Fine Particulate Matter in Urban Environments: A Trigger of Respiratory Symptoms in Sensitive Children

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind

Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effects. This study applies the gated recurrent unit (GRU) deep learning model to predict TSP concentrations in Zabol, Iran, during the dust period of the 120-day wind (3 June - 4 October 2014). Three uncertainty quantification (UQ) techniques consisting of the blackbox metamodel, heteroscedastic regression and infinitesimal jackknife were applied to quantify the uncertainty associated with GRU model. Permutation feature importance measure (PFIM), based on the game theory, was employed for the interpretability of the predictive model's outputs. A total of 80 TSP samples were collected and were randomly divided as training (70%) and validation (30%) datasets, while eight variables were used in the TSP prediction model. Our findings showed that GRU performed very well for TSP prediction (with r and Nash Sutcliffe coefficient (NSC) values above 0.99 for both datasets, and RMSE of 57 μg m-3 and 73 μg m-3 for training and validation datasets, respectively). Among the three UQ techniques, the infinitesimal jackknife was the most accurate one, while all the observed and predicted TSP values fell within the continence limitation estimated by the model. PFIM plots showed that wind speed and air humidity were the most and least important variables, respectively, impacting the predictive model's outputs. This is the first attempt of using an interpretable DL model for TSP prediction modelling, recommending that future research should involve aspects of uncertainty and interpretability of the predictive models. Overall, UQ and interpretability techniques have a key role in reducing the impact of uncertainties during optimization and decision making, resulting in better understanding of sophisticated mechanisms related to the predictive model.

First assessment of atmospheric pollution by trace elements and particulate matter after a severe collapse of a tailings dam, Minas Gerais, Brazil: An insight into biomonitoring with Tillandsia usneoides and a public health dataset

In this study, samples of bromeliad Tillandsia usneoides (n = 70) were transplanted and exposed for 15 and 45 days in 35 outdoor residential areas in Brumadinho (Minas Gerais state, Brazil) after one of the most severe mining dam collapses in the world. Trace elements aluminum (Al), arsenic (As), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), nickel (Ni) and zinc (Zn) were quantified by atomic absorption spectrometry. Scanning electron microscope generated surface images of T. usneoides fragments and particulate matter (PM2.5, PM10 and PM > 10). Aluminum, Fe and Mn stood out from the other elements reflecting the regional geological background. Median concentrations in mg kg-1 increased (p < 0.05) between 15 and 45 days for Cr (0.75), Cu (1.23), Fe (474) and Mn (38.1), while Hg (0.18) was higher at 15 days. The exposed-to-control ratio revealed that As and Hg increased 18.1 and 9.4-fold, respectively, not showing a pattern associated only with the most impacted sites. The PM analysis points to a possible influence of the prevailing west wind on the increase of total particles, PM2.5 and PM10 in transplant sites located to the east. Brazilian public health dataset revealed increase in cases of some cardiovascular and respiratory diseases/symptoms in Brumadinho in the year of the dam collapse (1.38 cases per 1000 inhabitants), while Belo Horizonte capital and its metropolitan region recorded 0.97 and 0.37 cases, respectively. Although many studies have been carried out to assess the consequences of the tailings dam failure, until now atmospheric pollution had not yet been evaluated. Furthermore, based on our exploratory analysis of human health dataset, epidemiological studies are required to verify possible risk factors associated with the increase in hospital admissions in the study area.

The Effects of Short-Term PM2.5 Exposure on Pulmonary Function among Children with Asthma-A Panel Study in Shanghai, China

Fine particulate matter (PM_2.5) has been reported to be an important risk factor for asthma. This study was designed to evaluate the relationship between PM_2.5 and lung function among children with asthma in Shanghai, China. From 2016 to 2019, a total of 70 Chinese children aged 4 to 14 in Shanghai were recruited for this panel study. The questionnaire was used to collect baseline information, and the lung function covering forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were carried out for each child more than twice during follow-up. Meanwhile, the simultaneous daily air atmospheric pollutants and meteorological data were collected. The linear mixed effect (LME) model was used to assess the relationship between air pollutants and lung function. A significantly negative association was found between PM_2.5 and lung function in children with asthma. In the single-pollutant model, the largest effects of PM_2.5 on lung function were found for lag 0-2, with FVC and FEV1 decreasing by 0.91% [95% confidence interval (CI): -1.75, -0.07] and 1.05% (95% CI: -2.09, 0.00), respectively, for each 10 μg/m³ increase in PM_2.5. In the multi-pollution model (adjusted PM_2.5 + SO₂ + O₃), the maximum effects of PM_2.5 on FVC and FEV1 also appeared for lag 0-2, with FVC and FEV1 decreasing by 1.57% (95% CI: -2.69, -0.44) and 1.67% (95% CI: -3.05, -0.26), respectively, for each 10 μg/m³ increase in PM_2.5. In the subgroup analysis, boys, preschoolers (<6 years old) and hot seasons (May to September) were more sensitive to changes. Our findings may contribute to a better understanding of the short-term exposure effects of PM_2.5 on lung function in children with asthma.

Association between Concentration of Air Pollutants and Prevalence of Inflammatory Sinonasal Diseases: A Nationwide Cross-sectional Study

BACKGROUND

Air pollution is a serious health concern and affects inflammatory sinonasal diseases such as allergic rhinitis (AR) and chronic rhinosinusitis (CRS). Clarifying the relationship between air pollutants and upper respiratory diseases could help the patients.

OBJECTIVE

To evaluate the association between the concentration of air pollutants and the prevalence of AR and CRS among South Koreans.

METHODS

In this cross-sectional study, nationwide data were reviewed for participants of the Korean National Health and Nutrition Examination Survey (KNHANES) 2008 to 2012. Participants were surveyed with health questionnaires, examined with endoscopies by otolaryngologists, and tested with serum immunoglobulin E levels. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter with aerodynamic diameters ≤10 µm (PM₁₀) were measured in 16 areas of South Korea. Air pollutant concentrations of geographic districts were matched to each participant's residence. Logistic regression analysis was performed.

RESULTS

Among 27 863 eligible adults, 3359 and 1606 participants had AR or CRS, respectively. In multivariable logistic regression analysis for AR, PM₁₀ showed statistically significant results (odds ratio [OR] = 1.145, 95% confidence interval [CI] = 1.042-1.258). No air pollutants showed statistically significant differences in the prevalence of CRS. In AR, PM₁₀ (OR = 1.458, 95% CI = 1.201-1.770) was associated with endoscopic findings of watery rhinorrhea, whereas SO₂ (OR = 1.202, 95% CI = 1.100-1.313) was associated with pale mucosa.

CONCLUSION

The prevalence of AR was significantly associated with PM₁₀ concentration. In patients with AR, endoscopic findings of watery rhinorrhea were associated with PM₁₀. However, CRS was not associated with the air pollutant concentrations. Lower concentration of PM₁₀ might help managing the clinical symptoms in patients of AR.

The Role of Trees in Winter Air Purification on Children’s Routes to School

Air pollution is now considered to be the world’s largest environmental health threat, accounting for millions of deaths globally each year. The social group that is particularly exposed to the harmful effects of air pollution is children. Their vulnerability results from higher breathing frequency and being subject to concentration peaks just above the ground. The negative effects of ambient particulate matter also depend on the time of exposure. A daily route to school can constitute an important component of children’s physical activity, but air pollution can pose a threat to their health. Numerous studies have proved that high loads of PM can be effectively reduced by vegetation. Little is known, however, on whether vegetation can also reduce PM during leaf dormancy. In this study we investigated the role of trees in air purification during the leafless period in children’s routes to selected schools located in Warsaw during winter. The results obtained show a weak impact of the tree canopy in winter.

Effects of PM2.5 on Chronic Airway Diseases: A Review of Research Progress

The adverse effects of polluted air on human health have been increasingly appreciated worldwide. It is estimated that outdoor air pollution is associated with the death of 4.2 million people globally each year. Accumulating epidemiological studies indicate that exposure to ambient fine particulate matter (PM2.5), one of the important air pollutants, significantly contributes to respiratory mortality and morbidity. PM2.5 causes lung damage mainly by inducing inflammatory response and oxidative stress. In this paper, we reviewed the research results of our group on the effects of PM2.5 on chronic obstructive pulmonary disease, asthma, and lung cancer. And recent research progress on epidemiological studies and potential mechanisms were also discussed. Reducing air pollution, although remaining a major challenge, is the best and most effective way to prevent the onset and progression of respiratory diseases.

Associations of fine particulate matter and its constituents with airway inflammation, lung function, and buccal mucosa microbiota in children

BACKGROUND

Previous studies have suggested acute effects of ambient fine particulate matter (PM_2.5) air pollution on respiratory health among children, but evidence for PM_2.5 constituents and respiratory health were still limited.

OBJECTIVES

To investigate associations of short-term exposure to PM_2.5 and its constituents with airway inflammation, lung function, and airway microbiota in children.

METHODS

We conducted a longitudinal panel study with 3 repeated health measurements among 62 children in Shanghai, China from November 2018 to June 2019. Respiratory health was measured by fractional exhaled nitric oxide (FeNO), saliva tumor necrosis factor-α (TNF-α), lung function (forced vital capacity and forced exhaled volume in 1 s), and microbiota diversity in buccal mucosa samples. Based on the linear mixed-effect models, we applied the single-constituent models and the constituent-PM_2.5 adjustment models to examine the associations between PM_2.5 constituents and health outcomes.

RESULT

Short-term exposure to PM_2.5 was associated with higher TNF-α, FeNO levels and reduced lung function. Among all constituents, organic carbon, elemental carbon, NO₃^- and NH₄⁺ had the consistent and strongest associations with airway inflammation biomarkers and lung function parameters, followed by metallic elements. We also found short-term PM_2.5 exposure was associated with decreased diversity in buccal mucosa bacterial community and two bacterial phyla, Fusobacteria and Proteobacteria, were identified as differential microbes with PM_2.5 exposure.

CONCLUSION

Short-term exposure to PM_2.5 may impair children's respiratory health represented by higher airway inflammation, lower lung function and altered buccal mucosa microbial colonization. Organic carbon, elemental carbon, NO₃^- and NH₄⁺ may dominate these effects.

Yearly variation in characteristics and health risk of polycyclic aromatic hydrocarbons and nitro-PAHs in urban shanghai from 2010-2018

This study encompassed the regular observation of nine polycyclic aromatic hydrocarbons (PAHs) and three nitro-PAHs (NPAHs) in particulate matter (PM) in Shanghai in summer and winter from 2010 to 2018. The results showed that the mean concentrations of ƩPAHs in summer decreased by 24.7% in 2013 and 18.1% in 2017 but increased by 10.2% in 2015 compared to the data in 2010. However, the mean concentrations of ƩPAHs in winter decreased by 39.7% from 2010 (12.8 ± 4.55 ng/m³) to 2018 (7.72 ± 3.33 ng/m³), and the mean concentrations of 1-nitropyrene in winter decreased by 79.0% from 2010 (42.3 ± 16.1 pg/m³) to 2018 (8.90 ± 2.09 pg/m³). Correlation analysis with meteorological conditions revealed that the PAH and NPAH concentrations were both influenced by ambient temperature. The diagnostic ratios of PAHs and factor analysis showed that they were mainly affected by traffic emissions with some coal and/or biomass combustion. The ratio of 2-nitrofluoranthene to 2-nitropyrene was near 10, which indicated that the OH radical-initiated reaction was the main pathway leading to their secondary formation. Moreover, backward trajectories revealed different air mass routes in each sampling period, indicating a high possibility of source effects from the northern area in winter in addition to local and surrounding influences. Meanwhile, the mean total benzo[a]pyrene-equivalent concentrations in Shanghai in winter decreased by 50.8% from 2010 (1860 ± 645 pg/m³) to 2018 (916 ± 363 pg/m³). These results indicated the positive effects of the various policies and regulations issued by Chinese authorities.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

Adolescent Haze-Related Knowledge Level Study: A Cross-Sectional Survey With Sensitivity Analysis

Objective: This study aimed to investigate the level of haze-related knowledge adolescents have and to explore relevant influencing factors. Methods: From June 2015 to January 2016, researchers randomly selected 2 districts from the 20 districts of Baoding, China. Then, researchers randomly selected two middle schools from two districts. By conducting a stratified cluster sampling and considering one class as a unit, researchers randomly selected, from the other middle school, five first-grade classes, five second-grade classes, five third-grade classes from the one middle school, and three first-grade classes, two second-grade classes, and two third-grade classes. Finally, 1,100 adolescents were investigated by using the demographic questionnaire and the Adolescent Haze-Related Knowledge Awareness Assessment Scale (AHRKAAS). Multiple linear regressions were conducted to explore factors affecting the adolescent haze-related knowledge. Sensitivity analysis was used to confirm associations between influencing factors and AHRKAAS scores. Results: The AHRKAAS score rate was 69.9%. The dimension of human factors of haze formation was the highest (score rate = 85.6%). The dimension of haze harms on the human body was the lowest (score rate = 57.1%). Compared with the group (monthly expenses <300 yuan), the group (monthly expenses ≥ 600 yuan) had a higher AHRKAAS score (β = 4.882, 95% CI: 0.979, 8.784). Compared with the group (Do not live with parents), the group (Live with parents) had a higher AHRKAAS score (β = 14.675, 95% CI: 9.494, 19.855). Compared with the group (Never undergo a physical examination), the group (Once a year) (β = 7.444, 95% CI: 2.922, 11.966) and the group (A few times a year) (β = 7.643, 95% CI: 2.367, 12.919) had a higher AHRKAAS score. Compared with the group (Know nothing), the group (Know most) (β = 9.623, 95% CI: 2.929, 16.316) and the group (Know very well) (β = 15.367, 95% CI: 7.220, 23.515) had a higher AHRKAAS score. These associations were still reliable and consistent in different sensitivity analysis models. Conclusion: The level of adolescent haze-related knowledge is low and is affected by monthly expenses, living condition, physical examination frequency, and knowledge of respiratory system diseases. Government bodies, schools, and research institutions should strengthen cooperation of health publicity and health education to improve adolescent haze-related knowledge.

Early-life exposure to ambient fine particulate air pollution and infant mortality: pooled evidence from 43 low- and middle-income countries

BACKGROUND

Many low- and middle-income countries are experiencing high and increasing exposure to ambient fine particulate air pollution (PM2.5). The effect of PM2.5 on infant and child mortality is usually modelled using concentration response curves extrapolated from studies conducted in settings with low ambient air pollution, which may not capture its full effect.

METHODS

We pool data on more than half a million births from 69 nationally representative Demographic and Health Surveys that were conducted in 43 low- and middle-income countries between 1998 and 2014, and we calculate early-life exposure (exposure in utero and post partum) to ambient PM2.5 using high-resolution calibrated satellite data matched to the child's place of residence. We estimate the association between the log of early-life PM2.5 exposure, both overall and separated by type, and the odds of neonatal and infant mortality, adjusting for child-level, parent-level and household-level characteristics.

RESULTS

We find little evidence that early-life exposure to overall PM2.5 is associated with higher odds of mortality relative to low exposure to PM2.5. However, about half of PM2.5 is naturally occurring dust and sea-salt whereas half is from other sources, comprising mainly carbon-based compounds, which are mostly due to human activity. We find a very strong association between exposure to carbonaceous PM2.5 and infant mortality, particularly neonatal mortality, i.e. mortality in the first 28 days after birth. We estimate that, at the mean level of exposure in the sample to carbonaceous PM2.5-10.9 µg/m3-the odds of neonatal mortality are over 50% higher than in the absence of pollution.

CONCLUSION

Our results suggest that the current World Health Organization guideline of limiting the overall ambient PM2.5 level to less than 10 µg/m³ should be augmented with a lower limit for harmful carbonaceous PM2.5.

Developing and Testing the Reliability and Validity of the Brief Haze Weather Health Protection Behavior Assessment Scale-Adolescent Version (BHWHPBAS-AV)

Objectives: To develop a Brief Haze Weather Health Protection Behavior Assessment Scale-Adolescent Version (BHWHPBAS-AV). Methods: Considering primary prevention, secondary prevention and tertiary prevention as a theoretical basis, researchers developed a Brief Haze Weather Health Protection Behavior Assessment Scale-Adolescent Version-I(BHWHPBAS-AV-I). After performing 6 reviews by related experts, and after conducting six adolescent tests for BHWHPBAS-AV-I, researchers developed an updated BHWHPBAS-AV-II. Out of the 20 districts in Baoding, two districts were randomly selected; moreover, two middle schools from these two districts were also randomly selected. Considering one class as a unit, researchers subsequently randomly selected 22 classes by using stratified sampling. In the end, 1,025 valid questionnaires were used as part of the study. At which point, researchers investigated the validity and reliability of the scale and obtained the final scale (BHWHPBAS-AV). Results: BHWHPBAS-AV Cronbach's α = 0.878, content validity = 0.948, and factor cumulative contribution rate = 54.058% using exploratory factor analysis. By confirmatory factor analysis, Chi square value (χ²) = 271.791, degrees of freedom (df) = 94, Chi square value/degrees of freedom (χ²/df) = 2.891, root-mean-square error of approximation (RMSEA) = 0.051, normed fit index (NFI) = 0.930, incremental fit index (IFI) = 0.953, goodness of fit index (GFI) = 0.955, Tueker-Lewis index (TLI) = 0.940, comparative fit index (CFI) = 0.953. BHWHPBAS-AV was composed of 16 items as well as 3 dimensions. Conclusions: A BHWHPBAS-AV scale that has an acceptable reliability and validity can be applied to assess adolescent haze weather health protection behavior, and can also help school teachers, as well as medical staff working in community health care institutions, to perform targeted behavioral interventions and deliver health education programs to adolescents.

Assessing the impact of air pollution on childhood asthma morbidity: how, when, and what to do

PURPOSE OF REVIEW

Exposure to air pollutants is linked with poor asthma control in children and represents a potentially modifiable risk factor for impaired lung function, rescue medication use, and increased asthma-related healthcare utilization. Identification of the most relevant pollutants to asthma as well as susceptibility factors and strategies to reduce exposure are needed to improve child health.

RECENT FINDINGS

The current available literature supports the association between pollutants and negative asthma outcomes. Ethnicity, socioeconomic status, and presence of certain gene polymorphisms may impact susceptibility to the negative health effects of air pollution. Improved air quality standards were associated with better asthma outcomes.

SUMMARY

The link between air pollution and pediatric asthma morbidity is supported by the recent relevant literature. Continued efforts are needed to identify the most vulnerable populations and develop strategies to reduce exposures and improve air quality.

Air pollution associated epigenetic modifications: Transgenerational inheritance and underlying molecular mechanisms

Air pollution is one of the leading causes of deaths in Southeast Asian countries including India. Exposure to air pollutants affects vital cellular mechanisms and is intimately linked with the etiology of a number of chronic diseases. Earlier work from our laboratory has shown that airborne particulate matter disturbs the mitochondrial machinery and causes significant damage to the epigenome. Mitochondrial reactive oxygen species possess the ability to trigger redox-sensitive signaling mechanisms and induce irreversible epigenomic changes. The electrophilic nature of reactive metabolites can directly result in deprotonation of cytosine at C-5 position or interfere with the DNA methyltransferases activity to cause alterations in DNA methylation. In addition, it also perturbs level of cellular metabolites critically involved in different epigenetic processes like acetylation and methylation of histone code and DNA hypo or hypermethylation. Interestingly, these modifications may persist through downstream generations and result in the transgenerational epigenomic inheritance. This phenomenon of subsequent transfer of epigenetic modifications is mainly associated with the germ cells and relies on the germline stability of the epigenetic states. Overall, the recent literature supports, and arguably strengthens, the contention that air pollution might contribute to transmission of epimutations from gametes to zygotes by involving mitochondrial DNA, parental allele imprinting, histone withholding and non-coding RNAs. However, larger prospective studies using innovative, integrated epigenome-wide metabolomic strategy are highly warranted to assess the air pollution induced transgenerational epigenetic inheritance and associated human health effects.

Leaf magnetic properties as a method for predicting heavy metal concentrations in PM2.5 using support vector machine: A case study in Nanjing, China

The aim of this study was to establish a method for predicting heavy metal concentrations in PM_2.5 (particulate matter with a diameter of less than 2.5 μm) using support vector machine (SVM) models combined with magnetic properties of leaves. In this study, PM_2.5 samples and the leaves of three common evergreen tree species were collected simultaneously during four different seasons in Nanjing, China. A SVM algorithm was used to establish models for the prediction of airborne heavy metal concentrations based on leaf magnetic properties, with or without meteorological factors and pollutant concentrations as input variables. Results showed that the annual average PM_2.5 concentration was 58.47 μg/m³. PM_2.5 concentrations, leaf magnetic properties, and nearly all airborne heavy metals had higher concentrations in winter than in spring, summer, or fall. Ferrimagnetic minerals preponderant in dust-loaded leaves were sampled from the three tree species. Models using magnetic properties of leaves from Ligustrum lucidum Ait and Osmanthus fragrans Lour yielded better prediction effects than those based on the leaves of Cedar deodara G. Don, showing relatively higher correlation coefficient (R) values and lower errors in both training and test stages. Fe and Pb concentrations were well-simulated by the prediction models, with R values > 0.7 in both training and test stages. By contrast, the concentrations of V, Co, Sb, Tl, and Zn were relatively poor-simulated, with most R values < 0.7 in both training and test stages. Predictions for the main urban areas of Nanjing showed that the highest heavy metal concentrations occurred near industrial and traffic pollution sources. Our results provide a cost-effective approach for the prediction of airborne heavy metal concentrations based on the biomagnetic monitoring of tree leaves.

Development and testing of the reliability and validity of the adolescent haze related knowledge awareness assessment scale (AHRKAAS)

Background

Haze leads to many direct serious public health impacts. Understanding haze related knowledge can not only help adolescents organize health protection awareness to prevent the harmful effects that haze has on the body, but also promote their normal growth and development.

Methods

By considering, as the theoretical basis, the reasons behind the formation of haze and the underlying mechanisms of the diseases that it causes, in addition to also investigating extensive literature references, our research team developed the Adolescent Haze Related Knowledge Awareness Assessment Scale (AHRKAAS-I). After 6 experts reviewed AHRKAAS-I, and 6 adolescents tested the scale, the research team further revised and improved AHRKAAS-I to form AHRKAAS-II. After which, researchers randomly selected 2 districts from the 20 districts of Baoding, and subsequently randomly selected 2 middle schools from these 2 districts. Conducting a stratified cluster sampling method, considering class as a unit, the research team randomly selected 22 classes. Finally, a total of 1100 adolescents were investigated and 1034 valid questionnaires were recovered. By analyzing the data of 1034 valid questionnaires, the researchers tested the reliability and validity of the scale and obtained the final scale (AHRKAAS).

Results

AHRKAAS Cronbach’s α=0.923, content validity = 0.940, criterion validity = 0.444, and factor cumulative contribution rate = 66.178% by exploratory factor analysis. Using confirmatory factor analysis, Chi square value = 662.780, degrees of freedom = 242, Chi square value/degrees of freedom = 2.739, root-mean-square error of approximation = 0.049, goodness of fit index = 0.929, adjusted goodness of fit index = 0.905, comparative fit index = 0.964, normed fit index = 0.944, and Tueker-Lewis index = 0.955. AHRKAAS consisted of 25 items and 4 dimensions.

Conclusion

AHRKAAS with a good reliability and validity can be used to assess the cognition level of haze related knowledge among the adolescents, help medical workers and coordinators in schools when conducting targeted behavior interventions. Furthermore, it can be used for health guidance for adolescents relating to the health prevention of haze.

The effects of PM2.5 on asthmatic and allergic diseases or symptoms in preschool children of six Chinese cities, based on China, Children, Homes and Health (CCHH) project

The urbanization and industrialization in China is accompanied by bad air quality, and the prevalence of asthma in Chinese children has been increasing in recent years. To investigate the associations between ambient PM_2.5 levels and asthmatic and allergic diseases or symptoms in preschool children in China, we assigned PM_2.5 exposure data from the Global Burden of Disease (GBD) project to 205 kindergartens at a spatial resolution of 0.1° × 0.1° in six cities in China (Shanghai, Nanjing, Chongqing, Changsha, Urumqi, and Taiyuan). A hierarchical multiple logistical regression model was applied to analyze the associations between kindergarten-level PM_2.5 exposure and individual-level outcomes of asthmatic and allergic symptoms. The individual-level variables, including gender, age, family history of asthma and allergic diseases, breastfeeding, parental smoking, indoor dampness, interior decoration pollution, household annual income, and city-level variable-annual temperature were adjusted. A total of 30,759 children (average age 4.6 years, 51.7% boys) were enrolled in this study. Apart from family history, indoor dampness, and decoration as predominant risk factors, we found that an increase of 10 μg/m³ of the annual PM_2.5 was positively associated with the prevalence of allergic rhinitis by an odds ratio (OR) of 1.20 (95% confidence interval [CI] 1.11, 1.29) and diagnosed asthma by OR of 1.10 (95% CI 1.03, 1.18). Those who lived in non-urban (vs. urban) areas were exposed to more severe indoor air pollution arising from biomass combustion and had significantly higher ORs between PM_2.5 and allergic rhinitis and current rhinitis. Our study suggested that long-term exposure to PM_2.5 might increase the risks of asthmatic and allergic diseases or symptoms in preschool children in China. Compared to those living in urban areas, children living in suburban or rural areas had a higher risk of PM_2.5 exposure.

Exposure to Ambient Fine Particulate Air Pollution in Utero as a Risk Factor for Child Stunting in Bangladesh

Pregnant mothers in Bangladesh are exposed to very high and worsening levels of ambient air pollution. Maternal exposure to fine particulate matter has been associated with low birth weight at much lower levels of exposure, leading us to suspect the potentially large effects of air pollution on stunting in children in Bangladesh. We estimate the relationship between exposure to air pollution in utero and child stunting by pooling outcome data from four waves of the nationally representative Bangladesh Demographic and Health Survey conducted between 2004 and 2014, and calculating children’s exposure to ambient fine particulate matter in utero using high resolution satellite data. We find significant increases in the relative risk of child stunting, wasting, and underweight with higher levels of in utero exposure to air pollution, after controlling for other factors that have been found to contribute to child anthropometric failure. We estimate the relative risk of stunting in the second, third, and fourth quartiles of exposure as 1.074 (95% confidence interval: 1.014–1.138), 1.150 (95% confidence interval: 1.069–1.237, and 1.132 (95% confidence interval: 1.031–1.243), respectively. Over half of all children in Bangladesh in our sample were exposed to an annual ambient fine particulate matter level in excess of 46 µg/m³; these children had a relative risk of stunting over 1.13 times that of children in the lowest quartile of exposure. Reducing air pollution in Bangladesh could significantly contribute to the Sustainable Development Goal of reducing child stunting.

Short-term effects of ambient air pollution on pediatric outpatient visits for respiratory diseases in Yichang city, China

Previous studies have suggested that short-term exposure to ambient air pollution was associated with pediatric hospital admissions and emergency room visits for certain respiratory diseases; however, there is limited evidence on the association between short-term air pollution exposure and pediatric outpatient visits. Our aim was to quantitatively assess the short-term effects of ambient air pollution on pediatric outpatient visits for respiratory diseases. We conducted a time-series study in Yichang city, China between Jan 1, 2014 and Dec 31, 2015. Daily counts of pediatric respiratory outpatient visits were collected from 3 large hospitals, and then linked with air pollution data from 5 air quality monitoring stations by date. We used generalized additive Poisson models to conduct linear and nonlinear exposure-response analyses between air pollutant exposures and pediatric respiratory outpatient visits, adjusting for seasonality, day of week, public holiday, temperature, and relative humidity. Each interquartile range (IQR) increase in PM_2.5 (lag 0), PM₁₀ (lag 0), NO₂ (lag 0), CO (lag 0), and O₃ (lag 4) concentrations was significantly associated with a 1.91% (95% CI: 0.60%, 3.23%), 2.46% (1.09%, 3.85%), 1.88% (0.49%, 3.29%), 2.00% (0.43%, 3.59%), and 1.91% (0.45%, 3.39%) increase of pediatric respiratory outpatient visits, respectively. Similarly, the nonlinear exposure-response analyses showed monotonic increases of pediatric respiratory outpatient visits by increasing air pollutant exposures, though the associations for NO₂ and CO attenuated at higher concentrations. These associations were unlikely modified by season. We did not observe significant association for SO₂ exposure. Our results suggest that short-term exposures to PM_2.5, PM₁₀, NO₂, CO, and O₃ may account for increased risk of pediatric outpatient visits for respiratory diseases, and emphasize the needs for reduction of air pollutant exposures for children.