Risks of hospital admissions from a spectrum of causes associated with particulate matter pollution

Burden of cardiovascular disease attributed to air pollution: a systematic review

BACKGROUND

Cardiovascular diseases (CVDs) are estimated to be the leading cause of global death. Air pollution is the biggest environmental threat to public health worldwide. It is considered a potentially modifiable environmental risk factor for CVDs because it can be prevented by adopting the right national and international policies. The present study was conducted to synthesize the results of existing studies on the burden of CVDs attributed to air pollution, namely prevalence, hospitalization, disability, mortality, and cost characteristics.

METHODS

A systematic search was performed in the Scopus, PubMed, and Web of Science databases to identify studies, without time limitations, up to June 13, 2023. Exclusion criteria included prenatal exposure, exposure to indoor air pollution, review studies, conferences, books, letters to editors, and animal and laboratory studies. The quality of the articles was evaluated based on the Agency for Healthcare Research and Quality Assessment Form, the Newcastle-Ottawa Scale, and Drummond Criteria using a self-established scale. The articles that achieved categories A and B were included in the study.

RESULTS

Of the 566 studies obtained, based on the inclusion/exclusion criteria, 92 studies were defined as eligible in the present systematic review. The results of these investigations supported that chronic exposure to various concentrations of air pollutants, increased the prevalence, hospitalization, disability, mortality, and costs of CVDs attributed to air pollution, even at relatively low levels. According to the results, the main pollutant investigated closely associated with hypertension was PM2.5. Furthermore, the global DALY related to stroke during 2016-2019 has increased by 1.8 times and hospitalization related to CVDs in 2023 has increased by 8.5 times compared to 2014.

CONCLUSION

Ambient air pollution is an underestimated but significant and modifiable contributor to CVDs burden and public health costs. This should not only be considered an environmental problem but also as an important risk factor for a significant increase in CVD cases and mortality. The findings of the systematic review highlighted the opportunity to apply more preventive measures in the public health sector to reduce the footprint of CVDs in human society.

Association between PM10 exposure and risk of myocardial infarction in adults: A systematic review and meta-analysis

BACKGROUND

Air pollution has several negative health effects. Particulate matter (PM) is a pollutant that is often linked to health adversities. PM2.5 (PM with an aerodynamic diameter of ≤2.5μm) exposure has been associated with negative cardiovascular (CV) outcomes. However, the impact of PM10 (PM with an aerodynamic diameter of ≤10μm) exposure is often overlooked due to its limited ability to pass the alveolar barrier. This study aims to assess the association between PM10 exposure and risk of myocardial infarction (MI) amongst adults (≥18 years of age) as this has been poorly studied.

METHODS

The study protocol was published on the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023409796) on March 31, 2023. Literature searches were conducted on 4 databases (Ovid Medline, Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Web of Science) on January 17, 2023, for studies looking at associations between PM and MI. English studies from all time periods were assessed. Studies selected for review were time-series, case-crossover, and cohort studies which investigated the risk of MI as an outcome upon PM10 exposure. The quality of evidence was assessed using Cochrane's Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Data for different risk outcomes (risk ratio (RR), odds ratio (OR), hazard ratio (HR)) and 3 lags was meta-analyzed using an inverse variance statistical analysis using a random effects model. The pooled effect sizes and the 95% confidence intervals (CIs) were reported in forest plots.

RESULTS

Among the 1,099 studies identified, 41 were included for review and 23 were deemed eligible for meta-analysis. Our analysis revealed that there is an increased risk (OR = 1.01; 95% CI:1.00-1.02) of MI with a 10 μg/m3 increase in PM10 after a lag 0 and lag 1 delay.

CONCLUSIONS

Our findings indicate that PM10 exposure is associated with an increased risk of MI. This can aid in informing environmental policy-making, personal-level preventative measures, and global public health action.

Association between short-term ambient air pollutants and type 2 diabetes outpatient visits: a time series study in Lanzhou, China

Diabetes is a global public health problem, and the impact of air pollutants on type 2 diabetes mellitus (T2DM) has attracted people's attention. This study aimed to assess the association of short-term exposure to six criteria air pollutants with T2DM outpatient visits in Lanzhou, China. We collected data on daily outpatient visits for T2DM, daily meteorological data and hourly concentrations of air pollutants in Lanzhou from 2013 to 2019. An over-dispersed passion generalized addictive model combined with a distributed lag non-linear model was applied to estimate the associations and stratified analyses were performed by gender, age, and season. The models were fitted with different lag structures, including single lag days from the current to the previous seven days (lag0 to lag7) and moving average concentrations over seven lag days (lag01 to lag07). A positive association between multiple air pollutants, especially PM2.5, NO2, O38h and CO and hospital outpatient visits for T2DM was observed. The largest association between T2DM outpatient visits and PM2.5 was observed at lag06 (RR 1.013, 95% CI: 1.001, 1.027), NO2 at lag03 (RR 1.034, 95% CI: 1.018, 1.050), O38h at lag05 (RR 1.012, 95% CI: 1.001, 1.023) for an increase of 10 μg m-3 and CO at lag03 (RR 1.084, 95% CI: 1.029, 1.142) for an increase of 1 mg m-3 in the concentrations. In addition, people aged <65 and males are more susceptible, and air pollutants have a greater impact on the cold season. This study showed that although the air pollution in Lanzhou was improved, there was still a statistical correlation between air pollution exposure and T2DM outpatient visits. Therefore, the local government still needs to strengthen the control of air pollution and enhance the protection awareness of the diabetic population through education and publicity.

Appraising the characteristics of particulate matter from leather tanning micro-environments, their respirational risks, and dysfunctions amid exposed working cohorts

Leather tanneries are known for chemical laden work environments and pulmonic complaints among workers. This study presents an analysis of tannery micro-environments emphasizing on size-based variation in composition of particulate matter and consequent respiratory dysfunctions. Qualitative (FTIR, SEM-EDX) and quantitative assessment (elemental composition, carbon forms) of PM10 and 2.5 has been employed. For lung function evaluation of workforce, spirometry with ATS proprieties was used. The peak concentrations of both PM10 and 2.5 have been found at PU, FU, and B&S. The LTCR for only Cr is high for both PM2.5 and PM10. HQ was high for Al, Cr, and Mn for both PM sizes. The maximum organic and secondary organic carbon in PM10 was found at FU and in PM2.5 at PU. The varied PM composition included carbohydrate (B&S, WMO), ether (S&S, P&S) and hydroxyl (B&S, S&S, P&S), proteins, polyenes, vinyl groups (S&S, P&S, FU), alcohols (PU and FU), and aldehyde present at PU. These results were armored by high organic and total carbon concentrations for the same sites. Therefore, PM are classified into biogenic (carbonaceous: microbial and animal remains) from PU and WMO, incidental (industrial, mixt physico-chemical character) from PU, FU, WMO, B&S and P&S, and geogenic (crustal mineral dust) from RHT, B&S, PU, and P&S. Furthermore, increase in metal concentrations in PM10 (Cr, Mn, Co, Ni, V, As, Be, Ba, and Cd) and PM2.5 (As, Pb) while TC, OC, and SOC in PM2.5 caused depreciation overall lung function. The exposure to biogenic and incidental PM nature are key cause of pulmonic dysfunction.

Criteria air pollutants and diabetes mortality classified by different subtypes and complications: A nationwide, case-crossover study

The associations between air pollution and diabetes mortality of different subtypes and complications were largely unclear. We performed an individual-level, time-stratified case-crossover study among over 0.9 million diabetes deaths from all administrative regions of Chinese mainland during 2013-2019. Daily concentrations of fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2) and ozone (O3) were obtained for each decedent using high-resolution prediction models. Conditional logistic regression models were utilized to analyze the data. Each interquartile range increment in PM2.5, PM2.5-10, NO2 and O3 concentrations on lag 0-2 d increased the risks of overall diabetes mortality by 2.81 %, 1.92 %, 3.96 % and 2.15 %, respectively. Type 2 diabetes had stronger associations with air pollution than type 1 diabetes. Air pollutants were associated with diabetic ketoacidosis and diabetic nephropathy, but not other complications. The exposure-response curves were approximately linear with a plateau at higher concentrations of PM2.5, PM2.5-10, and NO2, while the associations for O3 appear to be statistically significant beyond 60 μg/m3. This nationwide study reinforces the evidence of higher risks of acute diabetic events following short-term air pollution exposure. We identified differential effects of air pollutants on various subtypes and complications of diabetes, which require further mechanistic investigations.

Incidence, prevalence, and comorbidities of chronic pancreatitis: A 7-year population-based study

BACKGROUND

Chronic pancreatitis (CP) is a fibroinflammatory syndrome leading to reduced quality of life and shortened life expectancy. Population-based estimates of the incidence, prevalence, and comorbidities of CP in China are scarce.

AIM

To characterize the incidence, prevalence, and comorbidities of CP in Sichuan Province, China, with population-based data.

METHODS

Data on CP from 2015 to 2021 were obtained from the Health Information Center of Sichuan Province. During the study period, a total of 38090 individuals were diagnosed with CP in Sichuan Province. The yearly incidence rate and point prevalence rate (December 31, 2021) of CP were calculated. The prevalence of comorbid conditions in CP patients was estimated. The annual number of CP-related hospitalizations, hospital length of stay, and hospitalization costs for CP were evaluated. Yearly incidence rates were standardized for age by the direct method using the permanent population of Sichuan Province in the 2020 census as the standard population. An analysis of variance test for the linearity of scaled variables and the Cochran-Armitage trend test for categorical data were performed to investigate the yearly trends, and a two-sided test with P < 0.05 was considered statistically significant.

RESULTS

The 38090 CP patients comprised 23280 males and 14810 females. The mean age of patients at CP diagnosis was 57.83 years, with male patients (55.87 years) being younger than female patients (60.11 years) (P < 0.001). The mean incidence rate of CP during the study period was 6.81 per 100000 person-years, and the incidence of CP increased each year, from 4.03 per 100000 person-years in 2015 to 8.27 per 100000 person-years in 2021 (P < 0.001). The point prevalence rate of CP in 2021 was 45.52 per 100000 individuals for the total population, with rates of 55.04 per 100000 individuals for men and 35.78 per 100000 individuals for women (P < 0.001). Individuals aged 65 years or older had the highest prevalence of CP (113.38 per 100000 individuals) (P < 0.001). Diabetes (26.32%) was the most common comorbidity in CP patients. The number of CP-related hospitalizations increased from 3739 in 2015 to 11009 in 2021. The total costs for CP-related hospitalizations for CP patients over the study period were 667.96 million yuan, with an average of 17538 yuan per patient.

CONCLUSION

The yearly incidence of CP is increasing, and the overall CP hospitalization cost has increased by 1.4 times during the last 7 years, indicating that CP remains a heavy health burden.

Associations between short-term exposure to PM2.5, NO2 and O3 pollution and kidney-related conditions and the role of temperature-adjustment specification: A case-crossover study in New York state

Epidemiologic evidence on the relationship between air pollution and kidney disease remains inconclusive. We evaluated associations between short-term exposure to PM_2.5, NO₂ and O₃ and unplanned hospital visits for seven kidney-related conditions (acute kidney failure [AKF], urolithiasis, glomerular diseases [GD], renal tubulo-interstitial diseases, chronic kidney disease, dysnatremia, and volume depletion; n = 1,209,934) in New York State (2007-2016). We applied a case-crossover design with conditional logistic regression, controlling for temperature, dew point temperature, wind speed, and solar radiation. We used a three-pollutant model at lag 0-5 days of exposure as our main model. We also assessed the influence of model adjustment using different specifications of temperature by comparing seven temperature metrics (e.g., dry-bulb temperature, heat index) and five intraday temperature measures (e.g., daily mean, daily minimum, nighttime mean), according to model performance and association magnitudes between air pollutants and kidney-related conditions. In our main models, we adjusted for daytime mean outdoor wet-bulb globe temperature, which showed good model performance across all kidney-related conditions. We observed the odds ratios (ORs) for 5 μg/m³ increase in daily mean PM_2.5 to be 1.013 (95% confidence interval [CI]: 1.001, 1.025) for AKF, 1.107 (95% CI: 1.018, 1.203) for GD, and 1.027 (95% CI: 1.015, 1.038) for volume depletion; and the OR for 5 ppb increase in daily 1-hour maximum NO₂ to be 1.014 (95% CI; 1.008, 1.021) for AKF. We observed no associations with daily 8-hour maximum O₃ exposure. Association estimates varied by adjustment for different intraday temperature measures: estimates adjusted for measures with poorer model performance resulted in the greatest deviation from estimates adjusted for daytime mean, especially for AKF and volume depletion. Our findings indicate that short-term exposure to PM_2.5 and NO₂ is a risk factor for specific kidney-related conditions and underscore the need for careful adjustment of temperature in air pollution epidemiologic studies.

Chlorogenic Acid, a Component of Oenanthe javanica (Blume) DC., Attenuates Oxidative Damage and Prostaglandin E2 Production Due to Particulate Matter 10 in HaCaT Keratinocytes

Oenanthe javanica (OJ) is a perennial herb that grows wildly or is cultivated in Asia, and it is used as food or in traditional medicine. The antioxidant and anti-inflammatory effects of OJ-derived materials have been extensively explored previously, but their effects on the cytotoxicity of air pollution are currently unknown. Therefore, the present study aimed to evaluate the effect of the hot water extract of OJ on atmospheric particulate matter 10 (PM10)-induced cytotoxicity and oxidative damage in human HaCaT keratinocytes, and to identify its active ingredient and mechanism of action. When the hot water extract of OJ was divided into methylene chloride, ethyl acetate (EA), n-butanol (BA), and water fractions, caffeic acid was enriched in the EA fraction and chlorogenic acid was enriched in the BA fraction. PM10 increased reactive oxygen species (ROS) production, lipid peroxidation, protein carbonylation, and inflammatory prostaglandin (PG) E2 production in cells. The BA fraction reduced the PM10-induced ROS production in cells more effectively than the total extract and other solvent fractions. Chlorogenic acid was more effective in reducing ROS levels than caffeic acid and N-acetyl cysteine (NAC). Chlorogenic acid attenuated the increase in lipid peroxidation and the PG E2 production of cells due to PM10 exposure. Of the genes involved in PG E2 production, phospholipase A2 group IVA (PLA2G4A), Prostaglandin-endoperoxide synthase 1 (PTGS1), and 2 (PTGS2) were transcriptionally up-regulated by PM10, whereas phospholipase A2 group IIA (PLA2G2A) was down-regulated and prostaglandin E synthetase 1 (PTGES1) and 2 (PTGES2) were a little altered. The PM10-induced increase in PLA2G4A mRNA was alleviated by chlorogenic acid and NAC. Accordingly, PM10 increased the expression levels of cytosolic phospholipase A2 (cPLA2) protein and its phosphorylated form, which were attenuated by chlorogenic acid and NAC. Thus, chlorogenic acid may attenuate the PM10-induced PG E2 production through the suppression of PLA2G4A mRNA and cPLA2 protein expressions. This study suggests that chlorogenic acid contained in OJ extract may help alleviate the oxidative damage to and inflammatory responses of the skin cells due to exposure to air pollutants.

Effects of ambient air pollution on cause-specific hospitalizations in Wuhan during 2017-2019

BACKGROUND

Few studies have focused on the associations between air pollutants and multiple organ system diseases in the entire hospitalized population. The present study aims to explore the short-term effects of six routinely monitored air pollutants on the broad causes of hospital admissions and estimate the resulting hospital admission burdens.

METHODS

Daily hospital admission records from 2017 to 2019 were obtained from the Wuhan Information center of Health and Family Planning. Generalized additive models (GAMs) were employed to evaluate the effects of air pollutants on the percent increase in the cause-specific daily number of hospital admissions. Increased hospital admission numbers, days, and expenses were also estimated.

RESULTS

A total of 2636,026 hospital admissions were identified. We found that both PM_2.5 and PM₁₀ increased the risk of hospital admissions for most disease categories. Short-term exposure to PM_2.5 was positively associated with hospitalizations of several rarely studied disease categories, such as diseases of the eye and adnexa (2.83%, 95%CI: 0.96-4.73%, P < 0.01) and diseases of the musculoskeletal system and connective tissue (2.17%, 95% CI: 0.88-3.47%, P < 0.001). NO₂ was observed to have a robust effect on diseases of the respiratory system (1.36%, 95%CI: 0.74-1.98%, P < 0.001). CO was significantly associated with hospital admissions for six disease categories. Furthermore, each 10-μg/m³ increase in PM_2.5 was associated with an annual increase of 13,444 hospital admissions (95% CI: 6239-20,649), 124,344 admission days (95% CI: 57,705-190,983), and 166-million-yuan admission expenses (95% CI: 77-255).

CONCLUSION

Our study suggested that particulate matter (PM) had a short-term effect on hospital admissions of most major disease categories and resulted in a considerable hospital admission burden. In addition, the health effects of NO₂ and CO emissions require more attention in megacities.

Ambient air pollution and the risk of neurological diseases in residential areas near multi-purposed industrial complexes of korea: A population-based cohort study

Emerging evidence suggest that long-term exposure to air pollution may induce adverse effects on the central nervous system. However, no study explored the associations in large industrial complex (IC) areas which are one of the major contributors to air pollution. Therefore, we aimed to investigate the pollution status and the association between residential proximity and incidence of neurological diseases near two major ICs characterized as multi-purposed ICs in Korea. A retrospective cohort of residents near the ICs was constructed using Korea's health insurance data and monitored from 2008 to 2019. Emission amounts of the ICs and the air pollution status in the nearby (exposed) and remote (control) area were evaluated using data from national regulatory networks, and hazard ratios (HRs) and 95% confidence intervals (CIs) for neurological diseases of the exposed group compared to the control group were calculated using Cox proportional regression models. Overall, the complexes emitted large amounts of VOCs, CO, NOx, and PM10, and annual levels of ambient PM (2.5, 10), gaseous substances (NO₂, SO₂), VOCs and PAHs were higher in the exposed area compared to the control and/or the national average. The risk of inflammatory disease of the CNS (G00-09) and extrapyramidal and movement disorders (G20-26) were higher in the exposed area with a HR (95% CI) of 1.36 (1.10-1.68) and 1.33 (1.27-1.39) respectively. Among the subclasses, other extrapyramidal and movement disorders (G25) and epilepsy (G40) were associated with higher risks in the exposed area (HR (95%CI): 1.11 (1.04-1.18), 1.08 (1.00-1.16)) after adjusting for potential confounders. These results suggest that people living near ICs are more likely to be exposed to higher air pollution levels and have higher risks of developing several neurological disorders. However, further epidemiological studies in these industrial areas supplemented with other indicators of environmental exposure and control of other diverse factors are warranted.

Ambient air pollution and hospitalization for type 2 diabetes in China: A nationwide, individual-level case-crossover study

Scarce evidence is available on the short-term association between air pollution and type 2 diabetes (T2D). We aimed to evaluate the associations between short-term exposure to six criteria air pollutants and hospitalization for T2D based on a national registry. We conducted an individual-level, time-stratified case-crossover study among inpatients with a primary diagnosis of T2D from 153 hospitals across 20 provincial regions in China (2013-2021). Daily concentrations of fine particulate matter (PM_2.5), inhalable particle (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and carbon monoxide (CO), and ozone were collected from the nearest monitoring stations. T2D patients were separated into those admission for T2D with and without complications. Distributed lag non-linear models combined with conditional logistic regressions were used to estimate the associations. A total of 88,904 patients were hospitalized for T2D. Short-term exposures to all six air pollutants above except for ozone were significantly associated with the risk of hospitalization for T2D and both subclasses. An interquartile range increase in the concentrations of PM_2.5, PM₁₀, NO₂, SO₂, and CO at lag 0-2 d was associated with higher hospitalization risk of T2D by 1.71% (95%CI: 0.56%, 2.87%), 2.08% (0.88%, 3.29%), 4.85% (3.29%, 6.44%), 2.44% (1.22%, 3.67%) and 2.55% (1.24%, 3.88%), respectively. The associations of T2D hospitalizations were stronger in cold season than in warm season. Air pollutants had more acute and stronger associations with T2D with complications. The exposure-response relationship curves showed no thresholds, and the slopes were larger for T2D with complications. This nationwide individual-level, case-crossover study provides the first comprehensive evidence that short-term exposure to multiple criteria air pollutants may increase the risk of hospitalizations for T2D, especially for T2D with complications.

Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review

This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden.

Ambient particulate air pollution, blood cell parameters, and effect modification by psychosocial stress: Findings from two studies in three major Chinese cities

The associations between particulate matter (PM) exposure, psychosocial stress and blood cell parameters are bringing novel insights to characterize the early damage of multiple diseases. Based on two studies conducted in three Chinses cities using cross-sectional (Beijing, 425 participants) and panel study (Tianjin and Shanghai, 92 participants with 361 repeated measurements) designs, this study explored the associations between short-term exposure to ambient PM and blood cell parameters, and the effect modification by psychosocial stress. Increasing PM_2.5 exposure was significantly associated with decreases in red blood cell (RBC) count and mean corpuscular hemoglobin concentration (MCHC), and increases in mean corpuscular volume (MCV), platelets count (PLT) and platelet hematocrit (PCT) in both studies. For instance, a 10 μg/m³ increment in PM_2.5 concentration was associated with a 1.04% (95%CI: 0.16%, 1.92%) increase in PLT (4-d) and a 1.09% (95%CI: 0.31%, 1.87%) increase in PCT (4-d) in the cross-sectional study, and a 0.64% (95%CI: 0.06%, 1.22%) increase in PLT (1-d) and a 0.72% (95%CI: 0.33%, 1.11%) increase in PCT (1-d) in the panel study, respectively. In addition, stronger increases in MCV, PLT, and PCT associated with PM_2.5 exposure were found in higher psychosocial stress group compared to lower psychosocial stress group (p for interaction <0.10), indicating that blood cell parameters of individuals with higher psychosocial stress might be more susceptible to the early damages of PM_2.5 exposure.

Outpatient Department Visits and Mortality with Various Causes Attributable to Ambient Air Pollution in the Eastern Economic Corridor of Thailand

The Eastern Economic Corridor in Thailand is undergoing development, but industrial activities are causing serious air pollution. This study aimed to examine the effects of particulate matter (PM₁₀), fine particulate matter (PM_2.5), SO₂, NO₂, O₃, and CO on outpatient department (OPD) visits and mortality with various causes in the Eastern Economic Corridor, Thailand between 2013 and 2019 using a case-crossover design and conditional Poisson model. The corresponding burden of disease due to air pollution exposure was calculated. A 1 µg/m³ increase in the PM₁₀ was associated with significant increases in OPD visits for circulatory diseases (0.22, 95% CI 0.01, 0.34), respiratory diseases (0.21, 95% CI 0.13, 0.28), and skin and subcutaneous tissue diseases (0.18, 95% CI 0.10, 0.26). By contrast, a 1 µg/m³ increase in the PM₁₀ was associated with significant increases in mortality from skin and subcutaneous tissue diseases (0.79, 95% CI 0.04, 1.56). A 1 µg/m³ increase in PM_2.5 was associated with significant increases in mortality from circulatory diseases (0.75, 95% CI 0.20, 1.34), respiratory diseases (0.82, 95% CI 0.02, 1.63), and skin and subcutaneous tissue diseases (2.91, 95% CI 0.99, 4.86). The highest OPD burden was for circulatory diseases. Respiratory effects were attributed to PM₁₀ exceeding the national ambient air quality standards (NAAQS) of Thailand (120 μg/m³). The highest morbidity burden was for skin and subcutaneous tissue diseases attributed to PM_2.5 concentrations that exceeded the NAAQs (50 μg/m³). PM pollution in the EEC could strongly contribute to OPD visits and morbidity from various diseases. Preventing PM₁₀ concentrations from being higher than 60 µg/m³ could decrease OPD visits by more than 33,265 and 29,813 for circulatory and respiratory diseases, respectively. Our study suggests that such pollution increases the risks of OPD visits and mortality in various causes in the Thai EEC. Reducing the ambient air pollution concentration of NAAQSs in Thailand could reduce the health effect on the Thai population.

Antioxidant Effects of Korean Propolis in HaCaT Keratinocytes Exposed to Particulate Matter 10

Air pollution causes oxidative stress that leads to inflammatory diseases and premature aging of the skin. The purpose of this study was to examine the antioxidant effect of Korean propolis on oxidative stress in human epidermal HaCaT keratinocytes exposed to particulate matter with a diameter of less than 10 μm (PM₁₀). The total ethanol extract of propolis was solvent-fractionated with water and methylene chloride to divide into a hydrophilic fraction and a lipophilic fraction. The lipophilic fraction of propolis was slightly more cytotoxic, and the hydrophilic fraction was much less cytotoxic than the total extract. The hydrophilic fraction did not affect the viability of cells exposed to PM₁₀, but the total propolis extract and the lipophilic fraction aggravated the toxicity of PM₁₀. The total extract and hydrophilic fraction inhibited PM₁₀-induced ROS production and lipid peroxidation in a concentration-dependent manner, whereas the lipophilic fraction did not show such effects. High-performance liquid chromatography with photodiode array detection (HPLC-DAD) analysis showed that the hydrophilic fraction contained phenylpropanoids, such as caffeic acid, p-coumaric acid, and ferulic acid, whereas the lipophilic faction contained caffeic acid phenethyl ester (CAPE). The former three compounds inhibited PM₁₀-induced ROS production, lipid peroxidation, and/or glutathione oxidation, and ferulic acid was the most effective among them, but CAPE exhibited cytotoxicity and aggravated the toxicity of PM₁₀. This study suggests that Korean propolis, when properly purified, has the potential to be used as a cosmetic material that helps to alleviate the skin toxicity of air pollutants.

Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

The growing burden of eye disease worldwide has aroused increasing concern upon its environmental etiology. This study aims to evaluate the associations of air pollutants with emergency room visits for eye diseases and the effect modification by temperature. Based on 24,389 cases from a general hospital during 2014-2019 in Beijing, China, this study used generalized additive models to examine the associations of air pollutants and emergency room visits for total eye diseases (ICD10: H00-H59) and conjunctivitis (ICD10: H10). Short-term exposures to PM_2.5, PM₁₀, CO, and NO₂ were associated with increased visits for total eye diseases and conjunctivitis, and stronger effect estimates were observed in high (>75th) temperature group for PM_2.5, PM₁₀, CO, and NO₂ and low (<75th) temperature group for CO and NO₂. For instance, a 10 μg/m³ increase in PM_2.5 at lag0-1 were associated with a 0.73% (95% CI: 0.23%, 1.24%) increase in total eye disease visits and a 1.34% (95% CI: 0.55%, 2.13%) increase in conjunctivitis visits, respectively. Meanwhile, a 10 μg/m³ increase in PM_2.5 was associated with a 1.57% (95% CI: 0.49%, 2.64%) change in high temperature group and a 0.48% (95% CI: -0.24%, 1.19%) change in medium temperature group (P for interaction = 0.04) in total eye disease visits. Our study emphasizes the importance of controlling the potential hazards of air pollutants on eyes, especially on days with relatively higher or colder temperature.

Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring

Despite ample evidence that high levels of particulate matter (PM) are associated with increased emergency visits related to respiratory diseases, little has been understood about how prediction processes could be improved by incorporating real-time data from multipoint monitoring stations. While previous studies use traditional statistical models, this study explored the feasibility of deep learning algorithms to improve the accuracy of predicting daily emergency hospital visits by tracking their spatiotemporal association with PM concentrations. We compared the predictive accuracy of the models based on PM datasets collected between 1 December 2019 and 31 December 2021 from a single but more accurate air monitoring station in each district (Air Korea) and multiple but less accurate monitoring sites (Korea Testing & Research Institute; KTR) within Guro District in Seoul, South Korea. We used MLP (multilayer perceptron) to integrate PM data from multiple locations and then LSTM (long short-term memory) models to incorporate the intrinsic temporal PM trends into the learning process. The results reveal evidence that predictive accuracy is improved from 1.67 to 0.79 in RMSE when spatial variations of air pollutants from multi-point stations are incorporated in the algorithm as a 9-day time window. The findings suggest guidelines on how environmental and health policymakers can arrange limited resources for emergency care and design ambient air monitoring and prevention strategies.

Association between ozone exposure and prevalence of mumps: a time-series study in a Megacity of Southwest China

In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O₃) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O₃ exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O₃ exposure on mumps was mainly manifested in the lag of 0-7 days. The single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 μg/m³ in the O₃ exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O₃ exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.

Siegesbeckiae Herba Extract and Chlorogenic Acid Ameliorate the Death of HaCaT Keratinocytes Exposed to Airborne Particulate Matter by Mitigating Oxidative Stress

Airborne particulate matter with a size of 10 μm or less (PM₁₀) can cause oxidative damages and inflammatory reactions in the skin. This study was conducted to discover natural products that are potentially useful in protecting the skin from PM₁₀. Among the hot water extracts of a total of 23 medicinal plants, Siegesbeckiae Herba extract (SHE), which showed the strongest protective effect against PM₁₀ cytotoxicity, was selected, and its mechanism of action and active constituents were explored. SHE ameliorated PM₁₀-induced cell death, lactate dehydrogenase (LDH) release, lipid peroxidation, and reactive oxygen species (ROS) production in HaCaT cells. SHE decreased the expression of KEAP1, a negative regulator of NRF2, and increased the expression of NRF2 target genes, such as HMOX1 and NQO1. SHE selectively induced the enzymes involved in the synthesis of GSH (GCL-c and GCL-m), the regeneration of GSH (GSR and G6PDH), and GSH conjugation of xenobiotics (GSTκ1), rather than the enzymes that directly scavenge ROS (SOD1, CAT, and GPX1). SHE increased the cellular content of GSH and mitigated the oxidation of GSH to GSSG caused by PM₁₀ exposure. Of the solvent fractions of SHE, the n-butyl alcohol (BA) fraction ameliorated cell death in both the absence and presence of PM₁₀. The BA fraction contained a high amount of chlorogenic acid. Chlorogenic acid reduced PM₁₀-induced cell death, LDH release, and ROS production. This study suggests that SHE protects cells from PM₁₀ toxicity by increasing the cellular antioxidant capacity and that chlorogenic acid may be an active phytochemical of SHE.

Associations between Dust Exposure and Hospitalizations in El Paso, Texas, USA

The Southwestern USA has been identified as one of the most persistent dust-producing regions of North America, where exposure to inhalable particulate matter (PM10) originating from desertic landscape during dust events/dust exposures (DEs) can reach hazardous levels. El Paso, Texas’s ambient air has reached hazardous levels of PM10 from dust with near zero visibility due to these natural events originating in the surrounding Chihuahuan Desert. The aim of this study was to investigate whether dust exposures in El Paso (generally acute, short-term exposures from nearby source areas) are associated with significant increases in hospitalizations on the day of the exposure and up to seven days afterwards. Using a Poisson regression, it was found that the relative risks of hospitalizations due to a variety of conditions were associated with dust exposures (through increases of 100 μg/m3 maximum hourly PM10 and/or increases of 4.5 m/s maximum hourly wind speed) in El Paso County, Texas between 2010 and 2014. Valley fever, coronary atherosclerosis, genitourinary diseases, neurodegenerative diseases, injury and poisoning, circulatory system conditions, respiratory system diseases, births, septicemia, Associated Diseases (the aggregation of hospital admissions for all causes, each associated with at least 5% of hospitalizations), and all ICD-9 admissions were significantly positively associated with dust exposures, indicated from higher to lower significant risk, at different lag periods after exposure. These findings, showing that an association does exist between dust exposures and hospitalizations, have important implications for residents of the world’s dryland cities.

Characteristics of Particulate Matter at Different Pollution Levels in Chengdu, Southwest of China

Air pollution is becoming increasingly serious along with social and economic development in the southwest of China. The distribution characteristics of particle matter (PM) were studied in Chengdu from 2016 to 2017, and the changes of PM bearing water-soluble ions and heavy metals and the distribution of secondary ions were analyzed during the haze episode. The results showed that at different pollution levels, heavy metals were more likely to be enriched in fine particles and may be used as a tracer of primary pollution sources. The water-soluble ions in PM2.5 were mainly Sulfate-Nitrate-Ammonium (SNA) accounting for 43.02%, 24.23%, 23.50%, respectively. SO42−, NO3−, NH4+ in PM10 accounted for 34.56%, 27.43%, 19.18%, respectively. It was mainly SO42− in PM at Clean levels (PM2.5 = 0~75 μg/m3, PM10 = 0~150 μg/m3), and mainly NH4+ and NO3− at Light-Medium levels (PM2.5 = 75~150 μg/m3, PM10 = 150~350 μg/m3). At Heavy levels (PM2.5 = 150~250 μg/m3, PM10 = 350~420 μg/m3), it is mainly SO42− in PM2.5, and mainly NH4+ and NO3− in PM10. The contribution of mobile sources to the formation of haze in the study area was significant. SNA had significant contributions to the PM during the haze episode, and more attention should be paid to them in order to improve air quality.

An investigation into the impact of variations of ambient air pollution and meteorological factors on lung cancer mortality in Yangtze River Delta

Lung cancer (LC) mortality, as one of the top cancer deaths in China, has been associated with increased levels of exposure to ambient air pollutants. In this study, different lag times on weekly basis were applied to study the association of air pollutants (PM2.5, PM10, and NO2) and LC mortality in Ningbo, and in subpopulations at different age groups and genders. Furthermore, seasonal variations of pollutant concentrations and meteorological variables (temperature, relative humidity, and wind speed) were analysed. A generalised additive model (GAM) using Poisson regression was employed to estimate the effect of single pollutant model on LC mortality in Yangtze River Delta using Ningbo as a case study. It was reported that there were statistically significant relationships between lung cancer mortality and air pollutants. Increases of 6.2% (95% confidence interval [CI]: 0.2% to 12.6%) and 4.3% (95% CI: 0.1% to 8.5%) weekly total LC mortality with a 3-week lag time were linked to each 10 μg/m³ increase of weekly average PM_2.5 and PM₁₀ respectively. The association of air pollutants (PM_2.5, PM₁₀ and NO₂) and LC mortality with a 3-week lag time was also found statistically significant during periods of low temperature (T < 18 °C), low relative humidity (H < 73.7%) and low wind speed (u < 2.8 m/s), respectively. The female population was found to be more susceptible to the exposure to air pollution than the male population. In addition, the population with an age of 50 years or above was shown to be more sensitive to ambient air pollutant. These outcomes indicated that increased risk of lung cancer mortality was evidently linked to exposure to ambient air pollutant on a weekly basis. The impact of weekly variation on the LC mortality and air pollutant levels should be considered in air pollution-related health burden analysis.

Short-Term Exposure to Ambient Air Pollution and Increased Emergency Room Visits for Skin Diseases in Beijing, China

Skin diseases have become a global concern. This study aims to evaluate the associations between ambient air pollution and emergency room visits for skin diseases under the background of improving air quality in China. Based on 45,094 cases from a general hospital and fixed-site monitoring environmental data from 2014–2019 in Beijing, China, this study used generalized additive models with quasi-Poisson regression to estimate the exposure–health associations at lag 0–1 to lag 0–7. PM_2.5 and NO₂ exposure were associated with increased emergency room visits for total skin diseases (ICD10: L00-L99). Positive associations of PM_2.5, PM₁₀, O₃ and NO₂ with dermatitis/eczema (ICD-10: L20–30), as well as SO₂ and NO₂ with urticaria (ICD-10: L50) visits were also found. For instance, a 10 μg/m³ increase in PM_2.5 was associated with increases of 0.7% (95%CI: 0.2%, 1.2%) in total skin diseases visits at lag 0–5 and 1.1% (95%CI: 0.6%, 1.7%) in dermatitis/eczema visits at lag 0–1, respectively. For PM_2.5, PM₁₀ and CO, stronger annual associations were typically observed in the high-pollution (2014) and low-pollution (2018/2019) years. For instance, a 10 μg/m³ increase in PM_2.5 at lag 0–5 was associated with increases of 1.8% (95%CI: 1.0%, 2.6%) and 2.3% (95%CI: 0.4%, 4.3%) in total skin disease visits in 2014 and 2018, respectively. Our study emphasizes the necessity of controlling the potential health hazard of air pollutants on skin, although significant achievements in air quality control have been made in China.

The effect of consecutive ambient air pollution on the hospital admission from chronic obstructive pulmonary disease in the Chengdu region, China

Hospitalisation risks for chronic obstructive pulmonary disease (COPD) have been attributed to ambient air pollution worldwide. However, a rise in COPD hospitalisations may indicate a considerable increase in fatality rate in public health. The current study focuses on the association between consecutive ambient air pollution (CAAP) and COPD hospitalisation to offer predictable early guidance towards estimates of COPD hospital admissions in the event of consecutive exposure to air pollution. Big data analytics were collected from 3-year time series recordings (from 2015 to 2017) of both air data and COPD hospitalisation data in the Chengdu region in China. Based on the combined effects of CAAP and unit increase in air pollutant concentrations, a quasi-Poisson regression model was established, which revealed the association between CAAP and estimated COPD admissions. The results show the dynamics and outbreaks in the variations in COPD admissions in response to CAAP. Cross-validation and mean squared error (MSE) are applied to validate the goodness of fit. In both short-term and long-term air pollution exposures, Z test outcomes show that the COPD hospitalisation risk is greater for men than for women; similarly, the occurrence of COPD hospital admissions in the group of elderly people (> 65 years old) is significantly larger than that in lower age groups. The time lag between the air quality and COPD hospitalisation is also investigated, and a peak of COPD hospitalisation risk is found to lag 2 days for air quality index (AQI) and PM₁₀, and 1 day for PM_2.5. The big data-based predictive paradigm would be a measure for the early detection of a public health event in post-COVID-19. The study findings can also provide guidance for COPD admissions in the event of consecutive exposure to air pollution in the Chengdu region.

Determining the effects of socioeconomic and environmental determinants on chronic obstructive pulmonary disease (COPD) mortality using geographically and temporally weighted regression model across Xi'an during 2014-2016

Numerous methods have been implemented to evaluate the relationship between environmental factors and respiratory mortality. However, the previous epidemiological studies seldom considered the spatial and temporal variation of the independent variables. The present study aims to detect the relations between respiratory mortality and related affecting factors across Xi'an during 2014-2016 based on a novel geographically and temporally weighted regression model (GTWR). Meanwhile, the ordinary least square (OLS) and the geographically weighted regression (GWR) models were developed for cross-comparison. Additionally, the spatial autocorrelation and Hot Spot analysis methods were conducted to detect the spatiotemporal dynamic of respiratory mortality. Some important outcomes were obtained. Socioeconomic and environmental determinants represented significant effects on respiratory diseases. The respiratory mortality exhibited an obvious spatial correlation feature, and the respiratory diseases tend to occur in winter and rural areas of the study area. The GTWR model outperformed OLS and GWR for determining the relations between respiratory mortality and socioeconomic as well as environmental determinants. The influence degree of anthropic factors on COPD mortality was higher than natural factors, and the effects of independent variables on COPD varied timely and locally. The results can supply a scientific basis for respiratory disease controlling and health facilities planning.

Fine and coarse particulate matter, trace element content, and associated health risks considering respiratory deposition for Ergene Basin, Thrace

Ergene Basin is located in Thrace, Turkey, where industries are densely populated. This study aimed to determine exposure of people living in Ergene Basin (Çorlu and Çerkezköy) to fine and coarse PM, and its potentially toxic element (PTE) content by considering variation in respiratory airway deposition rates with daily activities and PM particle size by employing deposition models of International Commission on Radiological Protection and Multiple Path Particle Dosimetry. Fine and coarse PM samples were collected daily for a year at points in Çorlu and Çerkezköy representing urban and industrial settings, respectively. A questionnaire survey was conducted in the study area to obtain time-activity budgets, and associated variation was included in the health risk assessment by considering time-activity-dependent inhalation rates. The studied PTEs were Al, As, Ba, Cd, Cr, Co, Mn, Ni, Pb, and Se. The mean fine and coarse PM concentrations were measured as 23 and 14 μg/m³ in Çorlu, and 22 and 12 μg/m³ in Çerkezköy, respectively. The only PTE that exceeded acceptable risk in terms of total carcinogenic risk was Cr. Non-carcinogenic risks of all the PTEs including Cr were below the threshold. The use of deposition fractions in the health risk assessment (HRA) calculations was found to prevent overestimation of health risks by at least 91% and 87% for fine and coarse PM, respectively, compared to the regular HRA. Minor differences in risk between Çorlu and Çerkezköy suggest that urban pollution sources could be at least as influential on human health as industrial sources.

Public Health Considerations for PM10 in a High-Pollution Megacity: Influences of Atmospheric Condition and Land Coverage

This paper analyzes the PM10 concentrations and influences of atmospheric condition (AC) and land coverage (LC) on a high-pollution megacity (Bogota, Colombia) from a public health viewpoint. Information of monitoring stations equipped with measuring devices for PM10/temperature/solar-radiation/wind-speed were used. The research period lasted eight years (2007–2014). AC and LC were determined after comparing daily PM10 concentrations (DPM10) to reference limits published by the World Health Organization (WHO). ARIMA models for DPM10 were also developed. The results indicated that urban sectors with lower atmospheric instability (AI) had a 2.85% increase in daily mortality (DM) in relation to sectors with greater AI. In these sectors of lower AI, impervious LC predominated, instead of vegetated LC. An ARIMA analysis revealed that a greater extent of impervious LC around a station led to a greater effect on previous days’ DPM10 concentrations. Extreme PM10 episodes persisted for up to two days. Extreme pollution episodes were probably also preceded by low mixing-layer heights (between 722–1085 m). The findings showed a 13.0% increase in WHO standard excesses (PE) for each 10 µg/m3 increase in DPM10, and a 0.313% increase in DM for each 10% increase in PE. The observed average reduction of 14.8% in DPM10 (−0.79% in DM) was probably due to 40% restriction of the traffic at peak hours.

Intraday effects of outdoor air pollution on acute upper and lower respiratory infections in Australian children

Children's respiratory health are particularly vulnerable to outdoor air pollution, but evidence is lacking on the very acute effects of air pollution on the risk of acute upper respiratory infections (AURI) and acute lower respiratory infections (ALRI) in children. This study aimed to evaluate the risk of cause-specific AURI and ALRI, in children within 24 h of exposure to air pollution. We obtained data on emergency cases, including 11,091 AURI cases (acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and unspecified acute upper respiratory infections) and 11,401 ALRI cases (pneumonia, acute bronchitis, acute bronchiolitis, unspecified acute lower respiratory infection) in Brisbane, Australia, 2013-2015. A time-stratified case-crossover analysis was used to examine the hourly association of AURI and ALRI with high concentration (95th percentile) of four air pollutants (particulate matters with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM_2.5), ozone (O₃), nitrogen dioxide (NO₂)). We observed increased risk of acute tonsillitis associated with PM_2.5 within 13-24 h (odds ratio (OR), 1.45; 95% confidence interval [CI], 1.02-2.06) and increased risk of unspecified acute upper respiratory infections related to O₃ within 2-6 h (OR, 1.38, 95%CI, 1.12-1.70), NO₂ within 1 h (OR, 1.19; 95%CI, 1.01-1.40), and PM_2.5 within 7-12 h (OR, 1.21; 95%CI, 1.02-1.43). Cold season and nigh-time air pollution has greater effects on AURI, whereas greater risk of ALRI was seen in warm season and daytime. Our findings suggest exposures to particulate and gaseous air pollution may transiently increase risk of AURI and ALRI in children within 24 h. Prevention measures aimed at protecting children's respiratory health should consider the very acute effects of air pollution.

Association Between Consecutive Ambient Air Pollution and Chronic Obstructive Pulmonary Disease Hospitalization: Time Series Study During 2015-2017 in Chengdu China

This paper investigates the association between consecutive ambient air pollution and Chronic Obstructive Pulmonary Disease (COPD) hospitalization in Chengdu China. The three-year (2015-2017) time series data for both ambient air pollutant concentrations and COPD hospitalizations in Chengdu are approved for the study. The big data statistic analysis shows that Air Quality Index (AQI) exceeded the lighted air polluted level in Chengdu region are mainly attributed to particulate matters (i.e., PM_2.5 and PM₁₀). The time series study for consecutive ambient air pollutant concentrations reveal that AQI, PM_2.5, and PM₁₀ are significantly positive correlated, especially when the number of consecutive polluted days is greater than nine days. The daily COPD hospitalizations for every 10 μg/m³ increase in PM_2.5 and PM₁₀ indicate that consecutive ambient air pollution can lead to an appearance of an elevation of COPD admissions, and also present that dynamic responses before and after the peak admission are different. Support Vector Regression (SVR) is then used to describe the dynamics of COPD hospitalizations to consecutive ambient air pollution. These findings will be further developed for region specific, hospital early notifications of COPD in responses to consecutive ambient air pollution.

Association between NO2 cumulative exposure and influenza prevalence in mountainous regions: A case study from southwest China

While accumulating evidence shows that air pollution exposure is an important risk factor to influenza prevalence, their association has been inadequately investigated in mountainous regions with dense populations and high humidity. We aim to estimate the association and exposure-outcome effects between exposure to nitrogen dioxide (NO₂) and influenza prevalence in a mountainous region with a dense population and high humidity. We investigated 14,993 patients with confirmed influenza cases from January 2013 to December 2017 in Chongqing, a mountainous city in southwest China. We developed distributed lag non-linear models with quasi-Poisson link to take into account the lag and non-linear effects of NO₂ exposure on influenza prevalence. We estimated that the cumulative effect of a 10 μg/m³ increase in NO₂ with seven-day lag (i.e., summing all the contributions up to seven days) corresponded to relative risk of 1.24 (95% CI: 1.17-1.31) in daily influenza prevalence. Comparing to annual mean of the World Health Organization air quality guidelines of 40 μg/m³ for NO₂, we estimated that 14.01% (95% CI: 10.69-17.08%) of the influenza cases were attributable to excessive NO₂ exposure. Our results suggest that NO₂ exposure could worsen the risk of influenza infection in this mountainous city, filling the gap of relevant researches in densely populated and mountainous cities. Our findings provide evidence for developing influenza surveillance and early warning systems.

Particulate matter pollution and hospital outpatient visits for endocrine, digestive, urological, and dermatological diseases in Nanjing, China

Clinical or pathological evidence demonstrated that air pollution could undermine other organ systems of human body besides respiratory and circulation systems. Investigations that directly relate hospital outpatient visits for endocrine (ENDO), digestive (DIGE), urological (UROL), and dermatological (DERM) diseases categories with ambient particulate matter (PM) are still lacking, particularly in heavily polluted cities. Here, we conducted a time-series analysis using 812,624, 1,111,342, 539,803, and 741,662 hospital visits for ENDO, DIGE, UROL, and DERM, respectively, in Nanjing, China from 2013 to 2019. A generalized additive model was applied to estimate the exposure-response associations. Results showed that a 10 μg/m³ increase in PM_2.5 concentration on lag 0 day was significantly associated with 0.59% (95% CI: 0.30%, 0.88%), 0.43% (0.15%, 0.70%), 0.36% (0.06%, 0.66%), and 0.65% (0.42%, 0.87%) increase for ENDO, DIGE, UROL, and DERM hospital visits, respectively. The estimated effects of PM₁₀ were slightly smaller but still statistically significant. The magnitude and significance of the associations between PM and four health outcomes were sensitive to additional adjustment for co-pollutants. Exposure-response relationships were linear for PM concentrations lower than 100 μg/m³ but the curves became nonlinear across the full range of exposures due to a flatten slope at higher concentrations. We also explored the effect modifications by season (cold or warm), age (5-18, 18-64, 65-74, or 75+ years), and sex (male or female). Results showed that the DERM-related population aged 65 years or older was more vulnerable to PM exposure, compared with the 5 to 17-year age group; the DERM-related population aged 75 years or older and 65 years or older was more vulnerable to PM_2.5 and PM₁₀ exposure, respectively, compared with the 18 to 64-year age group. Our study provided suggestive evidence that ambient PM pollution was associated with ENDO, DIGE, UROL, and DERM outpatient hospital visits in Nanjing, China.

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

Background

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

Methods

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

Results

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

Conclusion

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

Examining health disparities and characteristics in general practice utilization: based on outpatient data from 2014 - 2018 in Shanghai

BACKGROUND

Since 2000, China has been developing primary care institutions to serve as the gateway to the healthcare system. However, the investment of resources in primary care institutions is not based on the actual medical demands of the public. This study analysed primary care utilization to provide targeted guidance for the improvement of primary healthcare delivery in China.

METHODS

We extracted outpatient visit data from all community healthcare centres in Shanghai from 2014 to 2018. Diseases were then classified according to ICD-10 codes. The disease spectrum (frequency, proportion, rank) was stratified by sex, age, and region.

RESULTS

Most primary care outpatients were female (58.20%), 60-79 years old (57.91%), and in suburban regions (62.18%). Chronic diseases accounted for the majority (91.41%). Hypertension, chronic ischaemic heart disease, diabetes, and acute upper respiratory tract infections were the top four disorders for primary care visits regardless of sex. In the group aged 0-18 years, symptoms, signs and abnormal clinical and laboratory findings not elsewhere classified accounted for 37.96% of the top 20 reasons. Acute upper respiratory tract infections were the most common diseases in the groups aged 0-18 (11.20%) and 19-39 (11.14%) years. However, hypertension was the most common disease in the group aged > 39 years old (> 20%). There were more outpatients with respiratory and digestive diseases in suburban areas than in urban areas. In addition, problems associated with medical equipment and other healthcare deficiencies were relatively more common in suburban areas (suburban: 4.13%, rank 5; urban: 2.29%, rank 10).

CONCLUSIONS

To meet the patients' needs and to develop the primary care system, the Shanghai government should focus on diseases with regionally high proportions. Disease diagnosis and treatment should be improved in the younger and suburban populations.

Occupational exposure to particulate matter from air pollution in the outdoor workplaces in Almaty during the cold season

Background

A large fraction of population in Almaty and other Kazakhstan cities is employed in the outdoor jobs and likely exposed to high levels of particulate matter (PM) during the cold season. The magnitude of such occupational exposure remains unknown; therefore, the aim was to quantify the levels of exposure to PM₁₀ in the outdoor workplaces in Almaty in order to guide future interventions of primary prevention.

Epidemiological and time series analysis of haemorrhagic fever with renal syndrome from 2004 to 2017 in Shandong Province, China

Shandong Province is an area of China with a high incidence of haemorrhagic fever with renal syndrome (HFRS); however, the general epidemic trend of HFRS in Shandong remains unclear. Therefore, we established a mathematical model to predict the incidence trend of HFRS and used Joinpoint regression analysis, a generalised additive model (GAM), and other methods to evaluate the data. Incidence data from the first half of 2018 were included in a range predicted by a modified sum autoregressive integrated moving average-support vector machine (ARIMA-SVM) combination model. The highest incidence of HFRS occurred in October and November, and the annual mortality rate decreased by 7.3% (p < 0.05) from 2004 to 2017. In cold months, the incidence of HFRS increased by 4%, −1%, and 0.8% for every unit increase in temperature, relative humidity, and rainfall, respectively; in warm months, this incidence changed by 2%, −3%, and 0% respectively. Overall, HFRS incidence and mortality in Shandong showed a downward trend over the past 10 years. In both cold and warm months, the effects of temperature, relative humidity, and rainfall on HFRS incidence varied. A modified ARIMA-SVM combination model could effectively predict the occurrence of HFRS.

The association between short-term exposure to ambient air pollution and the incidence of mumps in Wuhan, China: A time-series study

BACKGROUND

Previous studies have estimated the association between meteorological factors and mumps outbreaks without assessing the influence of air pollution. In this research, we explored the effects of short-term exposure to air pollution on the incidence of mumps.

METHODS

Our time-series analysis was conducted using data collected in Wuhan, China from 2015 to 2017. Daily number of mumps cases was obtained from Disease Reporting System in Hubei Provincial Center for Disease Control and Prevention. Data on air pollution was obtained from 10 national air quality monitoring stations, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ground-level ozone (O₃), particulate matter less than or equal to 10 μm in aerodynamic diameter (PM₁₀), and particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM_2.5). Daily meteorological data including temperature and relative humidity were obtained from Hubei Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to explore the association between the incidence of mumps and exposure to air pollution.

RESULTS

We observed that the effects of air pollutants were statistically significant mainly in two periods, lag 0 to lag 5 and lag 20 to lag 25, with the strongest effects appearing at lag 2 and lag 23. The cumulative effects were stronger than single-day lag effects. The stratified analysis showed the effect of pollutants during the hot season was stronger than that during the cold season, especially for NO₂ and SO₂.

CONCLUSIONS

We found that exposure to NO₂ and SO₂ was significantly associated with higher risk of developing mumps. Our findings could help deepen the understanding of how air pollution exposure affects the incidence of mumps.

Skin inflammation induced by ambient particulate matter in China

Most published studies on particulate matter (PM) concerning PM_2.5 and PM₁₀ have focused on PM-induced effects on the respiratory system (particularly lung) and cardiovascular system effects. However, epidemiological and mechanistic studies suggest that PM_2.5 and PM₁₀ also affects the skin, which is a key health issue. In this study, we first reviewed the current status of PM_2.5 and PM₁₀ in China, including relevant regulations, concentration levels, chemical components, and emission sources. Next, we summarized the association between PM_2.5 and PM₁₀ or its representative components, in relation to skin inflammation as well as inflammatory skin diseases, such as atopic dermatitis, acne, eczema, and skin aging. Finally, we determined the mechanism of oxidative stress or programmed cell death induced through PM, which can provide useful information for future research on PM-induced skin inflammation.