Association between sub-daily exposure to ambient air pollution and risk of asthma exacerbations in Australian children

Study on the impact of air pollutants on childhood asthma in Nanjing based on a distributed lag non-linear model

Background

Asthma, a chronic respiratory disease, is a significant public health concern globally. Air pollution has been identified as one of the key risk factors exacerbating respiratory conditions, particularly in children. Previous studies have shown a correlation between air pollution levels and asthma visits. However, the impact of air pollutants on childhood asthma visits stratified by gender, age and season remains a topic of interest, and further investigation is necessary to comprehend this complex relationship.

Objective

This study aimed to explore the association between air pollution and childhood asthma visits in Nanjing from 2013 to 2021. It focused on the effects of various pollutants, including PM2.5, PM10, NO2, SO2, CO, and O3, and examined variations in impact based on demographic characteristics (gender and age) and seasonal changes.

Methods

Data on childhood asthma visits and concentrations of air pollutants were collected and analyzed. The lag effects of pollutants on asthma visits were assessed, and the impacts were stratified by gender, age group (0-5 years, 6-11 years, and over 11 years), and season. Statistical methods were used to identify significant correlations and the timing of maximum effects of pollutants.

Results

A positive correlation was found between childhood asthma visits and concentrations of AQI, PM2.5, PM10, SO2, NO2, and CO, with the strongest effects typically occurring on lag day 1. The study revealed that PM2.5 and PM10 had a more pronounced impact on females, and children aged 0-5 years were the most affected age group. Seasonal analysis showed that PM2.5 and SO2 had the greatest impact in spring, while PM10 and NO2 were most significant in winter. Notably, SO2 showed no significant impact on childhood over 11 years old or during summer, and the negative correlation between CO concentrations and childhood asthma visits in the summer, while in other seasons, the correlation was positive.

Conclusion

The findings indicate a substantial effect of air pollutants, particularly PM2.5 and SO2, on childhood asthma, emphasizing the need for targeted pollution control measures. Variations in impact based on gender, age, and season suggest the importance of tailored interventions to protect vulnerable populations, especially young children in urban and industrial areas.

Developing and validating intracity spatiotemporal air quality health index in eastern China

BACKGROUND

Recently pilot published city-level air quality health index (AQHI) provides a useful tool for communicating short-term health risks of ambient air pollution, but fails to account for intracity spatial heterogeneity in exposure and associated population health impacts. This study aims to develop the intracity spatiotemporal AQHI (ST-AQHI) via refined air pollution-related health risk assessments.

METHODS

A three-stage analysis was conducted through integrating province-wide death surveillance data and high-resolution gridded estimates of air pollution and climate factors spanning 2016-2019 in Jiangsu Province, eastern China. First, an individual-level case-crossover design was employed to quantify the short-term risk of nonaccidental mortality associated with residential exposure to individual pollutant (i.e., PM2.5, NO2, O3, and SO2). Second, we accumulated and scaled the excess risks arising from multiple pollutants to formulate daily gridded ST-AQHI estimates at 0.1° × 0.1°, dividing exposure-related risks into low (0-3), moderate (4-6), high (7-9), and extreme high (10+) levels. Finally, the effectiveness of ST-AQHI as composite risk communication was validated through checking the dose-response associations of individual ST-AQHI exposure with deaths from nonaccidental and major cardiopulmonary causes via repeating case-crossover analyses.

RESULTS

We analyzed a total of 1,905,209 nonaccidental death cases, comprising 785,567 from circulatory diseases and 247,336 from respiratory diseases. In the first-stage analysis, for each 10-μg/m3 rise in PM2.5, NO2, O3, and SO2 exposure at lag-01 day, population risk of nonaccidental death was increased by 0.8% (95% confidence interval: 0.7%, 0.9%), 1.9% (1.7%, 2.0%), 0.4% (0.3%, 0.5%), and 4.1% (3.7%, 4.5%), respectively. Spatiotemporal distribution of ST-AQHI exhibited a consistent declining trend throughout the study period (2016-2019), with annual average ST-AQHI decreasing from 5.2 ± 1.3 to 4.0 ± 1.0 and high-risk days dropping from 15.8% (58 days) to 1.6% (6 days). Exposure associated health risks showed great intracity- and between-city heterogeneities. In the validation analysis, ST-AQHI demonstrated approximately linear, threshold-free associations with multiple death events from nonaccidental and major cardiopulmonary causes, suggesting excellent performance in predicting exposure-related health risks. Specifically, each 1-unit rise in ST-AQHI was significantly associated with an excess risk of 2.0% (1.8%, 2.1%) for nonaccidental mortality, 2.3% (2.1%, 2.6%) for overall circulatory mortality, and 2.7% (2.3%, 3.1%) for overall respiratory mortality, as well as 1.7%-3.0% for major cardiopulmonary sub-causes.

CONCLUSIONS

ST-AQHI developed in this study performed well in predicting intracity spatiotemporal heterogeneity of death risks related to multiple air pollutants, and may hold significant practical importance in communicating air pollution-related health risks to the public at the community scales.

Plasma metabolomics identifies differing endotypes of recurrent wheezing in preschool children differentiated by symptoms and social disadvantage

Preschool children with recurrent wheezing are a heterogeneous population with many underlying biological pathways that contribute to clinical presentations. Although the morbidity of recurrent wheezing in preschool children is significant, biological studies in this population remain quite limited. To address this gap, this study performed untargeted plasma metabolomic analyses in 68 preschool children with recurrent wheezing to identify metabolomic endotypes of wheezing. K-means cluster analysis was performed on metabolomic dataset including a total of 1382 named and unnamed metabolites. We identified three metabolomic clusters which differed in symptom severity, exacerbation occurrence, and variables associated with social disadvantage. Metabolites that distinguished the clusters included those involved in fatty acid metabolism, fatty acids (long chain monounsaturated fatty acids, long chain polyunsaturated fatty acids, and long chain saturated fatty acids), lysophospholipids, phosphatidylcholines, and phosphatidylethanolamines. Pathway analyses identified pathways of interest in each cluster, including steroid metabolism, histidine metabolism, sphingomyelins, and sphingosines, among others. This study highlights the biologic complexity of recurrent wheezing in preschool children and offers novel metabolites and pathways that may be amenable to future study and intervention.

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.

Short-Term Nitrogen Dioxide Exposure and Emergency Hospital Admissions for Asthma in Children: A Case-Crossover Analysis in England

Background

There is an increasing body of evidence associating short-term ambient nitrogen dioxide (NO2) exposure with asthma-related hospital admissions in children. However, most studies have relied on temporally resolved exposure information, potentially ignoring the spatial variability of NO2. We aimed to investigate how daily NO2 estimates from a highly resolved spatio-temporal model are associated with the risk of emergency hospital admission for asthma in children in England.

Methods

We conducted a time-stratified case-crossover study including 111,766 emergency hospital admissions for asthma in children (aged 0-14 years) between 1st January 2011 and 31st December 2015 in England. Daily NO2 levels were predicted at the patients' place of residence using spatio-temporal models by combining land use data and chemical transport model estimates. Conditional logistic regression models were used to obtain the odds ratios (OR) and confidence intervals (CI) after adjusting for temperature, relative humidity, bank holidays, and influenza rates. The effect modifications by age, sex, season, area-level income deprivation, and region were explored in stratified analyses.

Results

For each 10 µg/m³ increase in NO2 exposure, we observed an 8% increase in asthma-related emergency admissions using a five-day moving NO2 average (mean lag 0-4) (OR 1.08, 95% CI 1.06-1.10). In the stratified analysis, we found larger effect sizes for male (OR 1.10, 95% CI 1.07-1.12) and during the cold season (OR 1.10, 95% CI 1.08-1.12). The effect estimates varied slightly by age group, area-level income deprivation, and region.

Significance

Short-term exposure to NO2 was significantly associated with an increased risk of asthma emergency admissions among children in England. Future guidance and policies need to consider reflecting certain proven modifications, such as using season-specific countermeasures for air pollution control, to protect the at-risk population.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Intraday exposure to ambient ozone and emergency department visits among children: a case-crossover study in southern China

Most existing studies have investigated short-term associations between ozone exposure and acute disease events among children at a daily timescale, which might neglect risk effects happening within several hours after ozone exposure. In this research, we aimed to depict intraday associations between pediatric emergency department visits (PEDVs) and exposure to ozone in order to better detect ultra-short-term effects of ozone exposure on children. We obtained hourly data of all-cause PEDVs, air pollutants, and meteorological factors in Shenzhen and Guangzhou, China, 2015-2018. We applied time-stratified case-crossover design and conditional logistic regression models to estimate odds ratios per 10-μg/m³ rise of ozone concentrations at various exposure periods (e.g., 0-3, 4-6, 7-12, 13-24, 25-48, and 49-72 h) prior to PEDVs, controlling for hourly relative humidity and temperature. Subgroup analyses divided by gender, age, and season were undertaken to identify the potential susceptible population and period. A total of 358,285 cases of PEDVs were included in two cities, and hourly average concentration of ozone was 45.5 μg/m³ in Guangzhou and 58.9 μg/m³ in Shenzhen, respectively. Increased risks of PEDVs occurred within a few hours (0-3 h) after exposure to ozone and remained up to 48 h. Population risks for PEDVs increased by 0.8% (95% confidence interval, 0.6 to 1.0) in Shenzhen and 0.7% (0.5 to 0.9) in Guangzhou for a 10-μg/m³ increase in ozone concentrations at lag 4-6 h and lag 7-12 h, respectively. These findings were robust to co-exposure adjustments in our sensitivity analyses. Significantly greater ozone-associated risks were consistently observed during cold months (October to March of the following year) in both cities, while we did not identify evidence for effect modification of children's age and gender. This study provided novel evidence for increased risks of acute disease events among children within several hours after ozone exposure, highlighting the significant implications for policymakers to establish hourly air quality standards for better protecting children's health.

Air pollution and childhood asthma

PURPOSE OF REVIEW

Asthma is the most common chronic disease of childhood. Environmental exposures, such as allergens and pollutants, are ubiquitous factors associated with asthma development and asthma morbidity. In this review, we highlight the most recent studies relevant to childhood asthma risk, onset, and exacerbation related to air pollution exposure.

RECENT FINDINGS

In this article, we review current research that has been published between 2021 and 2022, demonstrating the effects of early-life exposure to key air pollutants (e.g., particulate matter (PM), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ) and ground-level ozone (O 3 ), environmental tobacco smoke, radon, and volatile organic compounds (VOC) on respiratory health.

SUMMARY

Air pollution continues to be a global burden with serious consequences related to respiratory health. Interventions aimed at reducing air pollution in the environment must be achieved in an effort to improve asthma outcomes and pediatric health.

Emergency Department Visits in Children Associated with Exposure to Ambient PM1 within Several Hours

BACKGROUND

Emerging evidence has integrated short-term exposure to PM₁ with children's morbidity and mortality. Nevertheless, most available studies have been conducted on a daily scale, ignoring the exposure variations over the span of a day.

OBJECTIVE

The main intention of this study was to examine the association between pediatric emergency department visits (PEDVs) and intra-day exposures to PM₁ and PM_2.5. We also aimed to investigate whether a high PM₁/PM_2.5 ratio elevated the risk of PEDVs independent from PM_2.5 exposure within several hours.

METHODS

We collected hourly data on aerial PM₁ and PM_2.5 concentrations, all-cause PEDVs, and meteorological factors from two megacities (i.e., Guangzhou and Shenzhen) in southern China during 2015-2016. Time-stratified case-crossover design and conditional logistic regression analysis were used to assess the associations of PEDVs with exposures to PM₁ and PM_2.5 at different lag hours. The contribution of PM₁ to PM_2.5-associated risk was quantified by introducing PM₁/PM_2.5 ratio as an additional exposure indicator in the analysis adjusting for PM_2.5. Subgroup analyses were performed stratified by sex, age, and season.

RESULTS

During this study period, 97,508 and 101,639 children were included from Guangzhou and Shenzhen, respectively. PM₁ and PM_2.5 exposures within several hours were both remarkably related to an increased risk of PEDVs. Risks for PEDVs increased by 3.9% (95% confidence interval [CI]: 2.7-5.0%) in Guangzhou and 3.2% (95% CI: 1.9-4.4%) in Shenzhen for each interquartile range (Guangzhou: 21.4 μg/m³, Shenzhen: 15.9 μg/m³) increase in PM₁ at lag 0-3 h, respectively. A high PM₁/PM_2.5 ratio was substantially correlated with increased PEDVs, with an excess risk of 2.6% (95% CI: 1.2-4.0%) at lag 73-96 h in Guangzhou and 1.2% (95% CI: 0.4-2.0%) at lag 0-3 h in Shenzhen. Stratified analysis showed a clear seasonal pattern in PM-PEDVs relationships, with notably stronger risks in cold months (October to March of the following year) than in warm months (April to September).

CONCLUSIONS

Exposures to ambient PM₁ and PM_2.5 within several hours were related to increased PEDVs. A high PM₁/PM_2.5 ratio may contribute an additional risk independent from the short-term impacts of PM_2.5. These findings highlighted the significance of reducing PM₁ in minimizing health risks due to PM_2.5 exposure in children.

Causal relationship between outdoor atmospheric quality and pediatric asthma visits in hangzhou

Many air pollutants and climate variables have proven to be significantly associated with pediatric asthma and have worsened asthma symptoms. However, their exact causal effects remain unclear. We explored the causality between air pollutants, climate, and daily pediatric asthma patient visits with a short-term lag effect. Based on eight years of daily environmental data and daily pediatric asthma patient visits, Spearman correlation analysis was used to select the air pollutants and climate variables that correlated with daily pediatric asthma patient visits at any time (with a lag of 1-6 days). We regarded these environmental variables as treatments and built multiple- and single-treatment causal inference models using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between these correlated variables and daily pediatric asthma patient visits in lag time. The multiple-treatment causal inference model was a model with 8 treatments (Visibility, Precipitation, PM₁₀, PM_2.5, SO₂, NO₂, AQI and CO), 1 outcome (daily pediatric asthma patients visits), and 5 confounders (Humidity, Temperature, Sea level pressure, wind speed and unobserved confounders "U"). Single-treatment causal inference models were 8 models, and each model has 1 treatment, 1 outcome and 12 confounders. Spearman correlation analysis showed that precipitation, wind speed, visibility, air quality index, PM_2.5, PM₁₀, SO₂, NO₂, and CO were significantly associated variables at all times (p < 0.05). The multiple-treatment model showed that pooled treatments had significant causality for the short-term lag (lag1-lag6; p < 0.05). Causality was mainly due to SO₂. In the single-treatment models, visibility, SO₂, NO₂, and CO exhibited significant causal effects at any one time (p < 0.05). SO₂ and CO exhibited stronger positive causal effects. The causal effect of SO₂ reached its maxima (causal effect = 11.41, p < 0.05) at lag5. The greatest causal effect of CO appeared at lag3 (causal effect = 10.67, p < 0.05). During the eight year-period, the improvements in SO₂, CO, and NO₂ in Hangzhou were estimated to reduce asthma visits by 8478.03, 3131.08, and 1341.39 per year, respectively. SO₂, NO₂, CO, and visibility exhibited causal effects on daily pediatric asthma patient visits; SO₂ was the most crucial causative variable with a relatively higher causal effect, followed by CO. Improvements in atmospheric quality in the Hangzhou area have effectively reduced the incidence of asthma.

Ambient ultrafine particle (PM0.1): Sources, characteristics, measurements and exposure implications on human health

The problem of ultrafine particles (UFPs; PM_0.1) has been prevalent since the past decades. In addition to become easily inhaled by human respiratory system due to their ultrafine diameter (<100 nm), ambient UFPs possess various physicochemical properties which make it more toxic. These properties vary based on the emission source profile. The current development of UFPs studies is hindered by the problem of expensive instruments and the inexistence of standardized measurement method. This review provides detailed insights on ambient UFPs sources, physicochemical properties, measurements, and estimation models development. Implications on health impacts due to short-term and long-term exposure of ambient UFPs are also presented alongside the development progress of potentially low-cost UFPs sensors which can be used for future UFPs studies references. Current challenge and future outlook of ambient UFPs research are also discussed in this review. Based on the review results, ambient UFPs may originate from primary and secondary sources which include anthropogenic and natural activities. In addition to that, it is confirmed from various chemical content analysis that UFPs carry heavy metals, PAHs, BCs which are toxic in its nature. Measurement of ambient UFPs may be performed through stationary and mobile methods for environmental profiling and exposure assessment purposes. UFPs PNC estimation model (LUR) developed from measurement data could be deployed to support future epidemiological study of ambient UFPs. Low-cost sensors such as bipolar ion and ionization sensor from common smoke detector device may be further developed as affordable instrument to monitor ambient UFPs. Recent studies indicate that short-term exposure of UFPs can be associated with HRV change and increased cardiopulmonary effects. On the other hand, long-term UFPs exposure have positive association with COPD, CVD, CHF, pre-term birth, asthma, and also acute myocardial infarction cases.

Seasonal characteristics of ambient temperature variation (DTR, TCN, and TV0-t) and air pollutants on childhood asthma attack in a dry and cold city in China

Very few researches have concentrated on a variety of time scales to evaluate the association between temperature variation (TV) and childhood asthma (CA), and the evidence for the interaction of air pollutants on this association is lacking. In this study, we aim to estimate the relative risks (RRs) of CA due to TV by following metrics: diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV_0-t); to quantify the seasonal attributable fraction (AF) and number (AN) of CA due to TV; to examine the interactive effects of the TV and air pollutants on CA in different seasons. We mainly applied distributed lagged nonlinear model (DLNM) and conditional Poisson models to evaluate the associations between TV and outpatient visits for CA during 2014-2019 in Lanzhou, China. Additionally, the bivariate response surface model was used to examine the interplay effect of air pollutants. We found that in warm season, the risks of DTR maximum at lag5 (RR = 1.073, 95% CI: 1.017-1.133); TCN showed protective effect. In cold season, the risks of DTR peaked at lag8 (RR = 1.063, 95% CI: 1.027-1.100); the risks of TCN maximum at lag0 (RR = 1.058 95% CI: 1.009-1.109); the estimation of total cases maximized at TV_0-4 in cold season (RR = 1.039 at TV_0-3, 95% CI: 1.001, 1.077) and was the lowest at TV_0-1 in warm season (RR = 0.999, 95% CI: 0.969, 1.030). In addition, the response surface model graphically pictured ambient air pollutants enhanced the DTR/TV_0-4-CA effect for girls. In conclusion, the RRs of CA are markedly increased by TV exposure, particularly during the colder months. A combined evaluation of DTR, TCN, TV_0-5∼TV_0-6, NO₂, SO₂, and PM_2.5 should be used to identify the adverse effects of TV on CA.

Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes

Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m³ of NO₂, and 14.1 µg/m³ of SO₂ at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM_2.5, and O₃ interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.