Is standard deviation of daily PM2.5 concentration associated with respiratory mortality?

Ambient fine particulate matter and its constituents may exacerbate the acceleration of aging in adults

Both ambient fine particulate matter (PM2.5) and aging are important urban concerns. However, the associations between PM2.5 constituents and the acceleration of aging (AA) remain unclear. We included 16,051 adults (aged 25-80 years) with 19,252 medical observations in Taiwan during 2008-2017. 2-year average PM2.5 and its five major constituents were assessed using a two-stage machine learning model at a resolution of 1 km2. AA was determined by the difference between the Klemera-Doubal biological age and chronological age. A linear mixed model (LMM) with inverse probability weights was used to examine the associations between AA and air pollution. In a semi-randomized study design, we applied a post-matching LMM to assess the impacts of changes in air pollution exposure on AA. Each interquartile range increase in ambient PM2.5, SO4-2, NO3-, NH4+, organic matters (OM), and black carbon (BC) was associated with a 0.20 (95 %confidence interval [CI]: 0.17-0.24), 0.19 (0.15-0.23), 0.14 (0.11-0.18), 0.21 (0.17-0.24), 0.22 (0.19-0.26) and 0.25 (0.21-0.28) year increase in AA, respectively. BC was generally associated with the greatest increase in AA as compared to other constituents. We did not find evident thresholds in their concentration-response associations. Participants exposed to increased levels of PM2.5, SO4-2, NO3-, NH4+, OM, and BC experienced an increase in AA of 0.11 (-0.07-0.29), 0.20 (0.02-0.39), 0.15 (-0.02-0.33), 0.12 (-0.07-0.31), 0.24 (0.07-0.41), and 0.30 (0.07-0.52) years, respectively, compared to those exposed to decreased/unchanged levels. Long-term exposure to ambient PM2.5 and its constituents may accelerate biological aging among Chinese adults. Exposed to increased levels may further aggregate the aging process. This study suggests that reducing exposure to air pollution is beneficial, even for residents within moderately-to-highly polluted regions, such as Taiwan. Rigorous regulation of PM2.5 and its constituents may prevent the acceleration of biological age.

Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis

In recent years, the precision of exposure assessment methods has been rapidly improved and more widely adopted in epidemiological studies. However, such methodological advancement has introduced additional heterogeneity among studies. The precision of exposure assessment has become a potential confounding factors in meta-analyses, whose impacts on effect calculation remain unclear. To explore, we conducted a meta-analysis to integrate the long- and short-term exposure effects of PM2.5, NO2, and O3 on all-cause, cardiovascular, and respiratory mortality in the Chinese population. Literature was identified through Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure before August 28, 2023. Sub-group analyses were performed to quantify the impact of exposure assessment precisions and pollution levels on the estimated risk. Studies achieving merely city-level resolution and population exposure are classified as using traditional assessment methods, while those achieving sub-kilometer simulations and individual exposure are considered finer assessment methods. Using finer assessment methods, the RR (under 10 μg/m3 increment, with 95% confidence intervals) for long-term NO2 exposure to all-cause mortality was 1.13 (1.05-1.23), significantly higher (p-value = 0.01) than the traditional assessment result of 1.02 (1.00-1.03). Similar trends were observed for long-term PM2.5 and short-term NO2 exposure. A decrease in short-term PM2.5 levels led to an increase in the RR for all-cause and cardiovascular mortality, from 1.0035 (1.0016-1.0053) and 1.0051 (1.0021-1.0081) to 1.0055 (1.0035-1.0075) and 1.0086 (1.0061-1.0111), with weak between-group significance (p-value = 0.13 and 0.09), respectively. Based on the quantitative analysis and literature information, we summarized four key factors influencing exposure assessment precision under a conceptualized framework: pollution simulation resolution, subject granularity, micro-environment classification, and pollution levels. Our meta-analysis highlighted the urgency to improve pollution simulation resolution, and we provide insights for researchers, policy-makers and the public. By integrating the most up-to-date epidemiological research, our study has the potential to provide systematic evidence and motivation for environmental management.

Characterization of airborne endotoxin in personal exposure to fine particulate matter (PM2.5) and bioreactivity for elderly residents in Hong Kong

The heavy metals and bioreactivity properties of endotoxin in personal exposure to fine particulate matter (PM2.5) were characterized in the analysis. The average personal exposure concentrations to PM2.5 were ranged from 6.8 to 96.6 μg/m3. The mean personal PM2.5 concentrations in spring, summer, autumn, and winter were 32.1±15.8, 22.4±11.8, 35.3±11.9, and 50.2±19.9 μg/m3, respectively. There were 85 % of study targets exceeded the World Health Organization (WHO) PM2.5 threshold (24 hours). The mean endotoxin concentrations ranged from 1.086 ± 0.384-1.912 ± 0.419 EU/m3, with a geometric mean (GM) varied from 1.034 to 1.869. The concentration of iron (Fe) (0.008-1.16 μg/m3) was one of the most abundant transition metals in the samples that could affect endotoxin toxicity under Toll-Like Receptor 4 (TLR4) stimulation. In summer, the interleukin 6 (IL-6) levels showed statistically significant differences compared to other seasons. Spearman correlation analysis showed endotoxin concentrations were positively correlated with chromium (Cr) and nickel (Ni), implying possible roles as nutrients and further transport via adhering to the surface of fine inorganic particles. Mixed-effects model analysis demonstrated that Tumor necrosis factor-α (TNF-α) production was positively associated with endotoxin concentration and Cr as a combined exposure factor. The Cr contained the highest combined effect (0.205-0.262), suggesting that Cr can potentially exacerbate the effect of endotoxin on inflammation and oxidative stress. The findings will be useful for practical policies for mitigating air pollution to protect the public health of the citizens.

PM2.5 Causes Increased Bacterial Invasion by Affecting HBD1 Expression in the Lung

Our research addresses the critical environmental issue of a fine particulate matter (PM2.5), focusing on its association with the increased infection risks. We explored the influence of PM2.5 on human beta-defensin 1 (HBD1), an essential peptide in mucosal immunity found in the airway epithelium. Using C57BL/6J mice and human bronchial epithelial cells (HBE), we examined the effects of PM2.5 exposure followed by Pseudomonas aeruginosa (P. aeruginosa) infection on HBD1 expression at both mRNA and protein levels. The study revealed that PM2.5's toxicity to epithelial cells and animals varies with time and concentration. Notably, HBE cells exposed to PM2.5 and P. aeruginosa showed increased bacterial invasion and decreased HBD1 expression compared to the cells exposed to P. aeruginosa alone. Similarly, mice studies indicated that combined exposure to PM2.5 and P. aeruginosa significantly reduced survival rates and increased bacterial invasion. These harmful effects, however, were alleviated by administering exogenous HBD1. Furthermore, our findings highlight the activation of MAPK and NF-κB pathways following PM2.5 exposure. Inhibiting these pathways effectively increased HBD1 expression and diminished bacterial invasion. In summary, our study establishes that PM2.5 exposure intensifies P. aeruginosa invasion in both HBE cells and mouse models, primarily by suppressing HBD1 expression. This effect can be counteracted with exogenous HBD1, with the downregulation mechanism involving the MAPK and NF-κB pathways. Our study endeavors to elucidate the pathogenesis of lung infections associated with PM2.5 exposure, providing a novel theoretical basis for the development of prevention and treatment strategies, with substantial clinical significance.

Nonlinear effect of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China: A time-series analysis

Many studies have illustrated adverse effects of short-term exposure to air pollution on human health, which usually assumes a linear exposure-response (E-R) function in the delineation of health effects due to air pollution. However, nonlinearity may exist in the association between air pollutant concentrations and health outcomes such as adult pneumonia hospital visits, and there is a research gap in understanding the nonlinearity. Here, we utilized both the distributed lag model (DLM) and nonlinear model (DLNM) to compare the linear and nonlinear impacts of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China. While both models show adverse effects of air pollutants on adult pneumonia hospital visits, the DLNM shows an attenuation of E-R curves at high concentrations. Moreover, the DLNM may reveal delayed health effects that may be missed in the DLM, e.g., ozone exposure and pneumonia hospital visits. With the stratified analysis of air pollutants on adult pneumonia hospital visits, both models consistently reveal that the influence of air pollutants is higher during the cold season than during the warm season. Nevertheless, they may behave differently in terms of other subgroups, such as age, gender and visit types. For instance, while no significant impact due to PM_2.5 in any of the subgroups abovementioned emerges based on DLM, the results from DLNM indicate statistically significant impacts for the subgroups of elderly, female and emergency department (ED) visits. With respect to adjustment by two-pollutants, PM₁₀ effect estimates for pneumonia hospital visits were the most robust in both DLM and DLNM, followed by NO₂ and SO₂ based on the DLNM. Considering the estimated health effects of air pollution relying on the assumed E-R functions, our results demonstrate that the traditional linear association assumptions may overlook some potential health risks.

Observed causative impact of fine particulate matter on acute upper respiratory disease: a comparative study in two typical cities in China

Association between fine particulate matter (PM_2.5) and respiratory health has attracted great concern in China. Substantial epidemiological evidences confirm the correlational relationship between PM_2.5 and respiratory disease in many Chinese cities. However, the causative impact of PM_2.5 on respiratory disease remains uncertain and comparative analysis is limited. This study aims to explore and compare the correlational relationship as well as the causal connection between PM_2.5 and upper respiratory tract infection (URTI) in two typical cities (Beijing, Shenzhen) with rather different ambient air environment conditions. The distributed lag nonlinear model (DLNM) was used to detect the correlational relationship between PM_2.5 and URTI by revealing the lag effect pattern of PM_2.5 on URTI. The convergent cross mapping (CCM) method was applied to explore the causal connection between PM_2.5 and URTI. The results from DLNM indicate that an increase of 10 μg/m³ in PM_2.5 concentration is associated with an increase of 1.86% (95% confidence interval: 0.74%-2.99%) in URTI at a lag of 13 days in Beijing, compared with 2.68% (95% confidence interval: 0.99-4.39%) at a lag of 1 day in Shenzhen. The causality detection with CCM quantitatively demonstrates the significant causative influence of PM_2.5 on URTI in both two cities. Findings from the two methods consistently show that people living in low-concentration areas (Shenzhen) are less tolerant to PM_2.5 exposure than those in high-concentration areas (Beijing). In general, our study highlights the adverse health effects of PM_2.5 pollution on the general public in cities with various PM_2.5 levels and emphasizes the needs for the government to provide appropriate solutions to control PM_2.5 pollution, even in cities with low PM_2.5 concentration.

The association between diurnal temperature range and clinic visits for upper respiratory tract infection among college students in Wuhan, China

The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.

Assessing PM2.5-associated risk of hospitalization for COPD: an application of daily excessive concentration hours

Existing PM2.5-morbidity studies using daily mean concentration as exposure metric may fail to capture intra-day variations of PM2.5 concentrations, resulting in underestimated health impacts to some extent. This study introduced a novel indicator, daily excessive concentration hours (DECH), defined as sums of per-hourly excessive concentrations of PM2.5 against a specific threshold within a day. PM2.5 DECHs were separately calculated as daily concentration-hours >8, 10, 15, 20, and 25 μg/m3 (abbreviations: DECH-8, DECH-10, DECH-15, DECH-20, and DECH-25). We adopted a time-stratified case-crossover design with conditional logistic regression models to compare risks of hospitalizations for chronic obstructive pulmonary disease (COPD) associated with PM2.5 mean and DECHs in Shenzhen, China. We observed highly comparable PM2.5-COPD associations using exposure metrics of daily mean and DECHs with above-defined thresholds. For instance, PM2.5 mean and DECHs showed similar increases in risks of COPD hospitalization for an interquartile range rise in exposure, with odds ratio estimates of 1.26 (95% confidence interval: 1.06-1.50) for PM2.5 mean, 1.24 (1.05-1.46) for DECH-10 and 1.21 (1.06-1.39) for DECH-25, respectively. Findings remained robust after further adjusting for gaseous pollutants (e.g., SO2, NO2, CO, and O3) and meteorologic factors (e.g., wind speed and air pressure). Our study strengthened the evidence that DECHs could come be as a novel exposure metric in health risk assessments associated with short-term exposure to ambient PM2.5.

A novel lncRNA, loc107985872, promotes lung adenocarcinoma progression via the notch1 signaling pathway with exposure to traffic-originated PM2.5 organic extract

PM2.5 pollution is an important and urgent problem in China that can increase mortality and hospital admissions. Traffic-originated PM2.5 organic component (tPo) mainly contains polycyclic aromatic hydrocarbons (PAHs). Research has shown that PAHs can promote invasion, metastasis, and cancer stem cell properties in lung adenocarcinoma cells, but the exact toxicological mechanism is unknown. In the present study, we investigated the effect of lncRNAs on the progression of lung adenocarcinoma induced by tPo and the underlying mechanisms mediated by lncRNA-signaling pathway interactions. We found that chronic tPo treatment upregulated the expression of loc107985872, which further promoted cell invasion and migration, EMT and cancer stem cell properties via notch1 pathway in lung adenocarcinoma cells. Meanwhile, activation of the notch1 signaling pathway through loc107985872 might be associated with abnormally high expression of its upstream proteins, such as ADAM17, PSEN1 and DLL1. Moreover, tPo exposure induced EMT and the acquisition of cancer stem cell-like properties via the notch1 signaling pathway in vivo. In summary, loc107985872 upregulated by tPo promoted lung adenocarcinoma progression via the notch1 signaling pathway.

The effects of excess degree-hours on mortality in Guangzhou, China

BACKGROUND

Prior studies that examined the association between temperature and mortality relied on mean temperature, maximum temperature, minimum temperature, humidex, and daily temperature variability, not accounting for variations in hourly temperature throughout the day. We proposed an indicator, excess degree-hours, to examine the association between temperature and mortality.

METHODS

A distributed lag non-linear model (DLNM) was used to determine the hot (27.8 °C) and cold (24.3 °C) threshold. Hourly temperature in Guangzhou, China were summarized with extreme heat expressed as sum of degree-hours >27.8 °C and extreme cold as sum of degree-hours <24.3 °C within one day from January 1, 2012 to December 31, 2015. We then estimated the associations of daily mortality with hot and cold degree-hours in both hot and cold season. We also calculated the mortality burden of excess degree-hours.

RESULTS

An interquartile range (IQR) increase of hot degree-hours was associated with 2.11% (95% confidence interval [95% CI]: 1.25%, 2.98%), 3.74% (95% CI: 0.71%, 6.86%), and 2.63% (95% CI: 0.70%, 4.59%) increments in non-injury related death, respiratory mortality, and cardiovascular mortality, respectively. While the corresponding excess risk for an IQR increase of cold degree-hours was 2.42% (95% CI: 1.97%, 2.88%), 3.16% (95% CI: 2.57%, 3.76%), and 2.93% (95% CI: 1.98%, 3.88%). The estimated mortality burdens for hot and cold degree-hours were 1366,2465, respectively.

CONCLUSION

The excess degree-hours reduced to a single indication in duration and intensity is an approach and shows a different perspective and significant extreme weather effects on human health.

Relationship of Meteorological and Air Pollution Parameters with Pneumonia in Elderly Patients

Background and Purpose

In this study, we aimed to evaluate the relationship between pneumonia and meteorological parameters (temperature, humidity, precipitation, airborne particles, sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), nitrite oxide (NO), and nitric oxide (NOX)) in patients with the diagnosis of pneumonia in the emergency department.

Methods

Our study was performed retrospectively with patients over 65 years of age who were diagnosed with pneumonia. The meteorological variables in the days of diagnosing pneumonia were compared with the meteorological variables in the days without diagnosis of pneumonia. The sociodemographic characteristics, complete blood count of the patients, and meteorological parameters (temperature, humidity, precipitation, airborne particles, SO2, CO, NO2, NO, and NOX) were investigated.

Results

When the temperature was high and low, the number of days consulted due to pneumonia was related to low air temperature (p < 0.05). During the periods when PM 10, NO, NO2, NOX, and CO levels were high, the number of days referred for pneumonia was increased (p < 0.05).

Conclusion

As a result, climatic (temperature, humidity, pressure levels, rain, etc.) and environmental factors (airborne particles, CO, NO, and NOX) were found to be effective in the number of patients admitted to the hospital due to pneumonia.

Possible Mediation by Methylation in Acute Inflammation Following Personal Exposure to Fine Particulate Air Pollution

Air pollution may increase cardiovascular and respiratory risk through inflammatory pathways, but evidence for acute effects has been weak and indirect. Between December 2014 and July 2015, we enrolled 36 healthy, nonsmoking college students for a panel study in Shanghai, China, a city with highly variable levels of air pollution. We measured personal exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) continuously for 72 hours preceding each of 4 clinical visits that included phlebotomy. We measured 4 inflammation proteins and DNA methylation at nearby regulatory cytosine-phosphate-guanine (CpG) loci. We applied linear mixed-effect models to examine associations over various lag times. When results suggested mediation, we evaluated methylation as mediator. Increased PM2.5 concentration was positively associated with all 4 inflammation proteins and negatively associated with DNA methylation at regulatory loci for tumor necrosis factor alpha (TNF-α) and soluble intercellular adhesion molecule-1. A 10-μg/m3 increase in average PM2.5 during the 24 hours preceding blood draw corresponded to a 4.4% increase in TNF-α and a statistically significant decrease in methylation at one of the two studied candidate CpG loci for TNF-α. Epigenetics may play an important role in mediating effects of PM2.5 on inflammatory pathways.

Concentration-Response Relationship between PM2.5 and Daily Respiratory Deaths in China: A Systematic Review and Metaregression Analysis of Time-Series Studies

The association between the particulate matters with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and daily respiratory deaths, particularly the concentration-response pattern, has not been fully examined and established in China. We conducted a systematic review of time-series studies to compile information on the associations between PM_2.5 concentration and respiratory deaths and used metaregression to assess the concentration-response relationship. Out of 1,957 studies screened, eleven articles in English and two articles in Chinese met the eligibility criteria. For single-day lags, per 10 μg/m³ increase in PM_2.5 concentration was associated with 0.30 [95% confidence interval (CI): 0.10, 0.50] percent increase in daily respiratory deaths; for multiday lags, the corresponding increase in respiratory deaths was 0.69 (95% CI: 0.55, 0.83) percent. Difference in the effects was observed between the northern cities and the south cities in China. No statistically significant concentration-response relationship between PM_2.5 concentrations and their effects was found. With increasingly wider location coverage for PM_2.5 data, it is crucial to further investigate the concentration-response pattern of PM_2.5 effects on respiratory and other cause-specific mortality for the refinement and adaptation of global and national air quality guidelines and targets.

Ambient fine and coarse particulate matter pollution and respiratory morbidity in Dongguan, China

We estimated the short-term effects of particulate matter (PM) pollution with aerodynamic diameters ≤2.5 μm (PM_2.5) and between 2.5 and 10 μm (PM_c) on hospital outpatient visits due to overall and specific respiratory diseases, as well as the associated morbidity burden in Dongguan, a subtropical city in South China. A time-series model with quasi-Poisson link was used to examine the association between PM pollution and morbidities from respiratory diseases, COPD, asthma and pneumonia in Dongguan during 2013-2015. We further estimated the morbidity burden (population attributable fraction and attributable morbidity) due to ambient PM pollution. A total of 44,801 hospital outpatient visits for respiratory diseases were recorded during the study period. Both PM_2.5 and PM_c were found to be significantly associated with morbidity of overall respiratory diseases, COPD, and asthma. An IQR (interquartile range) increase in PM_2.5 at lag₀₃ day was associated with 15.41% (95% CI: 10.99%, 20.01%) increase in respiratory morbidity, and each IQR increase in PM_c at lag₀₃ corresponded to 7.24% (95% CI: 4.25%, 10.32%) increase in respiratory morbidity. We did not find significant effects of PM_2.5 and PM_c on pneumonia. Using WHO's guideline (25 μg/m³) as reference concentration, about 8.32% (95% CI: 5.90%, 10.86%) of respiratory morbidity (3727, 95% CI: 2642, 4867, in morbidity number) were estimated to be attributed to PM_2.5, and 0.86% (95% CI: 0.50%, 1.23%) of respiratory morbidity, representing 385 (95% CI: 225, 551) hospital outpatient visits, could be attributed to coarse particulate pollutant. Our study suggests that both fine and coarse particulate pollutants are an important trigger of hospital outpatient visits for respiratory diseases, and account for substantial respiratory morbidity in Dongguan, China.