1.03) and 5-9 years of age (RR, 1.06; 95% CI, 1.04 to 1.08), but not at 10-14 (RR, 1.01; 95% CI, 0.98 to 1.04) or 15-19 years of age (RR, 1.01; 95% CI, 0.97 to 1.06). The association between ozone and hospital admissions due to pneumonia was stronger in cool seasons (from November to April) than in warm seasons (from May to October), but was similar between boys and girls.

CONCLUSIONS

Short-term exposure to ozone was associated with a higher risk of pneumonia at 0-4 years and 5-9 years of age, but not at 10-14 years or 15-19 years of age. Our findings can help identify vulnerable periods, determine the target populations for public health interventions, and establish air pollution standards.

Association of ambient ozone with pneumonia hospital admissions in Hong Kong and Taipei: A tale of two Southeast Asian cities

Ozone (O₃) is a reactive oxidant exerting both inflammatory and oxidative damages to the respiratory system. With the ground-level O₃ progressively increasing in the past decade, the reevaluation of the pneumonia hospitalization risk from exposure to O₃ is of public health interest. We conducted an ecological time-series study to examine the city-specific association between short-term O₃ exposure and pneumonia hospitalizations in Hong Kong and Taipei, respectively. We linked the daily pneumonia hospitalization count to air pollution concentrations and weather conditions according to the date of admission during 2010-2017. We applied a generalized additive distributed lag model to examine the association while adjusting for time-varying covariates. Stratified analysis by age group and the potential harvesting effect of O₃ were evaluated. We observed the harvesting effects of O₃ on pneumonia hospitalizations in children in both cities and adults in Taipei. The short-term effect of O₃ lasted for around one week. An interquartile range (IQR) increment of daytime 8-hour mean concentration of O₃ distributed over 0-6 lag days in Hong Kong (42.4 μg/m³) was associated with a 7.04% (95% CI: 5.35-8.76%) increase in hospital admissions for elderly pneumonia, while the corresponding cumulative excess risk per IQR increment of O₃ in Taipei (38.7 μg/m³) was 3.41% (95% CI: 1.63-5.22%). Different O₃ metrics, varying degrees of freedom for filtering the temporal trend, and three-pollutant models supported the robustness of the associations. We concluded that short-term O₃ exposure was associated with pneumonia hospitalizations in the elderly population. Understanding the pneumonia hospitalization risk of O₃ will help to inform public health policies in the planning of ozone control strategies and intervention measures to prevent ozone-related pneumonia in vulnerable elderly populations.

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

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

Identification and classification of pneumonia disease using a deep learning-based intelligent computational framework

Pneumonia is one of the hazardous diseases that lead to life insecurity. It needs to be diagnosed at the initial stages to prevent a person from more damage and help them save their lives. Various techniques are used to identify pneumonia, including chest X-ray, blood culture, sputum culture, fluid sample, bronchoscopy, and pulse oximetry. Chest X-ray is the most widely used method to diagnose pneumonia and is considered one of the most reliable approaches. To analyse chest X-ray images accurately, an expert radiologist needs expertise and experience in the desired domain. However, human-assisted approaches have some drawbacks: expert availability, treatment cost, availability of diagnostic tools, etc. Hence, the need for an intelligent and automated system comes into place that operates on chest X-ray images and diagnoses pneumonia. The primary purpose of technology is to develop algorithms and tools that assist humans and make their lives easier. This study proposes a scalable and interpretable deep convolutional neural network (DCNN) to identify pneumonia using chest X-ray images. The proposed modified DCNN model first extracts useful features from the images and then classifies them into normal and pneumonia classes. The proposed system has been trained and tested on chest X-ray images dataset. Various performance metrics have been utilized to inspect the stability and efficacy of the proposed model. The experimental result shows that the proposed model's performance is greater compared to the other state-of-the-art methodologies used to identify pneumonia.

Impact of a long-term air pollution exposure on the case fatality rate of COVID-19 patients-A multicity study

Evidence in the literature suggests that air pollution exposure affects outcomes of patients with COVID-19. However, the extent of this effect requires further investigation. This study was designed to investigate the relationship between long-term exposure to air pollution and the case fatality rate (CFR) of patients with COVID-19. The data on air quality index (AQI), PM2.5, PM10, SO2 , NO2 , and O3 from 14 major cities in China in the past 5 years (2015-2020) were collected, and the CRF of COVID-19 patients in these cities was calculated. First, we investigated the correlation between CFR and long-term air quality indicators. Second, we examined the air pollutants affecting CFR and evaluated their predictive values. We found a positive correlation between the CFR and AQI (1, 3, and 5 years), PM2.5 (1, 3, and 5 years), and PM10 (1, 3, and 5 years). Further analysis indicated the more significant correlation for both AQI (3 and 5 years) and PM2.5 (1, 3, and 5 years) with CFR, and moderate predictive values for air pollution indicators such as AQI (1, 3, and 5 years) and PM2.5 (1, 3, and 5 years) for CFR. Our results indicate that long-term exposure to severe air pollution is associated with higher CFR of COVID-19 patients. Air pollutants such as PM2.5 may assist with the prediction of CFR for COVID-19 patients.

Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis

BACKGROUND

Conjunctivitis, one of the most common ocular surface diseases, can be caused by many contributors. However, the important role of air pollution has been inadequately evaluated, particularly in countries with poor air quality. This study aims to explore the possible association of short-term ambient nitrogen dioxide (NO₂) exposure with the risk of outpatient visits for conjunctivitis.

METHODS

A total of 43,462 conjunctivitis patients from January 1, 2014 to December 31, 2018 were identified from the Department of Ophthalmology of The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Such data were linked to the daily mean concentration of NO₂ at ten fixed air quality monitoring stations. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear regression model was employed to assess the association between NO₂ exposure and the risk of outpatient visits for conjunctivitis. Stratified analyses were also performed on the basis of gender, age group and season.

RESULTS

The association of NO₂ exposure with the risk of outpatient visits for conjunctivitis was statistically significant. In the single-day lags (lag 0 to lag 11) analysis, the largest effect estimates were observed at lag 0. In the moving average exposure lags (lag 0-1 to lag 0-11) analysis, the cumulative effects were stronger than the single-day lag effects. The stratified analyses suggested that the effect of NO₂ exposure was more pronounced in females and patients aged 19-65 years and in the cold season.

CONCLUSIONS

This study confirms the evidence that short-term NO₂ exposure is associated with an increased risk of conjunctivitis outpatient visits. Our research encourages individuals to avoid outdoor activities on severe air pollution days and the government is obliged to adopt more stringent environmental policies to alleviate the effects of air pollution on human health, particularly for individuals at risk of developing conjunctivitis.

Short-term exposure to air pollution and hospital admission for pneumonia: a systematic review and meta-analysis

BACKGROUND

Air pollution is a major issue that poses a health threat worldwide. Although several studies investigated the adverse effects of air pollution on various diseases, few have directly demonstrated the effects on pneumonia. Therefore, we performed a systematic review and meta-analysis on the associations between short-term exposure of air pollutants and hospital admission or emergency room (ER) visit for pneumonia.

METHODS

A literature search was performed using PubMed, Embase, and Web of Science up to April 10, 2020. Pooled estimates were calculated as % increase with 95% confidence intervals using a random-effects model. A sensitivity analysis using the leave-one-out method and subgroup analysis by region were performed.

RESULTS

A total of 21 studies were included in the analysis. Every 10 μg/m3 increment in PM2.5 and PM10 resulted in a 1.0% (95% CI: 0.5-1.5) and 0.4% (95% CI: 0.2-0.6) increase in hospital admission or ER visit for pneumonia, respectively. Every 1 ppm increase of CO and 10 ppb increase of NO2, SO2, and O3 was associated with 4.2% (95% CI: 0.6-7.9), 3.2% (95% CI: 1.3-5.1), 2.4% (95% CI: - 2.0-7.1), and 0.4% (95% CI: 0-0.8) increase in pneumonia-specific hospital admission or ER visit, respectively. Except for CO, the sensitivity analyses yielded similar results, demonstrating the robustness of the results. In a subgroup analysis by region, PM2.5 increased hospital admission or ER visit for pneumonia in East Asia but not in North America.

CONCLUSION

By combining the inconsistent findings of several studies, this study revealed the associations between short-term exposure of air pollutants and pneumonia-specific hospital admission or ER visit, especially for PM and NO2. Based on the results, stricter intervention policies regarding air pollution and programs for protecting human respiratory health should be implemented.

Robust Inferential Techniques Applied to the Analysis of the Tropospheric Ozone Concentration in an Urban Area

This paper analyzes 12 years of tropospheric ozone (O₃) concentration measurements using robust techniques. The measurements were taken at an air quality monitoring station called Belisario, which is in Quito, Ecuador; the data collection time period was 1 January 2008 to 31 December 2019, and the measurements were carried out using photometric O₃ analyzers. Here, the measurement results were used to build variables that represented hours, days, months, and years, and were then classified and categorized. The index of air quality (IAQ) of the city was used to make the classifications, and robust and nonrobust confidence intervals were used to make the categorizations. Furthermore, robust analysis methods were compared with classical methods, nonparametric methods, and bootstrap-based methods. The results showed that the analysis using robust methods is better than the analysis using nonrobust methods, which are not immune to the influence of extreme observations. Using all of the aforementioned methods, confidence intervals were used to both establish and quantify differences between categories of the groups of variables under study. In addition, the central tendency and variability of the O₃ concentration at Belisario station were exhaustively analyzed, concluding that said concentration was stable for years, highly variable for months and hours, and slightly changing between the days of the week. Additionally, according to the criteria established by the IAQ, it was shown that in Quito, the O₃ concentration levels during the study period were not harmful to human health.

Air Pollution and Emergency Hospital Admissions—Evidences from Lisbon Metropolitan Area, Portugal

The relevance of air pollution in the public health agenda has recently been reinforced—it is known that exposure to it has negative effects in the health of individuals, especially in big cities and metropolitan areas. In this article we observed the evolution of air pollutants (CO, NO, NO2, O3, PM10) emissions and we confront them with health vulnerabilities related to respiratory and circulatory diseases (all circulatory diseases, cardiac diseases, cerebrovascular disease, ischemic heart disease, all respiratory diseases, chronic lower respiratory diseases, acute upper respiratory infections). The study is supported in two databases, one of air pollutants and the other of emergency hospital admissions, in the 2005–2015 period, applied to the Lisbon Metropolitan Area. The analysis was conducted through Ordinary Least Squares (OLS) regression, while also using semi-elasticity to quantify associations. Results showed positive associations between air pollutants and admissions, tendentially higher in respiratory diseases, with CO and O3 having the highest number of associations, and the senior age group being the most impacted. We concluded that O3 is a good predictor for the under-15 age group and PM10 for the over-64 age group; also, there seems to exist a distinction between the urban city core and its suburban areas in air pollution and its relation to emergency hospital admissions.

Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China

The pandemic of coronavirus disease 2019 (COVID-19) resulted in a stringent lockdown in China to reduce the infection rate. We adopted a machine learning technique to analyze the air quality impacts of the COVID-19 lockdown from January to April 2020 for six megacities with different lockdown durations. Compared with the scenario without lockdowns, we estimated that the lockdown reduced ambient NO2 concentrations by 36-53% during the most restrictive periods, which involved Level-1 public health emergency response control actions. Several cities lifted the Level-1 control actions during February and March, and the avoided NO2 concentrations subsequently dropped below 10% in late April. Traffic analysis during the same periods in Beijing and Chengdu confirmed that traffic emission changes were a major factor in the substantial NO2 reduction, but they were also associated with increased O3 concentrations. The lockdown also reduced PM2.5 concentrations, although heavy pollution episodes occurred on certain days due to the enhanced formation of secondary aerosols in association with the increased atmospheric oxidizing capacity. We also observed that the changes in air pollution levels decreased as the lockdown was gradually eased in various cities.

Short-Term Exposure to Ambient Ozone and Outpatient Visits for Respiratory Diseases - 5 Cities, China, 2013-2015

What is already known about this topic?

Few studies have elucidated the relationships between ambient ozone and respiratory morbidity, especially in developing countries.

What is added by this report?

This study involved 5 cities in China with a wide variation in ozone concentrations and therefore could add credible evidence for the associations between short-term ozone exposure and increased respiratory morbidity.

What are the implications for public health practice?

The results could be used to better assess disease burden of short-term exposure to ozone and further guide policymaking for reducing ozone air pollution and improving public health.

Association of hospital admission for bronchiectasis with air pollution: A province-wide time-series study in southern China

The relation of acute fluctuations of air pollution to hospital admission for bronchiectasis remained uncertain, and large-scale studies were needed. We collected daily concentrations of particulate matter (PM), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and daily hospitalizations for bronchiectasis for 21 cities across Guangdong Province from 2013 through 2017. We examined their association using two-stage time-series analysis. Our analysis was stratified by specific sub-diagnosis, sex and age group to assess potential effect modifications. Relative risks of hospitalization for bronchiectasis were 1.060 (95%CI 1.014-1.108) for PM₁₀ at lag0-6, 1.067 (95%CI 1.020-1.116) for PM_2.5 at lag0-6, 1.038 (95%CI 1.005-1.073) for PM_coarse at lag0-6, 1.058 (95%CI 1.015-1.103) for SO₂ at lag0-4, 1.057 (95%CI 1.030-1.084) for NO₂ at lag0 and 1.055 (95%CI 1.025-1.085) for CO at lag0-6 per interquartile range increase of air pollution. Specifically, acute fluctuations of air pollution might be a risk factor for bronchiectasis patients with lower respiratory infection but not with hemoptysis. Patients aged ≥65 years, and female patients appeared to be particularly susceptible to air pollution. Acute fluctuations of air pollution, particularly PM may increase the risk of hospital admission for bronchiectasis exacerbations, especially for the patients complicated with lower respiratory infection. This study strengthens the importance of reducing adverse impact on respiratory health of air pollution to protect vulnerable populations.

Short term effects of air pollutants on hospital admissions for respiratory diseases among children: A multi-city time-series study in China

Evidence concerning short-term acute association between air pollutants and hospital admissions for respiratory diseases among children in a multi-city setting was quite limited. We conducted a time-series analysis to evaluate the association of six common air pollutants with hospital admissions for respiratory diseases among children aged 0-14 years in 4 cities (Guangzhou, Shanghai, Wuhan and Xining), China during 2013-2018. We used generalized additive models incorporating penalized smoothing splines and random-effect meta-analysis to calculate city-specific and pooled estimates, respectively. The exposure-response relationship curves were fitted using the cubic spline regression. Subgroup analyses by gender, age, season and disease subtype were also performed. A total of 183,036 respiratory diseases hospitalizations were recorded during the study period, and 94.1% of the cases were acute respiratory infections. Overall, we observed that increased levels of air pollutants except O₃, were significantly associated with increased hospital admissions for respiratory disease. Each 10 μg/m³ increase in PM_2.5, SO₂ and NO₂ at lag 07, PM₁₀ at lag 03 and per 1 mg/m³ increase in CO at lag 01 corresponded to increments of 1.19%, 3.58%, 2.23%, 0.51% and 6.10% in total hospitalizations, respectively. Generally, exposure-response relationships of PM_2.5 and SO₂ in Guangzhou, SO₂, NO₂ and CO in Wuhan, as well as SO₂ and NO₂ in Xining with respiratory disease hospitalizations were also found. Moreover, the adverse effects of these pollutants apart from PM_2.5 in certain cities remained significant even at exposure levels below the current Chinese Ambient Air Quality Standards (CAAQS) Grade II. Children aged 4-14 years appeared to be more vulnerable to the adverse effects of PM_2.5, SO₂ and NO₂. Furthermore, with the exception of O₃, the associations were stronger in cold season than in warm season. Short-term exposure to PM_2.5, SO₂, NO₂ and CO were associated, in dose-responsive manners, with increased risks of hospitalizations for childhood respiratory diseases, and adverse effects of air pollutants except PM_2.5 held even at exposure levels below the current CAAQS Grade II in certain cities.

Ambient ozone pollution and years of life lost: Association, effect modification, and additional life gain from a nationwide analysis in China

BACKGROUND

Ozone is one of the dominant air pollutants due to its impact on disease burden and increasing trend in concentration. However, evidence regarding short-term effect of ozone on years of life lost (YLL) is scarce.

METHODS

A national time-series study was conducted in 48 large Chinese cities from 2013 to 2017. Generalized additive model coupled with random effects model were used to estimate national-average associations of ozone with YLL. Potential modifiers and additional life gain due to avoidable YLL under certain scenario were also evaluated.

RESULTS

The average annual mean ozone concentration of these cities was 86.9 μg/m³. For 10 μg/m³ increase in 3-day moving average ozone concentration, we estimated 0.37% [95% confidence interval (CI): 0.29%, 0.46%] increase in YLL from nonaccidental causes, 0.38% (95% CI: 0.30%, 0.46%) increase in YLL from cardiovascular diseases, and 0.36% (95% CI: 0.16%, 0.56%) increase in YLL from respiratory diseases. Moreover, the associations were more evident in people with less education and in cities with lower carbon monoxide concentration or those located at north region with lower mean temperature. Finally, an estimated life of 0.055 (95% CI: 0.043, 0.068) years would be gained per deceased people if ozone concentration could fall to 100 μg/m³.

CONCLUSIONS

Our findings indicated robust associations between short-term exposure to ozone and YLL from nonaccidental causes and cardiopulmonary diseases. Relevant intervention design should take the heterogeneity of both individual- and city-level characteristics into account. Implementation of more stringent standard is beneficial for alleviating YLL caused by ozone.