Multi-city study on air pollution and hospital outpatient visits for asthma in China

High altitude air pollution and respiratory disease: Evaluating compounded exposure events and interactions

Today, air pollution remains a significant issue, particularly in high-altitude areas where its impact on respiratory disease remains incompletely explored. This study aims to investigate the association between various air pollutants and outpatient visits for respiratory disease in such regions, specifically focussing on Xining from 2016 to 2021. By analysing over 570,000 outpatient visits using a time-stratified case-crossover design and conditional logistic regression, we assessed the independent effects of pollutants like PM2.5, PM10, SO2, NO2, and CO, as well as their interactions. The evaluation of interactions employed measures such as relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). We also conducted a stratified analysis to identify potentially vulnerable populations. Our findings indicated that exposure to PM2.5, PM10, SO2, NO2, and CO significantly increased outpatient visits for respiratory disease, with odds ratios (ORs) of 2.40 % (95 % CI: 2.05 %, 2.74 %), 1.07 % (0.98 %, 1.16 %), 3.86 % (3.23 %, 4.49 %), 4.45 % (4.14 %, 4.77 %), and 6.37 % (5.70 %, 7.04 %), respectively. However, exposure to O3 did not show a significant association. We found significant interactions among PM2.5, SO2, NO2, and CO, where combined exposure further exacerbated the risk of respiratory diseases. For example, in the combination of PM2.5 and SO2, the REOI, AP, and S were 0.07 (95 % CI: 0.06, 0.09), 0.07 (0.06, 0.07), and 1.07 (1.05, 1.09), respectively. Additionally, elderly individuals and females were more sensitive to these pollutants, but no statistically significant interaction effects were observed between different age and gender groups. In conclusion, our study highlights the strong link between air pollution and respiratory disease in high-altitude areas, with combined pollutant exposure posing an even greater risk. It underscores the need for enhanced air quality monitoring and public awareness campaigns, particularly to protect vulnerable populations like the elderly and females.

The short-term association between environmental variables and daily pediatric asthma patient visits in Hangzhou, China: A time-series study

Background

To date, a large number of studies have shown correlations between environmental variables and pediatric asthma in short-term lag time. However, their results are inconsistent. Therefore, we aimed to evaluate the short-term impact of environmental variables on daily pediatric asthma patients' visits (DPAPV) in Hangzhou, China, and find the most important risk factor.

Methods

Generalized additive distribution lag non-linear model (GAM-DLNM) was applied to explore the effect of environmental variables on DPAPV in single- and multi-variable models in Hangzhou, China from 2014 to 2021. Then, risk factors of pediatric asthma were selected (p < 0.05 both in single- and multi-variable models) and used weighted quantile sum (WQS) regression model to evaluate their relative importance.

Results

There were 313,296 pediatric asthma patient records between 2014 and 2021. Both in single- and multi-variable models, PM2.5, PM10, and NO2 exhibited significant positive correlations in short-term lag time and these correlations reached their maximum in lag day 2 (RR = 1.00, 95%CI:1.00 to 1.01), lag day 2 (RR = 1.00, 95%CI:1.00 to 1.01), and lag day 3 (RR = 1.04, 95%CI:1.02 to1.05), respectively. The WQS index showed that NO2 had the greatest relative importance (weight over 70 %). The relative importance of NO2 increased with time passing. Males were more susceptible to the adverse effects of NO2.

Conclusion

PM2.5, PM10, and NO2 had significant adverse effects on pediatric asthma. Among them, NO2 presented the greatest and most important adverse effect on the disease. Therefore, parents could give priority to paying attention to NO2 to control children's asthma.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

The changing health effects of air pollution exposure for respiratory diseases: a multicity study during 2017-2022

BACKGROUND

Multifaceted SARS-CoV-2 interventions have modified exposure to air pollution and dynamics of respiratory diseases. Identifying the most vulnerable individuals requires effort to build a complete picture of the dynamic health effects of air pollution exposure, accounting for disparities across population subgroups.

METHODS

We use generalized additive model to assess the likely changes in the hospitalisation and mortality rate as a result of exposure to PM2.5 and O3 over the course of COVID-19 pandemic. We further disaggregate the population into detailed age categories and illustrate a shifting age profile of high-risk population groups. Additionally, we apply multivariable logistic regression to integrate demographic, socioeconomic and climatic characteristics with the pollution-related excess risk.

RESULTS

Overall, a total of 1,051,893 hospital admissions and 34,954 mortality for respiratory disease are recorded. The findings demonstrate a transition in the association between air pollutants and hospitalisation rates over time. For every 10 µg/m3 increase of PM2.5, the rate of hospital admission increased by 0.2% (95% CI: 0.1-0.7%) and 1.4% (1.0-1.7%) in the pre-pandemic and dynamic zero-COVID stage, respectively. Conversely, O3-related hospitalization rate would be increased by 0.7% (0.5-0.9%) in the pre-pandemic stage but lowered to 1.7% (1.5-1.9%) in the dynamic zero-COVID stage. Further assessment indicates a shift of high-risk people from children and young adolescents to the old, primarily the elevated hospitalization rates among the old people in Lianyungang (RR: 1.53, 95%CI: 1.46, 1.60) and Nantong (RR: 1.65, 95%CI: 1.57, 1.72) relative to those for children and young adolescents. Over the course of our study period, people with underlying diseases would have 26.5% (22.8-30.3%) and 12.7% (10.8-14.6%) higher odds of having longer hospitalisation and over 6 times higher odds of deaths after hospitalisation.

CONCLUSIONS

Our estimates provide the first comprehensive evidence on the dynamic pollution-health associations throughout the pandemic. The results suggest that age and underlying diseases collectively determines the disparities of pollution-related health effect across population subgroups, underscoring the urgency to identifying the most vulnerable individuals to air pollution.

Medium-term exposure to size-fractioned particulate matter and asthma exacerbations in China: A longitudinal study of asthmatics with poor medication adherence

BACKGROUND

Studies have shown that short- and long-term exposure to particulate matter (PM) can increase the risk of asthma morbidity and mortality. However, the effect of medium-term exposure remains unknown. We aim to examine the effect of medium-term exposure to size-fractioned PM on asthma exacerbations among asthmatics with poor medication adherence.

METHODS

We conducted a longitudinal study in China based on the National Mobile Asthma Management System Project that specifically and routinely followed asthma exacerbations in asthmatics with poor medication adherence from April 2017 to May 2019. High-resolution satellite remote-sensing data were used to estimate each participant's medium-term exposure (on average 90 days) to size-fractioned PM (PM1, PM2.5, and PM10) based on the residential address and the date of the follow-up when asthma exacerbations (e.g., hospitalizations and emergency room visits) occurred or the end of the follow-up. The Cox proportional hazards model was employed to examine the hazard ratio of asthma exacerbations associated with each PM after controlling for sex, age, BMI, education level, geographic region, and temperature.

RESULTS

Modelling results revealed nonlinear exposure-response associations of asthma exacerbations with medium-term exposure to PM1, PM2.5, and PM10. Specifically, for emergency room visits, we found an increased hazard ratio for PM1 above 22.8 µg/m3 (1.060, 95 % CI: 1.025-1.096, per 1 µg/m3 increase), PM2.5 above 38.2 µg/m3 (1.032, 95 % CI: 1.010-1.054), and PM10 above 78.6 µg/m3 (1.019, 95 % CI: 1.006-1.032). For hospitalizations, we also found an increased hazard ratio for PM1 above 20.3 µg/m3 (1.055, 95 % CI: 1.001-1.111) and PM2.5 above 39.2 µg/m3 (1.038, 95 % CI: 1.003-1.074). Furthermore, the effects of PM were greater for a longer exposure window (90-180 days) and among participants with a high BMI.

CONCLUSION

This study suggests that medium-term exposure to PM is associated with an increased risk of asthma exacerbations in asthmatics with poor medication adherence, with a higher risk from smaller PM.

Cohort profile: China undergraduate cohort for environmental health study

The China Undergraduate Cohort (CUC) is an ambispective cohort study with its major purpose to better understand the effects of lifetime environmental exposures on health outcomes. We recruited 5322 college students with an average age of 18.3 ± 0.7 years in China from August 23, 2019 to October 28, 2019. Follow-up surveys were conducted annually. The dataset comprises individual demographic data (e.g. age, sex, height, weight, birth date, race, home address, annual family income, contact information), health-related behavior data (smoking status, smoking cessation, passive smoking exposure, drinking habit, physical activity, dietary status), lifestyle data (physical exercise, dietary habit, length of time spent outdoors), disease history (respiratory disease history, cardiovascular disease history, urinary system disease history, etc.), mental health status data (sleep quality, self-reported stress, anxiety and depression symptoms), lung function and blood samples data. Preliminary results from our cohort have found the association between air pollution, summer heat and mercury exposure and lung function among young adults in China.

Investigation analysis of the acute asthma risk factor and phenotype based on relational analysis with outdoor air pollutants in Xi'an, China

Asthma is a common chronic heterogeneous disease. Outdoor air pollutants are an important cause of acute asthma. Until now, the association between the risk of acute asthma and outdoor air pollutants is unclear. And the relationship between the different phenotypes of asthma and outdoor air pollutants has not been reported. Thus, an analysis of the association between outdoor air pollutants and daily acute asthma inpatient and outpatient visits in Xi'an, China, from January 1 to December 31, 2018, was conducted. A total of 3395 people were included in the study. The statistical analysis and relational analysis based on the logistic regression were used for illustrating the relatedness of the acute asthma risk factor and phenotype with outdoor air pollutants, while the age, gender, pollen peak and non-pollen peak periods, high type 2 (T2) asthma and non-high T2 asthma were also stratified. Results showed that particulate matter with particle size below 10 μm and 2.5 μm (PM10 and PM2.5), sulfur dioxide(SO2), nitrogen dioxide(NO2), and carbon monoxide(CO) increase the risk of acute asthma and that air pollutants have a lagged effect on asthma patients. PM10, NO2, CO, and Ozone (O3) are associated with an increased risk of acute attacks of high T2 asthma. PM10, PM2.5, SO2, NO2 and CO are associated with an increased risk of acute asthma in males of 0-16 years old. PM10 and PM2.5 are more harmful to asthma patients with abnormal lung function.

[Effect of Short-Term Exposure to Air Pollutants on Hospital Admissions for End-Stage Renal Disease Patients Undergoing Hemodialysis]

Objective

To evaluate the association between short-term exposure to air pollutants of end-stage renal disease (ESRD) patients on maintenance hemodialysis and the number of daily hospital admissions.

Methods

The data on hospitalizations were obtained from the database of the municipal Urban Employees' Basic Medical Insurance and Urban Residents' Basic Medical Insurance of a city in Southwest China. Single and multiple pollutant generalized additive models were utilized to estimate the effect of air pollutants (CO, NO2, O3, PM10, PM2.5, and SO2) on patient admissions after the lag time of different numbers of days. In addition, subgroup analyses stratified by sex, age, PM2.5 and PM10 concentration thresholds, seasonality, and comorbidity status for cardiovascular diseases and hypertension were conducted.

Results

In the single pollutant models, the pollutants significantly associated with patient admissions and the corresponding lag time of the strongest association were as follows, every time CO increased by 0.1 mg/m3, there was a 2.39% increase (95% confidence interval [CI]: 0.96%-3.83%) in patient admissions after 7 days of lag time; every time NO2, O3, PM2.5, PM10, and SO2 increased by 10 μg/m3, patient admissions increased by 4.02% (95% CI: 1.21%-6.91%) after 7 days of lag time, 3.57% (95% CI: 0.78%-6.44%) after 0-4 days of lag time, 2.00% (95% CI: 1.07%-2.93%) after 6 days of lag time, 1.19% (95% CI: 0.51%-1.88%) after 7 days of lag time, and 8.37% (95% CI: 3.08%-13.93%) after 7 days of lag time, respectively. In the multiple pollutant model, every time O3 and PM2.5 increased by 10 μg/m3, there was an increase of 3.18% (95% CI: 0.34%-6.09%) in daily patient admissions after 0-4 days of lag time and an increase of 1.85% (95% CI: 0.44%-3.28%) after 7 days of lag time. Furthermore, subgroup analyses showed that seasonality, the severity of air pollution, and patients' comorbidities might be the effect modifiers for the association between ambient air pollution and hospital admissions in ESRD patients receiving maintenance hemodialysis.

Conclusion

Air pollution is closely associated with hospital admissions in ESRD patients undergoing maintenance hemodialysis and the strength of this association varies according to seasonality, the severity of air pollution, and patients' status of comorbidities.

Impact of air pollution changes and meteorology on asthma outpatient visits in a megacity in North China Plain

The effects of air pollution and meteorology on asthma is less studied in North China Plain. In the last decade, air quality in this region is markedly mitigated. This study compared the short-term effects of air pollutants on daily asthma outpatient visits (AOV) within different sex and age groups from 2014 to 2016 and 2017-2019 in Tianjin, with the application of distributed lag nonlinear model. Moreover, relative humidity (RH) and temperature as well as the synergistic impact with air pollutants were assessed. Air pollutants-associated risk with linear (different reference values were used) and non-linear assumptions were compared. In 2014-2016, PM10 and PM2.5 exhibited a larger impact on AOV, with the corresponding cumulative excess risks (ER) for every 10 μg/m3 increase at 1.04 % (95%CI:0.67-1.40 %, similarly hereafter) and 0.79 % (0.35-1.23 %), as well as increased to 43 % (26-63 %) and 20 % (10-31 %) at severe pollution. In 2017-2019, NO2 and MDA8 O3 exhibited a larger impact on AOV, with a cumulative ER for every 10 μg/m3 increase at 1.0 (0.63-1.4 %) and 0.36 % (0.15-0.57 %), with corresponding values of 7.9 % (4.8-11 %) and 5.6 % (2.3-9.0 %), at severe pollution. SO2 associated risk was only significant from 2014 to 2016. Cold effect, including extremely low temperature exposure and sharp temperature drop could generate a pronounced increase in AOV at 9.6 % (3.8-16 %) and 24 % (9.1-41 %), respectively. Moderate low temperature combined with air pollutants can enhance AOV during winter. Higher temperature in spring and autumn could trigger asthma by increasing pollen levels. Low RH resulted in AOV increase by 4.6 % (2.4-6.9), while higher RH generated AOV increase by 3.4 % (1.6-5.3). Females, children, and older adults tended to have a higher risk for air pollution, non-optimum temperature, and RH. As air pollution-associated risks on AOV tends to be weaker due to air quality improvement in recent years, the impact of extreme meteorological condition amidst climate change on asthma visits warrants further attention.

The influence of PM2.5 exposure duration and concentration on outpatient visits of urban hospital in a typical heavy industrial city

To explain the duration and dose effects of pollutant exposure on public health and provide scientific data for air pollution prevention and control and disease prevention by examining the influence of PM2.5 concentration and exposure duration on daily outpatient visits among patients with cardiovascular, cerebrovascular, and respiratory diseases in a typical heavy industrial city in China. Daily outpatient data on cardiovascular, cerebrovascular, and respiratory diseases and regional PM2.5 exposure duration and concentration were collected from a provincial hospital in Taiyuan, China, from 2016 to 2021. The correlations of numeric variables were analyzed using the Pearson correlation method. A generalized additive model (GAMs) was also established to investigate the effects of PM2.5 concentration and exposure duration on outpatient visits. Correlation analysis showed that the outpatient visits in Taiyuan was significantly correlated with the PM2.5 concentration and exposure duration. The longer the exposure time of PM2.5 pollution, the stronger the correlation of PM2.5 with outpatient visits showed. Cardiovascular outpatient visits were extremely significant related with medium to long-term exposure of PM2.5 (exposure with more than 30 days) (p < 0.001). In addition, outpatient visits of cerebrovascular and respiratory disease were extremely significant correlated with PM2.5 (exposures within 0-360 days) (p < 0.001). The results of GAMs showed the linear or the nonlinear relationships between outpatient visits and exposure of PM2.5. Among the linear relationships, when average concentration of PM2.5 (exposure within less than 15 days) increased by 1 mg/m3, the cardiovascular outpatient visits increased most dramatically (by about 440 people). For nonlinear relationships, when the average PM2.5 concentration (exposure with over 30 days or more) increased by 1 mg/m3, the most dramatic increase occurred in cardiovascular outpatient visits (with a maximum increase of 7000), followed by cerebrovascular outpatient visits (with a maximum increase of 1200), and respiratory outpatient visits (with a maximum increase of 250). The GAMs also revealed a dose effect in the relationship between outpatient visits and PM2.5 exposure. In moderately polluted air (based on air quality standards of China, GB3095-2012), when the average concentration of PM2.5 increased by 1 mg/m3, the cardiovascular outpatient visits increased the most (by 1200 people), followed by cerebrovascular outpatient visits (by 200 people) and respiratory outpatient visits (by 20 people). We concluded that outpatient visits in cardiovascular, cerebrovascular, and respiratory disease are closely correlated with the concentration and exposure duration of air pollution. There is a linear relationship between short-term air pollution exposure (exposure within less than 15 days) and outpatient visits. As PM2.5 concentration increases, cardiovascular outpatient visits increase gradually, with its growth trend exceeding that of cerebrovascular and respiratory disease. There is a nonlinear relationship between medium and long-term air pollution exposure (exposure with more than 30 days) and outpatient visits, with cardiovascular and cerebrovascular outpatient visits showed a nonlinear but overall upward trend when the atmosphere is moderately polluted.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States

Background

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health.

Methods

We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season.

Results

Short-term exposure increases of 1 μg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)].

Conclusions

Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods.

Classification

environmental public health, fine particulate matter air pollution, respiratory infections.

Regional heterogeneity in short-term associations of meteorological factors, air pollution, and asthma hospitalizations in Guangxi, China

OBJECTIVES

This study aimed to identify and evaluate the short-term and lag effects of environmental factors on asthma hospitalizations in different regions.

STUDY DESIGN

The ecological study on asthma is performed in three regions of Guangxi, China, that are distinctly different in geography and climate.

METHODS

We used distributed lag non-linear models to investigate the exposure-response-lag relationship between meteorological factors, air pollutants, and asthma hospital admissions across the three regions during 2015 (January 1 to December 31).

RESULTS

Cold was an important meteorological factor affecting asthma. At lag 0, the relative risk (RR; 23°C as reference) of cold in the Northwest, Northeast, and South was 1.10 (10°C), 1.14 (8°C), and 1.30 (11°C), respectively. NO2 was identified as the most important air pollutant affecting asthma. The RR of asthma hospitalization increased by 10.9% (at lag 4), 8.1% (at lag 0), and 4.2% (at lag 2) for every 10 μg/m3 increase in NO2 concentration in the Northwest, Northeast, and South, respectively.

CONCLUSIONS

In the three regions of Guangxi, there were differences in the dominant factors affecting asthma hospitalizations. Differences in geography can inform governments as to how to prepare the healthcare system to meet the expected peaks.

Association between short-term exposure to ambient air pollution and outpatient visits for pulpitis in Hefei, China: a time series study

Evidence suggests a possible association between ambient air pollutants and oral diseases. Nevertheless, information regarding the relationship between air pollutants and pulpitis is scarce and inconclusive. In view of this, the present study aimed to investigate the relationship between short-term exposure to air pollution and outpatient visits for pulpitis. Daily data on outpatient visits for pulpitis, air pollutants, and meteorological data in Hefei, China, was collected from January 1, 2015 to December 31, 2021. The association between exposure to air pollutants and pulpitis outpatient visits was evaluated using distributed lag non-linear model (DLNM) and a generalized linear model (GLM). Furthermore, stratified analyses were performed by gender, age and season. A total of 93,324 records of outpatient visits for pulpitis were included in this study. The results showed that exposure to NO₂, PM_2.5, and CO were positively correlated with an increased risk of pulpitis outpatient visits. Each 10 μg/m³ increase in NO₂ and PM_2.5 concentration, at lag 0-2 day, was associated with a 2.4% (relative risk (RR) = 1.024, 95% confidence interval (CI): 1.014-1.035) and 0.5% (RR = 1.005, 95% CI: 1.000-1.010) increase in pulpitis outpatient visits, respectively. With a 1 mg/m³ increase in CO concentration, the risk of pulpitis outpatient visits increased by 9.1% (RR = 1.091, 95% CI: 1.031-1.154, lag 0-1 day). Intriguingly, exposure to O₃ was associated with a decreased risk of pulpitis outpatient visits (RR = 0.990, 95% CI: 0.984-0.995, lag 0-5 day). Subgroup analysis revealed that in the warm season, exposure to PM_2.5, O₃, and CO was related with a significantly higher outpatient risk of pulpitis than in the cold season. Additionally, the influence of PM_2.5 and CO exposure at age < 65 years was significantly stronger than at age ≥ 65 years. In conclusion, exposure to ambient NO₂, PM_2.5, and CO is associated with an increase in pulpitis outpatient visits in Hefei, China. Conversely, exposure to O₃ reduces the risk of outpatient visits for pulpitis. Age and season are effect modifiers of these associations.

Wearable Sensor-Based Monitoring of Environmental Exposures and the Associated Health Effects: A Review

Recent advances in sensor technology have facilitated the development and use of personalized sensors in monitoring environmental factors and the associated health effects. No studies have reviewed the research advancement in examining population-based health responses to environmental exposure via portable sensors/instruments. This study aims to review studies that use portable sensors to measure environmental factors and health responses while exploring the environmental effects on health. With a thorough literature review using two major English databases (Web of Science and PubMed), 24 eligible studies were included and analyzed out of 16,751 total records. The 24 studies include 5 on physical factors, 19 on chemical factors, and none on biological factors. The results show that particles were the most considered environmental factor among all of the physical, chemical, and biological factors, followed by total volatile organic compounds and carbon monoxide. Heart rate and heart rate variability were the most considered health indicators among all cardiopulmonary outcomes, followed by respiratory function. The studies mostly had a sample size of fewer than 100 participants and a study period of less than a week due to the challenges in accessing low-cost, small, and light wearable sensors. This review guides future sensor-based environmental health studies on project design and sensor selection.

Air pollution and risk of respiratory and cardiovascular hospitalizations in a large city of the Mekong Delta Region

It is important to explore air pollution and health effects in developing cities for early prevention rather than waiting for conditions to deteriorate as in the current megacities. This study aims to investigate the short-term health effects of air pollution in a large city in the Mekong Delta Region (MDR) of Vietnam. Air pollution data from January 2015 to December 2018 were collected from the Environmental Monitoring Centre of Can Tho City. The data of respiratory and cardiovascular disease (CVD) admissions in 18 hospitals and medical centers were collected. A time-series regression analysis was conducted using distributed lag models to examine the relationship between the air pollutants and hospitalizations including the delayed effect up to 7 days. The research findings reveal that a 10 μg increase in PM₁₀ was associated with an increase of 2.5% in the risk of respiratory admission for all people and 2.2% in the risk of CVD admission for the elderly on the same day. The analysis stratified by age and sex indicates that PM10 resulted in a higher risk of respiratory admission among children (0-5 years old) and males compared with other groups. PM10 and NO₂ were significantly associated with CVD admission among the elderly at lag 4 and 6 days. The effects of other air pollutants (SO₂, O₃) were not observed in this study. As development continues in this region, there is an urgent need for intervention measures to minimize the health impacts associated with the expected increases in air pollution in the MDR.

Particulate matter pollution and asthma mortality in China: A nationwide time-stratified case-crossover study from 2015 to 2020

BACKGROUND

A national and comprehensive evaluation is lacking on the relationship between short-term exposure to submicron particulate matter (PM₁) pollution and asthma mortality.

METHODS

Data was obtained from 29,553 asthma deaths from the China National Mortality Surveillance System from 2015 to 2020. We used a bilinear interpolation approach to estimate each participant's daily ambient particulate matter pollution and meteorological variables exposure based on their geocoded residential address and a 10 km × 10 km grid from China High Air Pollutants and the fifth generation of European ReAnalysis-Land reanalysis data set. The associations were estimated using a time-stratified case-crossover design and conditional logistic regressions.

RESULTS

Our results revealed significant associations between short-term exposure to various particulate matter and asthma mortality. The 5-day moving average of particulate matter exposure produced the most pronounced effect. Compared to fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀), significantly stronger effects on asthma mortality related to PM₁ pollution were noted. The ERs% for asthma mortality associated with each interquartile range (IQR) increase of exposures to PM₁ (IQR: 19.2 μg/m³) was 5.59% (95% CI: 2.11-9.19), which is 14% and 22% higher than that for PM_2.5 (IQR: 32.0 μg/m³, 4.82% (95% CI: 1.84-7.90)) and PM₁₀ (IQR: 52.2 μg/m³, 4.37% (95% CI: 1.16-7.69)), respectively. The estimates remained consistent in various sensitivity analyses.

CONCLUSIONS

Our study provided national evidence that acute exposures to various ambient particulate matter pollution can increase mortality due to asthma in China, highlighting stronger associations with ambient PM₁ than PM_2.5 and PM₁₀. China needs to adjust the current ambient air quality standards urgently and pay greater attention to the adverse health effects of PM₁.

Health impact assessment of air pollution in Lisbon, Portugal

BACKGROUND

Lisbon has about 500,000 inhabitants and it's the capital and the main economic hub of Portugal. Studies have demonstrated that exposure to Particulate Matter with an aerodynamic diameter<2.5 μm (PM_2.5) have strong association with health effects. Researchers continue to identify new harmful air pollutants effects in our health even in low levels.

OBJECTIVES

This study evaluates air pollution scenarios considering a Health Impact Assessment approach in Lisbon, Portugal.

METHODS

We have studied abatement scenarios of PM_2.5 concentrations and the health effects in the period from 2015 to 2017 using the APHEKOM tool and the associated health costs were assessed by Value of Life Year.

RESULTS

The mean concentration of PM_2.5 in Lisbon was 23 μg/m³ ± 10 μg/m³ (±Standard Deviation). If we consider that World Health Organization (WHO) standards of PM_2.5 (10 μg/m³) were reached, Lisbon would avoid more than 423 premature deaths (equivalent to 9,172 life years' gain) and save more than US$45 million annually. If Lisbon city could even diminish the mean of PM_2.5 by 5 μg/m³, nearly 165 deaths would be avoided, resulting in a gain of US$17 million annually.

CONCLUSION

According to our findings, if considered the worst pollution scenario, levels of PM2.5 could improve the life's quality and save a significant amount of economic resources.Implications: The manuscript addresses the health effects and costs of air pollution and constitutes an important target for improving public policies on air pollutants in Portugal. Although Portugal has low levels of air pollution, there are significant health and economic effects that, for the most part, are underreported. The health impact assessment approach associated with costs had not yet been addressed in Portugal, which makes this study more relevant in the analysis of policies aimed to drive stricter control on pollutants' emissions. Health costs are a fundamental element to support decision-making process and to orientate the trade-offs in investments for improving public policies so that to diminish health effects, which can impact the management of the local health services and the population's quality of life, especially after the pandemic period when resources are scarce.

Is higher ambient temperature associated with acute appendicitis hospitalizations? A case-crossover study in Tongling, China

Existing studies suggested that ambient temperature may affect the attack of acute appendicitis. However, the identification of the quantitative effect and vulnerable populations are still unknown. The purposes of this study were to quantify the impact of daily mean temperature on the hospitalization of acute appendicitis and clarify vulnerable groups, further guide targeted prevention of acute appendicitis in Tongling. Daily data of cases and meteorological factors were collected in Tongling, China, during 2015-2019. Time stratified case-crossover design and conditional logistic regression model were used to evaluate the odds ratio (OR) of ambient temperature on hospitalizations for acute appendicitis. Stratified analyses were performed by sex, age, and marital status. The odds ratio (OR) of hospitalizations for acute appendicitis increased by 1.6% for per 1 ℃ rise in mean temperature at lag3[OR = 1.016, 95% confidence interval (CI): 1.004-1.028]. In addition, our results suggest it is in the women that increased ambient temperature is more likely to contribute to acute appendicitis hospitalizations; we also found that the married are more susceptible to acute appendicitis hospitalizations due to increased ambient temperature than the unmarried; people in the 21-40 years old are more sensitive to ambient temperature than other age groups. The significant results of the differences between the subgroups indicate that the differences between the groups are all statistically significant. The elevated ambient temperatures increased the risk of hospitalizations for acute appendicitis. The females, married people, and patients aged 21-40 years old were more susceptible to ambient temperature. These findings suggest that more attention should be paid to the impact of high ambient temperature on acute appendicitis in the future.

Source apportionment of children daily exposure to particulate matter

The present study aims to investigate the sources of particulate pollution in indoor and outdoor environments, with focus on determining their contribution to the exposure of children to airborne particulate matter (PM). To this end, parallel indoor and outdoor measurements were carried out for a selection of 40 homes and 5 schools between September 2017 and October 2018. PM2.5 and PM2.5-10 samples were collected during five days in each microenvironment (ME) and analysed by X-Ray Fluorescence (XRF), for the determination of elements, and by a thermal-optical technique, for the measurement of organic and elemental carbon. The source apportionment analysis of the PM composition data, by means of the receptor model SoFi (Source Finder) 8 Pro, resulted in the identification of nine sources: exhaust and non-exhaust emissions from traffic, secondary particles, heavy oil combustion, industry, sea salt, soil, city dust, and an indoor source characterized by high levels of organic carbon. Integrated daily exposure to PM2.5 was on average 21 μg/m³. The organic matter, resulting from cleaning, cooking, smoking and biological material, was the major source contributing by 31% to the PM2.5 exposure. The source city dust, which was highly influenced by the resuspension of dust in classrooms, was the second main source (26%), followed by traffic (24%). The major sources affecting the integrated exposure to PM10, which was on average 33 μg/m³, were the city dust (39%), indoor organics (24%) and traffic (16%). This study provides important information for the design of measures to reduce the exposure of children to PM.

Impact of air pollutants on hospital visits for pediatric asthma in Fuzhou city, southeast China

Rapid social development in China has resulted in severe air pollution and adverse impacts on people's health. Although studies have been conducted on the relationship between exposure to air pollutants and asthma exacerbation, most studies were performed in relatively heavily polluted areas, while little is known about the effect of air pollutants in less polluted areas. We assessed the effects of air pollutants on the risk of asthma-related outpatient and emergency visits of infants and children aged from 0 to 13 years during 2018 to 2020 in Fuzhou city, southeast China. Data of six air pollutants: sulfur dioxide (SO₂), nitrogen dioxides (NO₂), carbon monoxide (CO), daily maximum 8-h average ozone (O₃-8 h), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), and particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5), were obtained from the Environmental Protection Administration of Fuzhou. Data of temperature, humidity, and wind speed were provided by the Meteorological Bureau of Fuzhou. Results revealed that on lag day 6, NO₂, SO₂, and CO were positively associated with the number of outpatient and emergency visits. Among the pollutants, SO₂ had the highest effects on both outpatient visits (RR = 1.672, 95%CI 1.545, 1.809) and emergency visits (RR = 1.495, 95%CI 1.241, 1.800), and its effect on outpatient visits was stronger in children aged 0-4 years than in those aged 5-13 years (RR = 2.331 vs. 1.439). In conclusion, SO₂ contributes substantially to the adverse effects of air pollutants on pediatric respiratory health in Fuzhou. Younger children were more affected by air pollution than their older counterparts.

Association between air pollution and hospital admissions for chronic respiratory disease in people aged over 65 years: a time series analysis in Ningbo, China, 2015-2017

PURPOSE

To provide essential information of environmental triggers leading to CRD.

METHODS

We investigated the short-term effects of ambient air pollutants on CRD-related hospitalizations in people aged ≥ 65 years in Ningbo. Data on 23,610 cases of CRD requiring hospitalization were collected from January 2015 to August 2017. After adjusting for temporal trends, seasonality, meteorological conditions, day of week (DOW), and public holidays, we used generalized additive Poisson distribution models to calculate the excess risks (ERs) and 95% confidence intervals (95% CIs) of CRD related hospitalizations.

RESULTS

Our results showed that fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) were associated with CRD-related hospitalizations in people aged ≥ 65 years. We observed that each 10 μg/m³ increase (except for each 0.1 mg/m³ increase in CO) in the concentration of air pollutants, the percentage of CRD-related hospitalizations due to PM_2.5, PM₁₀, and SO₂ exposure at lag 07, NO₂ exposure at lag 03, and CO exposure at lag 0 increased by 2.13% (95% CI: 0.55%, 3.74%), 1.76% (95% CI: 0.70%, 2.83%), 8.24% (95% CI: 0.92%, 16.09%), 2.16% (95% CI: 0.26%, 4.05%), and 1.19% (95% CI: 0.26%, 2.12%), respectively. In addition, we found stronger effects of particulate matter in 75-84 years age group, on warmer days, and in asthmatics.

CONCLUSION

In conclusion, air pollution may have adverse effects on CRD-related hospitalizations among people aged ≥ 65 years in Ningbo. Therefore, public health measures should be taken to improve air quality.

Ambient Air Pollution and Risk of Admission Due to Asthma in the Three Largest Urban Agglomerations in Poland: A Time-Stratified, Case-Crossover Study

Ambient air pollution in urban areas may trigger asthma exacerbations. We carried out a time-series analysis of the association between the concentrations of various air pollutants and the risk of hospital admission due to asthma over 7 days from exposure. We used distributed lag nonlinear models to analyze data gathered between 2010 and 2018 in the three largest urban agglomerations in Poland. Overall, there were 31,919 asthma hospitalizations. Over 7 days since exposure, the rate ratio (95%CI) for admission per 10 µg/m3 was 1.013 (1.002–1.024) for PM10; 1.014 (1.000–1.028) for PM2.5; 1.054 (1.031–1.078) for NO2; and 1.044 for SO2 (95%CI: 0.986–1.104). For all pollutants, the risk of admission was the greatest on the day of exposure (day 0), decreased below baseline on days 1 and 2, and then increased gradually up to day 6. The proportions (95%CI) of hospitalizations attributable to air pollution were 4.52% (0.80%–8.14%) for PM10; 3.74% (0.29%–7.11%) for PM2.5; 16.4% (10.0%–21.8%) for NO2; and 2.50% (−0.75%–5.36%) for SO2. In conclusion, PM2.5, PM10, NO2, and SO2 pollution was associated with an increased risk of hospital admission due to asthma in the three largest urban agglomerations in Poland over nine years.

Individual exposure to ambient PM2.5 and hospital admissions for COPD in 110 hospitals: a case-crossover study in Guangzhou, China

Few studies have evaluated the short-term association between hospital admissions and individual exposure to ambient particulate matter (PM_2.5). Particularly, no studies focused on hospital admissions for chronic obstructive pulmonary disease (COPD) at the individual level. We assessed the short-term effects of PM_2.5 on hospitalization admissions for COPD in Guangzhou, China, during 2014-2015, based on satellite-derived estimates of ambient PM_2.5 concentrations at a 1-km resolution near the residential address as individual-level exposure for each patient. Around 40,002 patients with COPD admitted to 110 hospitals were included in this study. A time-stratified case-crossover design with conditional logistic regression models was applied to assess the effects of PM_2.5 based on a 1-km grid data of aerosol optical depth provided by the National Aeronautics and Space Administration on hospital admissions for COPD. Further, we performed stratified analyses by individual demographic characteristics and season of hospital admission. Around 10 μg/m³ increase in individual-level PM_2.5 was associated with an increase of 1.6% (95% confidence interval [CI]: 0.6%, 2.7%) in hospitalization for COPD at a lag of 0-5 days. The impact of PM_2.5 on hospitalization for COPD was greater significantly in males and patients admitted in summer. Our study strengthened the evidence for the adverse effect of PM_2.5 based on satellite-based individual-level exposure data.

Effects of particulate matter on hospital admissions for respiratory diseases: an ecological study based on 12.5 years of time series data in Shanghai

BACKGROUND

Previous epidemiological studies on the association between short-term exposure to particulate matter (PM) with hospital admission in major cities in China were limited to shorter study periods or a single hospital. The aim of this ecological study based on a 12.5-year time series was to investigate the association of short-term exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and aerodynamic diameter ≤ 10 μm (PM₁₀) with hospital admissions for respiratory diseases.

METHODS

Daily hospital admissions data were from the Shanghai Medical Insurance System for the period January 1, 2008 to July 31, 2020. We estimated the percentage change with its 95% confidence interval (CI) for each 10 μg/m³ increase in the level of PM_2.5 and PM₁₀ after adjustment for calendar time, day of the week, public holidays, and meteorological factors applying a generalized additive model with a quasi-Poisson distribution.

RESULTS

There were 1,960,361 hospital admissions for respiratory diseases in Shanghai during the study period. A 10 μg/m³ increase in the level of each class of PM was associated with increased total respiratory diseases when the lag time was 0 day (PM_2.5: 0.755%; 95% CI: 0.422, 1.089%; PM₁₀: 0.250%; 95% CI: 0.042, 0.459%). The PM_2.5 and PM₁₀ levels also had positive associations with admissions for COPD, asthma, and pneumonia. Stratified analyses demonstrated stronger effects in patients more than 45 years old and during the cold season. Total respiratory diseases increased linearly with PM concentration from 0 to 100 μg/m³, and increased more slowly at higher PM concentrations.

CONCLUSIONS

This time-series study suggests that short-term exposure to PM increased the risk for hospital admission for respiratory diseases, even at low concentrations. These findings suggest that reducing atmospheric PM concentrations may reduce hospital admissions for respiratory diseases.

Short-term ambient particulate air pollution exposure, microRNAs, blood pressure and lung function

Ambient particulate air pollution is a risk factor for cardiovascular and respiratory disease, yet the biological mechanisms underlying this association are not well understood. The current study aimed to investigate the mediation role of microRNAs on the association between personal PM_2.5 exposure and blood pressure and lung function. One hundred and twenty adults (60 truck drivers and 60 office workers) aged 18-46 years were assessed on the June 15, 2008 and at follow-up (1- to 2-weeks later). MicroRNAs were extracted from the peripheral blood samples. Compared to truck drivers, there is a significant increase in FEF_25-75, FEV₁, and FEV₁/FVC and a decrease in PM_2.5 in office workers (all p < 0.05). According to the Bonferroni corrected threshold p-value < 6.81 × 10^-5 (0.05/734) used, personal PM_2.5 data showed a significant positive association with miR-644 after the adjustment for age, BMI, smoking status, and habitual alcohol use. The mediation effect of miR-644 on the association between personal PM_2.5 exposure and FEF_25-75 [B (95%CI) = -1.342 (-2.810, -0.113)], PEF [B (95%CI) = -1.793 (-3.926, -0.195)], and FEV₁/FVC [B (95%CI) = -0.119‰ (-0.224‰, -0.026‰)] was significant only for truck drivers after the adjustment for covariates. There were no similar associations with blood pressure. These results demonstrate microRNAs to potentially mediate association of PM_2.5 with lung function. Subsequent studies are needed to further elucidate the potential mechanisms of action by which the mediation effect of microRNAs is achieved with this process.

Outdoor air pollution and the risk of asthma exacerbations in single lag0 and lag1 exposure patterns: a systematic review and meta-analysis

Objective: To synthesize evidence regarding the relationship between outdoor air pollution and risk of asthma exacerbations in single lag0 and lag1 exposure patterns.Methods: We performed a systematic literature search using PubMed, Embase, Cochrane Library, Web of Science, ClinicalTrials, China National Knowledge Internet, Chinese BioMedical, and Wanfang databases. Articles published until August 1, 2020 and the reference lists of the relevant articles were reviewed. Two authors independently evaluated the eligible articles and performed structured extraction of the relevant information. Pooled relative risks (RRs) and 95% confidence intervals (CIs) of lag0 and lag1 exposure patterns were estimated using random-effect models.Results: Eighty-four studies met the eligibility criteria and provided sufficient information for meta-analysis. Outdoor air pollutants were associated with increased risk of asthma exacerbations in both single lag0 and lag1 exposure patterns [lag0: RR (95% CI) (pollutants), 1.057(1.011, 1.103) (air quality index, AQI), 1.007 (1.005, 1.010) (particulate matter of diameter ≤ 2.5 μm, PM_2.5), 1.009 (1.005, 1.012) (particulate matter of diameter, PM₁₀), 1.010 (1.006, 1.014) (NO₂), 1.030 (1.011, 1.048) (CO), 1.005 (1.002, 1.009) (O₃); lag1:1.064(1.022, 1.106) (AQI), 1.005 (1.002, 1.008) (PM_2.5), 1.007 (1.004, 1.011) (PM₁₀), 1.008 (1.004, 1.012) (NO₂), 1.025 (1.007, 1.042) (CO), 1.010 (1.006, 1.013) (O₃)], except SO₂ [lag0: RR (95% CI), 1.004 (1.000, 1.007); lag1: RR (95% CI), 1.003 (0.999, 1.006)]. Subgroup analyses revealed stronger effects in children and asthma exacerbations associated with other events (including symptoms, lung function changes, and medication use).Conclusion: Outdoor air pollution increases the asthma exacerbation risk in single lag0 and lag1 exposure patterns.Trial registration: PROSPERO, CRD42020204097. https://www.crd.york.ac.uk/.Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2008429 .

Exposure Response Relationship of Acute Effects of Air Pollution on Respiratory Diseases - China, 2013-2018

What is already known about this topic?

Short-term exposure to air pollutants has been associated with chronic obstructive pulmonary disease (COPD) and asthma, which needs continuous observation.

What is added by this report?

This study uses the longest time series data so far from 2013 to 2018 and adds additional data analysis for ozone (O₃) to existing studies.

What are the implications for public health practice?

This study suggests that air pollutants have certain acute effects on outpatient and hospital admission of patients with COPD and asthma, which can be combined with the disease diagnosis and treatment guidelines to guide clinical practice.

The association between air pollution parameters and emergency department visits and hospitalizations due to cardiovascular and respiratory diseases: a time-series analysis

OBJECTIVE

In this study, the association between cardiovascular and respiratory Emergency Department (ED) visits and hospitalizations and Sulfur Dioxide (SO₂) and particulate matter with an aerodynamic diameter ≤ 10 µm (PM₁₀) was determined.

METHODS

The records of a total of 632,223 people diagnosed with cardiovascular diseases (ICD-10 code I00-I99) and respiratory diseases (ICD-10 code J00-J99) at and over the age of 18 between 2012 and 2018 in three hospitals in Karaman in Turkey were examined in the present study. The daily 24-h averages for SO₂ and PM₁₀ concentrations were acquired in National Air Quality Monitoring. A time-series analysis with Poisson Generalized Linear Model was used.

RESULTS

Among the air pollution parameters, the mean ± standard deviation of SO₂ and PM₁₀ were 16.2 ± 22.1 and 75.8 ± 48.2 μg/m³, respectively. An increase of 10 μg/m³ in SO₂ was associated with a 3% [Relative Risk (RR), 95% Confidence Interval (CI): 2-4)] increase in cardiovascular ED visit and 2% (RR, 95% CI 2-3) increase in respiratory ED visit, and 1% (RR, 95% CI 1-3) increase in respiratory hospitalizations. An increase of 10 μg/m³ in PM₁₀ was associated with a 1% (RR, 95% CI 1-2) increase in cardiovascular hospitalizations.

CONCLUSIONS

Increases in SO₂ are a risk factor for cardiovascular and respiratory ED visits, and respiratory hospitalizations. Increases in PM₁₀ are a risk factor for cardiovascular hospitalizations.

Effects of Air Pollutants on Airway Diseases

Air pollutants include toxic particles and gases emitted in large quantities from many different combustible materials. They also include particulate matter (PM) and ozone, and biological contaminants, such as viruses and bacteria, which can penetrate the human airway and reach the bloodstream, triggering airway inflammation, dysfunction, and fibrosis. Pollutants that accumulate in the lungs exacerbate symptoms of respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Asthma, a heterogeneous disease with complex pathological mechanisms, is characterized by particular symptoms such as shortness of breath, a tight chest, coughing, and wheezing. Patients with COPD often experience exacerbations and worsening of symptoms, which may result in hospitalization and disease progression. PM varies in terms of composition, and can include solid and liquid particles of various sizes. PM concentrations are higher in urban areas. Ozone is one of the most toxic photochemical air pollutants. In general, air pollution decreases quality of life and life expectancy. It exacerbates acute and chronic respiratory symptoms in patients with chronic airway diseases, and increases the morbidity and risk of hospitalization associated with respiratory diseases. However, the mechanisms underlying these effects remain unclear. Therefore, we reviewed the impact of air pollutants on airway diseases such as asthma and COPD, focusing on their underlying mechanisms.

EKC Test of the Relationship between Nitrogen Dioxide Pollution and Economic Growth-A Spatial Econometric Analysis Based on Chinese City Data

During the just concluded 13th Five-Year Plan, China continued to maintain the momentum of rapid economic development, but still faced environmental pollution problems caused by this. Finding the relationship between Nitrogen Dioxide pollution and economic development is helpful and significant in better achieving and optimizing sustainable environmental development. Taking China’s 333 prefecture-level cities as samples from 2016 to 2018, the spatial lag model (SAR) was used to study the impact of economic growth on urban Nitrogen Dioxide pollution. The results show that Nitrogen Dioxide has strong positive characteristics of spatial spillover, but there is a linear relationship between economic growth and Nitrogen Dioxide concentration that slowly rises, and there is no inverted U-shaped relationship, which does not support the Environmental Kuznets Curve (EKC) hypothesis; The results also show the impact of per capita GDP, natural gas consumption, residential natural gas consumption, industrialization, and transportation development on the increase of Nitrogen Dioxide concentration, and the impact of green coverage on the decrease of Nitrogen Dioxide concentration. However, there is no significant relationship between technological investment and Nitrogen Dioxide concentration. The above conclusions are still valid after the robustness test, and recommendations are put forward to reduce Nitrogen Dioxide pollution.

Effects of ambient air pollution on emergency room visits of children for acute respiratory symptoms in Delhi, India

The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (≤15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ≤2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 μg/m³ increase of NO₂ on previous day 1, 46.78% (21.01, 78.05) for 10 μg/m³ of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 μg/m³ of SO₂ on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.

Development and evaluation of air pollution-linked quality of life (AP-QOL) questionnaire: insight from two different cohorts

In this study, the air pollution-related quality of life (AP-QOL) questionnaire was carried out in two geographically and economically different groups including New Delhi (Megacity) and Hamirpur, Himachal Pradesh (town), and APE scores were linked with respiratory and cardiovascular illness. The APE-Score was developed by AP-QOL questionnaire responses using Delphi technique and further analyzed using principal component analysis (PCA). For reliability of APE-Score and AP-QOL questionnaire, α-Cronbach's test and basic statistics were performed. The linear mixed-effect model and odds ratios were used to evaluate air pollution exposure and health outcomes. Overall, 720 academicians and 276 security guards were invited to participate in the questionnaire. Cronbach's α coefficients ranged from 0.70 to 0.84 indicated significant reliability in the AP-QOL questionnaire conducted in this study. Substantial variation in respiratory symptoms and their medical history were found - 76.9% ([95% confidential interval (CI)]: (- 83.8, - 66.9) (p < 0.05)) and - 28.6% (95% CI: (- 37.8, - 18.0) (p < 0.05)), respectively, with interquartile range (IQR) increase of APE score. The odds ratios (ORs) of respiratory medical history (MH Res.) showed a significant increase from 1.01 to 1.35 for low to high air pollution exposure in the academic group of IIT Delhi. Interestingly, for an academic group of NITH, the ORs for medical history of cardiovascular (MH Card.) showed an increase from 1.08 to 1.13 for low to high APE which was not the case for IIT Delhi academicians.

Exacerbation-Prone Asthma: A Biological Phenotype or a Social Construct

Asthma is a complex syndrome with multiple phenotypes and endotypes. Asthma exacerbations are not only the clearest indictor of the morbidity of asthma and of the risk for mortality due to asthma, but also comprise a significant amount of the cost to care for poorly controlled asthma. There continues to be significant disparity in the prevalence, mortality, and morbidity due to asthma. Patients with asthma who suffer recurrent exacerbations are considered to have exacerbation-prone asthma (EPA). Efforts to characterize patients with frequent exacerbations show that the etiology is likely multifactorial. Research to determine the intrinsic risk factors for EPA include studies of both genetic and inflammatory biomarkers. External factors contributing to exacerbations have been extensively reviewed and include viral infection, environmental exposures, air pollution, and psychosocial and economic barriers to optimizing health. It is likely that EPA occurs when patients who have an increased underlying intrinsic/biological risk are placed in a given exposome (environments with a variety of exposures and triggers including allergens, pollution, stress, barriers, and occupational exposures). It is the social construct combined with underlying biology that frequently drives an EPA phenotype.

Impact of a pollution breach at a coke oven factory on asthma control in nearby vulnerable adults

BACKGROUND

Previous studies have related sulfur dioxide (SO₂) exposure to asthma exacerbations. We utilized the University of Pittsburgh Asthma Institute registry to study associations of asthma exacerbations between 2 geographically distinct populations of adults with asthma.

OBJECTIVE

Our objective was to examine whether asthma symptoms worsened following a significant fire event that destroyed pollution control equipment at the largest coke works in the United States.

METHODS

Two groups of patients with asthma, namely, those residing within 10 miles of the coke works fire (the proximal group [n = 39]) and those residing beyond that range (the control group [n = 44]), were geocoded by residential address. Concentrations of ambient air SO₂ were generated by using local University of Pittsburgh Asthma Institute registry air monitoring data. Factory emissions were also evaluated. Data from a patient historical acute exposure survey and in-person follow-up data were evaluated. Inferential statistics were used to compare the groups.

RESULTS

In the immediate postfire period (6-8 weeks), the level of emissions of SO₂ from the factory emissions increased to 25 times more than the typical level. Following the pollution control breach, the proximal cohort self-reported an increase in medication use (risk ratio = 1.76; 95% CI = 1.1-2.8; P < .01) and more exacerbations. In a small subset of the follow-up cohort of those who completed the acute exposure survey only, asthma control metrics improved.

CONCLUSIONS

Real-world exposure to a marked increase in ambient levels of SO₂ from a pollution control breach was associated with worsened asthma control in patients proximal to the event, with the worsened control improving following repair of the controls. Improved spatial resolution of air pollutant measurements would enable better examination of exposures and subsequent health impacts.

COVID-19 pandemic in Wuhan: Ambient air quality and the relationships between criteria air pollutants and meteorological variables before, during, and after lockdown

As a result of the lockdown (LD) control measures enacted to curtail the COVID-19 pandemic in Wuhan, almost all non-essential human activities were halted beginning on January 23, 2020 when the total lockdown was implemented. In this study, changes in the concentrations of the six criteria air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) in Wuhan were investigated before (January 1 to 23, 2020), during (January 24 to April 5, 2020), and after the COVID-19 lockdown (April 6 to June 20, 2020) periods. Also, the relationships between the air pollutants and meteorological variables during the three periods were investigated. The results showed that there was significant improvement in air quality during the lockdown. Compared to the pre-lockdown period, the concentrations of NO₂, PM_2.5, PM₁₀, and CO decreased by 50.6, 41.2, 33.1, and 16.6%, respectively, while O₃ increased by 149% during the lockdown. After the lockdown, the concentrations of PM_2.5, CO and SO₂ declined by an additional 19.6, 15.6, and 2.1%, respectively. However, NO₂, O₃, and PM₁₀ increased by 55.5, 25.3, and 5.9%, respectively, compared to the lockdown period. Except for CO and SO₂, WS had negative correlations with the other pollutants during the three periods. RH was inversely related with all pollutants. Positive correlations were observed between temperature and the pollutants during the lockdown. Easterly winds were associated with peak PM_2.5 concentrations prior to the lockdown. The highest PM_2.5 concentrations were associated with southwesterly wind during the lockdown, and northwesterly winds coincided with the peak PM_2.5 concentrations after the lockdown. Although, COVID-19 pandemic had numerous negative effects on human health and the global economy, the reductions in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits. This study improves the understanding of the mechanisms that lead to air pollution under diverse meteorological conditions and suggest effective ways of reducing air pollution in Wuhan.

The Age, Sex, and Geographical Distribution of Self-Reported Asthma Triggers on Children With Asthma in China

Background: Asthma can be exacerbated by many triggers, and the heterogeneity of asthma triggers is clear among children with asthma. This study describes asthma triggers using a large-scale electronic dataset from the smartphone-based Chinese Children's Asthma Action Plan (CCAAP) app and aims to examine the difference in asthma triggers among different subgroups of children with asthma. Methods: Data from the smartphone-based CCAAP app between February 22, 2017, and November 23, 2020, were reviewed, and children with asthma who reported their asthma triggers were enrolled. Eight common asthma triggers were listed in the software: upper respiratory infection (URI), allergen sensitization, exercise, emotional disturbances, pungent odors, air pollution/smog, weather change, and tobacco smoke. We compared the incidence of asthma triggers among different subgroups (<6 years vs. 6-17 years; boy vs. girl; eastern region vs. central region vs. western region). Results: We enrolled 6,835 patients with self-reported asthma triggers. When compared by sex, boys had a higher proportion of exercise-triggered asthma than girls (boys vs. girls, 22.5 vs. 19.7%, p < 0.05). The proportion of patients <6 years of age with URI-triggered asthma was higher than that of patients 6-17 years of age (<6 vs. 6-17 years, 80.9 vs. 74.9%, p < 0.001). Patients 6-17 years of age were more likely than patients <6 years of age to report five of the asthma triggers: allergen sensitization (<6 vs. 6-17 years, 26.6 vs. 35.8%, p < 0.001), exercise (<6 vs. 6-17 years, 19.3 vs. 23.7%, p < 0.001), pungent odors (<6 vs. 6-17 years, 8.8 vs. 12.7%, p < 0.001), air pollution/smog (<6 vs. 6-17 years, 9.4 vs. 16.2%, p < 0.001), and tobacco smoke (<6 vs. 6-17 years, 3.5 vs. 5.3%, p < 0.001). In subgroups based on geographical distribution, asthma triggering of allergen sensitization was reported to be the most common in patients from the eastern region (eastern region vs. central region vs. western region, 35.0 vs. 24.6 vs. 28.0%, p < 0.001). Exercise-triggered asthma was found to be the most prevalent among patients from the central region (eastern region vs. central region vs. western region, 21.6 vs. 24.8 vs. 20.4%, p < 0.05). However, the proportion of patients with air pollution/smog as an asthma trigger was the lowest among those from the western region (eastern region vs. central region vs. western region, 14.1 vs. 14.1 vs. 10.8%, p < 0.05). Conclusion: Children with asthma present different types of asthma triggers, both allergenic and nonallergenic. Age, sex, and geographical distribution affect specific asthma triggers. Preventive measures can be implemented based on a patient's specific asthma trigger.

Short-term exposure to ambient particulate matter and outpatient visits for respiratory diseases among children: A time-series study in five Chinese cities

There was limited evidence regarding the association between short-term exposure to ambient particulate matter (PM) and respiratory outpatient visits among children at a multicity level. In this study, a time-series study was conducted among children aged 0-14 years in five Chinese cities from 2013 to 2018. City-specific effects of fine particles (PM_2.5), inhalable particles (PM₁₀) and coarse particles (PM_10-2.5) were estimated for time lags of zero up to seven previous days using the overdispersed generalized additive models after adjusting for time trends, meteorological variables, day of the week and holidays. Meta-analyses were applied to pool the overall effects, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. The overall effects of PM were significantly associated with total and cause-specific respiratory outpatients among children, even at PM_2.5 and PM₁₀ levels below the current Chinese Ambient Air Quality Standards (CAAQS) Grade II. Each 10 μg/m³ increment in PM_2.5, PM₁₀ and PM_10-2.5 at lag 07 was associated with a 1.39% (95% CI: 0.38%, 2.40%), 1.10% (95% CI: 0.38%, 1.83%) and 2.93% (95% CI: 1.05%, 4.84%) increase in total respiratory outpatients, respectively. An E-R relationship was observed except for PM_2.5 in Beijing and PM₁₀ and PM_10-2.5 in Shanghai. The effects of PM were stronger in cold season in 3 southern cities, while it was stronger in transition season in 2 northern cities. In conclusion, short-term PM exposures were dose-responsive associated with increased respiratory outpatient visits among children, even for PM_2.5 and PM₁₀ levels below current CAAQS II in certain cities.

Assessing NO2-related health effects by non-linear and linear methods on a national level

Exposure to NO₂ pollution has a significant adverse effect on residents' health. However, few studies have assessed the health effects associated with NO₂ pollution. Compared with PM_2.5 pollution, the harmfulness of NO₂ pollution has not been quantitatively studied or clearly identified. In this study, we assessed the NO₂ exposure-related health effects by non-linear and linear methods, taking advantage of online monitoring and survey data. We also assessed the economic cost of NO₂ pollution in 338 cities in China. Our results showed that the average annual concentration of NO₂ in the top fifteen cities with more than ten million permanent residents (except for Shenzhen, in the Guangdong province) exceeded the annual Grade II standards (40 μg/m³). The estimated national NO₂-related all-cause mortality for non-linear and linear methods were 388.5 × 10³ (95% CI: 198.1 × 10³-748.2 × 10³) and 374.1 × 10³ (95% CI: 194.3 × 10³-695.9 × 10³), respectively. The total calculated national economic cost was about 28.8 billion US$ (95% CI: 14.7-55.4) in 2016. In addition, the comparison results showed that the harm caused by PM_2.5 pollution was about four times that of NO₂ pollution. Our statistics contribute to the limited research on NO₂ pollution's effects on health and the economy in China.

A review on fly ash from coal-fired power plants: chemical composition, regulations, and health evidence

Throughout the world, coal is responsible for generating approximately 38% of power. Coal ash, a waste product, generated from the combustion of coal, consists of fly ash, bottom ash, boiler slag, and flue gas desulfurization material. Fly ash, which is the main component of coal ash, is composed of spherical particulate matter with diameters that range from 0.1 μm to >100 μm. Fly ash is predominately composed of silica, aluminum, iron, calcium, and oxygen, but the particles may also contain heavy metals such as arsenic and lead at trace levels. Most nations throughout the world do not consider fly ash a hazardous waste and therefore regulations on its disposal and storage are lacking. Fly ash that is not beneficially reused in products such as concrete is stored in landfills and surface impoundments. Fugitive dust emissions and leaching of metals into groundwater from landfills and surface impoundments may put people at risk for exposure. There are limited epidemiological studies regarding the health effects of fly ash exposure. In this article, the authors provide an overview of fly ash, its chemical composition, the regulations from nations generating the greatest amount of fly ash, and epidemiological evidence regarding the health impacts associated with exposure to fly ash.

Impact of Air Pollution on Asthma Outcomes

Asthma is a chronic respiratory disease characterized by variable airflow obstruction, bronchial hyperresponsiveness, and airway inflammation. Evidence suggests that air pollution has a negative impact on asthma outcomes in both adult and pediatric populations. The aim of this review is to summarize the current knowledge on the effect of various outdoor and indoor pollutants on asthma outcomes, their burden on its management, as well as to highlight the measures that could result in improved asthma outcomes. Traffic-related air pollution, nitrogen dioxide and second-hand smoking (SHS) exposures represent significant risk factors for asthma development in children. Nevertheless, a causal relation between air pollution and development of adult asthma is not clearly established. Exposure to outdoor pollutants can induce asthma symptoms, exacerbations and decreases in lung function. Active tobacco smoking is associated with poorer asthma control, while exposure to SHS increases the risk of asthma exacerbations, respiratory symptoms and healthcare utilization. Other indoor pollutants such as heating sources and molds can also negatively impact the course of asthma. Global measures, that aim to reduce exposure to air pollutants, are highly needed in order to improve the outcomes and management of adult and pediatric asthma in addition to the existing guidelines.