The joint effect of ambient air pollution and agricultural pesticide exposures on lung function among children with asthma

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Recent Insights into the Environmental Determinants of Childhood Asthma

PURPOSE OF REVIEW

Ubiquitous environmental exposures, including ambient air pollutants, are linked to the development and severity of childhood asthma. Advances in our understanding of these links have increasingly led to clinical interventions to reduce asthma morbidity.

RECENT FINDINGS

We review recent work untangling the complex relationship between air pollutants, including particulate matter, nitrogen dioxide, and ozone and asthma, such as vulnerable windows of pediatric exposure and their interaction with other factors influencing asthma development and severity. These have led to interventions to reduce air pollutant levels in children's homes and schools. We also highlight emerging environmental exposures increasingly associated with childhood asthma. Growing evidence supports the present threat of climate change to children with asthma. Environmental factors play a large role in the pathogenesis and persistence of pediatric asthma; in turn, this poses an opportunity to intervene to change the course of disease early in life.

Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

The joint effect of cumulative doses for outdoor air pollutants exposure in early life on asthma and wheezing among young children

BACKGROUND

Constrained by no proper way to assess cumulative exposure, the joint effect of air pollution cumulative exposure doses on childhood asthma and wheezing (AW) was not understood.

OBJECTIVE

To assess the association between cumulative exposure to multiple air pollutants in early life and childhood AW.

METHODS

We designed a nested case-control study based on the birth cohort in Jinan City. Children with AW followed up within 2 years after birth were treated as cases, and non-cases in this cohort were treated as the control source population, and the propensity score matching method was used to match each case to 5 controls. We calculated the individual cumulative outdoor exposure doses for each period using an inverse distance weighted model, alongside the complex Simpson's formula, accounting for outdoor time and respiratory volume. The Least absolute shrinkage and selection operator (Lasso) regression was performed to screen for covariates. To analyze the joint effects of pollutants, we employed the weighted quantile sum (WQS) regression model in conjunction with conditional logistic regression.

RESULTS

84 cases and 420 controls were included in this study. The odds ratio (OR) with 95% confidence interval (CI) of the impact of cumulative exposure (mg/m3) after birth on childhood AW was 1.78 (1.15-2.74) for SO2, 1.69 (1.11-2.57) for NO2, and 1.65 (1.09-2.52) for PM2.5, respectively. Furthermore, with each 25th percentile increase in the WQS index, the overall risk of cumulative doses for six pollutants exposure after birth on AW increased by an adjusted OR of 1.10 (1.03, 1.18), and SO2, PM2.5, and NO2 contributed the most to the WQS index. However, no statistically significant association was found between cumulative exposure to all pollutants before birth and childhood AW.

CONCLUSIONS

There was a joint effect of the cumulative exposure dose of outdoor air pollutants after birth on AW in children aged 0-2 years. And traffic-related pollutants (SO2, PM2.5, and NO2) make a greater contribution to the joint effect.

Strategies for mitigation of pesticides from the environment through alternative approaches: A review of recent developments and future prospects

Chemical-based peticides are having negative impacts on both the healths of human beings and plants as well. The World Health Organisation (WHO), reported that each year, >25 million individuals in poor nations are having acute pesticide poisoning cases along with 20,000 fatal injuries at global level. Normally, only ∼0.1% of the pesticide reaches to the intended targets, and rest amount is expected to come into the food chain/environment for a longer period of time. Therefore, it is crucial to reduce the amounts of pesticides present in the soil. Physical or chemical treatments are either expensive or incapable to do so. Hence, pesticide detoxification can be achieved through bioremediation/biotechnologies, including nano-based methodologies, integrated approaches etc. These are relatively affordable, efficient and environmentally sound methods. Therefore, alternate strategies like as advanced biotechnological tools like as CRISPR Cas system, RNAi and genetic engineering for development of insects and pest resistant plants which are directly involved in the development of disease- and pest-resistant plants and indirectly reduce the use of pesticides. Omics tools and multi omics approaches like metagenomics, genomics, transcriptomics, proteomics, and metabolomics for the efficient functional gene mining and their validation for bioremediation of pesticides also discussed from the literatures. Overall, the review focuses on the most recent advancements in bioremediation methods to lessen the effects of pesticides along with the role of microorganisms in pesticides elimination. Further, pesticide detection is also a big challenge which can be done by using HPLC, GC, SERS, and LSPR ELISA etc. which have also been described in this review.

The impact of outdoor pollution and extreme temperatures on asthma-related outcomes: A systematic review for the EAACI guidelines on environmental science for allergic diseases and asthma

Air pollution is one of the biggest environmental threats for asthma. Its impact is augmented by climate change. To inform the recommendations of the EAACI Guidelines on the environmental science for allergic diseases and asthma, a systematic review (SR) evaluated the impact on asthma-related outcomes of short-term exposure to outdoor air pollutants (PM2.5, PM10, NO2 , SO2 , O3 , and CO), heavy traffic, outdoor pesticides, and extreme temperatures. Additionally, the SR evaluated the impact of the efficacy of interventions reducing outdoor pollutants. The risk of bias was assessed using ROBINS-E tools and the certainty of the evidence by using GRADE. Short-term exposure to PM2.5, PM10, and NO2 probably increases the risk of asthma-related hospital admissions (HA) and emergency department (ED) visits (moderate certainty evidence). Exposure to heavy traffic may increase HA and deteriorate asthma control (low certainty evidence). Interventions reducing outdoor pollutants may reduce asthma exacerbations (low to very low certainty evidence). Exposure to fumigants may increase the risk of new-onset asthma in agricultural workers, while exposure to 1,3-dichloropropene may increase the risk of asthma-related ED visits (low certainty evidence). Heatwaves and cold spells may increase the risk of asthma-related ED visits and HA and asthma mortality (low certainty evidence).

Use of Transcriptomics to Reveal the Joint Immunotoxicity Mechanism Initiated by Difenoconazole and Chlorothalonil in the Human Jurkat T-Cell Line

It is very important to evaluate the immunotoxicity and molecular mechanisms of pesticides. In this study, difenoconazole and chlorothalonil were evaluated for immunotoxicity by using the human Jurkat T-cell line, and the EC50 were 24.66 and 1.17 mg/L, respectively. The joint exposure of difenoconazole and chlorothalonil showed a synergistic effect at low concentrations (lower than 10.58 mg/L) but an antagonistic effect at high concentrations (higher than 10.58 mg/L). With joint exposure at a concentration of EC10, the proportion of late apoptotic cells was 2.26- and 2.91-fold higher than that with exposure to difenoconazole or chlorothalonil alone, respectively. A transcriptomics analysis indicated that the DEGs for single exposure are associated with immunodeficiency disease. Single exposure to chlorothalonil was mainly involved in cation transportation, extracellular matrix organization, and leukocyte cell adhesion. Single exposure to difenoconazole was mainly involved in nervous system development, muscle contraction, and immune system processes. However, when the joint exposure dose was EC10, the DEGs were mainly involved in the formation of cell structures, but the DEGs were mainly involved in cellular processes and metabolism when the joint exposure dose was EC25. The results indicated that the immunotoxicological mechanisms underlying joint exposure to difenoconazole and chlorothalonil are different under low and high doses.

Socio-Environmental Determinants of Mental and Behavioral Disorders in Youth: A Machine Learning Approach

Growing evidence indicates that extreme environmental conditions in summer months have an adverse impact on mental and behavioral disorders (MBD), but there is limited research looking at youth populations. The objective of this study was to apply machine learning approaches to identify key variables that predict MBD-related emergency room (ER) visits in youths in select North Carolina cities among adolescent populations. Daily MBD-related ER visits, which totaled over 42,000 records, were paired with daily environmental conditions, as well as sociodemographic variables to determine if certain conditions lead to higher vulnerability to exacerbated mental health disorders. Four machine learning models (i.e., generalized linear model, generalized additive model, extreme gradient boosting, random forest) were used to assess the predictive performance of multiple environmental and sociodemographic variables on MBD-related ER visits for all cities. The best-performing machine learning model was then applied to each of the six individual cities. As a subanalysis, a distributed lag nonlinear model was used to confirm results. In the all cities scenario, sociodemographic variables contributed the greatest to the overall MBD prediction. In the individual cities scenario, four cities had a 24-hr difference in the maximum temperature, and two of the cities had a 24-hr difference in the minimum temperature, maximum temperature, or Normalized Difference Vegetation Index as a leading predictor of MBD ER visits. Results can inform the use of machine learning models for predicting MBD during high-temperature events and identify variables that affect youth MBD responses during these events.

The exposome concept: how has it changed our understanding of environmental causes of chronic respiratory diseases?

The exposome approach can help us better understand multifactorial respiratory diseases through multidisciplinary collaboration, harmonised resources and use of sophisticated methods addressing combined exposures and longitudinal data. https://bit.ly/3Ng9MNn.

Incorporating Bioaccessibility into Inhalation Exposure Assessment of Emamectin Benzoate from Field Spraying

The inhalation exposure of pesticide applicators and residents who live close to pesticide-treated fields is a worldwide concern in public health. Quantitative assessment of exposure to pesticide inhalation health risk highlights the need to accurately assess the bioaccessibility rather than the total content in ambient air. Herein, we developed an in vitro method to estimate the inhalation bioaccessibility of emamectin benzoate and validated its applicability using a rat plasma pharmacokinetic bioassay. Emamectin benzoate was extracted using the Gamble solution, with an optimized solid-to-liquid ratio (1/250), extraction time (24 h), and agitation (200 rpm), which obtained in vitro inhalation bioaccessibility consistent with its inhalation bioavailability in vivo (32.33%). The margin of exposure (MOE) was used to assess inhalation exposure risk. The inhalation unit exposures to emamectin benzoate of applicators and residents were 11.05-28.04 and 0.02-0.04 ng/m³, respectively, varying markedly according to the methods of application, e.g., formulations and nozzles. The inhalation risk assessment using present application methods appeared to be acceptable; however, the MOE of emamectin benzoate might be overestimated by 32% without considering inhalation bioaccessibility. Collectively, our findings contribute insights into the assessment of pesticide inhalation exposure based on bioaccessibility and provide guidance for the safe application of pesticides.

Health effects of air pollutant mixtures (volatile organic compounds, particulate matter, sulfur and nitrogen oxides) - a review of the literature

The health risks associated with individual air pollutant exposures have been studied and documented, but in real-life, the population is exposed to a multitude of different substances, designated as mixtures. A body of literature on air pollutants indicated that the next step in air pollution research is investigating pollutant mixtures and their potential impacts on health, as a risk assessment of individual air pollutants may actually underestimate the overall risks. This review aims to synthesize the health effects related to air pollutant mixtures containing selected pollutants such as: volatile organic compounds, particulate matter, sulfur and nitrogen oxides. For this review, the PubMed database was used to search for articles published within the last decade, and we included studies assessing the associations between air pollutant mixtures and health effects. The literature search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A number of 110 studies were included in the review from which data on pollutant mixtures, health effects, methods used, and primary results were extracted. Our review emphasized that there are a relatively small number of studies addressing the health effects of air pollutants as mixtures and there is a gap in knowledge regarding the health effects associated with these mixtures. Studying the health effects of air pollutant mixtures is challenging due to the complexity of components that mixtures may contain, and the possible interactions these different components may have.

The Moderating Role of Housing Quality on Concentrated Poverty and Asthma-Related Emergency Department Visits Among Hispanics/Latinos

Background. Rates of asthma-related emergency department visits have been shown to vary significantly by place (i.e., neighborhood) and race/ethnicity. The moderating factors of asthmatic events among Hispanic/Latino-specific populations are known to a much lesser degree. Objective. To assess the extent to which housing moderates the effect of poverty on Hispanic/Latino-specific asthma-related emergency department (ED) visits at an ecological level. Methods. Using data from the Office of Statewide Health Planning and Development (OSHPD) and the 2016-2017 U.S. Census, a cross-sectional ecological analysis at the census tract-level was conducted. Crosswalk files from the U.S. Department of Housing and Urban Development were used to associate zip codes to census tracts. Negative binomial regression was used to estimate rate ratios. Results. The effect of poverty on asthma-related ED visits was significantly moderated by the median year of housing structures built. The effect of mid-level poverty (RR= 1.57, 95% CI 1.27, 1.95) and high-level poverty (RR= 1.47, 95% CI 1.22, 1.78) in comparison to low-level poverty, was significantly greater among census tracts with housing built prior to 1965 in comparison to census tract with housing built between 1965-2020. Conclusion. Communities with older housing structures tend to be associated with increased Hispanic/Latino ED visits apart from affluent communities.

Interactions between microbiome and underlying mechanisms in asthma

Microbiome primes host innate immunity in utero and play fundamental roles in the development, training, and function of the immune system throughout the life. Interplay between the microbiome and immune system maintains mucosal homeostasis, while alterations of microbial community dysregulate immune responses, leading to distinct phenotypic features of immune-mediated diseases including asthma. Microbial imbalance within the mucosal environments, including upper and lower airways, skin, and gut, has consistently been observed in asthma patients and linked to increased asthma exacerbations and severity. Microbiome research has increased to uncover hidden microbial members, function, and immunoregulatory effects of bacterial metabolites within the mucosa. This review provides an overview of environmental and genetic factors that modulate the composition and function of the microbiome, and the impacts of microbiome metabolites and skin microbiota on immune regulation in asthma.

Are there joint effects of different air pollutants and meteorological factors on mental disorders? A machine learning approach

Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM_2.5, PM₁₀, O₃, SO₂, and NO₂), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients' average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m³ increase in O₃, PM_2.5 and PM₁₀ exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O₃ and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O₃ and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.

Aberrant mitochondrial DNA methylation and declined pulmonary function in a population with polycyclic aromatic hydrocarbon composition in particulate matter

Air pollution exposure has been found to be associated with epigenetic modification of the mitochondrial genome, which could subsequently induce adverse health outcomes. However, very limited studies exist regarding the association between fine particulate matter (PM_2.5) exposure and pulmonary function at the molecular level of mitochondrial epigenetic changes. This study aimed to investigate the association of platelet mitochondrial DNA (mtDNA) methylation with occupational PM_2.5 exposure and pulmonary function. First, 768 participants were occupationally exposed to polycyclic aromatic hydrocarbon (PAH)-enriched PM_2.5 in a coke-oven plant in East China. The levels of PM_2.5, PAH components bound to PM_2.5, and urinary PAH metabolites in the workplace environment were measured as an internal dose, respectively. mtDNA methylation was measured by bisulfite pyrosequencing of two genes of ATP synthase (MT-ATP6 and MT-ATP8). Mediation analysis was conducted to evaluate the role of mtDNA methylation in pulmonary alteration induced by PAH. A decreasing trend of platelet mtDNA methylation was observed with increase in PM_2.5 exposure across all participants. As an important PAH metabolite in urine, 1-hydroxypyrene (1-OHP) was significantly negatively associated with FEV1/FVC (Forced Expiratory Volume in 1s/Forced Vital Capacity) ratio. The participants with high serum folate levels (≥10 nmol/L) showed positive association between MT-ATP6 methylation and FEV1/FVC ratio. Mediation analysis suggested that MT-ATP6 methylation mediated the significant association of urinary 1-OHP with FEV1/FVC. Our findings suggested the methylation of platelet mitochondrial gene MT-ATP6 and FEV1/FVC to be negatively associated with PM exposure. Platelet mtDNA methylation acted as an intermediary between PAH exposure and lung function decline. The mitochondrial epigenetic regulation in platelets, in response to PM exposure, might be involved in subsequent progress of abnormal pulmonary function.

Co-exposure to multiple air pollutants and sleep disordered breathing in patients with or without obstructive sleep apnea: A cross-sectional study

BACKGROUND

Air pollution may be a contributing risk factor for obstructive sleep apnea (OSA). However, the health effects of co-exposure to multiple air pollutants on OSA patients remain unclear.

OBJECTIVES

To assess the joint effect of multi-pollutant on sleep disordered breathing (SDB) parameters in patients with or without OSA and identify the dominant pollutants.

METHODS

A total of 2524 outpatients from April 2020 to May 2021 were recruited in this cross-sectional study. Ambient air pollutant data were obtained from the nearest central monitoring stations to participants' residential address. SDB parameters were measured by the ApneaLink devices, including apnea-hypopnea index (AHI), hypopnea index (HI), oxygen desaturation index (ODI), average oxygen saturation (SpO₂), percentage sleep time with <90% saturation (T90), and desaturation. Bayesian kernel machine regression (BKMR) was applied to evaluate the effects of multiple pollutants.

RESULTS

Significant associations were observed between air pollutants and SDB parameters (including increases in AHI, HI, ODI, and desaturation) among patients with OSA. Co-exposure to air pollutants was positively correlated with AHI, HI, and ODI. PM₁₀ and O₃ dominated the effects of pollutant mixtures on OSA, with the highest posterior inclusion probability (PIP) values of 0.592 and 0.640, respectively. Stratified analysis showed that, compared to male patients with OSA, stronger effects on the SDB parameters were observed in female patients. Stronger associations were also found in the warm season than those in the cold season.

CONCLUSION

Co-exposure to air pollutants was associated with SDB parameters among patients with OSA, PM₁₀ and O₃ might play the dominant roles.

Pre- and postnatal exposure to multiple ambient air pollutants and child behavioral problems at five years of age

Ambient air pollution is emerging as a risk factor for adverse neurological symptoms and early childhood diseases. This study aimed to evaluate the association between pre- and postnatal exposure to air pollutants and childhood behavior by using MOCEH prospective birth cohort data. In total, 353 mother-child pairs at birth, who completed child behavioral assessments using the Korean version of the Child Behavior Checklist at five years of age, were included in the study. Multivariate linear regression (MLR) for single pollutant and Bayesian kernel machine regression (BKMR) for multiple pollutants were conducted. MLR analysis showed that air pollutant exposures during the first trimester were significantly associated with the internalizing problems score after adjusting for covariates. The estimates were 0.19 (0.05-0.32) per 1 μg/m³ increase in PM_2.5, 0.13 (0.04-0.22) per 1 μg/m³ increase in PM₁₀, and 0.20 (0.02-0.37) per 1 ppb increase in NO₂. The BKMR model analysis revealed that the overall effects of multiple air pollutants during the first trimester of pregnancy and 0-6 months of the infantile period were significantly associated with behavioral problems. Boys showed a stronger associations than girls. Taken together, these results showed that the first trimester of pregnancy and 0-6 months of the infantile period were important for air pollutant exposure because exposure at these periods was associated with behavioral problems in 5-year-old children. Future efforts are required to control air pollution levels and reduce the health burden of vulnerable populations, including pregnant women and children.

Driving factors to air pollutant reductions during the implementation of intensive controlling policies in 2020 in Ulsan, South Korea

Evaluation for the controlling policy's effectiveness to mitigate criteria air pollutants (CAPs) in South Korea during December 1, 2019-March 31, 2020 is difficult because of its coincidence with the COVID-19 social distancing. In this study, we differentiated the influence of three major driving factors (intensive controlling policy by the government, meteorological conditions, and social distancing) to the CAP variation in Ulsan, the largest industrial city in South Korea. In 2013-2019, the concentrations of PM_2.5 (2015-2019), PM₁₀, SO₂, and NO₂ decreased by 6.7, 1.6, 4.2, and 3.3%/year, respectively, whereas the O₃ concentration slightly increased by 0.7%/year. Trend analysis was used to predict the CAP concentrations before (January 1-February 21) and during (February 22-March 31) the social distancing in 2020. The difference between the measured and predicted concentrations was designated as the contribution of the three factors. The controlling policy was the most important driver of the CAP reductions. In particular, its contributions were 94.1% (January 1-February 21) and 87.4% (February 22-March 31) to the PM_2.5 decrease. The change in meteorological conditions considerably affected the CAP reductions, with the highest contributions of 35.2% (January 1-February 21) and 39.2% (February 22-March 31) to the O₃ decrease. On February 22-March 31, the effects of social distancing were 1.6, 0.6, 1.3, and 1.4% to the reduction of SO₂, NO₂, PM₁₀, and PM_2.5, respectively. Overall, a decrease in the CAP concentrations was apparent during January-March 2020 in Ulsan primarily due to the intensive controlling policies, not by the COVID-19 social distancing.

Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors - mental disorders (MDs), especially for exposure to air pollution mixture. In this study, we combined deep learning neural networks (DLNNs) with SHapley Additive exPlanation (SHAP) to predict the illness risk of MDs on the population level, and then provided explanations for risk factors. The modeling system, which was trained on day-by-day hospital outpatient visits of two major hospitals in Nanjing, China from 2013/07/01 through 2019/02/28, visualized the time-varying prediction, contributing factors, and interaction effects of informative features. Our results suggested that NO₂, SO₂, and CO made outstanding contributions in magnitude of feature attributions under circumstances of mixed air pollutants. In particular, NO₂ at high concentration level was associated with an increase in illness risk of MDs, and the maximum and mean absolute SHAP value were approximated to 10 and 2 as a local and global measure of feature importance, respectively. It presented a marginally antagonistic effect for two pairs of gaseous pollutants, i.e., NO₂ vs. SO₂ and CO vs. NO₂. In contrast, CO and SO₂ displayed the opposite direction of feature effects to the rise of observed concentrations, but an apparent synergistic effect was obviously captured. The primary risk factors driving a sharp increase in acute attack or exacerbation of MDs were also identified by depicting prediction paths of time-series samples. We believe that the significance of coupling accurate predictions from DLNNs with interpretable explanations of why a prediction is completed has broad applicability throughout the field of environmental health.

Systematic Review of Ozone Effects on Human Lung Function, 2013 through 2020

Background

Ozone effects on lung function are particularly important to understand in the context of the air pollution-health outcomes epidemiologic literature, given the complex relationships between ozone and other air pollutants with known lung function effects.

Research Question

What has been learned about the association between ozone exposures and lung function from epidemiology studies published from 2013 through 2020?

Study Design and Methods

On March 18, 2018, and September 8, 2020, PubMed was searched using the terms health AND ozone, filtering to articles in English and about humans, from 2013 or later. An additional focused review searching for ozone AND (lung function OR FEV₁OR FVC) was performed June 26, 2021. Articles were selected for this review if they reported a specific relationship between a lung function outcome and ozone exposure.

Results

Of 3,271 articles screened, 53 ultimately met criteria for inclusion. A systematic review with assessment of potential for bias was conducted, but a meta-analysis was not carried out because of differences in exposure duration and outcome quantification. Consistent evidence exists of small decreases in children’s lung function, even associated with very low levels of short-term ozone exposure. The effects on adult lung function from exposure to low-level, short-term ozone are less clear, although ozone-associated decrements may occur in the elderly. Finally, long-term ozone exposure decreases both lung function and lung function growth in children, although few new studies have examined long-term ozone and lung function in adults.

Interpretation

Much of this literature involves concentrations below the current US Environmental Protection Agency’s National Ambient Air Quality Standard of 70 parts per billion over an 8-h averaging time, suggesting that this current standard may not protect children adequately from ozone-related decrements in lung function.

Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study

Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma.

Differential effects of size-specific particulate matter on lower respiratory infections in children: A multi-city time-series analysis in Sichuan, China

Evidence on the short-term effects of size-specific particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), and their difference (PM_C) on children's Lower Respiratory Infections (LRI) is scare. This study aimed to estimate the differential effects of three size-specific PM on hospitalizations of children aged <18 years for pneumonia and bronchitis in 18 cities of southwestern China. The city-specific association was firstly estimated using the over-dispersed generalized additive model and then combined to obtain the regional average association. Further, to evaluate the robustness of the key findings, subgroup analyses and co-pollutant models were constructed. PM-related risks of LRI differed by PM fractions and cause-specific LRI. A 10 μg/m³ increment in PM_2.5_lag03, PM₁₀_lag06, and PM_C_lag06 was associated with a 0.79% (95% CI: 0.29%, 1.29%), 0.77% (95% CI: 0.13%, 1.41%), and 2.33% (95% CI: 1.23%, 3.44%) increase in children's LRI hospitalizations, respectively. After adjustment for gaseous pollutants, adverse effects of the three types of size-specific PM on pneumonia hospitalizations were stable, ranging from 0.29% (95% CI: 0.05%, 0.54%) for PM_2.5-2.50% (95% CI: 1.38%, 3.64%) for PM_C. Additionally, PM_C-related risk of bronchitis hospitalizations remained stable after adjustment for gaseous pollutants. Associations of pneumonia with PM_C and PM₁₀ in infants, bronchitis with PM_2.5 in children aged 6-17 years, pneumonia and bronchitis with PM_2.5, PM_C, and PM₁₀ in children aged 1-5 years were all statistical significant. Specifically, the effects of PM_2.5 on LRI hospitalizations increased by age, with the highest effect of 1.72% (95%CI: 1.01%, 2.43%) in children aged 6-17 years. Our study provided evidence for short-term effects of different PM fractions on children LRI hospitalizations in Southwestern China, which will be useful for making and promoting policies on air quality standards in order to protect children's health.

Agriculture Development, Pesticide Application and Its Impact on the Environment

Pesticides are indispensable in agricultural production. They have been used by farmers to control weeds and insects, and their remarkable increases in agricultural products have been reported. The increase in the world's population in the 20th century could not have been possible without a parallel increase in food production. About one-third of agricultural products are produced depending on the application of pesticides. Without the use of pesticides, there would be a 78% loss of fruit production, a 54% loss of vegetable production, and a 32% loss of cereal production. Therefore, pesticides play a critical role in reducing diseases and increasing crop yields worldwide. Thus, it is essential to discuss the agricultural development process; the historical perspective, types and specific uses of pesticides; and pesticide behavior, its contamination, and adverse effects on the natural environment. The review study indicates that agricultural development has a long history in many places around the world. The history of pesticide use can be divided into three periods of time. Pesticides are classified by different classification terms such as chemical classes, functional groups, modes of action, and toxicity. Pesticides are used to kill pests and control weeds using chemical ingredients; hence, they can also be toxic to other organisms, including birds, fish, beneficial insects, and non-target plants, as well as air, water, soil, and crops. Moreover, pesticide contamination moves away from the target plants, resulting in environmental pollution. Such chemical residues impact human health through environmental and food contamination. In addition, climate change-related factors also impact on pesticide application and result in increased pesticide usage and pesticide pollution. Therefore, this review will provide the scientific information necessary for pesticide application and management in the future.