Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association

Proteomics Reveals Divergent Cardiac Inflammatory and Metabolic Responses After Inhalation of Ambient Particulate Matter With or Without Ozone

Inhalation of ambient particulate matter (PM) and ozone (O3) has been associated with increased cardiovascular morbidity and mortality. However, the interactive effects of PM and O3 on cardiac dysfunction and disease have not been thoroughly examined, especially at a proteomic level. The purpose of this study was to identify and compare proteome changes in spontaneously hypertensive (SH) rats co-exposed to concentrated ambient particulates (CAPs) and O3, with a focus on investigating inflammatory and metabolic pathways, which are the two major ones implicated in the pathophysiology of cardiac dysfunction. For this, we measured and compared changes in expression status of 9 critical pro- and anti-inflammatory cytokines using multiplexed ELISA and 450 metabolic proteins involved in ATP production, oxidative phosphorylation, cytoskeletal organization, and stress response using two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) in cardiac tissue of SH rats exposed to CAPs alone, O3 alone, and CAPs + O3. Proteomic expression profiling revealed that CAPs alone, O3 alone, and CAPs + O3 differentially altered protein expression patterns, and utilized divergent mechanisms to affect inflammatory and metabolic pathways and responses. Ingenuity Pathway Analysis (IPA) of the proteomic data demonstrated that the metabolic protein network centered by gap junction alpha-1 protein (GJA 1) was interconnected with the inflammatory cytokine network centered by nuclear factor kappa beta (NF-kB) potentially suggesting inflammation-induced alterations in metabolic pathways, or vice versa, collectively contributing to the development of cardiac dysfunction in response to CAPs and O3 exposure. These findings may enhance understanding of the pathophysiology of cardiac dysfunction induced by air pollution and provide testable hypotheses regarding mechanisms of action.

Running Through the Haze: How Wildfire Smoke Affects Physical Activity and Mental Well-Being

BACKGROUND

With a warming climate, extreme wildfires are more likely to occur, which may adversely affect air quality, physical activity (PA), and therefore, mental well-being.

METHODS

We assessed PA engagement and mental well-being between periods with and without wildfire smoke, and whether there were associations between changes in PA behavior and mental well-being. Questionnaires on PA and mental well-being during a period of wildfire smoke were completed by 348 participants; of these participants, 162 also completed a follow-up PA and mental well-being questionnaire during a period without wildfire smoke. Data were analyzed using generalized/linear mixed models. Relationships between mental well-being and PA were analyzed using repeated-measures correlations.

RESULTS

Leisure-time walking, moderate PA, and vigorous PA were all significantly lower during periods of smoke compared to periods without smoke. Participants also experienced significantly higher symptoms of stress (11.63 [1.91] vs 10.20 [1.70], P = .039), anxiety (7.75 [2.24] vs 4.38 [1.32], P < .001), and depression (9.67 [0.90] vs 7.27 [0.76], P < .001) during the period of wildfire smoke. Vigorous PA, the proportion of PA time spent outdoors, and the sum of PA during leisure time, were significantly negatively correlated with mental well-being, therefore, it is possible that PA could be used as a tool during times of wildfire smoke.

CONCLUSIONS

These data suggest that PA and mental well-being are adversely impacted during wildfire smoke events. Future research should consider the impact of strategies to support PA during wildfire events on PA and mental well-being.

Comparison Between Smoked Tobacco and Medical Cannabis Cigarettes Concerning Particulate Matter

Introduction: Cannabis is a widely used drug like tobacco and alcohol. In the meantime, it is also prescribed for medical treatment in some countries. Tobacco smoke contains chemical carcinogens and particulate matter (PM) that are both harmful to health. Method: In this study, we investigated PM levels in second-hand smoke (SHS) of hand-tamped cannabis cigarettes compared to cigarettes with tubing tobacco and the 3R4F reference cigarette. Results: It could be demonstrated that the largest proportion of the particle mass is attributable to particles with a diameter of less than 1μm and that every tested cigarette emitted more PM than the 3R4F reference cigarette. In addition, our data clearly revealed that cannabis smoke contains higher PM levels in SHS than tobacco cigarettes. Compared to the reference cigarette, the PM1 emissions of cannabis were 105% higher. Also, the cannabis mixed cigarettes had higher PM levels than the 3R4F cigarettes. For instance, the PM10 emissions were 93% higher. Also, the Gauloises Mélange tubing tobacco also reached higher PM concentrations than the 3R4F cigarette. Discussion: Regardless of negative health effects, cannabis is seen as a harmless drug in the public eye. We found strong indications for potential health risks by PM from cannabis products and, therefore, the public should be educated about a potential harm.

Spatiotemporal distribution and source analysis of PM2.5 and its chemical components in national industrial complexes of Korea: a case study of Ansan and Siheung

This study investigated the sources and distribution characteristics of PM2.5 and its chemical components (ions, carbons, elements) at five locations within the Banwal and Sihwa National Industrial Complexes in Ansan and Siheung. These large-scale industrial clusters, comprising 7642 businesses across sectors such as petrochemicals, steel, machinery, and electronics, operate throughout the year. From 2020 to 2023, the average PM2.5 concentration in the study area was 28.66 ± 16.72 μg/m3, with notable seasonal differences observed across the five measurement points. Ionic components were the primary contributors to PM2.5, while carbon and trace element concentrations fluctuated with the seasons. The coefficient of divergence (COD) analysis indicated that emission source differences between sites were insignificant, with COD values consistently below the threshold of 0.3. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) identified secondary aerosols and vehicle emissions as the main sources of PM2.5, alongside additional contributions from Asian dust, industrial emissions, road dust, coal combustion, metal processing, biomass burning, and soil dust. These results highlight the need for systematic and economical air pollution control strategies in complex industrial areas, using COD to identify source differences and quantify contributions at different sites.

The growing interdisciplinarity of developmental psychopathology: Implications for science and training

The field of developmental psychopathology has grown exponentially over the past decades, and has become increasingly multifaceted. The initial focus on understanding abnormal child psychology has broadened to the study of the origins of psychopathology, with the goals of preventing and alleviating disorder and promoting healthy development. In this paper, we discuss how technological advances and global events have expanded the questions that researchers in developmental psychopathology can address. We do so by describing a longitudinal study that we have been conducting for the past dozen years. We originally planned to examine the effects of early adversity on trajectories of brain development, endocrine function, and depressive symptoms across puberty; it has since become an interdisciplinary study encompassing diverse domains like inflammation, sleep, biological aging, the environment, and child functioning post-pandemic, that we believe will advance our understanding of neurobehavioral development. This increase in the breadth in our study emerged from an expansion of the field; we encourage researchers to embrace these dynamic changes. In this context, we discuss challenges, opportunities, and institutional changes related to the growing interdisciplinarity of the field with respect to training the next generation of investigators to mitigate the burden of mental illness in youth.

PM2.5-mediated cardiovascular disease in aging: Cardiometabolic risks, molecular mechanisms and potential interventions

Air pollution, particularly fine particulate matter (PM2.5) with <2.5 μm in diameter, is a major public health concern. Studies have consistently linked PM2.5 exposure to a heightened risk of cardiovascular diseases (CVDs) such as ischemic heart disease (IHD), heart failure (HF), and cardiac arrhythmias. Notably, individuals with pre-existing age-related cardiometabolic conditions appear more susceptible. However, the specific impact of PM2.5 on CVDs susceptibility in older adults remains unclear. Therefore, this review addresses this gap by discussing the factors that make the elderly more vulnerable to PM2.5-induced CVDs. Accordingly, we focused on physiological aging, increased susceptibility, cardiometabolic risk factors, CVDs, and biological mechanisms. This review concludes by examining potential interventions to reduce exposure and the adverse health effects of PM2.5 in the elderly population. The latter includes dietary modifications, medications, and exploration of the potential benefits of supplements. By comprehensively analyzing these factors, this review aims to provide a deeper understanding of the detrimental effects of PM2.5 on cardiovascular health in older adults. This knowledge can inform future research and guide strategies to protect vulnerable populations from the adverse effects of air pollution.

Evaluation of low-and middle-income countries according to cardiovascular disease risk factors by using pythagorean fuzzy AHP and TOPSIS methods

BACKGROUND

Cardiovascular disease risk factors play a crucial role in determining individuals' future health status and significantly affect health. This paper aimed to address cardiovascular disease risk factors in low- and middle-income countries using multi-criteria decision-making methods.

METHODS

In line with this objective, 22 evaluation criteria were identified. Due to the unequal importance levels of the criteria, the interval-valued Pythagorean Fuzzy AHP (PF-AHP) method was employed for weighting. The TOPSIS method was utilized to rank the countries.

RESULTS

The application of interval-valued PF-AHP revealed that metabolic, behavioral, and economic factors are more important in contributing to disease risk. Among adults, tobacco use prevalence was identified as the most significant risk factor. According to the TOPSIS method, Lebanon, Jordan, Solomon Islands, Serbia, and Bulgaria ranked highest, while Timor Leste, Benin, Ghana, Niger, and Ethiopia ranked lowest.

CONCLUSIONS

Identifying disease risk factors and preventing or reducing risks are crucial in combating cardiovascular diseases. Therefore, it is recommended that countries ranking higher take remedial actions to reduce disease risk.

Combined Effects of Air Pollution and Changes in Physical Activity With Cardiovascular Disease in Patients With Dyslipidemia

BACKGROUND

Sedentary behavior elevates cardiovascular disease (CVD) risk in patients with dyslipidemia. Increasing physical activity (PA) is recommended alongside pharmacological therapy to prevent CVD, though benefits across environmental conditions are unclear.

METHODS AND RESULTS

We analyzed data from 113 918 newly diagnosed patients with dyslipidemia (2009-2012) without prior CVD, sourced from the Korea National Health Insurance Service. Ambient particulate matter (PM) 2.5 and PM10 levels were collected from the National Ambient Air Monitoring System in South Korea. Changes in PA, measured in metabolic equivalents of task-min/wk before and after dyslipidemia diagnosis, were evaluated for associations with air pollution levels and CVD risk using Cox proportional hazards regression. Patients were followed from January 1, 2013, until CVD onset, death, or December 31, 2021. Among patients exposed to low to moderate PM2.5 levels (≤25 μg/m3), increasing PA from inactive to ≥1000 metabolic equivalents of tasks-min/wk was associated with a lower risk of CVD (adjusted hazard ratio, 0.82 [95% CI, 0.70-0.97]; P for trend=0.022). In high PM2.5 (>25 μg/m3) conditions, increasing PA from inactive and decreasing PA from ≥1000 metabolic equivalents of task-min/wk was associated with reduced (P for trend=0.010) and elevated (P for trend=0.028) CVD risks, respectively. For PM10, increased PA was linked to reduced CVD risk (P for trend=0.002) and decreased PA to elevated risk (P for trend=0.042) in low to moderate PM10 (≤50 μg/m3) conditions, though benefits diminished at high PM10 (>50 μg/m3) exposures.

CONCLUSIONS

Promoting PA, while considering the high potential cardiovascular risk associated with air pollution, may be an effective intervention against CVD in patients with dyslipidemia.

Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions

The primary source of measurement error from widely used particulate matter (PM) PurpleAir sensors is ambient relative humidity (RH). Recently, the US EPA developed a national correction model for PM2.5 concentrations measured by PurpleAir sensors (Barkjohn model). However, their study included few sites in the southeastern US, the most humid region of the country. To provide high-quality spatial and temporal data and inform community exposure risks in this area, our study developed and evaluated PurpleAir correction models for use in the warm-humid climate zones of the US. We used hourly PurpleAir data and hourly reference-grade PM2.5 data from the EPA Air Quality System database from January 2021 to August 2023. Compared with the Barkjohn model, we found improved performance metrics, with error metrics decreasing by 16 %-23 % when applying a multilinear regression model with RH and temperature as predictive variables. We also tested a novel semi-supervised clustering method and found that a nonlinear effect between PM2.5 and RH emerges around RH of 50 %, with slightly greater accuracy. Therefore, our results suggested that a clustering approach might be more accurate in high humidity conditions to capture the nonlinearity associated with PM particle hygroscopic growth.

Long-term exposure to low-level ozone and the risk of hypertension: A prospective cohort study conducted in a low-pollution region of southwestern China

BACKGROUND

The current evidence regarding the association between long-term exposure to ozone (O3) and hypertension incidence is limited and inconclusive, particularly at low O3 concentrations. Therefore, our research aims to investigate the potential link between long-term O3 exposure and hypertension in a region with low pollution levels.

METHODS

From 2010 to 2012, we conducted a cohort prospective study by recruiting nearly 10,000 attendees through multistage cluster random sampling in Guizhou Province, China. These individuals were followed up from 2016 to 2020, and 5563 cases were finally included in the analysis. We employed a high-resolution model with both temporal and spatial accuracy to estimate the maximum daily 8-h average O3 and utilized annual average O3 concentrations for three exposure periods (2009_10, 2007_10, 2005_10) as the exposure indicator. Time-dependent covariates Cox regression model was exerted to estimate the hazard ratios (HRs) of hypertension incidence. Generalized linear model was employed to assess the association between O3 and systolic, diastolic, pulse, and mean arterial pressure. The dose-response curve was explored using a restricted cubic spline function.

RESULTS

1213 hypertension incidents occurred during 39,001.80 person-years, with an incidence density of 31.10/1000 Person Years (PYs). The average O3 concentrations during the three exposure periods were 66.76 μg/m3, 67.85 μg/m3, and 67.21 μg/m3, respectively. Per 1 μg/m3 increase in O3 exposure was associated with 11 % increase in the incidence of hypertension in the single-pollution model, and the association was more pronounced in Han, urban, and higher altitude areas. SBP, PP, and MAP were increased by 0.619 (95 % CI, 0.361-0.877) mm Hg, 0.477 (95 % CI, 0.275-0.679) mm Hg, 0.301 (95 % CI, 0.127-0.475) mm Hg, respectively. Furthermore, we observed a nonlinear exposure-response relationship between O3 and hypertension incidence.

CONCLUSIONS

Long-term exposure to low-level O3 exposure is associated with an increased risk of hypertension.

Ambient PMs pollution, blood pressure, potential mediation by short-chain fatty acids: A prospective panel study of young adults in China

BACKGROUND

The concurrent effects of particulate matter (PM) on both blood pressure (BP) and short-chain fatty acids (SCFAs) are insufficiently explored, with limited research on the potential mediating roles of SCFAs.

METHODS

In this prospective panel study with 4 follow-ups, we recruited 40 college students in Hefei, China, to assess the impacts of short-term exposure to PM (aerodynamic diameter ≤10 μm (PM10), ≤2.5 μm (PM2.5), and ≤1 μm (PM1)) on BP and SCFAs, along with potential mechanisms. Real-time PM data, urinary SCFAs levels, and BP indicators were systematically collected. Linear mixed-effects models assessed the relationships between PM, SCFAs, and BP. Mediation analyses explored SCFAs' mediating role in the PM-BP association.

RESULTS

PM exposure was positively linked to BP and negatively associated with SCFAs. For a 10 μg/m3 rise in PM10 at lag 0-72 h, there were notable reductions of 0.0019 % (95 %CI: -0.0028, -0.0010) in Acetic acid, 0.0262 % (-0.0369, -0.0155) in Propionic acid, and 0.0702 % (-0.1025, -0.0378) in Butyric acid. Systolic BP, diastolic BP, and mean arterial pressure (MAP) increased by 2.60 mmHg (0.96, 4.25), 2.24 mmHg (1.18, 3.31), and 2.36 mmHg (1.20, 3.53), respectively, per 10-μg/m3 rise in PM1 at lag 0-24 h. Decreased SCFAs levels explained significant portions (24.69-31.80 %) of the elevated MAP due to PM10. Stronger associations were found in females and individuals with abnormal BMI.

CONCLUSIONS

Our study shows that PM exposure decreases urinary SCFAs levels, which partially mediate the impact of PM on elevated BP. These findings enhance our comprehension of the pathways linking PM exposure to BP changes.

Associations of ambient air pollution with incidence and dynamic progression of atrial fibrillation

The influence of air pollution on dynamic changes in clinical state from healthy to atrial fibrillation (AF), further AF-related complications and ultimately, death are unclear. We aimed to investigate the relationships between air pollution and the occurrence and progression trajectories of AF. We retrieved 442,150 participants free of heart failure (HF), myocardial infarction (MI), stroke and dementia at baseline from UK Biobank. Exposures to air pollution for each transition stage were estimated at the geocoded residential address of each participant using the bilinear interpolation approach. The outcomes were incident AF, complications, and death. Multi-stage models were used to evaluate the associations between air pollution and dynamic progression of AF. Over a 12.6-year median follow-up, a total of 21,670 incident AF patients were identified, of whom, 4103 developed complications and 1331 died. PM2.5, PM10, NOx and NO2 were differentially positively associated, while O3 was negatively associated with risks of progression trajectories of AF. PM2.5 exposure was significantly associated with an increased risk of progression. The associations of PM2.5, PM10, NOx, and NO2 on incident AF were generally more pronounced compared to other transitions. The cumulative transition probabilities were generally higher in individuals with higher exposure levels of PM2.5, PM10, NOx, and NO2 and lower exposure to O3. Air pollution could potentially have a role in increasing the risk of both the occurrence and progression of AF, emphasizing the significance of air pollution interventions in both the primary prevention of AF and the management of AF-related outcomes.

Rural-urban difference in the association between particulate matters and stroke incidence: The evidence from a multi-city perspective cohort study

Available evidence suggests that air pollutants can cause stroke, but little research has investigated the confounding effects of urban-rural differences. Here, we investigated the urban-rural difference in the correlation between particulate matter (PM2.5 and PM10) exposure and stroke. This cohort study was based on a prospective multi-city community-based cohort (Guizhou Population Health Cohort Study (GPHCS)) in Guizhou Province, China. A total of 7988 eligible individuals (≥18 years) were enrolled with baseline assessments from November 2010 to December 2012, and follow-up was completed by June 2020. Two major particulate matters (PMs, including PM2.5 and PM10) were assessed monthly from 2000 by using satellite-based spatiotemporal models. The risk of stroke was estimated using a Cox proportional hazard regression model. The association between particulate matters' exposure and stroke in different areas (total, urban, and rural) and the potential modification effect of comorbidities (hypertension, diabetes, and dyslipidemia) and age (≤65/>65 years) were examined using stratified analyses. The risk of stroke increased for every 10 μg/m3 increase in mean PMs' concentrations during the previous 1 year at the residential address (HR: 1.26, 95%CI: 1.24, 1.29 (PM2.5); HR: 1.13, 95%CI: 1.11, 1.15 (PM10)). The presence of diabetes and dyslipidemia increased the risk of PM10-induced stroke in whole, urban, and rural areas. Specifically, people living in rural areas were more likely to experience the effects of PMs in causing a stroke. The risk of stroke due to PMs was statistically increased in the young and older populations living in rural areas. In conclusion, long-term exposure to PMs increased the risk of stroke and such association was more pronounced in people living in rural areas with lower income levels. Diabetes and dyslipidemia seemed to strengthen the association between PMs and stroke.

The last decade of air pollution epidemiology and the challenges of quantitative risk assessment

Epidemiologic research and quantitative risk assessment play a crucial role in transferring fundamental scientific knowledge to policymakers so they can take action to reduce the burden of ambient air pollution. This commentary addresses several challenges in quantitative risk assessment of air pollution that require close attention. The background to this discussion provides a summary of and conclusions from the epidemiological evidence on ambient air pollution and health outcomes accumulated since the 1990s. We focus on identifying relevant exposure-health outcome pairs, the associated concentration-response functions to be applied in a risk assessment, and several caveats in their application. We propose a structured and comprehensive framework for assessing the evidence levels associated with each exposure-health outcome pair within a health impact assessment context. Specific issues regarding the use of global or regional concentration-response functions, their shape, and the range of applicability are discussed.

Short- and Long-Term Effects of Inhaled Ultrafine Particles on Blood Pressure: A Systematic Review and Meta-Analysis

Background: Air pollution contributes to up to 60% of premature mortality worldwide by worsening cardiovascular conditions. Ultrafine particles (UFPs) may negatively affect cardiovascular outcomes, and epidemiological studies have linked them to short- and long-term blood pressure (BP) imbalance. Methods: We conducted a systematic review and meta-analysis of the short- and long-term effects of UFP exposure on systolic (SBP) and diastolic (DBP) blood pressure. Eligibility criteria were established using the Population, Exposure, Comparator, Outcome, and Study Design (PECOS) model, and literature searches were conducted in Web of Science, PubMed, Embase, and Scopus for studies published between 1 January 2013 and 9 October 2024. Risk of Bias (RoB) was assessed following World Health Organization (WHO) instructions. Separate meta-analyses were performed for the short- and long-term effects of UFP exposure on SBP and DBP. Additionally, we analyzed SBP and DBP imbalances across different timespans following short-term exposure. Results: The results showed an increase in BP during short-term UFP exposure, which returned to baseline values after a few hours. Changes in SBP were greater than in DBP following both short- and long-term exposure. Prolonged exposure to UFPs is associated with increased SBP and concurrently low DBP values. Chronic exposure to UFPs may lead to a persistent increase in SBP, even without a concurrent increase in DBP. Conclusions: The findings presented here highlight that UFPs may contribute to worsening cardiovascular outcomes in vulnerable populations living in air-polluted areas.

Air pollution associated with cardiopulmonary disease and mortality among participants with preserved ratio impaired spirometry

BACKGROUND

Epidemiological evidence regarding the association between air pollutants and cardiopulmonary disease, mortality in individuals with preserved ratio impaired spirometry (PRISm), and their combined effects remains unclear.

METHODS

We followed 36,149 participants with PRISm in the UK Biobank study. Annual concentrations of PM2.5, PM10, NO2, NOx, and SO2 at residential addresses were determined using a bilinear interpolation method, accounting for address changes. A multistate model assessed the dynamic associations between air pollutants and cardiopulmonary diseases and mortality in PRISm. Quantile g-computation was used to investigate the joint effects of air pollutants.

RESULTS

Long-term exposure to PM2.5, PM10, NO2, NOx, and SO2 was significantly associated with the risk of cardiopulmonary disease in PRISm. The corresponding hazard ratios (HRs) [95 % confidence intervals (95 % CIs)] per interquartile range (IQR) were 1.49 (1.43, 1.54), 1.52 (1.46, 1.57), 1.34 (1.30, 1.39), 1.30 (1.26, 1.34), and 1.44 (1.41, 1.48), respectively. For mortality, the corresponding HRs (95 % CIs) per IQR were 1.36 (1.25, 1.47), 1.35 (1.24, 1.46), 1.27 (1.18, 1.36), 1.23 (1.15, 1.31), and 1.29 (1.20, 1.39), respectively. In PRISm, quantile g-computation analysis demonstrated that a quartile increase in exposure to a mixture of all air pollutants was positively associated with the risk of cardiopulmonary disease and mortality, with HRs (95 % CIs) of 1.84 (1.76, 3.84) and 1.45 (1.32, 1.57), respectively.

CONCLUSION

Long-term individual and joint exposure to air pollutants (PM2.5, PM10, NO2, NOx, and SO2) might be an important risk factor for cardiopulmonary disease and mortality in high-risk populations with PRISm.

Landscape fire PM2.5 and hospital admissions for cause-specific cardiovascular disease in urban China

There is a growing interest in the health impacts of PM2.5 originating from landscape fires. We conducted a time-series study to investigate the association between daily exposure to landscape fire PM2.5 and hospital admissions for cardiovascular events in 184 major Chinese cities. We developed a machine learning model combining outputs from chemical transport models, meteorological information and observed air pollution data to determine daily concentrations of landscape fire PM2.5. Furthermore, we fitted quasi-Poisson regression to evaluate the link between landscape fire PM2.5 concentrations and cardiovascular hospitalizations in each city, and conducted random-effects meta-analysis to pool the city-specific estimates. Here we show that, on a national scale, a rise of 1-μg/m3 in landscape fire PM2.5 concentrations is positively related to a same-day 0.16% (95% confidence interval: 0.01%-0.32%) increase in hospital admissions for cardiovascular disease, 0.28% (0.12%-0.44%) for ischemic heart disease, and 0.25% (0.02%-0.47%) for ischemic stroke. The associations remain significant even after adjusting for other sources of PM2.5. Our findings indicate that transient elevation in landscape fire PM2.5 levels may increase risk of cardiovascular diseases.

Inhaling Poor Health: The Impact of Air Pollution on Cardiovascular Kidney Metabolic Syndrome

Air pollution, mostly from fossil fuel sources, is the leading environmental cause of global morbidity and mortality and is intricately linked to climate change. There is emerging evidence indicating that air pollution imposes most of its risk through proximate cardiovascular kidney and metabolic (CKM) etiologies. Indeed, there is compelling evidence linking air pollution to the genesis of insulin resistance, type 2 diabetes, hypertension, and other risk factors. Air pollution frequently coexists with factors such as noise, with levels and risks influenced substantially by additional factors such as social determinants and natural and built environment features. Persistent disparities regarding the impact and new sources of air pollution, such as wildfires attributable to climate change, have renewed the urgency to better understand root sources, characterize their health effects, and disseminate this information for personal protection and policy impacts. In this review, we summarize evidence associating air pollution with cardiovascular health, the impact of air pollution on CKM health, and how interactions with other exposures and personal characteristics may modify these associations. Finally, we discuss new integrated approaches to capture risk from air pollution in the context of an exposomic framework.

Harnessing Wearables and Digital Technologies to Decode the Cardiovascular Exposome

The cardiovascular exposome encompasses the array of external and internal factors affecting cardiovascular health throughout life, inviting comprehensive monitoring and analysis to enhance prevention, diagnosis, and treatment strategies. Wearable and digital technologies have emerged as promising tools in this domain, offering longitudinal, real-time data on physiological parameters such as heart rate, heart rhythm, physical activity, and sleep patterns. This review explores the advancements in wearable sensor technology, the methodologies for data collection and analysis, and the integration of these technologies into clinical practice and research. Primary findings indicate significant improvements in device accuracy and functionality, facilitated by enhanced sensor technology, artificial intelligence, and data connectivity. These advancements enable precise monitoring, early detection of cardiovascular anomalies, and personalized healthcare interventions. Ultimately, wearables and digital health technologies have the potential to facilitate a deeper understanding of cardiovascular disease and behavior and bridge gaps in traditional healthcare models to help usher in more efficient, personalized, patient-centered care.

Associations between PM 2.5 and its chemical constituents and blood pressure: a cross-sectional study

OBJECTIVES

To investigate the associations between PM 2.5 and its chemical constituents with blood pressure (BP), assess effects across BP quantiles, and identify the key constituent elevating BP.

METHODS

A total of 36 792 adults were included in the cross-sectional study, representing 25 districts/counties of southeast China. Quantile regression models were applied to estimate the associations of PM 2.5 and its chemical constituents (ammonium [NH 4+ ], nitrate [NO 3- ], sulfate [SO 42- ], black carbon [BC], organic matter [OM]) with systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean artery pressure (MAP). A weighted quantile sum (WQS) index was used to estimate the relative importance of each PM 2.5 chemical constituent to the joint effect on BP.

RESULTS

The adverse effects of each interquartile range (IQR) increase in PM 2.5 , NH 4+ , NO 3- , SO 42- , and BC on BP were found to be greater with elevated BP, especially when SBP exceeded 133 mmHg and DBP exceeded 82 mmHg. Each IQR increase in all five PM 2.5 chemical constituents was associated with elevated SBP ( β [95% CI]: 0.90 [0.75, 1.05]), DBP ( β : 0.44 [0.34, 0.53]), and MAP ( β : 0.57 [0.45, 0.69]), NH 4+ (for SBP: weight = 99.43%; for DBP: 12.78%; for MAP: 60.73%) and BC (for DBP: 87.06%; for MAP: 39.07%) predominantly influencing these effects. The joint effect of PM 2.5 chemical constituents on risks for elevated SBP and DBP exhibited an upward trend from the 70 th quantile (SBP exceeded 133 mmHg, DBP exceeded 82 mmHg).

CONCLUSION

Long-term exposure to PM 2.5 and its chemical constituents was associated with increased risk for elevated BP, with NH 4+ and BC being the main contributors, and such associations were significantly stronger at 70th to 90th quantiles (SBP exceeded 133 mmHg, DBP exceeded 82 mmHg).

Lipidomics identified novel cholesterol-independent predictors for risk of incident coronary heart disease: Mediation of risk from diabetes and aggravation of risk by ambient air pollution

INTRODUCTION

Previous lipidomics studies have identified various lipid predictors for cardiovascular risk, however, with limited predictive increment, sometimes using too many predictor variables at the expense of practical efficiency.

OBJECTIVES

To search for lipid predictors of future coronary heart disease (CHD) with stronger predictive power and efficiency to guide primary intervention.

METHODS

We conducted a prospective nested case-control study involving 1,621 incident CHD cases and 1:1 matched controls. Lipid profiling of 161 lipid species for baseline fasting plasma was performed by liquid chromatography-mass spectrometry.

RESULTS

In search of CHD predictors, seven lipids were selected by elastic-net regression during over 90% of 1000 cross-validation repetitions, and the derived composite lipid score showed an adjusted odds ratio of 3.75 (95% confidence interval: 3.15, 4.46) per standard deviation increase. Addition of the lipid score into traditional risk model increased c-statistic to 0.736 by an increment of 0.077 (0.063, 0.092). From the seven lipids, we found mediation of CHD risk from baseline diabetes through sphingomyelin (SM) 41:1b with a considerable mediation proportion of 36.97% (P < 0.05). We further found that the positive associations of phosphatidylcholine (PC) 36:0a, SM 41:1b, lysophosphatidylcholine (LPC) 18:0 and LPC 20:3 were more pronounced among participants with higher exposure to fine particulate matter or its certain components, also to ozone for LPC 18:0 and LPC 20:3, while the negative association of cholesteryl ester (CE) 18:2 was attenuated with higher black carbon exposure (P < 0.05).

CONCLUSION

We identified seven lipid species with greatest predictive increment so-far achieved for incident CHD, and also found novel biomarkers for CHD risk stratification among individuals with diabetes or heavy air pollution exposure.

The interplay of climate change and physical activity: Implications for cardiovascular health

Cardiovascular disease (CVD) is one of the top contributors to global disease burden. Meeting the physical activity guidelines can effectively control and prevent several CVD risk factors, including obesity, hypertension and diabetes mellitus. The effects of climate change are multifactorial and have direct impacts on cardiovascular health. Increasing ambient temperatures, worsening air and water quality and urbanisation and loss of greenspace will also have indirect effects of cardiovascular health by impacting the ability and opportunity to participate in physical activity. A changing climate also has implications for large scale sporting events and policies regarding risk mitigation during exercise in hot climates. This review will discuss the impact of a changing climate on cardiovascular health and physical activity and the implications for the future of organised sport.

Exposure to air pollutants and subclinical carotid atherosclerosis measured by magnetic resonance imaging: A cross-sectional analysis

OBJECTIVES

Long-term exposure to air pollution has been associated with higher risk of cardiovascular mortality. Less is known about the association of air pollution with initial development of cardiovascular disease. Herein, the association between low-level exposure to air pollutants and subclinical carotid atherosclerosis in adults without known clinical cardiovascular disease was investigated.

DESIGN

Cross-sectional analysis within a prospective cohort study.

SETTING

The Canadian Alliance for Healthy Hearts and Minds Cohort Study; a pan-Canadian cohort of cohorts.

PARTICIPANTS

Canadian adults (n = 6645) recruited between 2014-2018 from the provinces of British Columbia, Alberta, Ontario, Quebec, and Nova Scotia, were studied, for whom averages of exposures to nitrogen dioxide (NO2), ozone (O3), and fine particulate matter (PM2.5) were estimated for the years 2008-2012.

MAIN OUTCOME MEASURE

Carotid vessel wall volume (CWV) measured by magnetic resonance imaging (MRI).

RESULTS

In adjusted linear mixed models, PM2.5 was not consistently associated with CWV (per 5 μg/m3 PM2.5; adjusted estimate = -8.4 mm3; 95% Confidence Intervals (CI) -23.3 to 6.48; p = 0.27). A 5 ppb higher NO2 concentration was associated with 11.8 mm3 lower CWV (95% CI -16.2 to -7.31; p<0.0001). A 3 ppb increase in O3 was associated with 9.34 mm3 higher CWV (95% CI 4.75 to 13.92; p<0.0001). However, the coarse/insufficient O3 resolution (10 km) is a limitation.

CONCLUSIONS

In a cohort of healthy Canadian adults there was no consistent association between PM2.5 or NO2 and increased CWV as a measure of subclinical atherosclerosis by MRI. The reasons for these inconsistent associations warrant further study.

Association Between Long-Term Exposure to Ambient Air Pollution and Fasting Blood Glucose: A Systematic Review and Meta-Analysis

Increasing studies are indicating a potential association between ambient air pollution exposure and fasting blood glucose (FBG), an indicator of prediabetes and diabetes. However, there is inconsistency within the existing literature. The aim of this study was to summarize the associations of exposures to particulate matters (PMs) (with aerodynamic diameters of ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), respectively) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) with FBG based on the existing epidemiological research for a better understanding of the relationship between air pollution and diabetes. Up to 2 July 2024, we performed a comprehensive literature retrieval from various electronic databases (PubMed, Web of Science, Scopus, and Embase). Random-effect and fixed-effect models were utilized to estimate the pooled percent changes (%) and 95% confidence intervals (CIs). Then, subgroup meta-analyses and meta-regression analyses were applied to recognize the sources of heterogeneity. There were 33 studies eligible for the meta-analysis. The results showed that for each 10 μg/m3 increase in long-term exposures to PM1, PM2.5, PM10, and SO2, the pooled percent changes in FBG were 2.24% (95% CI: 0.54%, 3.96%), 1.72% (95% CI: 0.93%, 2.25%), 1.19% (95% CI: 0.41%, 1.97%), and 0.52% (95% CI:0.40%, 0.63%), respectively. Long-term exposures to ambient NO2 and O3 were not related to alterations in FBG. In conclusion, our findings support that long-term exposures to PMs of various aerodynamic diameters and SO2 are associated with significantly elevated FBG levels.

An Ensemble Machine Learning Model to Enhance Extrapolation Ability of Predicting Coarse Particulate Matter with High Resolutions in China

Accurate exposure assessment is important for conducting PM10-2.5-related epidemiological studies, which have been limited thus far. In this study, we aimed to develop an ensemble machine learning method to estimate PM10-2.5 concentrations in mainland China during 2013-2020. The study was conducted in two stages. In the first stage, we developed two methods: the indirect method refers to developing models for PM2.5 and PM10 separately and subsequently calculating PM10-2.5 as the difference between them; and the direct method refers to establishing a model between PM10-2.5 measurements and relevant predictors directly. In the second stage, we employed an ensemble method by integrating predictions from both indirect and direct methods. Internal and external cross-validation (CV) were performed to validate the extrapolation capacity of models. The ensemble method demonstrated enhanced extrapolation accuracy in both internal and external CV compared to indirect and direct methods. The predictions produced by the ensemble method captured the spatiotemporal pattern of PM10-2.5, even in the sand and dust storm seasons. Our study introduces an ensemble strategy leveraging the strengths of both indirect and direct methods to estimate PM10-2.5 concentrations, which holds significant potential to support future epidemiological studies to address knowledge gaps in understanding the health effects of PM10-2.5.

Challenges posed by climate hazards to cardiovascular health and cardiac intensive care: implications for mitigation and adaptation

Global warming, driven by increased greenhouse gas emissions, has led to unprecedented extreme weather events, contributing to higher morbidity and mortality rates from a variety of health conditions, including cardiovascular disease (CVD). The disruption of multiple planetary boundaries has increased the probability of connected, cascading, and catastrophic disasters with magnified health impacts on vulnerable populations. While the impact of climate change can be manifold, non-optimal air temperatures (NOTs) pose significant health risks from cardiovascular events. Vulnerable populations, especially those with pre-existing CVD, face increased risks of acute cardiovascular events during NOT. Factors such as age, socio-economic status, minority populations, and environmental conditions (especially air pollution) amplify these risks. With rising global surface temperatures, the frequency and intensity of heatwaves and cold spells are expected to increase, emphasizing the need to address their health impacts. The World Health Organization recommends implementing heat-health action plans, which include early warning systems, public education on recognizing heat-related symptoms, and guidelines for adjusting medications during heatwaves. Additionally, intensive care units must be prepared to handle increased patient loads and the specific challenges posed by extreme heat. Comprehensive and proactive adaptation and mitigation strategies with health as a primary consideration and measures to enhance resilience are essential to protect vulnerable populations and reduce the health burden associated with NOTs. The current educational review will explore the impact on cardiovascular events, future health projections, pathophysiology, drug interactions, and intensive care challenges and recommend actions for effective patient care.

Air pollutants, residential greenspace, and the risk of kidney stone disease: a large prospective cohort study from the UK Biobank

BACKGROUND

The epidemiological evidence regarding the correlation between air pollution, residential greenspace, and the risk of kidney stone disease (KSD) is limited, with no large-scale prospective studies conducted on this relationship.

OBJECTIVE

We conducted a large-scale prospective study from the UK Biobank to explore the correlation between air pollution, residential greenspace, and the risk of KSD.

METHODS

This study included 419,835 UK Biobank participants who did not have KSD at baseline. An air pollution score was derived through the summation of concentrations for five air pollutants, including particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM2.5), ranging from 2.5 to 10 μm (PM2.5-10), ≤10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx). Various covariates were adjusted for in Cox proportional hazard regression to evaluate the risk of KSD associated with air pollution score, single air pollutant, and residential greenspace.

RESULTS

During a follow-up period of 12.7 years, 4503 cases of KSD were diagnosed. Significant associations were found between KSD risk and air pollution score (HR: 1.08, 95% CI: 1.03-1.13), PM2.5 (1.06, 1.02-1.11), PM10 (1.04, 1.01-1.07), NO2 (1.09, 1.02-1.16), NOx (1.08, 1.02-1.11), greenspace buffered at 300 m (0.95, 0.91-0.99), and greenspace buffered at 1000 m (0.92, 0.86-0.98) increase per interquartile range (IQR). PM2.5 and NO2 reductions may be a key mechanism for the protective impact of residential greenspace on KSD (P for indirect path < 0.05).

IMPACT

Prolonged exposure to air pollution was correlated with a higher risk of KSD, while residential greenspace exhibits an inverse association with KSD risk, partially mediated by the reduction in air pollutants concentrations. These findings emphasize the significance of mitigating air pollution and maintaining substantial greenspace exposure as preventive measures against KSD.

Spatial source, simulating improvement, and short-term health effect of high PM2.5 exposure during mutation event in the key urban agglomeration regions in China

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM2.5 in urban agglomeration regions continue to occur frequently. Identifying the spatial sources and influencing factors, as well as improving the prediction accuracy of high PM2.5 during mutation events, are crucial for public health. In this study, we firstly introduced discrete wavelet transform (DWT) to identify the mutation events with high PM2.5 concentration in the four key urban agglomerations, and evaluated the spatial sources for the polluted scenario using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Additionally, DWT was combined with a widely used artificial neural network (ANN) to improve the prediction accuracy of PM2.5 concentration seven days in advance (seven-day forecast). Results indicated that mutation events commonly occurred in the northern regions during winter time, which were under the control of both short-range transportation of dirty airmass as well as negative meteorology conditions. Compared with the ANN model alone, the average band errors decreased by 9% when using DWT-ANN model. The average correlation coefficient (R) and root mean square error (RMSE) obtained using the DWT-ANN improved by 10% and 12% compared to those obtained using the ANN, indicating the efficiency and accuracy of simulating PM2.5, by combining the DWT and ANN. The short-term mortality during mutation events was then calculated, with the total averted all-cause, cardiovascular, and respiratory deaths in the four regions, being 4751, 2554, and 582 persons, respectively. A declining trend in prevented deaths from 2018 to 2020 demonstrated that the pollution intensity during mutation events gradually decreased owing to the implementation of the Three-Year Action Plan to Win the Blue Sky Defense War. The method proposed in this study can be used by policymakers to take preventive measures in response to a sudden increase in PM2.5, thereby ensuring public health.

Wildland Fire-Related Smoke PM 2.5 and Cardiovascular Disease ED Visits in the Western United States

Background

The impact of short-term exposure to fine particulate matter (PM 2.5 ) due to wildland fire smoke on the risk of cardiovascular disease (CVD) remains unclear. We investigated the association between short-term exposure to wildfire smoke PM 2.5 and Emergency Department (ED) visits for acute CVD in the Western United States from 2007 to 2018.

Methods

ED visits for primary or secondary diagnoses of atrial fibrillation (AF), acute myocardial infarction (AMI), heart failure (HF), stroke, and total CVD were obtained from hospital associations or state health departments in California, Arizona, Nevada, Oregon, and Utah. ED visits included those that were subsequently hospitalized. Daily smoke, non-smoke, and total PM 2.5 were estimated using a satellite-driven multi-stage model with a high resolution of 1 km. The data were aggregated to the zip code level and a case-crossover study design was employed. Temperature, relative humidity, and day of the year were included as covariates.

Results

We analyzed 49,759,958 ED visits for primary or secondary CVD diagnoses, which included 6,808,839 (13.7%) AFs, 1,222,053 (2.5%) AMIs, 7,194,474 (14.5%) HFs, and 808,396 (1.6%) strokes. Over the study period from 2007-01-01 to 2018-12-31, the mean smoke PM 2.5 was 1.27 (Q1: 0, Q3: 1.29) µg/m 3 . A 10 µg/m 3 increase in smoke PM 2.5 was associated with a minuscule decreased risk for AF (OR 0.994, 95% CI 0.991-0.997), HF (OR 0.995, 95% CI 0.992-0.998), and CVD (OR 0.9997, 95% CI 0.996-0.998), but not for AMI and stroke. Adjusting for non-smoke PM 2.5 did not alter these associations. A 10 µg/m 3 increase in total PM 2.5 was linked to a small increased risk for all outcomes except stroke (OR for CVD 1.006, 95% CI 1.006-1.007). Associations were similar across sex and age groups.

Conclusion

We identified an unexpected slight lower risk of CVD ED visits associated with short-term wildfire smoke PM 2.5 exposure. Whether these findings are due to methodological issues, behavioral changes, or other factors requires further investigation.

Association between Long-Term Exposure to Traffic-Related Air Pollution and Cardio-Metabolic Phenotypes: An MRI Data-Based Analysis

Long-term exposure to traffic-related air pollution (TRAP) is associated with cardiometabolic disease; however, its role in subclinical stages of disease development is unclear. Thus, we aimed to explore this association in a cross-sectional analysis, with cardiometabolic phenotypes derived from magnetic resonance imaging (MRI). Phenotypes of the left (LV) and right cardiac ventricle, whole-body adipose tissue (AT), and organ-specific AT were obtained by MRI in 400 participants of the KORA cohort. Land-use regression models were used to estimate residential long-term exposures to TRAP, e.g., nitrogen dioxides (NO2) or particle number concentration (PNC). Associations between TRAP and MRI phenotypes were modeled using linear regression. Participants' mean age was 56 ± 9 years, and 42% were female. Long-term exposure to TRAP was associated with decreased LV wall thickness; a 6.0 μg/m3 increase in NO2 was associated with a -1.9% [95% confidence interval: -3.7%; -0.1%] decrease in mean global LV wall thickness. Furthermore, we found associations between TRAP and increased cardiac AT. A 2,242 n/cm3 increase in PNC was associated with a 4.3% [-1.7%; 10.4%] increase in mean total cardiac AT. Associations were more pronounced in women and in participants with diabetes. Our exploratory study indicates that long-term exposure to TRAP is associated with subclinical cardiometabolic disease states, particularly in metabolically vulnerable subgroups.

Effects of long-term exposure to air pollutant mixture on blood pressure in typical areas of North China

BACKGROUND

Studies about the combined effects of gaseous air pollutants and particulate matters are still rare.

OBJECTIVES

This study was performed based on baseline survey of the Diverse Life-Course Cohort in the Beijing-Tianjin-Hebei (BTH) Region of North China to evaluate the association of long-term air pollutants with blood pressure and the combined effect of the air pollutants mixture among 32821 natural han population aged 20 years or above.

METHODS

Three-year average exposure to air pollutants (PM10, PM2.5, PM1, O3, SO2, NO2, and CO) and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-), and organic matter (OM)] of residential areas were calculated based on well-validated models. Generalized linear mixed models (GLMMs) were used to estimate the associations of air pollutants exposure with the systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean arterial pressure (MAP), pulse pressure (PP) and prevalent hypertension. Quantile g-Computation and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined effect of the air pollutant mixture.

RESULTS

We found that long-term exposures of O3, PM2.5, and PM2.5 components were stably and strongly associated with elevated SBP, DBP, and MAP and prevalent hypertension. O3 increased SBP, DBP, and MAP at a similar extent, but with greater effects; while, PM2.5 and PM2.5 components had a greater impact on SBP than DBP, which increased PP simultaneously. In multi-pollutant models, the combined effects of the air pollutant mixture on blood pressure and prevalent hypertension was predominantly influenced by O3, PM2.5, and O3, OM in different models, respectively. For example, O3, PM2.5 contributed 57.25 %, 39.22 % of the positive combined effect of the air pollutant mixture on SBP; and O3, OM positively contributed 70.00 %, 30.00 % on prevalent hypertension, respectively. There were interactions between O3, CO, SO2 and PM2.5 components on hbp, SBP and PP.

CONCLUSIONS

The results showed positive associations of air pollutant mixtures with blood pressure, where O3 and PM2.5 (especially OM) might be primary contributors. There were interactions between gaseous air pollutants and PM2.5 components on blood pressure and prevalent hypertension.

Effect of air pollution on the global burden of cardiovascular diseases and forecasting future trends of the related metrics: a systematic analysis from the Global Burden of Disease Study 2021

BACKGROUND

This study assesses the worldwide cardiovascular disease (CVD) burden attributed to air pollution, utilizing data from the Global Burden of Disease Study 2021.

METHODS

We explored the impact of air pollution on CVDs globally, regionally, and nationally, while considering correlations with age, gender, and socio-demographic index (SDI). A decomposition analysis was conducted to discern the contributions of aging, population growth, and epidemiological shifts to the changes in disability-adjusted life years (DALYs) from 1990 to 2021. Additionally, an ARIMA model was used to forecast the future CVD burden through 2050.

RESULTS

In 2021, air pollution was responsible for approximately 2.46 million deaths and 58.3 million disability-adjusted life years (DALYs) attributable to CVDs, with a discernible decrease over the period studied. The greatest impacts were observed in individuals aged 75-79 and over 80, particularly among males. The decomposition analysis indicated that shifts in epidemiology were the primary factors driving these changes. Future projections suggest potential increases in mortality and DALY rates in regions with low and high-middle SDI, alongside rising age-standardized death and mortality rates in high SDI areas.

CONCLUSION

These findings underscore the urgency of implementing targeted CVD prevention and air pollution control strategies to mitigate the impact on public health.

Impact of elevated fine particulate matter (PM 2.5 ) during landscape fire events on cardiorespiratory hospital admissions in Perth, Western Australia

BACKGROUND

Australia has experienced extreme fire weather in recent years. Information on the impact of fine particulate matter (PM 2.5 ) from landscape fires (LFs) on cardiorespiratory hospital admissions is limited.

METHODS

We conducted a population-based time series study to assess associations between modelled daily elevated PM 2.5 at a 1.5×1.5 km resolution using a modified empirical PM 2.5 exposure model during LFs and hospital admissions for all-cause and cause-specific respiratory and cardiovascular diseases for the study period (2015-2017) in Perth, Western Australia. Multivariate Poisson regressions were used to estimate cumulative risk ratios (RR) with lag effects of 0-3 days, adjusted for sociodemographic factors, weather and time.

RESULTS

All-cause hospital admissions and overall cardiovascular admissions increased significantly across each elevated PM 2.5 concentration on most lag days, with the strongest associations of 3% and 7%, respectively, at the high level of ≥12.60 µg/m3 on lag 1 day. For asthma hospitalisation, there was an excess relative risk of up to 16% (RR 1.16, 95% CI 1.00 to 1.35) with same-day exposure for all people, up to 93% on a lag of 1 day in children and up to 52% on a lag of 3 days in low sociodemographic groups. We also observed an increase of up to 12% (RR 1.12, 95% CI 1.02 to 1.24) for arrhythmias on the same exposure day and with over 154% extra risks for angina and 12% for heart failure in disadvantaged groups.

CONCLUSIONS

Exposure to elevated PM 2.5 concentrations during LFs was associated with increased risks of all-cause hospital admissions, total cardiovascular conditions, asthma and arrhythmias.

Clean air policy reduces the atherogenic lipid profile levels: Results from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) Study

Evidence of the associations between long-term exposure to PM2.5 and O3 and human blood lipid concentrations is abundant yet inconclusive. Whether clean air policies could improve lipid profiles remains unclear. In total, 2979312 participants from a Chinese nationwide prospective study were included. For cross-sectional analyses, linear mixed-effects models were utilized to assess the associations of pollutants with lipid profiles (TC, LDL-C, TG, HDL-C). For longitudinal analyses, a quasi-experimental design and difference-in-differences models were employed to investigate the impact of China's Clean Air Act. In the cross-sectional analyses, each IQR increase in PM2.5 was associated with 2.49 % (95 % CI: 2.36 %, 2.62 %), 2.51 % (95 % CI: 2.26 %, 2.75 %), 3.94 % (95 % CI: 3.65 %, 4.23 %), and 1.54 % (95 % CI: 1.38 %, 1.70 %) increases in TC, LDL-C, TG, and HDL-C, respectively. For each IQR increase in O3, TC, LDL-C, TG, and HDL-C changed by 1.06 % (95 % CI: 0.95 %, 1.17 %), 1.21 % (95 % CI: 1.01 %, 1.42 %), 1.78 % (95 % CI: 1.54 %, 2.02 %), and -0.63 % (95 % CI: -0.76 %, -0.49 %), respectively. Longitudinal analyses showed that the intervention group experienced greater TC, LDL-C, and HDL-C reductions (1.77 %, 4.26 %, and 7.70 %, respectively). Our findings suggest that clean air policies could improve lipid metabolism and should be implemented in countries with heavy air pollution burdens.

3D printed micro-cyclones with improved geometries for low-cost aerosol size separation

The impact of suspended particles on health, climate, and industrial applications is highly size-dependent. Thus, regulations are typically based on particles with diameters below a specific size, such as particulate matter less than 2.5 μm (PM2.5). For over a century, cyclones have been employed to isolate particles below a certain diameter by removing large particles from a gas stream, but cyclones are typically relatively large, heavy, and expensive to fabricate compared to objects made with low-cost 3-dimensional (3D) printers. Herein, we present one-piece 3D-printed micro-cyclones (PM2.5 and PM1) to isolate particles smaller than a specific diameter. The collection efficiencies and 50% cut-off diameters (d50) of multiple cyclones were evaluated with both monodisperse and polydisperse standards ranging from 0.1 to 3 μm, as well as ambient aerosol. By altering the inlet orientation relative to the micro-cyclone centerline (orthogonal, 50% offset, and fully offset), we show that shifting the inlet radially outward increased the steepness of the transmission curve resulting in a sharper cut-point. The d50 also decreased below the designed for diameter, (PM1 = 1.4, 1.0, and 0.9 μm; PM2.5 = 3.2, 2.0, 1.9 μm), which was attributed to imperfect models, internal surface roughness, and print errors versus machining. These single piece, 3D-printed cyclones provide a cheaper (< $1), faster, and more accessible approach to manufacture micro-cyclones for use in a range of aerosol applications.

Impact of Wildfire Smoke on Acute Illness

Climate change increases wildfire smoke exposure. Inhaled smoke causes inflammation, oxidative stress, and coagulation, which exacerbate cardiovascular and respiratory disease while worsening obstetric and neonatal outcomes.

Long-term exposure to particulate matter pollution and incidence of ischemic and hemorrhagic stroke: A prospective cohort study in Eastern China

Although epidemiological studies have demonstrated significant associations of long-term exposure to particulate matter (PM) air pollution with stroke, evidence on the long-term effects of PM exposure on cause-specific stroke incidence is scarce and inconsistent. We incorporated 33,282 and 33,868 individuals aged 35-75 years without a history of ischemic or hemorrhagic stroke at the baseline in 2014, who were followed up till 2021. Residential exposures to particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) and particulate matter with an aerodynamic diameter less than 10 μm (PM10) for each participant were predicted using a satellite-based model with a spatial resolution of 1 × 1 km. We employed time-varying Cox proportional hazards models to assess the long-term effect of PM pollution on incident stroke. We identified 926 cases of ischemic stroke and 211 of hemorrhagic stroke. Long-term PM exposure was significantly associated with increased incidence of both ischemic and hemorrhagic stroke, with almost 2 times higher risk on hemorrhagic stroke. Specifically, a 10 μg/m³ increase in 3-year average concentrations of PM2.5 was linked to a hazard ratio (HR) of 1.35 (95% confidence interval (CI): 1.18-1.54) for incident ischemic stroke and 1.79 (95% CI: 1.36-2.34) for incident hemorrhagic stroke. The HR related to PM10, though smaller, remained statistically significant, with a HR of 1.25 for ischemic stroke and a HR of 1.51 for hemorrhagic stroke. The excess risks are larger among rural residents and individuals with lower educational attainment. The present cohort study contributed to the mounting evidence on the increased risk of incident stroke associated with long-term PM exposures. Our results further provide valuable evidence on the heightened sensitivity of hemorrhagic stroke to air pollution exposures compared with ischemic stroke.

Whole-body exposure to filtered fraction of diesel exhaust induced localized testicular damage through attenuated functional response of glutathione-s-transferase in adult male Wistar rats

The possible vulnerability of the male reproductive system to environmental pollutants such as air pollution necessitates a thorough investigation of the underlying mechanisms involved in the dysregulation of male reproductive function. The present study was designed to investigate the influence of the filtered fraction of diesel exhaust (predominantly comprising gases) on male reproductive function in Wistar rat model. Adult male rats were randomly assigned into three groups (n=8/group): Control (unexposed) group (CG-A), the Clean air group in WBE chamber (CAG-A), and Filtered diesel exhaust group in WBE chamber (FDG-A). The exposure protocol for CAG-A and FDG-A was 6 h/day x 5d/week x 6 weeks,evaluation of sperm parameters, testicular histopathology, quantification of hormones (testosterone, LH, FSH, 17β-Estradiol, and prolactin), and GST levels were performed. Results showed that WBE to FDE leads to a significant decline in sperm concentration (p=0.008, CG-A vs FDG-A; p=0.014, CAG-A vs FDG-A), motility (p=0.008, CG-A vs FDG-A; p=0.029, CAG-A vs FDG-A), serum testosterone (p=0.024, CG-A vs FDG-A; p=0.007, CAG-A vs FDG-A), testicular testosterone (p=0.008, CG-A vs FDG-A; p=0.028, CAG-A vs FDG-A), 17β-Estradiol (p=0.007, CG-A vs FDG-A), and GST levels (p=0.0002, CG-A vs FDG-A; p=0.0019, CAG-A vs FDG-A). These findings demonstrate the disruption of testosterone-estradiol balance in the intratesticular milieu without significant alterations in other principal pituitary hormones in adult rats exposed to FDE. The predominant presence of gaseous components in FDE can cause testicular damage due to oxidative imbalance. This underscores the causality of FDE exposure and impaired male reproductive outcomes.

Ambient Air Pollution Exposure and Outcomes in Patients Receiving Lung Transplant

Importance

Elevated ambient fine particulate matter (PM2.5) air pollution exposure has been associated with poor health outcomes across several domains, but its associated outcomes among lung transplant recipients are poorly understood.

Objective

To investigate whether greater PM2.5 exposure at the zip code of residence is associated with a higher hazard for mortality and graft failure in patients with lung transplants.

Design, Setting, and Participants

This retrospective cohort study used panel data provided by the United Network for Organ Sharing, which includes patients receiving transplants across all active US lung transplant programs. Adult patients who received lung transplants between May 2005 and December 2016 were included, with a last follow-up of September 10, 2020. Data were analyzed from September 2022 to May 2023.

Exposure

Zip code-level annual PM2.5 exposure was constructed using previously published North American estimates.

Main Outcomes and Measures

The primary outcome was time to death or lung allograft failure after lung transplant. A gamma shared frailty Cox proportional hazards model was used to produce unadjusted and adjusted hazard ratios (HRs) to estimate the association of zip code PM2.5 exposure at the time of transplant with graft failure or mortality.

Results

Among 18 265 lung transplant recipients (mean [SD] age, 55.3 [13.2] years; 7328 female [40.2%]), the resident zip code's annual PM2.5 exposure level was greater than or equal to the Environmental Protection Agency (EPA) standard of 12μg/m3 for 1790 patients (9.8%) and less than the standard for 16 475 patients (90.2%). In unadjusted analysis, median graft survival was 4.87 years (95% CI, 4.57-5.23 years) for recipients living in high PM2.5 areas and 5.84 years (95% CI, 5.71-5.96 years) for recipients in the low PM2.5 group. Having an annual PM2.5 exposure level greater than or equal to the EPA standard 12 μg/m3 was associated with an increase in the hazard of death or graft failure (HR, 1.11; 95% CI, 1.05-1.18; P < .001) in the unadjusted analysis and after adjusting for covariates (HR, 1.08; 95% CI, 1.01-1.15; P = .02). Each 1 μg/m3 increase in exposure was associated with an increase in the hazard of death or graft failure (adjusted HR, 1.01; 95% CI, 1.00-1.02; P = .004) when treating PM2.5 exposure as a continuous variable.

Conclusions and Relevance

In this study, elevated zip code-level ambient PM2.5 exposure was associated with an increased hazard of death or graft failure in lung transplant recipients. Further study is needed to better understand this association, which may help guide risk modification strategies at individual and population levels.

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization.

METHODS

We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups.

RESULTS

After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064).

CONCLUSION

NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Incidence of cardiovascular disease in a cohort of mine workers exposed to ultrafine aluminum powder in Ontario, Canada

BACKGROUND

A retrospective cohort study was conducted to estimate associations between an ultrafine aluminum powder, McIntyre Powder (MP), and cardiovascular disease incidence in a cohort of mine workers from Ontario, Canada. Disease outcomes included ischemic heart disease (IHD), acute myocardial infarction (AMI), congestive heart failure (CHF), and strokes and transient ischemic attacks (STIA).

METHODS

Using work history records from the Ontario Mining Master File (MMF) mine workers were followed for disease incidence in administrative health records. The analysis included 25,813 mine workers who were exposed to MP between 1943 and 1979 and followed for cardiovascular disease (CVD) diagnoses between 2006 and 2018. Cardiovascular disease cases were ascertained using physician, hospital, and ambulatory care records. Poisson regression models were used to estimate age and birth-year adjusted incidence rate ratios (RR) and 95% confidence intervals (CI) for associations between MP exposure and CVD outcomes.

RESULTS

Ever-exposure to MP was positively associated with modest increases in the incidence rate of IHD, AMI, and CHF, but not STIA, using both assessment approaches. Duration of self-reported MP exposure was positively associated with monotonically increasing rates of IHD and AMI compared to never-exposed miners, with the greatest association observed among miners with >20 years of exposure (for IHD: RR 1.24, 95% CI: 0.91-1.68; and for AMI: RR 1.52, 95% CI 1.01-2.28).

CONCLUSION

Mine workers ever-exposed to MP had modestly elevated rates of CVD. The rate of CVD diagnoses appeared to increase with longer duration of exposure when assessed by both self-reported exposure and through historical records.

PM2.5 chemical components are associated with in-hospital case fatality among acute myocardial infarction patients in China

Recent studies have linked the cardiovascular events with the exposure to ambient fine particulate matter (PM2.5); however, the impact of PM2.5 chemical components on acute myocardial infarction (AMI) case fatality remains poorly understood. To address this gap, we included 178,340 hospitalised patients with AMI utilising the inpatient discharge database from Sichuan, Shanxi, Guangxi, and Guangdong, China spanning 2014-2019. We evaluated exposure to PM2.5 and its components (black carbon (BC), organic matter (OM), sulphate (SO42-), nitrate (NO3-), and ammonium (NH4+)) using bilinear interpolation based on the patient's residential address. We used mixed-effects logistic regression models to investigate the associations of PM2.5 and its five components with in-hospital AMI case fatality. Per interquartile range (IQR) increment in short-term exposure (7-day average) to overall PM2.5 (odds ratio (OR): 1.086, 95 % confidence interval (CI): 1.045-1.128), SO42-(1.063, 1.024-1.104), BC (1.055, 1.023-1.089), OM (1.052, 1.019-1.086, and NO3- (1.045, 1.003-1.089) were significantly associated with high risk of in-hospital AMI case fatality. The ORs per IQR increment in long-term exposure (annual average) were 1.323 (95 % CI: 1.255-1.394) for PM2.5, followed by BC (1.271, 1.210-1.335), OM (1.243, 1.188-1.300), SO42- (1.212, 1.157-1.270), NO3- (1.116, 1.075-1.159), and NH4+ (1.068, 1.031-1.106). Our study suggests that PM2.5 chemical components might be important risk factors for in-hospital AMI case fatality, highlighting the importance of targeted reduction of PM2.5 emissions, particularly BC, OM, and SO42-.

Plant-based diet indices and their interaction with ambient air pollution on the ovarian cancer survival: A prospective cohort study

BACKGROUND

Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions.

METHODS

The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales.

RESULTS

Throughout a median follow-up of 37.60 (interquartile: 24.77-50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend < 0.01), whereas no significant associations were found between either overall PDI or hPDI and OC survival. Higher APS (HR for per interquartile range = 1.27, 95 % CI = 1.01, 1.60) was significantly associated with worse OC survival, and the association was exacerbated by adherence to uPDI. Notably, an additive interaction was identified between combined air pollution and uPDI (P < 0.005 for high APS and high uPDI). We also found that adherence to overall PDI aggravated associations of air pollution with OC survival (P-interaction = 0.006).

CONCLUSIONS

Joint exposure to various ambient air pollutants was significantly associated with lower survival among patients with OC, particularly for those who predominantly consumed unhealthy plant-based foods.

How does the macroenvironment influence brain and behaviour-a review of current status and future perspectives

The environment influences brain and mental health, both detrimentally and beneficially. Existing research has emphasised the individual psychosocial 'microenvironment'. Less attention has been paid to 'macroenvironmental' challenges, including climate change, pollution, urbanicity, and socioeconomic disparity. Notably, the implications of climate and pollution on brain and mental health have only recently gained prominence. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

Feasibility of low-cost particulate matter sensors for long-term environmental monitoring: Field evaluation and calibration

Low-cost sensor networks offer the potential to reduce monitoring costs while providing high-resolution spatiotemporal data on pollutant levels. However, these sensors come with limitations, and many aspects of their field performance remain underexplored. During October to December 2023, this study deployed two identical low-cost sensor systems near an urban standard monitoring station to record PM2.5 and PM10 concentrations, along with environmental temperature and humidity. Our evaluation of the monitoring performance of these sensors revealed a broad data distribution with a systematic overestimation; this overestimation was more pronounced in PM10 readings. The sensors showed good consistency (R2 > 0.9, NRMSE<5 %), and normalization residuals were tracked to assess stability, which, despite occasional environmental influences, remained generally stable. A lateral comparison of four calibration models (MLR, SVR, RF, XGBoost) demonstrated superior performance of RF and XGBoost over others, particularly with RF showing enhanced effectiveness on the test set. SHAP analysis identified sensor readings as the most critical variable, underscoring their pivotal role in predictive modeling. Relative humidity consistently proved more significant than dew point and temperature, with higher RH levels typically having a positive impact on model outputs. The study indicates that, with appropriate calibration, sensors can supplement the sparse networks of regulatory-grade instruments, enabling dense neighborhood-scale monitoring and a better understanding of temporal air quality trends.

High-quality models for assessing the effects of environmental pollutants on the nervous system: 3D brain organoids

The prevalence of environmental problems and the increasing risk of human exposure to environmental pollutants have become a global concern. The increasing environmental pollution is one of the main reasons for the rising incidence of most neurological-related diseases in recent years. However, the ethical constraints of direct human research and the racial limitations of animal models have slowed the progress of research in this area. The purpose of this study is to review the neurotoxicity of different environmental pollutants on the brain using brain organoids as a new model and to conclude that brain organoids may play a key role in assessing the mechanisms by which environmental pollutants affect neurogenesis and cause neurological pathogenesis. To accurately determine the negative effects of environmental pollutants on the nervous system, self-organizing brain organoids that are highly similar to the developing brain have become a new model system for studying the effects of environmental pollutants on human brain development and disease. This study uses brain organoids as a model to summarize the neurotoxicity of different environmental pollutants on the nervous system, including structural changes in brain organoids, inhibition of neuronal differentiation and migration, impairment of mitochondrial function, damage to cellular cilia, and influence on signaling pathways. In conclusion, exposure to environmental pollutants may cause different neurotoxicity to the nervous system. Therefore, it is crucial to understand how to use brain organoids to ameliorate neurological disorders caused by environmental pollution.

Long-term exposure to NO2 and PM2.5 and the occurrence of chronic kidney disease among patients with type 2 diabetes in Taiwan

BACKGROUND

Individuals diagnosed with type 2 diabetes (T2D) frequently exhibit chronic kidney disease (CKD) which may be caused by environmental hazards such as exposure to air pollutants. However, limited research has explored the effects of prolonged exposure to air pollutants on CKD development in this population. This study examines the relationship between long-term exposure to air pollutants and CKD incidence in a longitudinal cohort of individuals with type 2 diabetes in Taiwan METHODS: Between 2003 and 2005, we recruited 1316 T2D patients (693 females [52.66 %]; mean age 56.16 ± 8.97 years). Patients were followed until December 31, 2012, with at least two clinical visits. Baseline demographics, medical history, and biomarker levels were collected. The development of CKD was determined by eGFR level < 60 mL/min/1.73 m2. Monthly averages of nitrogen dioxide (NO2) and fine particulate matter [PM ≤ 2.5 μm in aerodynamic diameter (PM2.5)] were acquired from 72 ambient air monitoring stations. The kriging method was employed to estimate the exposure levels to PM2.5, NO2, temperature, and relative humidity in the participants' residential areas. Cox regression with time-dependent covariates regression was applied to assess the impact of long-term exposure to air pollutants and CKD risk.

RESULTS

Of 992 patients with normal renal function at baseline, 411 (41.43 %) experienced CKD occurrence over a median follow-up period of 5.45 years. The incidence of CKD was 93.96 cases per 1000 person-years. In multivariable adjusted models, patients exposed to PM2.5 levels above the third quartile of (>33.44 μg/m3) and NO2 levels above the fourth quartile (>22.55 ppb) were found to have an increased risk of CKD occurrence compared to lower exposure levels.

CONCLUSIONS

This longitudinal study highlights the increased risk of CKD in individuals with type 2 diabetes due to prolonged exposure to NO2 and PM2.5, emphasizing the need for tailored air quality management strategies for this high-risk population.

Air pollution below US regulatory standards and cardiovascular diseases using a double negative control approach

Growing evidence suggests that long-term air pollution exposure is a risk factor for cardiovascular mortality and morbidity. However, few studies have investigated air pollution below current regulatory limits, and causal evidence is limited. We use a double negative control approach to examine the association between long-term exposure to air pollution at low concentration and cardiovascular hospitalizations among US Medicare beneficiaries aged ≥65 years between 2000 and 2016. The expected values of the negative outcome control (preceding-year hospitalizations) regressed on exposure and negative exposure control (subsequent-year exposure) are treated as a surrogate for omitted confounders. With analyses separately restricted to low-pollution areas (PM2.5 < 9 μg/m³, NO2 < 75.2 µg/m3 [40 ppb], warm-season O3 < 88.2 μg/m3 [45 ppb]), we observed positive associations of the three pollutants with hospitalization rates of stroke, heart failure, and atrial fibrillation and flutter. The associations generally persisted in demographic subgroups. Stricter national air quality standards should be considered.