Indoor PM2.5, VOCs and asthma outcomes: A systematic review in adults and their home environments

Investigation of the spatial variation of ambient air VOCs and their effects on the health risk caused by long-term exposure in urban area

Long-term exposure to Volatile Organic Compounds (VOCs) is a health risk for citizens. In this study, the cumulative health risk of exposure to VOCs in Tehran was assessed by investigating the concentration of these pollutants in ambient air in a five-year period. Health risk assessment was calculated by the quantitative method and the carcinogenic risk level was determined using the lifetime carcinogenic risk (LCR) method. The average concentration of benzene, toluene, ortho-xylene, and ethylbenzene was 1.4-1.8, 4.8-5.4, 5-6.5, and 3.6-4 ppb, respectively. Although HQ was not greater than 1, but it was very close in the case of benzene, ortho-xylene, meta-xylene, and para-xylene. Benzene and ethylbenzene had the largest effect in the assessed health risk. So the long-term exposure of Tehran citizens to VOCs has serious health consequences for them, which could be different according to the exposure time and spatial variations.

Assessing the Impact of Spatial and Temporal Variability in Fine Particulate Matter Pollution on Respiratory Health Outcomes in Asthma and COPD Patients

Ambient air pollution's health impacts are well documented, yet the domestic environment remains underexplored. We aimed to compare indoor versus outdoor (I/O) air quality and estimate the association between indoor/ambient fine particulate matter (PM2.5) exposure and lung function in asthma and chronic obstructive pulmonary disease (COPD) patients. The study involved 24 h monitoring of PM2.5 levels indoors and outdoors, daily peak expiratory flow (PEF), and biweekly symptoms collection from five patients with asthma and COPD (average age of 50 years, 40% male) over a whole year. Data analysis was performed with linear mixed effect models for PEF and generalized estimating equations (GEE) for exacerbations. More than 5 million PM2.5 exposure and meteorological data were collected, demonstrating significant I/O PM2.5 ratio variability with an average ratio of 2.20 (±2.10). Identified indoor PM2.5 sources included tobacco use, open fireplaces, and cooking, resulting in average indoor PM2.5 concentrations of 63.89 μg/m3 (±68.41), significantly exceeding revised World Health Organization (WHO) guidelines. Analysis indicated a correlation between ambient PM2.5 levels and decreased PEF over 0-to-3-day lag, with autumn indoor exposure significantly impacting PEF and wheezing. The study underscores the need to incorporate domestic air quality into public health research and policy-making. A personalized approach is required depending on the living conditions, taking into account the exposure to particulate pollution.

Revolutionizing indoor air quality monitoring through IoT innovations: a comprehensive systematic review and bibliometric analysis

Indoor air quality (IAQ) in the built environment is significantly influenced by particulate matter, volatile organic compounds, and air temperature. Recently, the Internet of Things (IoT) has been integrated to improve IAQ and safeguard human health, comfort, and productivity. This review seeks to highlight the potential of IoT integration for monitoring IAQ. Additionally, the paper details progress by researchers in developing IoT/mobile applications for IAQ monitoring, and their transformative impact in smart building, healthcare, predictive maintenance, and real-time data analysis systems. It also outlines the persistent challenges (e.g., data privacy, security, and user acceptability), hampering effective IoT implementation for IAQ monitoring. Lastly, the global developments and research landscape on IoT for IAQ monitoring were examined through bibliometric analysis (BA) of 106 publications indexed in Web of Science from 2015 to 2022. BA revealed the most significant contributing countries are India and Portugal, while the top productive institutions and researchers are Instituto Politecnico da Guarda (10.37% of TP) and Marques Goncalo (15.09% of TP), respectively. Keyword analysis revealed four major research themes: IoT, pollution, monitoring, and health. Overall, this paper provides significant insights for identifying prospective collaborators, benchmark publications, strategic funding, and institutions for future IoT-IAQ researchers.

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

Systematic review using GRADE of the impact of exposure to volatile organic compounds (VOCs), cleaning agents, mould/damp, pesticides on the risk of (i) new-onset asthma (incidence) and (ii) adverse asthma-related outcomes (impact). MEDLINE, EMBASE and Web of Science were searched for indoor pollutant exposure studies reporting on new-onset asthma and critical and important asthma-related outcomes. Ninety four studies were included: 11 for VOCs (7 for incidenceand 4 for impact), 25 for cleaning agents (7 for incidenceand 8 for impact), 48 for damp/mould (26 for incidence and 22 for impact) and 10 for pesticides (8 for incidence and 2 for impact). Exposure to damp/mould increases the risk of new-onset wheeze (moderate certainty evidence). Exposure to cleaning agents may be associated with a higher risk of new-onset asthma and with asthma severity (low level of certainty). Exposure to pesticides and VOCs may increase the risk of new-onset asthma (very low certainty evidence). The impact on asthma-related outcomes of all major indoor pollutants is uncertain. As the level of certainty is low or very low for most of the available evidence on the impact of indoor pollutants on asthma-related outcomes more rigorous research in the field is warranted.

What occupational risk factors significantly affect miners' health: Findings from meta-analysis and association rule mining

INTRODUCTION

The workplace's health hazard remains a significant concern to workers in the mining industry, where miners are continually exposed to various kinds of exposure sources.

METHOD

First, the determinants of miners' health were systematically extracted from 259 publications, comprising chemical, physical, ergonomic, and psychosocial stressors, vulnerability factors, and common health outcomes. Then, 16 meta-analyses were performed to ascertain the epidemiological evidence for associations between four stressors and three health outcomes. The seven top contributing factors affecting miners' health were identified through 166 available prospective studies. Finally, based on the classic and domestic measurement scales, a cross-sectional survey of 559 Chinese miners was conducted to determine the core psychosocial predictors. In addition to the traditional mechanisms, complex interactive networks among the antecedents and consequences and the reversed effects of consequences were also obtained, where 379 strong association rules were yielded via the Apriori algorithm.

RESULTS

The results showed that occupational dust, NO2, heavy metals, heat, vibration, awkward posture, and job stress are significant risk factors associated with individuals' health conditions. Psychological capital, coping style, job demand, social support, organizational support, justice, and culture are core psychosocial predictors of miners.

CONCLUSIONS

This study presents a case for identifying the most significant occupational risk factors related to individuals' health, which could be extended and applied to other industries, as working populations around the world are suffering from various chemical, physical, ergonomic, and psychosocial stressors.

PRACTICAL APPLICATIONS

Identifying the significant occupational risk factors affecting workers' health conditions is essential for comprehensive occupational health risk assessment and management. Therefore, this study could be important for health management in mines and other industries.

Systematically quantifying the dynamic characteristics of PM2.5 in multiple indoor environments in a plateau city: Implication for internal contribution

People generally spend most of their time indoors, making a comprehensive evaluation of air pollution characteristics in various indoor microenvironments of great significance for accurate exposure estimation. In this study, field measurements were conducted in Kunming City, Southwest China, using real-time PM2.5 sensors to characterize indoor PM2.5 in ten different microenvironments including three restaurants, four public places, and three household settings. Results showed that the daily average PM2.5 concentrations in restaurants, public spaces, and households were 78.4 ± 24.3, 20.1 ± 6.6, and 18.0 ± 4.3 µg/m3, respectively. The highest levels of indoor PM2.5 in restaurants were owing to strong internal emissions from cooking activities. Dynamic changes showed that indoor PM2.5 levels increased during business time in restaurants and public places, and cooking time in residential kitchens. Compared with public places, restaurants generally exhibit more rapid increases in indoor PM2.5 due to cooking activities, which can elevate indoor PM2.5 to high levels (5.1 times higher than the baseline) in a short time. Furthermore, indoor PM2.5 in restaurants were dominated by internal emissions, while outdoor penetration contributed mostly to indoor PM2.5 in public places and household settings. Results from this study revealed large variations in indoor PM2.5 in different microenvironments, and suggested site-specific measures for indoor PM2.5 pollution alleviation.

Urban airborne PM2.5 induces pulmonary fibrosis through triggering glycolysis and subsequent modification of histone lactylation in macrophages

Airborne fine particulate matter (PM2.5) can cause pulmonary inflammation and even fibrosis, however, the underlying molecular mechanisms of the pathogenesis of PM2.5 exposure have not been fully appreciated. In the present study, we explored the dynamics of glycolysis and modification of histone lactylation in macrophages induced by PM2.5-exposure in both in vivo and in vitro models. Male C57BL/6 J mice were anesthetized and administrated with PM2.5 by intratracheal instillation once every other day for 4 weeks. Mouse RAW264.7 macrophages and alveolar epithelial MLE-12 cells were treated with PM2.5 for 24 h. We found that PM2.5 significantly increased lactate dehydrogenase (LDH) activities and lactate contents, and up-regulated the mRNA expression of key glycolytic enzymes in the lungs and bronchoalveolar lavage fluids of mice. Moreover, PM2.5 increased the levels of histone lactylation in both PM2.5-exposed lungs and RAW264.7 cells. The pro-fibrotic cytokines secreted from PM2.5-treated RAW264.7 cells triggered epithelial-mesenchymal transition (EMT) in MLE-12 cells through activating transforming growth factor-β (TGF-β)/Smad2/3 and VEGFA/ERK pathways. In contrast, LDHA inhibitor (GNE-140) pretreatment effectively alleviated PM2.5-induced pulmonary inflammation and fibrosis via inhibiting glycolysis and subsequent modification of histone lactylation in mice. Thus, our findings suggest that PM2.5-induced glycolysis and subsequent modification of histone lactylation play critical role in the PM2.5-associated pulmonary fibrosis.

A densely connected causal convolutional network separating past and future data for filling missing PM2.5 time series data

Air pollution poses a significant threat to human health and the environment globally. Precise analysis and prediction of pollutant concentrations are essential for monitoring and managing air quality. However, reliable analysis and prediction require comprehensive and high-quality data, which is often compromised due to missing data during collection. Unfortunately, conventional methods for addressing missing data fall short of providing adequate solutions. The missing data for air quality indicators are commonly systematic, with all data points missing for extended periods. This makes it difficult to establish correlations and populate the missing data accurately. To address this problem, we propose a Densely Connected Causal Convolutional Network Separating Past and Future Data (DCCN-SPF), a deep learning-based model that fills in continuous missing PM2.5 concentration data in the original dataset. It extracts features from past and future data separately using densely connected causal convolutional networks and incorporates linear interpolation and deep learning structures to improve prediction accuracy. Using air quality monitoring data from the China Environmental Monitoring Station between 2017 and 2021 in Beijing, we compare our proposed model with baseline models and find that our model outperforms others in predicting PM2.5 concentrations. The evaluation metrics MAE and RMSE are used, revealing significant reductions of 8.7-21.6 % for MAE and 7.1-23.5 % for RMSE in favor of our proposed DCCN-SPF model.

The impact of air pollution on asthma: clinical outcomes, current epidemiology, and health disparities

INTRODUCTION

Air pollution has been shown to have a significant impact on morbidity and mortality of respiratory illnesses including asthma.

AREAS COVERED

Outdoor air pollution consists of a mixture of individual pollutants including vehicle traffic and industrial pollution. Studies have implicated an array of individual components of air pollution, with PM2.5, NO2, SO2, and ozone being the most classically described, and newer literature implicating other pollutants such as black carbon and volatile organic compounds. Epidemiological and cohort studies have described incidence and prevalence of pollution-related asthma and investigated both acute and chronic air pollution exposure as they relate to asthma outcomes. There is an increasing body of literature tying disparities in pollution exposure to clinical outcomes. In this narrative review, we assessed the published research investigating the association of pollution with asthma outcomes, focusing on the adult population and health care disparities.

EXPERT OPINION

Pollution has multiple deleterious effects on respiratory health but there is a lack of data on individualized pollution monitoring, making it difficult to establish a temporal relationship between exposure and symptoms, thereby limiting our understanding of safe exposure levels. Future research should focus on more personalized monitoring and treatment plans for mitigating exposure.

Burden of diseases attributable to second-hand smoke exposure in Iran adolescents from 2009 to 2020

Exposure to second-hand smoke (SHS) is prevalent in many countries, but the problem's scope is poorly understood globally, especially in developing countries. We aimed to estimate SHS exposure and its national and subnational burden of diseases in Iran, the second-largest country in the Middle East, during 2009-2020. The burden of diseases from SHS was estimated as disability-adjusted life years (DALYs) for adolescents (10-18) year's non-smokers. Using comparative risk assessment methodologies, the calculations were based on disease-specific relative risk estimates with national and subnational SHS exposure data, and the uncertainty and sensitivity analysis was performed. The results of study showed that the trend of exposure to SHS is increasing in Iran. The highest DALY was related to lower respiratory infection (LRI), asthma, and otitis media, respectively. The national average asthma burden (DALY/100,000) has increased from 17.4 (11.8_23.9) in 2009 to 21.3 (13.9_30) in 2020, LRI decreased from 25.8 (21.5_30.2) to 19.8 (16.7_23.1), and national average burden of otitis media (DALY/100,000) has increased from 3.1(1.9_4.6) to 3.9(2.4_5.6). The increasing trend of otitis media and asthma DALYs attributable to SHS exposure in Iran requires more attention from policymakers to protect the population.

Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO₂ concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO₂ concentration was below 10% compared with the simulation. Fast decision reduced CO₂ concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Contributions of particulate and gas phases of simulated burn pit smoke exposures to impairment of respiratory function

OBJECTIVE

Inhalation of smoke from the burning of waste materials on military bases is associated with increased incidences of cardiopulmonary diseases. This study examined the respiratory and inflammatory effects of acute inhalation exposures in mice to smoke generated by military burn pit-related materials including plywood (PW), cardboard (CB), mixed plastics (PL), and a mixture of these three materials (MX) under smoldering (0.84 MCE) and flaming (0.97 MCE) burn conditions.

METHODS

Mice were exposed nose-only for one hour on two consecutive days to whole or filtered smoke or clean air alone. Smoldering combustion emissions had greater concentrations of PM (∼40 mg/m3) and VOCs (∼5-12 ppmv) than flaming emissions (∼4 mg/m3 and ∼1-2 ppmv, respectively); filtered emissions had equivalent levels of VOCs with negligible PM. Breathing parameters were assessed during exposure by head-out plethysmography.

RESULTS

All four smoldering burn pit emission types reduced breathing frequency (F) and minute volumes (MV) compared with baseline exposures to clean air, and HEPA filtration significantly reduced the effects of all smoldering materials except CB. Flaming emissions had significantly less suppression of F and MV compared with smoldering conditions. No acute effects on lung inflammatory cells, cytokines, lung injury markers, or hematology parameters were noted in smoke-exposed mice compared with air controls, likely due to reduced respiration and upper respiratory scrubbing to reduce the total deposited PM dose in this short-term exposure.

CONCLUSION

Our data suggest that material and combustion type influences respiratory responses to burn pit combustion emissions. Furthermore, PM filtration provides significant protective effects only for certain material types.

Do Synthetic Fragrances in Personal Care and Household Products Impact Indoor Air Quality and Pose Health Risks?

Fragrance compounds (synthetic fragrances or natural essential oils) comprise formulations of specific combinations of individual materials or mixtures. Natural or synthetic scents are core constituents of personal care and household products (PCHPs) that impart attractiveness to the olfactory perception and disguise the unpleasant odor of the formula components of PCHPs. Fragrance chemicals have beneficial properties that allow their use in aromatherapy. However, because fragrances and formula constituents of PCHPs are volatile organic compounds (VOCs), vulnerable populations are exposed daily to variable indoor concentrations of these chemicals. Fragrance molecules may trigger various acute and chronic pathological conditions because of repetitive human exposure to indoor environments at home and workplaces. The negative impact of fragrance chemicals on human health includes cutaneous, respiratory, and systemic effects (e.g., headaches, asthma attacks, breathing difficulties, cardiovascular and neurological problems) and distress in workplaces. Pathologies related to synthetic perfumes are associated with allergic reactions (e.g., cutaneous and pulmonary hypersensitivity) and potentially with the perturbation of the endocrine-immune-neural axis. The present review aims to critically call attention to odorant VOCs, particularly synthetic fragrances and associated formula components of PCHPs, potentially impacting indoor air quality and negatively affecting human health.

Patterns of Emergency Room Visits for Respiratory Diseases in New York State in Relation to Air Pollution, Poverty and Smoking

We have explored differences in rates of emergency room (ER) visits for respiratory diseases in the counties of New York State (NYS) in relation to levels of air pollution, poverty, and smoking. Air pollution information was derived from the National Emissions Inventory, which provides information on road, non-road, point, and non-point sources of 12 different air pollutants. This information is only available at the county level. Four types of respiratory diseases were considered: asthma, chronic obstructive pulmonary disease (COPD), acute lower respiratory diseases, and acute upper respiratory diseases. Asthma ER visits were elevated in counties with greater total air pollution. All forms of respiratory diseases were elevated in counties with a greater rate of poverty, although this may reflect the fact that poor people often use ERs for routine care. There was a very strong association between rates of smoking for COPD and acute lower respiratory diseases. There was an apparent negative association between smoking and asthma ER visits, but this must reflect the fact that smoking was much more common in upstate counties while asthma was more common in the New York City area, where air pollution is high. Air pollution was much greater in urban than in rural areas. Our evidence indicates that air pollution is the greatest risk factor for asthma attacks, whereas smoking is the greatest risk factor for chronic obstructive pulmonary disease (COPD) and lower respiratory disease. Poor people are more vulnerable to all forms of respiratory diseases.

Long-term effect of intermediate particulate matter (PM1-2.5) on incident asthma among middle-aged and elderly adults: A national population-based longitudinal study

BACKGROUND

There is insufficient evidence about the long-term effects of intermediate particulate matter (PM_1-2.5) on asthma development in adults aged 45 years and above. This study aimed to investigate the relationship between long-term exposure to PM_1-2.5 and the incidence of asthma in adults aged 45 years and above.

METHODS

A cohort study based on the China Health and Retirement Longitudinal Study (CHARLS) database was conducted to investigate the long-term effects of PM_1-2.5 on self-reported asthma incidence in adults aged 45 years and above in China from 2011 to 2018. The PM concentrations were estimated using a high-resolution (1 km²) satellite-based spatiotemporal model. A covariate-adjusted generalized linear mixed model was used to analyze the relationship between long-term exposure to PM_1-2.5 and the incidence of asthma. Effect modifications and sensitivity analysis were conducted.

RESULTS

After a 7-year follow-up, 103 (1.61 %) of the 6400 participants developed asthma. Each 10 μg/m³ increment in the 1-, 2-, 3-, and 4-year moving average concentrations of PM_1-2.5 corresponded to a 1.82 [95 % confidence interval (CI):1.11-2.98], 1.95 (95 % CI: 1.24-3.07), 1.95 (95 % CI: 1.26-3.03) and 1.88 (95 % CI: 1.26-2.81) fold risk for incident asthma, respectively. A significant multiplicative interaction was observed between socioeconomic level and long-term exposure to PM_1-2.5. Stratified analysis showed that smokers and those with lower socioeconomic levels were at higher risk of incident asthma related to PM_1-2.5. Restricted cubic splines showed an increasing trend in asthma incidence with increasing PM_1-2.5. Sensitivity analyses showed that our model was robust.

CONCLUSION

Long-term exposure to PM_1-2.5 was positively associated with incident asthma in middle-aged and elderly individuals. Participants with a history of smoking and lower socioeconomic levels had a higher risk. More studies are warranted warrant to establish an accurate reference value of PM_1-2.5 to mitigate the growing asthma burden.

Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic

During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, including lockdowns, to prevent the spread of the infection. COVID-19 lockdowns led to a reduction in gaseous and particulate pollutants in ambient air. In the present study, we investigated the substantial changes in selected volatile organic compounds (VOCs) after the outbreak of the coronavirus pandemic and associations with health risk assessments in industrial areas. VOC data from 1 January 2019 to 31 December 2021 were collected from the Central Pollution Control Board (CPCB) website, to identify percentage changes in VOC levels before, during, and after COVID-19. The mean TVOC levels at all monitoring stations were 47.22 ± 30.15, 37.19 ± 37.19, and 32.81 ± 32.81 µg/m³ for 2019, 2020, and 2021, respectively. As a result, the TVOC levels gradually declined in consecutive years due to the pandemic in India. The mean TVOC levels at all monitoring stations declined from 9 to 61% during the pandemic period as compared with the pre-pandemic period. In the current study, the T/B ratio values ranged from 2.16 (PG) to 26.38 (NL), which indicated that the major pollutant contributors were traffic and non-traffic sources during the pre-pandemic period. The present findings indicated that TVOC levels had positive but low correlations with SR, BP, RF, and WD, with correlation coefficients (r) of 0.034, 0.118, 0.012, and 0.007, respectively, whereas negative correlations were observed with AT and WS, with correlation coefficients (r) of -0.168 and -0.150, respectively. The lifetime cancer risk (LCR) value for benzene was reported to be higher in children, followed by females and males, for the pre-pandemic, pandemic, and post-pandemic periods. A nationwide scale-up of this study's findings might be useful in formulating future air pollution reduction policies associated with a reduction in health risk factors. Furthermore, the present study provides baseline data for future studies on the impacts of anthropogenic activities on the air quality of a region.

Comprehensive control of PM 2.5 capture and ozone emission in two-stage electrostatic precipitators

Indoor air purification is extremely urgent to eliminate the health threat of PM 2.5, VOCs and microbial aerosol for exposing people, for which ESPs enjoy exceptional advantage for its special high-voltage characteristic. However, the secondary air pollutant of ozone is produced to possibly cause potential risk. In this work, six kinds of two-stage ESPs containing various charger and collector units, whose structure and size design are determined according to the indoor application, are developed to investigate the comprehensive control of PM 2.5 capture and ozone emission. Responsive surface methodology is employed to explore the relationship among ozone concentration, wire number, charger current and airflow velocity, and obtain regression model for predicting ozone emission. The comprehensive evaluation standard considering efficiency-ozone double factors is proposed to optimize structure design and working conditions of two-stage ESPs. Experimental results show that two-stage ESPs with a unit ratio of >3/4 can keep relatively good stable state, whose current reduction is in around 10 μA, for preventing particle charging function of charger from basically affecting. For the two-stage ESP with Ra = 2/5, it finds the optimization of working conditions of collector can bring rapid improvement of collection efficiency for 0.25 μm particles, which reaches up to be >60 %, while the optimization of that of the charger can only result in an enhancement of <30 %. RSM analysis exhibits a strong connection between the interactive effect of charger current and airflow velocity for presenting a steep response surface. Based on comprehensive control of PM 2.5 and ozone pollutants, it suggests the two-stage ESP with Ra = 2/5 is selected at the first priority and then that with Ra = 1/6, while two-stage ESP with Ra = 4/3 is not recommended for unsatisfied consequence of both of PM 2.5 capture and ozone emission.

Using Sensor Data to Identify Factors Affecting Internal Air Quality within 279 Lower Income Households in Cornwall, South West of England

(1) Background: Poor air quality affects health and causes premature death and disease. Outdoor air quality has received significant attention, but there has been less focus on indoor air quality and what drives levels of diverse pollutants in the home, such as particulate matter, and the impact this has on health; (2) Methods: This study conducts analysis of cross-sectional data from the Smartline project. Analyses of data from 279 social housing properties with indoor sensor data were used to assess multiple factors that could impact levels of particulate matter. T-Tests and Anova tests were used to explore associations between elevated PM2.5 and building, household and smoking and vaping characteristics. Binary logistic regression was used to test the association between elevated particulate matter and self-reported health; (3) Results: Of the multiple potential drivers of the particulate matter investigated, smoking and vaping were significantly associated with mean PM2.5. Following multivariate analysis, only smoking remained significantly associated with higher mean concentrations. Properties in which <15 cigarettes/day were smoked were predicted to have PM2.5 concentrations 9.06 µg/m3 higher (95% CI 6.4, 12.82, p ≤ 0.001) than those in which residents were non-smokers and 11.82 µg/m3 higher (95% CI 7.67, 18.19, p ≤ 0.001) where >15 cigarettes were smoked; (4) Conclusions: A total of 25% of social housing properties in this study experienced levels of indoor PM greater than WHO guideline levels for ambient air pollution. Although there are many factors that impact air quality, in this study the main driver was smoking. This highlights the importance of targeting smoking in indoor environments in future smoking cessation and control policy and practice and of understanding how pollutants interact in the home environment. There is also a need for further research into the impact on indoor air quality of vaping, particularly due to the rise in use and uncertainty of its long-term impact.

Asthma triggered by extreme temperatures: From epidemiological evidence to biological plausibility

BACKGROUND

There is rapidly growing evidence indicating that extreme temperature is a crucial trigger and potential activator of asthma; however, the effects of extreme temperature on asthma are inconsistently reported and the its potential mechanisms remain undefined.

OBJECTIVES

This review aims to estimate the impacts of extreme heat, extreme cold, and temperature variations on asthma by systematically summarizing the existing studies from epidemiological evidence to biological plausibility.

METHODS

We conducted a systematic search in PubMed, Embase, and Web of Science from inception to June 30, 2022, and we retrieved articles of epidemiology and biological studies which assessed associations between extreme temperatures and asthma. This protocol was registered with PROSPERO (CRD42021273613).

RESULTS

From 12,435 identified records, 111 eligible studies were included in the qualitative synthesis, and 37 articles were included in the meta-analysis (20 for extreme heat, 16 for extreme cold, and 15 for temperature variations). For epidemiological evidence, we found that the synergistic effects of extreme temperatures, indoor/outdoor environments, and individual vulnerabilities are important triggers for asthma attacks, especially when there is extreme heat or cold. Meta-analysis further confirmed the associations, and the pooled relative risks for asthma attacks in extreme heat and extreme cold were 1.07 (95%CI: 1.03-1.12) and 1.20 (95%CI: 1.12-1.29), respectively. Additionally, this review discussed the potential inflammatory mechanisms behind the associations between extreme temperatures and asthma exacerbation, and highlighted the regulatory role of immunological pathways and transient receptor potential ion channels in asthma triggered by extreme temperatures.

CONCLUSIONS

We concluded that both extreme heat and cold could significantly increase the risk of asthma. Additionally, we proposed a potential mechanistic framework, which is important for understanding the disease pathogenesis that uncovers the complex mechanisms of asthma triggered by extreme temperatures and protects the sensitive individuals from impacts of extreme weather events and climate change.

Persistent Asthma at School Age: Associated Factors in Preschool Children with Asthma

Most patients with childhood asthma present their first symptoms at preschool age. Identifying modifiable risks and protective factors at an early age may help develop asthma prevention and control strategies. This study aimed to identify factors at preschool age that are associated with persistent asthma at school age. This retrospective observational study included preschool children with asthma from 2015 to 2020 at a university hospital in Southern Thailand. In total, 189 eligible participants (70.9% boys; median age, 7.6 [6.7, 8.5] years) were included. Wheeze characteristics included early transient wheeze, persistent wheeze, and late-onset wheeze that accounted for 55%, 27.5%, and 19.5% of the patients, respectively. Approximately 20% of the participants had persistent asthma. Breastfeeding was a protective factor (odds ratio [OR] 0.4 [0.2, 0.9], p = 0.04). The modifiable risk factors were siblings living in the same household (OR 2.6 [1.1, 6.2], p = 0.02) and residence in an industrial area (OR 3.8 [1.4, 10.5], p = 0.009). Additionally, presence of allergic rhinitis was associated with an increased risk of persistent asthma at school age (OR 3.6 [1.6, 8.2], p = 0.002). Early therapeutic interventions targeting modifiable factors provide a window of opportunity to prevent persistent asthma at school age.

Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept

In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions. Here we present a method for real-time monitoring of the resonance frequency, with a proof of concept for real-time monitoring of gaseous biomarkers based on resonance frequency. This method was validated with a MEGS based on a Metglass 2826 MB microribbon with a polyvinylpyrrolidone (PVP) nanofiber electrospun functionalization. The device provided a low-noise (RMS = 1.7 Hz), fast (<2 min), and highly reproducible response to humidity (Δf = 46−182 Hz for 17−95% RH), ammonia (Δf = 112 Hz for 40 ppm), and acetone (Δf = 44 Hz for 40 ppm). These analytes are highly important in biomedical applications, particularly ammonia and acetone, which are biomarkers related to diseases such as diabetes. Furthermore, the capability of distinguishing between breath and regular air was demonstrated with real breath measurements. The sensor also exhibited strong resistance to benzene, a common gaseous interferent in breath analysis.

A comprehensive survey analysis focusing on the effect of living literacy on residential environment and health recognition under COVID-19 in Japan

Appropriate knowledge and actions of residents in housing are expected to reduce health effects, defined as "living literacy." With the spread of COVID-19 and the diversification of lifestyles, a quantitative evaluation of a comprehensive model that includes living literacy in the housing environment is required. In this study, the author conducted two web-based surveys of approximately 2000 different households in Japan during the summer of 2020 and winter of 2021, and a statistical analysis based on the survey results. As a result, ventilation by opening windows was observed as a new resident behavior trend under COVID-19. In addition, structural equation modeling using the survey samples confirmed the certain relationship between living literacy and subjective evaluation of the indoor environment and health effects in both periods.

Impacts of particulate matter (PM2.5) on the health status of outdoor workers: observational evidence from Malaysia

Ambient air pollution is a significant contributor to disease burden, leading to an estimated 4.2 million premature deaths and 103.1 million disability-adjusted life years (DALYs) annually worldwide. As industrialization and urbanization surge in Asia, air pollution and its corresponding health issues follow suit. Findings on disease burden in developing countries are extremely scanty. This study aimed to determine the concentration of PM_2.5 and its impact on respiratory health of outdoor workers in Malaysia. A 2-cycled 3-month cohort study involving 440 participants was conducted. Workers' health status was assessed via (1) Total Ocular Symptom Score (TOSS), (2) Total Nasal Symptom Score (TNSS), (3) St. George's Respiratory Questionnaire (SGPQ), and (4) Asthma Control Test (ACT). The maximum PM_2.5 concentration was measured at 122.90 ± 2.07 µg/m³ during third week of August 2016. Meanwhile, the minimum concentration was measured at 57.47 ± 3.80 µg/m³ and 57.47 ± 1.64 µg/m³ during fourth week of July 2016 and first week of August 2017 respectively. Findings revealed that TOSS, TNSS, and SGPQ changes were significantly (p < 0.05) associated with the concentration of PM_2.5. Outdoor workers were more significantly (p < 0.05) affected by changes in PM_2.5 compared to indoor workers with a moderate correlation (r value ranged from 0.4 to 0.7). Ironically, no significant association was found between ACT assessment and PM_2.5. Collectively, our findings suggested that changes in the concentration of PM_2.5 threatened the respiratory health of outdoor workers. The existing policy should be strengthened and preventive measures to be enforced safeguarding health status of outdoor workers.

Early pregnancy PM2.5 exposure and its inorganic constituents affect fetal growth by interrupting maternal thyroid function

Early pregnancy is crucial for fetal growth. Maternal thyroid hormone is critical for fetal growth and can be disturbed under exogenous exposure. However, it's uncertain whether exposure to PM_2.5 and inorganic constituents during early pregnancy can affect TH and fetal growth. We focused on the associations of early-pregnancy PM_2.5 and inorganic constituents with fetal growth and maternal THs. PM_2.5 concentration was estimated using a satellite-based spatiotemporal model. Fetal biparietal diameter (BPD), head circumference (HC), femur length (FL), and humerus length (HL) were measured by ultrasonography at median 15.6, 22.2, and 33.1 gestational weeks. Levels of 28 PM_2.5 constituents were measured in a sub-group of 329 pregnancies. Maternal serum free thyroxine (fT4), free triiodothyronine, and thyroid-stimulating hormone levels were measured at 14 weeks of gestation. Mixed-effect models and multiple linear regression were applied to evaluate the associations of PM_2.5 and its constituents with fetal growth measures. Mediation analysis was used to examine the mediating role of the THs. Results showed that each 10 μg/m³ increase in PM_2.5 was associated with 0.20 mm reductions in BPD (95%CI: 0.33, -0.01), 0.27 mm decreases in FL (95%CI: 0.40, -0.13), and 0.36 decreases in HL (95%CI: 0.49, -0.23). Per 10 μg/m³ increment in PM_2.5 was correlated with 5.82% decreases in the fT4 level (95% CI: 8.61%, -2.96%). FT4 accounted for 14.3% of PM_2.5 exposure-induced change in BPD at first follow-up. Al (β = -2.91, 95%CI: 5.17, -0.66), Si (β = -1.20, 95%CI: 2.22, -0.19), K (β = -3.09, 95%CI: 5.41, -0.77), Mn (β = -47.20, 95%CI: 83.68, -10.79) and Zn (β = -3.02, 95%CI: 5.55, -0.49) were associated with decreased fetal BPD, especially in first follow-up. Zn (β = -38.12%, 95% CI: 58.52%, -8.61%) was also associated with decreased fT4 levels. Overall, early pregnancy exposure to PM_2.5 and its constituents was associated with fetal growth restriction and decreased maternal fT4 levels might mediate the effect of PM_2.5.

Utilizing Real-time Technology to Assess the Impact of Home Environmental Exposures on Asthma Symptoms: Protocol for an Observational Pilot Study

BACKGROUND

It is estimated that over 60% of adults with asthma have uncontrolled symptoms, representing a substantial health and economic impact. The effects of the home environment and exposure to volatile organic compounds (VOCs) and fine particulate matter (PM2.5) on adults with asthma remain unknown. In addition, methods currently used to assess the home environment do not capture real-time data on potentially modifiable environmental exposures or their effect on asthma symptoms.

OBJECTIVE

The aims of this study are to (1) determine the feasibility and usability of ecological momentary assessment (EMA) to assess self-report residential environmental exposures and asthma symptoms, home monitoring of objective environmental exposures (total VOCs and PM2.5), and lung function in terms of forced expiratory volume in 1 second (FEV1%); (2) assess the frequency and level of residential environmental exposures (eg, disinfectants/cleaners, secondhand smoke) via self-reported data and home monitoring objective measures; (3) assess the level of asthma control as indicated by self-reported asthma symptoms and lung function; and (4) explore associations of self-reported and objective measures of residential environmental exposures with self-reported and objective measures of asthma control.

METHODS

We will recruit 50 adults with asthma who have completed our online Global COVID-19 Asthma Study, indicated willingness to be contacted for future studies, reported high use of disinfectant/cleaning products, and have asthma that is not well controlled. Participants will receive an indoor air quality monitor and a home spirometer to measure VOCs, PM2.5, and FEV1%, respectively. EMA data will be collected using a personal smartphone and EMA software platform. Participants will be sent scheduled and random EMA notifications to assess asthma symptoms, environmental exposures, lung function, and mitigation strategies. After the 14-day data collection period, participants will respond to survey items related to acceptability, appropriateness, and feasibility.

RESULTS

This study was funded in March 2021. We pilot tested our procedures and began recruitment in April 2022. The anticipated completion of the study is 2023.

CONCLUSIONS

Findings from this feasibility study will support a powered study to address the impact of home environmental exposures on asthma symptoms and develop tailored, home-based asthma interventions that are responsive to the changing home environment and home routines.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05224076; https://clinicaltrials.gov/ct2/show/NCT05224076.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39887.

Associations between ambient temperature and adult asthma hospitalizations in Beijing, China: a time-stratified case-crossover study

Background

Studies on the associations between ambient temperature and asthma hospitalizations are limited, and the results are controversial. We aimed to assess the short-term effects of ambient temperature on the risk of asthma hospitalizations and quantify the hospitalization burdens of asthma attributable to non-optimal temperature in adults in Beijing, China.

Methods

We collected daily asthma hospitalizations, meteorological factors and air quality data in Beijing from 2012 to 2015. We applied a time-stratified case-crossover design and fitted a distributed lag non-linear model with a conditional quasi-Poisson regression to explore the association between ambient temperature and adult asthma hospitalizations. The effect modifications of these associations by gender and age were assessed by stratified analyses. We also computed the attributable fractions and numbers with 95% empirical confidence intervals (eCI) of asthma hospitalizations due to extreme and moderate temperatures.

Results

From 2012 to 2015, we identified a total of 18,500 hospitalizations for asthma among adult residents in Beijing, China. Compared with the optimal temperature (22 °C), the cumulative relative risk (CRR) over lag 0–30 days was 2.32 with a 95% confidence interval (CI) of 1.57–3.42 for extreme cold corresponding to the 2.5th percentile (− 6.5 °C) of temperature distribution and 2.04 (95% CI 1.52–2.74) for extreme heat corresponding to the 97.5th percentile (29 °C) of temperature distribution. 29.1% (95% eCI 17.5–38.0%) of adult asthma hospitalizations was attributable to non-optimum temperatures. Moderate cold temperatures yielded most of the burdens, with an attributable fraction of 20.3% (95% eCI 9.1–28.7%). The temperature-related risks of asthma hospitalizations were more prominent in females and younger people (19–64 years old).

Conclusions

There was a U-shaped association between ambient temperature and the risk of adult asthma hospitalizations in Beijing, China. Females and younger patients were more vulnerable to the effects of non-optimum temperatures. Most of the burden was attributable to moderate cold. Our findings may uncover the potential impact of climate changes on asthma exacerbations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-01960-8.

Considering biomarkers in asthma disease severity

Amongst patients with asthma, reliance on the type/dose of prescribed medication and symptom control does not adequately capture those at risk of adverse outcomes, and we need biomarkers for risk and treatment stratification which are consistently accurate, readily quantifiable and reproducible. The majority of patients with severe asthma, regardless of age, have predominant type-2 (T2) inflammation mediated disease, making airway/blood eosinophils, FeNO, periostin and/or allergic sensitization potentially important biomarkers for severe disease. In both adult and pediatric asthma, there is scope to improve prediction of severe attacks by using a composite T2 biomarkers of blood eosinophils and FeNO. Technological advances in component-resolved diagnostics (CRD) microarray technologies coupled with the development of interpretation software offer a possibility to use CRD as biomarkers of asthma severity amongst sensitized asthmatics. Genetic predisposition and polygenic risk scores of relevant traits (e.g., lung function, host immune responses, biomarkers of exposure from the indoor and outdoor environment, infection and microbial dysbiosis) may also contribute to prediction algorithms. We challenge the idea that asthma can be accurately defined in an individual patient by a discrete and static "endotype" (e.g., T2-high asthma). As we traverse the new era of molecular endotyping in asthma, we need to understand how relevant mechanisms impact patient outcomes, and in parallel develop new tools and approaches to stratify therapies and define individual patient trajectories.