Association of ambient air pollution with lengths of hospital stay for hanoi children with acute lower-respiratory infection, 2007-2016

Effect of ambient air pollution on hospital admission for respiratory diseases in Hanoi children during 2007-2019

Air pollution poses a threat to children's respiratory health. This study aims to quantify the association between short-term air pollution exposure and respiratory hospital admissions among children in Hanoi, Vietnam, and estimate the population-attributable burden using local data. A case-crossover analysis was conducted based on the individual records where each case is their own control. The health data was obtained from 13 hospitals in Hanoi and air pollution data was collected from four monitoring stations from 2007 to 2019. We used conditional logistic regression to estimate Percentage Change (PC) and 95% Confidence Interval (CI) in odd of hospital admissions per 10 μg/m3 increase in daily average particulate matter (e.g. PM1, PM2.5, PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), 8-h maximum Ozone and per 1000 μg/m3 increase in daily mean of Carbon Monoxide (CO). We also calculated the number and fraction of admissions attributed to air pollution in Hanoi by using the coefficient at lag 0. A 10 μg/m3 increase in the concentration of PM10, PM2.5, PM1, SO2, NO2, O3 8-h maximum and 1000 μg/m3 increase in CO concentration was associated with 0.6%, 1.2%, 1.4%, 0.8%, 1.6%, 0.3%, and 1.7% increase in odd of admission for all respiratory diseases among children under 16 years at lag 0-2. All PM metrics and NO2 are associated with childhood admission for pneumonia and bronchitis. Admissions due to asthma and upper respiratory diseases are related to increments in NO2 and CO. For attributable cases, PM2.5 concentrations in Hanoi exceeding the World Health Organization Air Quality Guidelines accounted for 1619 respiratory hospital admissions in Hanoi children in 2019. Our findings show that air pollution has a detrimental impact on the respiratory health of Hanoi children and there will be important health benefits from improved air quality management planning to reduce air pollution in Vietnam.

Benefits of Short-term Premature Mortality Reduction Attributed to PM2.5 Pollution: A Case Study in Long an Province, Vietnam

PM2.5 pollution exposure is the leading cause of disease burden globally, especially in low- and middle-income countries, including Vietnam. Therefore, economic damage in this context must be quantified. Long An province in the Southern Key Economic (SKE) region was selected as a research area. This study aimed to evaluate PM2.5-related human health effects causing early deaths attributable to respiratory, cardiovascular, and circulatory diseases in all ages and genders. Health end-points and health impact estimation, economic loss model, groups of PM2.5 concentration data, data of exposed population, data of baseline premature mortality rate, and data of health impact functions were used. Hourly PM2.5 concentration data sets were generated specifically using the coupled Weather Research and Forecasting Model (WRF)/Community Multiscale Air Quality Modelling System (CMAQ) models. Daily PM2.5 pollution levels considered mainly in the dry season (from January to April 2018) resulted in 12.9 (95% CI - 0.6; 18.7) all-cause premature deaths per 100,000 population, of which 7.8 (95% CI 1.1; 7.1), 1.5 (95% CI - 0.2; 3.1), and 3.6 (95% CI - 1.5; 8.5) were due to respiratory diseases (RDs; 60.54%), cardiovascular diseases (CVDs; 11.81%), and circulatory system diseases (CSDs; 27.65%) per 100,000 population, respectively. The total economic losses due to acute PM2.5 exposure-related premature mortality cases reached 62.0 (95% CI - 2.7; 89.6) billion VND, equivalent to 8.3 (95% CI - 0.4; 12.0) million USD. The study outcomes contributed remarkably to the generation and development of data sources for effectively managing ambient air quality in Long An.

Impacts of industrial production and air quality by remote sensing on nitrogen dioxide concentration and related effects: An econometric approach

The high concentration of nitrogen dioxide (NO2) is to blame for West Java's poor Air Quality Index (AQI). So, this study aims to determine the influence of industrial activity as reflected by the value of its imports and exports, wind speed, and ozone (O3) on the high concentration of tropospheric NO2. The method used is the econometric Vector Error Correction Model (VECM) approach to capture the existence of a short-term and long-term relationship between tropospheric NO2 and its predictor variables. The data used in this study is in the form of monthly time series data for the 2018-2022 period sourced from satellite images (Sentinel-5P and ECMWF Climate Reanalysis) and publications of the Central Bureau of Statistics (BPS-Statistics Indonesia). The results explained that, in the short-term, tropospheric NO2 and O3 influence each other as they would in a photochemical reaction. In the long-term, exports from the industrial sector and wind speed have a significant effect on the concentration of tropospheric NO2. The short-term effect occurs directly in the first month after the shock, while the long-term effect occurs in the second month after the shock. Wind gusts originating from industrial areas cause air conditions to be even more alarming because tropospheric NO2 pollutants spread throughout the region in West Java. Based on the coefficient correlation result, the high number of pneumonia cases is one of the impacts caused by air pollution.

Risk Factors for Respiratory Viral Infections: A Spotlight on Climate Change and Air Pollution

Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world's population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.

Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China

Ambient fine particulate matter (PM_2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM_2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM_2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM_2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49–15.18%), compared with 11.20% (95% CI: 8.34–14.13%) for daily mean and 9.73% (95% CI: 6.97–12.55%) for hourly peak. The associations between the three metrics of PM_2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM_2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM_2.5.

Impact of Particulate Matter on Hospitalizations for Respiratory Diseases and Related Economic Losses in Wuhan, China

Background

Prior studies have reported the effects of particulate matter (PM) on respiratory disease (RD) hospitalizations, but few have quantified PM-related economic loss in the central region of China. This investigation aimed to assess the impacts of PM pollution on the risk burden and economic loss of patients admitted with RD.

Methods

Daily cases of RD admitted to the hospital from 1 January 2015 to 31 December 2020 were collected from two class-A tertiary hospitals in Wuhan, China. Time series analysis incorporated with a generalized additive model (GAM) was adopted to assess the impacts of fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀) exposures on patients hospitalized with RD. Stratified analyses were performed to investigate underlying effect modification of RD risk by sex, age, and season. The cost of illness (COI) approach was applied to evaluate the related economic losses caused by PM.

Results

A total of 51,676 inpatients with a primary diagnosis of RD were included for the analysis. PM_2.5 and PM₁₀ exposures were associated with increased risks of hospitalizations for RD. Subgroup analysis demonstrated that men and children in the 0–14 years age group were more vulnerable to PM, and the adverse effects were promoted by low temperature in the cold season. A 152.4 million China Yuan (CNY) economic loss could be avoided if concentrations of PM_2.5 and PM₁₀ declined to 10 and 20 μg/m³, respectively.

Conclusions

PM_2.5 and PM₁₀ concentrations were positively associated with RD hospitalization. Men and children were more vulnerable to PM. Effective air pollution control measures can reduce hospitalizations significantly and save economic loss substantially.

Mortality Burden due to Exposure to Outdoor Fine Particulate Matter in Hanoi, Vietnam: Health Impact Assessment

Objective: This study reports the mortality burden due to PM_2.5 exposure among adults (age >25) living in Hanoi in 2017.

Methods: We applied a health impact assessment methodology with the global exposure mortality model and a PM_2.5 map with 3 × 3 km resolution derived from multiple data sources.

Results: The annual average PM_2.5 concentration for each grid ranged from 22.1 to 37.2 µg/m³. The district average concentration values ranged from 26.9 to 37.2 µg/m³, which means that none of the 30 districts had annual average values below the Vietnam Ambient National Standard of 25 µg/m³. Using the Vietnam Ambient National Standard as the reference standard, we estimated that 2,696 deaths (95% CI: 2,225 to 3,158) per year were attributable to exposure to elevated PM_2.5 concentrations in Hanoi. Using the Interim Target 4 value of 10 µg/m³ as the reference standard, the number of excess deaths attributable to elevated PM_2.5 exposure was 4,760 (95% CI: 3,958–5,534).

Conclusion: A significant proportion of deaths in Hanoi could be avoided by reducing air pollution concentrations to a level consistent with the Vietnam Ambient National Standard.

Large spatio-temporal variations of size-resolved particulate matter and volatile organic compounds in urban area with heavy traffic

A monitoring campaign, the first of this kind for a heavy traffic urban area of Vietnam, was conducted which generated nearly 200 daily filter samples of PM_2.5, PM₁₀, and black carbon (BC), 1300 online hourly PMx (PM₁₀, PM_2.5, and PM₁), 900 hourly/bi-hourly BTEX data, 700 h of traffic counts, and online meteorology records. PMx and BTEX levels show large horizontal gradients across this small urban area of 300 m width suggesting that the pollution data should be generated with sufficient spatial resolutions for assessment of the exposure and health effects. This paper focuses on analyzing PMx with reference to the previously published BTEX to provide a more complete picture of the traffic-related pollution in the area. Spatio-temporal variations of pollutants are analyzed in relation to traffic flows and fleet compositions, weekday-weekend effects, local and regional meteorology. PM₁₀ and BTEX levels had larger variations between the sites indicating their stronger associations with the traffic activities than the finer particles. Twenty-four-hour (24 h) PM_2.5 levels ranged between 19 and 191 µg/m³ with high PM₁/PM_2.5 ratios of above 0.8 at ambient site (AA) and above 0.7 at roadsides. Multivariate relationship analysis (PCA) for the bi-hourly datasets of meteorology, traffic flows, and pollutant levels indicated overwhelming influence of on-road traffic fleet compositions on the roadside pollutants levels. At AA, PCA results showed a complex interaction between local emissions, meteorological conditions, and regional/long-range transport. Higher pollution levels were associated with the airmass types having the continental origin and pathways.

Machine Learning Models for Predicting the Occurrence of Respiratory Diseases Using Climatic and Air-Pollution Factors

Objectives

Because climatic and air-pollution factors are known to influence the occurrence of respiratory diseases, we used these factors to develop machine learning models for predicting the occurrence of respiratory diseases.

Methods

We obtained the daily number of respiratory disease patients in Seoul. We used climatic and air-pollution factors to predict the daily number of patients treated for respiratory diseases per 10,000 inhabitants. We applied the relief-based feature selection algorithm to evaluate the importance of feature selection. We used the gradient boosting and Gaussian process regression (GPR) methods, respectively, to develop two different prediction models. We also employed the holdout cross-validation method, in which 75% of the data was used to train the model, and the remaining 25% was used to test the trained model. We determined the estimated number of respiratory disease patients by applying the developed prediction models to the test set. To evaluate the performance of each model, we calculated the coefficient of determination (R²) and the root mean square error (RMSE) between the original and estimated numbers of respiratory disease patients. We used the Shapley Additive exPlanations (SHAP) approach to interpret the estimated output of each machine learning model.

Results

Features with negative weights in the relief-based algorithm were excluded. When applying gradient boosting to unseen test data, R² and RMSE were 0.68 and 13.8, respectively. For GPR, the R² and RMSE were 0.67 and 13.9, respectively. SHAP analysis showed that reductions in average temperature, daylight duration, average humidity, sulfur dioxide (SO₂), total solar insolation amount, and temperature difference increased the number of respiratory disease patients, whereas increases in atmospheric pressure, carbon monoxide (CO), and particulate matter ≤2.5 μm in aerodynamic diameter (PM_2.5) increased the number of respiratory disease patients.

Conclusion

We successfully developed models for predicting the occurrence of respiratory diseases using climatic and air-pollution factors. These models could evolve into public warning systems.

Size-Specific Particulate Matter Associated With Acute Lower Respiratory Infection Outpatient Visits in Children: A Counterfactual Analysis in Guangzhou, China

The burden of lower respiratory infections is primarily evident in the developing countries. However, the association between size-specific particulate matter and acute lower respiratory infection (ALRI) outpatient visits in the developing countries has been less studied. We obtained data on ALRI outpatient visits (N = 105,639) from a tertiary hospital in Guangzhou, China between 2013 and 2019. Over-dispersed generalized additive Poisson models were employed to evaluate the excess risk (ER) associated with the size-specific particulate matter, such as inhalable particulate matter (PM₁₀), coarse particulate matter (PM_c), and fine particulate matter (PM_2.5). Counterfactual analyses were used to examine the potential percent reduction of ALRI outpatient visits if the levels of air pollution recommended by the WHO were followed. There were 35,310 pneumonia, 68,218 bronchiolitis, and 2,111 asthma outpatient visits included. Each 10 μg/m³ increase of 3-day moving averages of particulate matter was associated with a significant ER (95% CI) of outpatient visits of pneumonia (PM_2.5: 3.71% [2.91, 4.52%]; PM_c: 9.19% [6.94, 11.49%]; PM₁₀: 4.36% [3.21, 5.52%]), bronchiolitis (PM_2.5: 3.21% [2.49, 3.93%]; PM_c: 9.13% [7.09, 11.21%]; PM₁₀: 3.12% [2.10, 4.15%]), and asthma (PM_2.5: 3.45% [1.18, 5.78%]; PM_c: 11.69% [4.45, 19.43%]; PM₁₀: 3.33% [0.26, 6.49%]). The association between particulate matter and pneumonia outpatient visits was more evident in men patients and in the cold seasons. Counterfactual analyses showed that PM_2.5 was associated with a larger potential decline of ALRI outpatient visits compared with PM_c and PM₁₀ (pneumonia: 11.07%, 95% CI: [7.99, 14.30%]; bronchiolitis: 6.30% [4.17, 8.53%]; asthma: 8.14% [2.65, 14.33%]) if the air pollutants were diminished to the level of the reference guidelines. In conclusion, short-term exposures to PM_2.5, PM_c, and PM₁₀ are associated with ALRI outpatient visits, and PM_2.5 is associated with the highest potential decline in outpatient visits if it could be reduced to the levels recommended by the WHO.

Is micronucleus assay in oral exfoliated cells a suitable tool for biomonitoring children exposed to environmental pollutants? A systematic review

The aim of this review was to evaluate if micronucleus assay in oral exfoliated cells is a suitable tool for biomonitoring children exposed to environmental pollutants. Through the electronic databases PubMed/Medline, Scopus, and Web of Science, all published studies until April 2021 that examined the relationship between exposure to environmental pollutants and micronucleus frequency in oral cells were searched. All relevant articles using a combination of the following keywords-"children," "micronucleus," "oral cells," and "environmental pollution"-were considered. A total of 20 papers met the criteria for inclusion in the systematic review. The results regarding the cytogenetic damage induced by environmental pollutants are conflicting. Some authors have demonstrated that environmental pollution induces mutagenesis in oral cells while others did not. Following the parameters of the Project for Effective Public Health Practices (EPHPP) and after extensive reading of all the articles included, a total of 12 articles had moderate and strong scores and 8 had a classification considered weak. Taken together, this review was able to demonstrate the association between micronucleus frequency and exposure to environmental pollutants in oral exfoliated cells of children.

Trading quality for quantity? Evidence from patient level data in China

In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient's length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted.

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

Acute effects of ambient air pollution on clinic visits of college students for upper respiratory tract infection in Wuhan, China

Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM2.5), particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM2.5 (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM10 (0.61% (95%CI: 0.12, 1.11)) and O3 (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO2 (9.18% (95%CI: 3.27, 15.42)) and NO2 (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM10 and NO2 were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO2 after inclusion of O3 appeared to be the largest and the effects of NO2 were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM10 and O3, while females seemed more vulnerable to exposure to SO2 and NO2. This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO2 and NO2 were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.

Implication of excessive length of stay of asthma patient with heterogenous status attributed to air pollution

OBJECTIVE

Air pollution has potential risk on asthma patients, further prolongs the length of stay. However, it is unclear that the impact of air pollution on excessive length of stay (ELoS) of heterogeneous asthma patients. In this study, we proposed a K-Nearest Neighbor (KNN) embedded approach incorporating with patient status to analyze the impact of short-term air pollution on the ELoS of asthma patients.

METHODS

The KNN embedded approach includes two stages. Firstly, the KNN algorithm was employed to search for the most similar patient community and approximate kernel proxy of each index patient by Euclidean distance. Then, we built the differential fixed-effect linear model to estimate the risk of air pollution to the ELoS.

RESULTS

We analyzed 6563 asthma patients' medical insurance records in a large city of China from January to December in 2014. It was found that when the duration of exposure to air pollution (i.e., PM2.5, PM10, SO2, NO2, and CO) reaches around 4-5 days, the risk of increasing the ELoS becomes the largest. But only O3 shows the opposite effect. What's more, CO is the dominant risk to increase the ELoS. With a 1 mg/m3 increment of CO average concentration in 5 days, the ELoS will go up by 0.8157 day (95%CI:0.72,0.9114). Based on the kernel proxy in the top 1% similar patient community, the additional financial burden posed on each patient increases by RMB 488.6002 (95%CI:430.1962,547.0043) due to the ELoS.

CONCLUSIONS

The KNN embedded approach is an innovative method that takes into account the heterogeneous patient status, and effectively estimates the impact of air pollution on the ELoS. It is concluded that air pollution poses adverse effects and additional financial burdens on asthma patients. Heterogeneous patients should adopt different strategies in health management to reduce the risk of increasing the ELoS due to air pollution, and improve the efficiency of medical resource utilization.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40201-020-00584-8.

Ambient air pollution exposure and risk of chronic kidney disease: A systematic review of the literature and meta-analysis

Ambient air pollution has been identified as one of the leading causes of global burden of disease. The relationship between ambient air pollution exposure and risk of chronic kidney disease (CKD) has stimulated increasing scientific interest in the past few years. However, evidence from human epidemiological studies is still limited and inconsistent. We performed an updated systematic review and meta-analysis to clarify the potential association comprehensively. Selected electronic databases were searched for related English language studies until March 1, 2020 with a final follow-up in December 31, 2020. Risk of bias assessment for individual studies were assessed using the OHAT (Office of Health Assessment and Translation) risk-of-bias rating tool. Confidence rating and level-of-evidence conclusions were developed for bodies of evidence for a given ambient air pollutant. Summary effect estimates were calculated using random-effects meta-analyses when three or more studies are identified for the same air pollutant-CKD combination. A total of 13 studies were finally identified in our study. The meta-analytic estimates (ORs) for risk of CKD were 1.15 (95% CI: 1.07, 1.24) for each 10 μg/m³ increase in PM_2.5, 1.25 (95% CI: 1.11, 1.40) for each 10 μg/m³ increase in PM₁₀, 1.10 (95% CI: 1.03, 1.17) for each 10 ppb increase in NO₂, 1.06 (95% CI: 0.98, 1.15) for each 1 ppb increase in SO₂ and 1.04 (95% CI: 1.00, 1.08) for each 0.1 ppm increase in CO, respectively. The level of evidence was appraised as moderate for four of the five tested air pollutant-CKD combinations using an adaptation of the GRADE (Grading of Recommendations Assessment, Development and Evaluation) tool. In conclusion, this study suggests that certain ambient air pollutant exposure was significantly associated with an increased risk of CKD. Given the limitations, the results of this study should be interpreted with caution, and further well-designed epidemiological studies are needed to draw a definite evidence of a causal relationship.

Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant

Background

While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model.

Results

CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO₂) and ozone (O₃8h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO₂ + 0.0008 *O₃8h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor.

Conclusion

Low temperatures, wind speed, and SO₂ and high daily temperature changes, O₃8h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12919-021-00206-7.

Associations between acute exposure to ambient air pollution and length of stay for inpatients with ischemic heart disease: a multi-city analysis in central China

Ambient air pollution (AAP) has been widely associated with increased morbidity of ischemic heart disease (IHD). However, no prior studies have investigated the effects of AAP exposure on the length of stay (LOS) due to IHD. Hospital data during 2015-2017 were obtained from hospital information system in five cities of Hubei province, China. We collected daily mean concentrations of air pollutants, including PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO, and meteorological data during the same time period. Poisson regression was applied to estimate the acute impacts of AAP on the LOS of IHD inpatients. A total of 42,114 inpatients with primary diagnosis of IHD were included, 50.63% of which were chronic IHD inpatients. Annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO were 61.93 μg/m³, 95.47 μg/m³, 18.59 μg/m³, 35.87 μg/m³, 100.30 μg/m³, and 1.117 mg/m³, respectively. After adjusting for temperature, relative humidity, gender, age group, payment method, number of hospital beds, location of hospital, and surgery or not, exposures to PM_2.5, PM₁₀, SO₂, O₃, and CO were associated with increased LOS for all IHD patients in both single- and multi-pollutant models, and stronger associations were observed among chronic IHD patients. In addition, subgroup analyses demonstrated that males and the group aged 65+ years were more vulnerable to air pollution, and the adverse effects were also promoted by low temperature in cold season. This study provides the first investigation of the adverse effects of AAP on the LOS for IHD patients. In order to shorten the LOS of IHD, measures should be taken to strengthen the AAP management and protect the high-risk population.

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.

Effects of short-term ambient air pollution exposure on HPV infections: A five-year hospital-based study

Human papillomavirus (HPV) infections are common sexually-transmitted diseases among reproductive-aged women with increasing concern. Until now, there are no prior study about the association between HPV infections and ambient air pollution. This study aimed to explore the relationship between short-term exposure to ambient pollutants and daily outpatient visits for HPV infections in China. Data of daily outpatient visits for HPV infections were obtained from January 1, 2014 to December 31, 2018 (1826 days). Over-dispersed Poisson generalized additive models were applied by adjusting weather conditions and day of the week. We identified a total of 39,746 cases for HPV infections. A 10 μg/m³ increase of PM₁₀, PM_2.5, SO₂, and NO₂ or a 0.1 mg/m³ rise of CO in concurrent day (lag 0) concentrations was related to an elevation of 0.822% (95% Cl: 0.282%, 1.36%), 1.05% (95% Cl: 0.280%, 1.81%), 5.72% (95% Cl: 1.79%, 9.65%), 5.02% (95% Cl: 3.45%, 6.60%), and 2.40% (95% Cl: 1.43%, 3.37%) in daily outpatient-visits for HPV infections, respectively. The association was more significant in those women aged 41 or over. As for 10 μg/m³ increase of O₃, a -1.33% (95% Cl: -2.13%, -0.530%) change was observed on the lag 03 and such effects appeared to be more obvious in the aged 18-40 group. Our results provided the first evidence that short-term exposure to ambient pollutants was related to, which may be indirectly, the increased risk of HPV infections while O₃ may act as a "protective" factor.

Effects of air pollutants on the transmission and severity of respiratory viral infections

Particulate matter, sulfur dioxide, nitrogen oxides, ozone, carbon monoxide, volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) are among the outdoor air pollutants that are major factors in diseases, causing especially adverse respiratory effects in humans. On the other hand, the role of respiratory viruses in the pathogenesis of severe respiratory infections is an issue of great importance. The present literature review was aimed at assessing the potential effects of air pollutants on the transmission and severity of respiratory viral infections. We have reviewed the scientific literature regarding the association of outdoor air pollution and respiratory viruses on respiratory diseases. Evidence supports a clear association between air concentrations of some pollutants and human respiratory viruses interacting to adversely affect the respiratory system. Given the undoubted importance and topicality of the subject, we have paid special attention to the association between air pollutants and the transmission and severity of the effects caused by the coronavirus named SARS-CoV-2, which causes the COVID-19. Although to date, and by obvious reasons, the number of studies on this issue are still scarce, most results indicate that chronic exposure to air pollutants delays/complicates recovery of patients of COVID-19 and leads to more severe and lethal forms of this disease. This deserves immediate and in-depth experimental investigations.

Effects of short-term fine particulate matter exposure on acute respiratory infection in children

BACKGROUND

Previous studies on the association between fine particulate matter (PM_2.5) exposure and acute respiratory infection in children are scarce and present inconsistent results. We estimated the association between short-term PM_2.5 exposure and acute respiratory infection among children aged 0-4 years using a difference-in-differences approach.

METHODS

We used data on the daily PM_2.5 concentrations, hospital admissions for acute respiratory infection, and meteorological factors of the 15 regions in the Republic of Korea (2013-2015). To estimate the cumulative effects, we used a difference-in-differences approach generalized to multiple spatial units (regions) and time periods (day) with distributed lag non-linear models.

RESULTS

With PM_2.5 levels of 20.0 μg/m³ as a reference, PM_2.5 levels of 30.0 μg/m³ were positively associated with the risk of acute upper respiratory infection (relative risk (RR) = 1.048, 95% confidence interval (CI): 1.028, 1.069) and bronchitis or bronchiolitis (RR = 1.060, 95% CI: 1.038, 1.082) but not with the risk of acute lower respiratory infection and pneumonia. PM_2.5 levels of 40.0 μg/m³ were also positively associated with the risk of acute upper respiratory infection (RR = 1.083, 95% CI: 1.046, 1.122) and bronchitis or bronchiolitis (RR = 1.094, 95% CI: 1.054, 1.136).

CONCLUSIONS

We found the associations of short-term PM_2.5 exposure with acute upper respiratory infection and bronchitis or bronchiolitis among children aged 0-4 years. As causal inference methods can provide more convincing evidence of the effects of PM_2.5 levels on respiratory infections, public health policies and guidelines regarding PM_2.5 need to be strengthened accordingly.

Association between Ambient Air Pollution and Hospital Length of Stay among Children with Asthma in South Texas

Although hospital length of stay (LOS) has been identified as a proxy measure of healthcare expenditures in the United States, there are limited studies investigating the potentially important association between outdoor air pollution and LOS for pediatric asthma. This study aims to examine the effect of ambient air pollution on LOS among children with asthma in South Texas. It included retrospective data on 711 children aged 5–18 years old admitted for asthma to a pediatric tertiary care hospital in South Texas between 2010 and 2014. Air pollution data including particulate matter (PM_2.5) and ozone were collected from the U.S. Centers for Disease Control and Prevention. The multivariate binomial logistic regression analyses were performed to determine the association between each air pollutant and LOS, controlling for confounders. The regression models showed the increased ozone level was significantly associated with prolonged LOS in the single- and two-pollutant models (p < 0.05). Furthermore, in the age-stratified models, PM_2.5 was positively associated with LOS among children aged 5–11 years old (p < 0.05). In conclusion, this study revealed a concerning association between ambient air pollution and LOS for pediatric asthma in South Texas.

Impact of climate variability on length of stay in hospital for childhood pneumonia in rural Bangladesh

OBJECTIVES

Pneumonia is a significant contributor to mortality and morbidity in children aged <5 years, and it is also one of the leading causes of hospitalisation for children in this age group. This study assessed the association between climate variability, patient characteristics (i.e. age, sex, weight, parental education, socio-economic status) and length of stay (LOS) in hospital for childhood pneumonia and its economic impact on rural Bangladesh.

STUDY DESIGN

An ecological study design was used.

METHODS

Data on daily hospitalisation for pneumonia in children aged <5 years (including patient characteristics) and daily climate data (temperature and relative humidity) between 1st January 2012 and 31st December 2016 were obtained from the Matlab Hospital (the International Centre for Diarrhoeal Disease Research, Bangladesh) and the Bangladesh Meteorological Department, respectively. A generalised linear model with Poisson link was used to quantify the association between climate factors, patient characteristics and LOS in hospital.

RESULTS

The study showed that average temperature, temperature variation and humidity variation were positively associated with the LOS in hospital for pneumonia. A 1°C rise in average temperature and temperature variation during hospital stay increased the LOS in hospital by 1% (relative risk [RR]: 1.010, 95% confidence interval [CI]: 1.001-1.018) and 9.3% (RR: 1.093, 95% CI: 1.051-1.138), respectively. A 1% increase in humidity variation increased the LOS in hospital for pneumonia by 2.2% (RR: 1.022, 95% CI: 1.004-1.039). In terms of economic impact, for every 1° C temperature variation during the period of hospital stay, there is an addition of 0.81 USD/day/patient as a result of direct costs and 1.8 USD/day/patient for total costs. Annually, this results in an additional 443 USD for direct and 985 USD for total costs.

CONCLUSIONS

Climate variation appears to significantly contribute to the LOS in hospital for childhood pneumonia. These findings may help policymakers to develop effective disease management and prevention strategies.

Regional Variation of Hospitalization Rates for Asthma in Korea: Association with Ambient Carbon Monoxide and Health Care Supply

This study was performed to investigate the relationship between the hospitalization rate for asthma and the ambient carbon monoxide (CO) by examining regional variation of the hospitalization rates for asthma in Korea and its factors. The hospital inpatient claims for asthma were acquired from the National Health Insurance database in 2015. A multivariate linear regression was performed with the hospitalization rate for asthma as a dependent variable. The annual ambient concentration of CO showed a negative association with the hospitalization rates for asthma while that of sulfur dioxide showed a positive association. The number of primary care physicians showed a negative association with the hospitalization rates for asthma while the number of beds in hospitals with less than 300 beds showed a positive association. The negative association of the ambient concentration of CO with the hospitalization rates for asthma showed results upon further investigation.

Particulate air pollution in Ho Chi Minh city and risk of hospital admission for acute lower respiratory infection (ALRI) among young children

High levels of air pollutants in Vietnam, especially particulate matters including PM_2.5, can be important risk factors for respiratory diseases among children of the country. However, few studies on the effects of ambient air pollution on human health have been conducted in Vietnam so far. The aim of this study is to examine the association between PM_2.5 and hospital admission due to acute lower respiratory infection (ALRI) among children aged < 5 years old in Ho Chi Minh city, the largest city of Vietnam. Data relating PM_2.5 and hospital admission were collected from February 2016-December 2017 and a time series regression analysis was performed to examine the relationship between PM_2.5 and hospital admission including the delayed effect up to three days prior to the admission. We found that each 10 μg/m³ increase in PM_2.5 was associated with an increase of 3.51 (95%CI: 0.96-6.12) risk of ALRI admission among children. According to the analysis, male children are more sensitive to exposure to PM_2.5 than females, while children exposed to PM_2.5 are more likely to be infected with acute bronchiolitis than with pneumonia. The study demonstrated that young children in HCMC are at increased risk of ALRI admissions due to the high level of PM_2.5 concentration in the city's ambient air.

Associations between ambient air pollution and mortality from all causes, pneumonia, and congenital heart diseases among children aged under 5 years in Beijing, China: A population-based time series study

BACKGROUND

Previous studies have mainly focused on the associations between particulate matters and infant mortality. However, evidence regarding the associations between gaseous pollutants and mortality among children aged <5 years remains sparse.

OBJECTIVES

The aim of this study was to investigate the associations between ambient air pollution and death among children aged <5 years in Beijing, China, and explore the impact of age, gender and specific causes of death on these associations.

METHODS

Concentrations of ambient air pollution and the number of deaths among children aged <5 years in Beijing from January 2014 to September 2016 were extracted from authoritative electronic databases. The associations were estimated for a single-month lag from the current month up to the previous 5 months (lag0-lag5) and moving averages of the current and previous months (lag01-lag05) using generalized additive Poisson regression (adjusted for time trends, season, meteorological variables and holidays). Subgroup analyses related to age, gender and specific diseases were performed. Two-pollutant models were used to evaluate the possible role of single pollutants.

RESULTS

Sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and carbon monoxide (CO) demonstrated the strongest associations with death among children aged <5 years at lag0, and the estimates decreased or even turned negative with the increasing lag periods. For an interquartile range increase in SO₂, NO₂ and CO at lag0, the odds ratios (OR) were 1.332 (95% CI 1.152-1.539), 1.383 (95% CI 1.113-1.718) and 1.273 (95% CI 1.028-1.575). However, CO lost significance after adjusting for SO₂ and NO₂, and PM_2.5 gained significance (OR 1.548, 95% CI 1.061-2.258) after adjusting for PM₁₀. The ORs for SO₂ and NO₂ remained the most stable across all two-pollutant models. The associations for children aged 1-5 years were stronger than those reported for infants at lag0 but lower at the other lag months. The pollutant associations were stronger for congenital heart disease-related death than overall and pneumonia-related death. We did not find significant differences in terms of gender.

CONCLUSION

Exposure to air pollution may increase the incidence of death among children aged <5 years. SO₂ and NO₂ may be the most stable pollutants reflecting associations between air pollution and death, deserving further attention. Children with congenital heart diseases are more susceptible to air pollution. Therefore, it is urgent to implement the clean air targets established by WHO and reduce the exposure of children to air pollution.