Association of systemic inflammation and coagulation biomarkers with source-specific PM2.5 mass concentrations among young and elderly subjects in central Tehran

Long-term exposures to low concentrations of source-specific air pollution, road-traffic noise, and systemic inflammation and cardiovascular disease biomarkers

OBJECTIVES

Air pollution and traffic noise are detrimental to cardiovascular health. However, the effects of different sources of these exposures on cardiovascular biomarkers remain unclear. We explored the associations of long-term exposure to source-specific air pollution (vehicular exhausts and residential woodsmoke) at low concentrations and road-traffic noise with systemic inflammation and cardiovascular disease biomarkers.

MATERIAL AND METHODS

Modeled outdoor exposure to fine particulate matter (aerodynamic diameter ≤ 2.5 μm; PM2.5) from vehicular exhausts and residential woodsmoke, nitrogen dioxide (NO2) from road traffic, and road-traffic noise were linked to the home addresses of the participants (Finnish residents aged 25-74) in the FINRISK study 1997-2012. The participants were located in the cities of Helsinki, Vantaa, and the region of Turku, Finland. The outcomes were high-sensitivity C-reactive protein (CRP), a biomarker for systemic inflammation, and cardiovascular disease biomarkers N-terminal pro-B-type natriuretic peptide (NT-proBNP) and troponin I. We performed cross-sectional analyses with linear and additive models and adjusted for potential confounders.

RESULTS

We found no association between PM2.5 from vehicular exhausts (% CRP difference for 1 μg/m3 increase in PM2.5: -0.9, 95% confidence interval, CI: -7.2, 5.8), or from residential woodsmoke (% difference: -8.1, 95% CI: -21.7, 7.9) and CRP (N = 4147). Road-traffic noise > 70 dB tended to be positively associated with CRP (% CRP difference versus noise reference category of ≤ 45 decibels: 18.3, 95% CI: -0.5, 40.6), but the association lacked significance and robustness (N = 7142). Otherwise, we found no association between road-traffic noise and CRP, nor between NO2 from road traffic and NT-proBNP (N = 1907) or troponin I (N = 1951).

CONCLUSION

Long-term exposures to source-specific, fairly low-level air pollution from vehicular exhausts and residential woodsmoke, or road-traffic noise were not associated with systemic inflammation and cardiovascular disease biomarkers in this urban area.

Impact of urban space on PM2.5 distribution: A multiscale and seasonal study in the Yangtze River Delta urban agglomeration

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities.

Ambient PM2.5 Components Are Associated With Bone Strength: Evidence From a China Multi-Ethnic Study

CONTEXT

The relationship between the components of particulate matter with an aerodynamic diameter of 2.5 or less (PM2.5) and bone strength remains unclear.

OBJECTIVE

Based on a large-scale epidemiologic survey, we investigated the individual and combined associations of PM2.5 and its components with bone strength.

METHODS

A total of 65 906 individuals aged 30 to 79 years were derived from the China Multi-Ethnic Cohort Annual average concentrations of PM2.5 and its components were estimated using satellite remote sensing and chemical transport models. Bone strength was expressed by the calcaneus quantitative ultrasound index (QUI) measured by quantitative ultrasound. The logistic regression model and weighted quantile sum method were used to estimate the associations of single and joint exposure to PM2.5 and its components with QUI, respectively.

RESULTS

Our analysis shows that per-SD increase (μg/m3) in 3-year average concentrations of PM2.5 (mean difference [MD] -7.38; 95% CI, -8.35 to -6.41), black carbon (-7.91; -8.90 to -6.92), ammonium (-8.35; -9.37 to -7.34), nitrate (-8.73; -9.80 to -7.66), organic matter (-4.70; -5.77 to -3.64), and soil particles (-5.12; -6.10 to -4.15) were negatively associated with QUI. In addition, these associations were more pronounced in men, and people older than 65 years with a history of smoking and chronic alcohol consumption.

CONCLUSION

We found that long-term exposure to PM2.5 and its components may lead to reduced bone strength, suggesting that PM2.5 and its components may potentially increase the risk of osteoporosis and even fracture. Nitrate may be responsible for increasing its risk to a greater extent.

Personal Exposure to Source-Specific Particulate Polycyclic Aromatic Hydrocarbons and Systemic Inflammation: A Cross-Sectional Study of Urban-Dwelling Older Adults in China

Environmental exposure to ambient polycyclic aromatic hydrocarbons (PAHs) can disturb the immune response. However, the evidence on adverse health effects caused by exposure to PAHs emitted from specific sources among different vulnerable subpopulations is limited. In this cross-sectional study, we aimed to evaluate whether exposure to source-specific PAHs could increase systemic inflammation in older adults. The present study included community-dwelling older adults and collected filter samples of personal exposure to PM2.5 during the winter of 2011. Blood samples were collected after the PM2.5 sample collection. We analyzed PM2.5 bound PAHs and serum inflammatory cytokines (interleukin (IL)1β, IL6, and tumor necrosis factor alpha levels. The Positive Matrix Factorization model was used to identify PAH sources. We used a linear regression model to assess the relative effects of source-specific PM2.5 bound PAHs on the levels of measured inflammatory cytokines. After controlling for confounders, exposure to PAHs emitted from biomass burning or diesel vehicle emission was significantly associated with increased serum inflammatory cytokines and systemic inflammation. These findings highlight the importance of considering exposure sources in epidemiological studies and controlling exposures to organic materials from specific sources.

Impact of lifetime air pollution exposure patterns on the risk of chronic disease

Long-term exposure to air pollution can lead to cardiovascular disease, metabolic syndrome, and chronic respiratory disease. However, from a lifetime perspective, the critical period of air pollution exposure in terms of health risk is unknown. This study aimed to evaluate the impact of air pollution exposure at different life stages. The study participants were recruited from community centers in Northern Taiwan between October 2018 and April 2021. Their annual averages for fine particulate matter (PM2.5) exposure were derived from a national visibility database. Lifetime PM2.5 exposures were determined using residential address information and were separated into three stages (<20, 20-40, and >40 years). We employed exponentially weighted moving averages, applying different weights to the aforementioned life stages to simulate various weighting distribution patterns. Regression models were implemented to examine associations between weighting distributions and disease risk. We applied a random forest model to compare the relative importance of the three exposure life stages. We also compared model performance by evaluating the accuracy and F1 scores (the harmonic mean of precision and recall) of late-stage (>40 years) and lifetime exposure models. Models with 89% weighting on late-stage exposure showed significant associations between PM_2.5 exposure and metabolic syndrome, hypertension, diabetes, and cardiovascular disease, but not gout or osteoarthritis. Lifetime exposure models showed higher precision, accuracy, and F1 scores for metabolic syndrome, hypertension, diabetes, and cardiovascular disease, whereas late-stage models showed lower performance metrics for these outcomes. We conclude that exposure to high-level PM_2.5 after 40 years of age may increase the risk of metabolic syndrome, hypertension, diabetes, and cardiovascular disease. However, models considering lifetime exposure showed higher precision, accuracy, and F1 scores and lower equal error rates than models incorporating only late-stage exposures. Future studies regarding long-term air pollution modelling are required considering lifelong exposure pattern. .¹.

Associations between Short-Term Air Pollution Exposure and the Peripheral Leukocyte Distribution in the Adult Male Population in Beijing, China

The inflammatory effects of air pollution exposure may account for increased public health risk. However, evidence regarding the effects of air pollution on peripheral blood leukocytes in the population is inconsistent. We investigated the association between the short-term effects of ambient air pollution and the peripheral blood leukocyte distribution in adult men in Beijing, China. From January 2015 to December 2019, a total of 11,035 men aged 22-45 years in Beijing were included in the study. Their peripheral blood routine parameters were measured. The ambient pollution monitoring parameters (particulate matter ≤ 10 µm (PM₁₀), PM_2.5, nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃)) were collected daily. The potential association between ambient air pollution exposure and peripheral blood leukocyte count and classification was analyzed with generalized additive models (GAMs). After adjusting for confounding factors, PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO were significantly correlated with changes to at least one peripheral leukocyte subtype. Short-term and cumulative air pollutant exposure dramatically increased the participants' peripheral blood neutrophil, lymphocyte, and monocyte numbers and decreased eosinophils and basophils. Our results demonstrated that air pollution induced inflammation in the participants. The peripheral leukocyte count and classification can be utilized to evaluate the inflammation induced by air pollution in the exposed male population.

Modifiable contributing factors to COVID-19: A comprehensive review

The devastating complications of coronavirus disease 2019 (COVID-19) result from an individual's dysfunctional immune response following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events ultimately leading to COVID-19. The current study identifies eighty immune system dysfunction-enabling toxic stressors and behaviors (hereafter called modifiable contributing factors (CFs)) that also link directly to COVID-19. Each CF is assigned to one of the five categories in the CF taxonomy shown in Section 3.3.: Lifestyle (e.g., diet, substance abuse); Iatrogenic (e.g., drugs, surgery); Biotoxins (e.g., micro-organisms, mycotoxins); Occupational/Environmental (e.g., heavy metals, pesticides); Psychosocial/Socioeconomic (e.g., chronic stress, lower education). The current study shows how each modifiable factor contributes to decreased immune system capability, increased inflammation and coagulation, and increased neural damage and neurodegeneration. It is unclear how real progress can be made in combatting COVID-19 and other similar diseases caused by viral variants without addressing and eliminating these modifiable CFs.

Subclinical cardiovascular outcomes of acute exposure to fine particulate matter and its constituents: A glutathione S-transferase polymorphism-based longitudinal study

To explore the acute subclinical cardiovascular effects of fine particulate matter (PM_2.5) and its constituents, a longitudinal study with 61 healthy young volunteers was conducted in Xinxiang, China. Linear mixed-effect models were used to analyze the association of PM_2.5 and its constituents with cardiovascular outcomes, respectively, including blood pressure (BP), heart rate (HR), serum levels of high-sensitivity C-reactive protein (hs-CRP), 8-hydroxy-2'-deoxyguanosine (8-OHdG), tissue-type plasminogen activator (t-PA), and platelet-monocyte aggregation (PMA). Additionally, the modifying effects of glutathione S-transferase mu 1 (GSTM1) and glutathione S-transferase theta 1 (GSTT1) polymorphisms were examined. A 10 μg/m³ increase in PM_2.5 was associated with -1.04 (95 % CI: -1.86 to -0.22) mmHg and -0.90 (95 % CI: -1.69 to -0.11) mmHg decreases in diastolic BP (DBP) and mean arterial BP (MABP) along with 1.83 % (95 % CI: 0.59-3.08 %), 5.93 % (95 % CI: 0.70-11.16 %) increases in 8-OHdG and hs-CRP, respectively. Ni content was positively associated with the 8-OHdG levels whereas several other metals presented negative association with 8-OHdG and HR. Intriguingly, GSTT1+/GSTTM1+ subjects showed higher susceptibility to PM_2.5-induced alterations of DBP and PMA, and GSTT1-/GSTM1+ subjects showed higher alteration on t-PA. Taken together, our findings indicated that short-term PM_2.5 exposure induced oxidative stress, systemic inflammation, autonomic alterations, and fibrinolysis in healthy young subjects. Among multiple examined metal components Ni appeared to positively associated with systematic oxidative stress. In addition, GST-sufficient subjects might be more prone to PM_2.5-induced autonomic alterations.

Source apportionment, identification and characterization, and emission inventory of ambient particulate matter in 22 Eastern Mediterranean Region countries: A systematic review and recommendations for good practice

Little is known about the main sources of ambient particulate matter (PM) in the 22 Eastern Mediterranean Region (EMR) countries. We designed this study to systematically review all published and unpublished source apportionment (SA), identification and characterization studies as well as emission inventories in the EMR. Of 440 articles identified, 82 (11 emission inventory ones) met our inclusion criteria for final analyses. Of 22 EMR countries, Iran with 30 articles had the highest number of studies on source specific PM followed by Pakistan (n = 15 articles) and Saudi Arabia (n = 8 papers). By contrast, there were no studies in Afghanistan, Bahrain, Djibouti, Libya, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen. Approximately 72% of studies (51) were published within a span of 2015-2021.48 studies identified the sources of PM_2.5 and its constituents. Positive matrix factorization (PMF), principal component analysis (PCA) and chemical mass balance (CMB) were the most common approaches to identify the source contributions of ambient PM. Both secondary aerosols and dust, with 12-51% and 8-80% (33% and 30% for all EMR countries, on average) had the greatest contributions in ambient PM_2.5. The remaining sources for ambient PM_2.5, including mixed sources (traffic, industry and residential (TIR)), traffic, industries, biomass burning, and sea salt were in the range of approximately 4-69%, 4-49%, 1-53%, 7-25% and 3-29%, respectively. For PM₁₀, the most dominant source was dust with 7-95% (49% for all EMR countries, on average). The limited number of SA studies in the EMR countries (one study per approximately 9.6 million people) in comparison to Europe and North America (1 study per 4.3 and 2.1 million people respectively) can be augmented by future studies that will provide a better understanding of emission sources in the urban environment.

The Association Between Long-term Exposure to Ambient Air Pollution and Bone Strength in China

CONTEXT

Evidence regarding the association of long-term exposure to air pollution on bone strength or osteoporosis is rare, especially in highly polluted low- and middle-income countries. Little is known about whether the association between air pollution and bone strength changes at different bone strength distributions.

OBJECTIVE

Using the baseline data from the China Multi-Ethnic Cohort, we investigated the association between long-term air pollution exposure and bone strength.

METHODS

We used multiple linear models to estimate the association between air pollution and bone strength, and we conducted quantile regression models to investigate the variation of this association in the distribution of bone strength. The 3-year concentrations of PM1, PM2.5, PM10, and NO2 for each participant were assessed using spatial statistical models. Bone strength was expressed by the calcaneus quantitative ultrasound index (QUI) measured by quantitative ultrasound, with higher QUI values indicating greater bone strength.

RESULTS

A total of 66 598 participants were included. Our analysis shows that every 10 μg/m3 increase in 3-year average PM1, PM2.5, PM10, and NO2 was associated with -5.38 units (95% CI: -6.17, -4.60), -1.89 units (95% CI: -2.33, -1.44), -0.77 units (95% CI: -1.08, -0.47), and -2.02 units (95% CI: -2.32, -1.71) changes in the QUI, respectively. In addition, populations with higher bone strength may be more susceptible to air pollution.

CONCLUSION

Long-term exposure to PM1, PM2.5, PM10, and NO2 was significantly associated with decreased bone strength in southwestern China adults. Air pollution exposure has a more substantial adverse effect on bones among populations with higher bone strength.

Key Characteristics of Cardiovascular Toxicants

BACKGROUND

The concept of chemical agents having properties that confer potential hazard called key characteristics (KCs) was first developed to identify carcinogenic hazards. Identification of KCs of cardiovascular (CV) toxicants could facilitate the systematic assessment of CV hazards and understanding of assay and data gaps associated with current approaches.

OBJECTIVES

We sought to develop a consensus-based synthesis of scientific evidence on the KCs of chemical and nonchemical agents known to cause CV toxicity along with methods to measure them.

METHODS

An expert working group was convened to discuss mechanisms associated with CV toxicity.

RESULTS

The group identified 12 KCs of CV toxicants, defined as exogenous agents that adversely interfere with function of the CV system. The KCs were organized into those primarily affecting cardiac tissue (numbers 1-4 below), the vascular system (5-7), or both (8-12), as follows: 1) impairs regulation of cardiac excitability, 2) impairs cardiac contractility and relaxation, 3) induces cardiomyocyte injury and death, 4) induces proliferation of valve stroma, 5) impacts endothelial and vascular function, 6) alters hemostasis, 7) causes dyslipidemia, 8) impairs mitochondrial function, 9) modifies autonomic nervous system activity, 10) induces oxidative stress, 11) causes inflammation, and 12) alters hormone signaling.

DISCUSSION

These 12 KCs can be used to help identify pharmaceuticals and environmental pollutants as CV toxicants, as well as to better understand the mechanistic underpinnings of their toxicity. For example, evidence exists that fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution, arsenic, anthracycline drugs, and other exogenous chemicals possess one or more of the described KCs. In conclusion, the KCs could be used to identify potential CV toxicants and to define a set of test methods to evaluate CV toxicity in a more comprehensive and standardized manner than current approaches. https://doi.org/10.1289/EHP9321.