Air pollution in the Asia-Pacific Region: A Joint Asian Pacific Society of Respirology/American Thoracic Society perspective (Republication)

Assessing the Global Impact of Ambient Air Pollution on Cancer Incidence and Mortality: A Comprehensive Meta-Analysis

PURPOSE

This study aims to examine the association between exposure to major ambient air pollutants and the incidence and mortality of lung cancer and some nonlung cancers.

METHODS

This meta-analysis used PubMed and EMBASE databases to access published studies that met the eligibility criteria. Primary analysis investigated the association between exposure to air pollutants and cancer incidence and mortality. Study quality was assessed using the Newcastle Ottawa Scale. Meta-analysis was conducted using R software.

RESULTS

The meta-analysis included 61 studies, of which 53 were cohort studies and eight were case-control studies. Particulate matter 2.5 mm or less in diameter (PM2.5) was the exposure pollutant in half (55.5%), and lung cancer was the most frequently studied cancer in 59% of the studies. A pooled analysis of exposure reported in cohort and case-control studies and cancer incidence demonstrated a significant relationship (relative risk [RR], 1.04 [95% CI, 1.02 to 1.05]; I2, 88.93%; P < .05). A significant association was observed between exposure to pollutants such as PM2.5 (RR, 1.08 [95% CI, 1.04 to 1.12]; I2, 68.52%) and nitrogen dioxide (NO2) (RR, 1.03 [95% CI, 1.01 to 1.05]; I2, 73.52%) and lung cancer incidence. The relationship between exposure to the air pollutants and cancer mortality demonstrated a significant relationship (RR, 1.08 [95% CI, 1.07 to 1.10]; I2, 94.77%; P < .001). Among the four pollutants, PM2.5 (RR, 1.15 [95% CI, 1.08 to 1.22]; I2, 95.33%) and NO2 (RR, 1.05 [95% CI, 1.02 to 1.08]; I2, 89.98%) were associated with lung cancer mortality.

CONCLUSION

The study confirms the association between air pollution exposure and lung cancer incidence and mortality. The meta-analysis results could contribute to community cancer prevention and diagnosis and help inform stakeholders and policymakers in decision making.

Association between ambient air pollutants and lipid profile: A systematic review and meta-analysis

BACKGROUND

Studies of the effects of atmospheric pollutants on lipid profiles remain inconsistent and controversial.

AIM

The study was aimed to investigate the relationship between the exposure to ambient air pollutants and variations in the blood lipid profiles in the population.

METHODS

A comprehensive search of three different databases (PubMed, Web of Science, and the Cochrane Library) until December 17, 2022, yielded 17 origional studies fulfilling the inclusion criteria for a meta-analysis. Aggregate effect measures and 95% confidence intervals (95% CI) for the relevant ambient air pollutants were deduced employing random effects models.

RESULTS

The collective meta-analysis indicated that long-term exposure to PM₁, PM_2.5, PM₁₀ and CO showed a substantial correlation with TC (PM₁: β = 2.04, 95%CI = 0.15-3.94; PM_2.5: β = 1.11, 95%CI = 0.39-1.84; PM₁₀: β = 1.70, 95%CI = 0.67-2.73; CO: β = 0.08, 95%CI = 0.06-0.10), PM₁₀ exhibited a significant association with TG (β = 0. 537,95% CI = 0.09-0.97), whereas HDL-C demonstrated notable relationships with PM₁, PM₁₀, SO₂ and CO (PM₁: β = -2.38, 95%CI = -4.00 to -2.76; PM₁₀: β = -0.77, 95%CI = -1.33 to -0.21; SO₂: β = -0.91, 95%CI = -1.73 to -0.10; CO: β = -0.03, 95%CI = -0.05 to 0.00). PM_2.5, PM₁₀ also showed significant associations with LDL-C (PM_2.5: β = 1.44 95%CI = 0.48-2.40; PM₁₀: β = 1.62 95%CI = 0.90-2.34). Subgroup analysis revealed significant or stronger correlations predominantly in cohort study designs, with higher male comparisons, and in regions exhibiting elevated contaminant levels.

CONCLUSION

In summary, the analysis substantiates that ambient air pollutants can be recognized as potent contributors to alterations in lipid profiles, particularly particulate pollutants which exert more obvious effects on lipid profiles.

The Association between Childhood Exposure to Ambient Air Pollution and Obesity: A Systematic Review and Meta-Analysis

Obesity has become a worldwide epidemic; 340 million of children and adolescents were overweight or obese in 2016, and this number continues to grow at a rapid rate. Epidemiological research has suggested that air pollution affects childhood obesity and weight status, but the current evidence remains inconsistent. Therefore, the aim of this meta-analysis was to estimate the effects of childhood exposure to air pollutants on weight. A total of four databases (PubMed, Web of Science, Embase, and Cochrane Library) were searched for publications up to December 31, 2021, and finally 15 studies met the inclusion criteria for meta-analysis. Merged odds ratios (ORs), coefficients (β), and 95% confidence intervals (95% CIs) that were related to air pollutants were estimated using a random-effects model. The meta-analysis indicated that air pollutants were correlated with childhood obesity and weight gain. For obesity, the association was considerable for PM₁₀ (OR = 1.12, 95% CI: 1.06, 1.18), PM_2.5 (OR = 1.28, 95% CI: 1.13, 1.45), PM₁ (OR = 1.41, 95% CI: 1.30, 1.53), and NO₂ (OR = 1.11, 95% CI: 1.06, 1.18). Similarly, BMI status increased by 0.08 (0.03-0.12), 0.11 (0.05-0.17), and 0.03 (0.01-0.04) kg/m² with 10 μg/m³ increment in exposure to PM₁₀, PM_2.5, and NO₂. In summary, air pollution can be regarded as a probable risk factor for the weight status of children and adolescents. The next step is to conduct longer-term and large-scale studies on different population subgroups, exposure concentrations, and pollutant combinations to provide detailed evidence. Meanwhile, integrated management of air pollution is essential.

Health Effects of Long-Term Exposure to Ambient PM2.5 in Asia-Pacific: a Systematic Review of Cohort Studies

Abstract

Purpose of Review

Health effects of long-term exposure to ambient PM_2.5 vary with regions, and 75% of the deaths attributable to PM_2.5 were estimated in Asia-Pacific in 2017. This systematic review aims to summarize the existing evidence from cohort studies on health effects of long-term exposure to ambient PM_2.5 in Asia-Pacific.

Recent Findings

In Asia-Pacific, 60 cohort studies were conducted in Australia, Mainland China, Hong Kong, Taiwan, and South Korea. They consistently supported associations of long-term exposure to PM_2.5 with increased all-cause/non-accidental and cardiovascular mortality as well as with incidence of cardiovascular diseases, type 2 diabetes mellitus, kidney diseases, and chronic obstructive pulmonary disease. Evidence for other health effects was limited. Inequalities were identified in PM_2.5-health associations.

Summary

To optimize air pollution control and public health prevention, further studies need to assess the health effects of long-term PM_2.5 exposure in understudied regions, the health effects of long-term PM_2.5 exposure on mortality and risk of type 2 diabetes mellitus, renal diseases, dementia and lung cancer, and inequalities in PM_2.5-health associations. Study design, especially exposure assessment methods, should be improved.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40572-022-00344-w.

Semi-outdoor filterless air purifier for smog and microbial protection with water purifier system

PURPOSE

Air pollution and COVID-19 problems are being increasingly scrutinized. This article discusses the optimum design of an indoor and semi-outdoor air purifier, using a water-based filtration system.

METHODS

An air purifier was fabricated, then comparison of purifying efficacy of the system between untreated air and using an air pump was done. Incense smoke was generated within a room for 10 seconds. The number of particle sizes of PM0.3, PM0.5, PM1.0, PM3.0, PM5.0, and PM10 μm (particle/ m3) as well as the detection of mass concentration of PM1.0, PM2.5, PM5.0, and PM10 (mg/m3) at 0 and 5 min were recorded. Each experiment was repeated 10 times.

RESULTS

Particles in untreated air, except PM10, showed the maximum increase rate of the number of particle sizes greater than the air pump experiment. The highest differentiation between two methods was that PM1.0 and PM0.5 of untreated air increased to 113.647 and 61.539 % whereas the air pump method showed 4.720 and 2.533 %, respectively. The PM mass concentration of untreated air increased from 50.217 to 51.167 % while the increased rate of PM using an air pump was 2.784 to 2.902 %.

CONCLUSION

This study proposed a water-based air filtration technique, which can reduce the level of particulate matter, and also is a low-cost prototype. For the next experiment, the study should extend test length, clarify an optimum ratio of disinfectant technologies, connect with the internet of things, compare the efficiency with a HEPA filter air purifier, and then also measure some particles which are smaller than 0.2 μm.

Exposure to PM2.5 is a risk factor for acute exacerbation of surgically diagnosed idiopathic pulmonary fibrosis: a case-control study

Background

Short-term exposure to ozone and nitrogen dioxide is a risk factor for acute exacerbation (AE) of idiopathic pulmonary fibrosis (AE-IPF). The comprehensive roles of exposure to fine particulate matter in AE-IPF remain unclear. We aim to investigate the association of short-term exposure to fine particulate matter with the incidence of AE-IPF and to determine the exposure-risk time window during 3 months before the diagnosis of AE-IPF.

Methods

IPF patients were retrospectively identified from the nationwide registry in Japan. We conducted a case–control study to assess the correlation between AE-IPF incidence and short-term exposure to eight air pollutants, including particulate matter < 2.5 µm (PM_2.5). In the time-series data, we compared monthly mean exposure concentrations between months with AE (case months) and those without AE (control months). We used multilevel mixed-effects logistic regression models to consider individual and institutional-level variables, and also adjusted these models for several covariates, including temperature and humidity. An additional analysis with different monthly lag periods was conducted to determine the risk-exposure time window for 3 months before the diagnosis of AE-IPF.

Results

Overall, 152 patients with surgically diagnosed IPF were analyzed. AE-IPF was significantly associated with an increased mean exposure level of nitric oxide (NO) and PM_2.5 30 days prior to AE diagnosis. Adjusted odds ratio (OR) with a 10 unit increase in NO was 1.46 [95% confidence interval (CI) 1.11–1.93], and PM_2.5 was 2.56 (95% CI 1.27–5.15). Additional analysis revealed that AE-IPF was associated with exposure to NO during the lag periods lag 1, lag 2, lag 1–2, and lag 1–3, and PM_2.5 during the lag periods lag 1 and lag 1–2.

Conclusions

Our results show that PM_2.5 is a risk factor for AE-IPF, and the risk-exposure time window related to AE-IPF may lie within 1–2 months before the AE diagnosis. Further investigation is needed on the novel findings regarding the exposure to NO and AE-IPF.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01671-6.

Air Pollution Is Associated with Poor Cognitive Function in Taiwanese Adults

The issue of air pollution is gaining increasing attention worldwide, and mounting evidence has shown an association between air pollution and cognitive decline. The aim of this study was to investigate the relationships between air pollutants and cognitive impairment using the Mini-Mental State Exam (MMSE) and its sub-domains. In this study, we used data from the Taiwan Biobank combined with detailed daily data on air pollution. Cognitive function was assessed using the MMSE and its five subgroups of cognitive functioning. After multivariable linear regression analysis, a high level of particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5), low ozone (O₃), high carbon monoxide (CO), high sulfur dioxide (SO₂), high nitric oxide (NO), high nitrogen dioxide (NO₂), and high nitrogen oxide (NO_x) were significantly associated with low total MMSE scores. Further, high SO₂ and low O₃ were significantly associated with low MMSE G1 scores. Low O₃, high CO, high SO₂, high NO₂, and high NO_x were significantly associated with low MMSE G4 scores, and high PM_2.5, high particulate matter with an aerodynamic diameter of ≤10 μm (PM₁₀), high SO₂, high NO₂, and high NO_x were significantly associated with low MMSE G5 scores. Our results showed that exposure to different air pollutants may lead to general cognitive decline and impairment of specific domains of cognitive functioning, and O₃ may be a protective factor. These findings may be helpful in the development of policies regarding the regulation of air pollution.

Health Effects of Ozone on Respiratory Diseases

Ozone is known to cause bronchial inflammation and airway hyper-responsiveness via oxidative injury and inflammation. While other ambient air pollutants such as particulate matter (PM) and nitrogen dioxide showed decreasing trends in mean annual concentrations, ozone concentrations have not declined recently in most countries across the world. Short-term exposure to high concentrations of ozone has been associated with increased mortality and cardiovascular and respiratory morbidity in many regions of the world. However, the long-term effects of ozone have been less investigated than the short-term exposure due to the difficulty in modeling ozone exposure and linking between individual exposures and health outcome data. A recently developed model of ozone exposure enabled the investigation of long-term ozone effects on health outcomes. Recent findings suggested that long-term exposure to ozone was associated with an increased risk of cardiovascular and respiratory mortality. Longitudinal studies using large cohorts also revealed that long-term exposure to ozone was associated with a greater decline in lung function and the progression of emphysema. The development of long-term standards for ozone as well as PM should be considered to protect the respiratory health of the general population and people with chronic respiratory diseases.

Association between secondhand smoke exposure and hypertension: nearly as large as smoking

: Active smoking is a widely accepted risk factor for cardiovascular disease and is recognized as a major public health problem. Passive smoking, also known as secondhand smoke exposure (SHSE), is thought to have similar cardiovascular consequences and the risk has been postulated to be equivalent to that of active smoking. A major component of this risk involves the connection with chronic hypertension. There are several population-based observational studies investigating the relationship between SHSE and chronic hypertension, all of which demonstrate a positive association. Given that SHSE appears to be a risk factor for chronic hypertension, SHSE should also be a risk factor for hypertensive end-organ disease. Many studies have sought to investigate this relationship, but this has yet to be fully elucidated. In this review, we focus on the current evidence regarding the association between SHSE and hypertension as well as exploration of the links between SHSE and hypertensive end-organ damage.

Ambient air pollution and body weight status in adults: A systematic review and meta-analysis

Overweight and obesity have become a global epidemic and concern, and contributed to at least 4.0 million deaths each year worldwide. However, current evidence regarding the impact of air pollution on body weight status remains inconsistent. We therefore conducted a systematic review and meta-analysis to evaluate the effect of long-term exposure to ambient air pollutants on body weight status in adults. Three databases were searched up to Dec 31, 2019 for articles investigating the association of gaseous (sulfur dioxide, nitrogen dioxide, ozone) and particulate (diameter ≤ 10 μm or ≤ 2.5 μm) air pollutants with body weight status. Random effect models were used to estimate the pooled odds ratios (ORs), regression coefficients (β) and their 95% confidence intervals (95% CIs) associated with air pollution. Among twelve studies that were eligible in the systematic review, ten were used to estimate the pooled effect size, and most of them were cross-sectional studies. We identified that ambient air pollution had adverse effects on body weight status. For example, elevated PM_2.5 and O₃ were associated with higher level of body mass index, with the pooled β (95% CIs) of 0.34 (0.30-0.38) and 0.21 (0.17-0.24) per 10 μg/m³ increment, respectively. In addition, increased NO₂, SO₂ and O₃ were associated with higher risk of having overweight/obesity, with the corresponding pooled OR (95% CI) of 1.13 (1.01-1.26), 1.04 (1.01-1.06) and 1.07 (1.02-1.13) per 10 μg/m³ increment. Overall, air pollution is a potential risk factor for body weight status in adults, and more high-quality studies, especially prospective studies from severely polluted regions, are warranted for comprehensive understanding of its health effects.

Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea

Amidst recent industrialization in South Korea, Seoul has experienced high levels of air pollution, an issue that is magnified due to a lack of effective air pollution prediction techniques. In this study, the Prophet forecasting model (PFM) was used to predict both short-term and long-term air pollution in Seoul. The air pollutants forecasted in this study were PM2.5, PM10, O3, NO2, SO2, and CO, air pollutants responsible for numerous health conditions upon long-term exposure. Current chemical models to predict air pollution require complex source lists making them difficult to use. Machine learning models have also been implemented however their requirement of meteorological parameters render the models ineffective as additional models and infrastructure need to be in place to model meteorology. To address this, a model needs to be created that can accurately predict pollution based on time. A dataset containing three years worth of hourly air quality measurements in Seoul was sourced from the Seoul Open Data Plaza. To optimize the model, PFM has the following parameters: model type, changepoints, seasonality, holidays, and error. Cross validation was performed on the 2017-18 data; then, the model predicted 2019 values. To compare the predicted and actual values and determine the accuracy of the model, the statistical indicators: mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), and coverage were used. PFM predicted PM2.5 and PM10 with a MAE value of 12.6 µg/m3 and 19.6 µg/m3, respectively. PFM also predicted SO2 and CO with a MAE value of 0.00124 ppm and 0.207 ppm, respectively. PFM's prediction of PM2.5 and PM10 had a MAE approximately 2 times and 4 times less, respectively, than comparable models. PFM's prediction of SO2and CO had a MAE approximately five times and 50 times less, respectively, than comparable models. In most cases, PFM's ability to accurately forecast the concentration of air pollutants in Seoul up to one year in advance outperformed similar models proposed in literature. This study addresses the limitations of the prior two PFM studies by expanding the modelled air pollutants from three pollutants to six pollutants while increasing the prediction time from 3 days to 1 year. This is also the first research to use PFM in Seoul, Korea. To achieve more accurate results, a larger air pollution dataset needs to be implemented with PFM. In the future, PFM should be used to predict and model air pollution in other regions, especially those without advanced infrastructure to model meteorology alongside air pollution. In Seoul, Seoul's government can use PFM to accurately predict air pollution concentrations and plan accordingly.

Decreased lung function is associated with elevated ferritin but not iron or transferrin saturation in 42,927 healthy Korean men: A cross-sectional study

Objectives

Though elevated ferritin level and decreased lung function both predispose people to cardio-metabolic disease, few reports have investigated the association between them. Furthermore, it remains unclear whether the association reflects a change in iron stores or an epiphenomenon reflecting metabolic stress. Therefore, we looked for possible associations between ferritin, iron, and transferrin saturation (TSAT) and lung function to clarify the role of iron-related parameters in healthy men.

Methods

We conducted a cohort study of 42,927 healthy Korean men (mean age: 38.6 years). Percent predicted forced expiratory volume in one second (FEV1%) and forced vital capacity (FVC%) were categorized into quartiles. Adjusted odds ratios (aORs) and 95% confidence intervals (using the highest quartile as reference) were calculated for hyperferritinemia, high iron, and high TSAT after controlling for potential confounders.

Results

The median ferritin level was 199.8 (141.5–275.6) ng/mL. The prevalence of hyperferritinemia (defined as >300 ng/mL) was 19.3%. Subjects with hyperferritinemia had lower FEV1% and FVC% than those with normal ferritin level with a slight difference, but those were statistically significant (99.22% vs.99.61% for FEV1%, p = 0.015 and 98.43% vs. 98.87% for FVC, p = 0.001). However, FEV1/FVC ratio was not significantly different between groups (P = 0.797). Compared with the highest quartile, the aORs for hyperferritinemia across decreasing quartiles were 1.081 (1.005–1.163), 1.100 (1.007–1.200), and 1.140 (1.053–1.233) for FEV1% (p for trend = 0.007) and 1.094 (1.018–1.176), 1.101 (1.021–1.188), and 1.150 (1.056–1.252) for FVC% (p for trend = 0.001). However, neither FEV1% nor FVC% was associated with iron or TSAT.

Conclusions

Hyperferritinemia was associated with decreased lung function in healthy Korean men, but iron and TSAT were not. Longitudinal follow-up studies are required to validate our findings.

Air pollution and human health

[No abstract available]

Identification of long non-coding RNA and circular RNA in mice after intra-tracheal instillation with fine particulate matter

BACKGROUND

Fine particulate matter (PM_2.5) exposure has been proved to be associated with respiratory diseases in epidemiological studies, but the underlying mechanisms are not clear. One of the most important mechanisms involved is inflammation. Non-coding RNAs are proposed to play crucial roles in epigenetic modulation and post-transcriptional regulation. Identification of non-coding RNAs can show us the new insight into the molecular toxicity of PM_2.5.

MATERIALS AND METHODS

Intra-tracheal instillation of saline or PM_2.5 was performed in BALB/c Mice once a week for consecutive eight weeks. Genomewide transcriptome profiling of coding genes, long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in mice lung were done by ribosomal RNA-depleted RNA sequencing. Lung histological alternations were observed in haematoxylin and eosin (HE) staining sections. The expressions of pro-inflammatory cytokines and Nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome were quantified by qRT-PCR、ELISA and Western blot.

RESULTS

1873 coding genes, 885 lncRNAs and 142 circRNAs were differentially expressed in lung tissues of the saline and PM_2.5 exposed mice. The upregulated expressions of lncRNA NONMMUT065867, lncRNA NONMMUT064312, lncRNA NONMMUT018123 and the downregulated expressions of circRNA CBT15_circR_1011, circRNA mm9_circ_005915 were identified by qRT-PCR in PM_2.5 group. The pulmonary inflammation score was higher in PM_2.5 group. What's more, the expressions of pro-inflammatory cytokines and NLRP3 inflammasome were upregulated in PM_2.5 exposed mice.

CONCLUSION

PM_2.5 causes lung inflammation and increases the expression of NLRP3 inflammasome. The identified novel lncRNAs and circRNAs may paly important role in the development of lung inflammation caused by PM_2.5.