Pairwise associations among fine particulate matter (PM2.5), gut microbiota, and cardiovascular disease (CVD) have been established. However, the mediating role of gut microbiota in the relationship between PM2.5 and its components and CVD remains unclear.

We included 1459 participants from the China Multi-Ethnic Cohort between May 2018 and September 2019. CVD was identified using ICD-10 codes based on hospital surveillance system. PM2.5 and its components were sourced from the ChinaHighAirPollutants dataset. Gut microbiota was obtained from 16S rRNA sequencing of stool samples, and five α-indexes along with 1088 gut compositions were used as mediators. Cox proportional hazards and multiple linear regression were used to explore the associations among PM2.5 and its components, gut microbiota, and CVD. Causal mediation analysis was conducted to evaluate the potential mediating role of gut microbiota between PM2.5 and its components and CVD.

Among all the participants, 204 (14.0 %) had developed CVD during a 5501 person-year follow-up (median, 3.8 years). The ACE, Chao1, and Obs indexes positively mediated the associations of PM2.5 and its components with both CVD and stroke, with mediation proportions ranging from 7.9 % to 8.9 % for CVD and 10.0 %-12.1 % for stroke. The ACE index had the highest mediation proportion (12.1 %) in the relationship between sulfate and stroke. The genus Pasteurella also demonstrated a mediating role, accounting for 2.6 %-3.2 % for CVD, and 2.5 %-3.6 % for stroke, exhibiting the highest mediation proportion (3.6 %) on the association between black carbon or nitrate and stroke.

Three α-indexes (ACE, Chao1, and Obs) and the Pasteurella positively mediated the association between PM2.5 and its components and CVD risk. Enhancing the richness of gut microbiota could potentially reduce the risk of CVD induced by PM2.5 and its components.

Sulfate, nitrate, ammonium, organic matter, and black carbon account for more than two-thirds of the total mass of PM2.5 and have stronger cardiovascular toxicity than other components. However, evidence regarding the gestational cardiovascular toxicity of these PM2.5 components is lacking. A prospective cohort study was conducted among 1913 pregnant women in Guangzhou, Pearl River Delta, China, from 2017 to 2020. Each participant underwent two office blood pressure (BP) measurements: baseline BP was assessed during the first and second trimesters (mean gestational age: 13.77 ± 2.76 weeks) and follow-up BP was measured during the third trimester (mean gestational age: 39.00 ± 1.46 weeks). The level of the five main PM2.5 components were estimated using a tracking air pollution dataset. Changes in PM2.5 component concentrations and BP levels were determined by calculating the differences between follow-up and baseline values. We found that changes in PM2.5 mass and components significantly affected gestational BP variations (β = 1.88-3.42, P < 0.001). Most associations exhibited an inverted U-shaped non-linear relationship, initially increasing steeply before leveling off, without a clear threshold. Systolic blood pressure (SBP) was more sensitive to concentration changes in PM2.5 components, with nitrate showing a particularly pronounced effect. Our findings suggest that changes in PM2.5 mass and its specific components levels were associated with maternal BP, especially increased SBP, with nitrate being the major contributor. Stricter emission reduction measures are needed to mitigate urban pollution sources associated with particulate nitrate.

Climate change-induced environmental stressors, including ambient particulate matter (PM2.5) and extreme heat stress (HS), pose serious health risks, particularly for neurodegenerative diseases. PM2.5 exacerbates cardiovascular and neurodegenerative conditions, while HS increases mortality and worsens air pollution. Combined exposure may amplify these effects, especially in vulnerable populations at risk for Alzheimer's disease (AD). In our experimental study using a mouse model of early-onset Alzheimer's disease (EOAD), we explored the combined effects of extreme weather conditions, particularly exposure to ambient PM2.5 and HS. Our research indicated that even short, repeated exposure to these environmental stressors disrupts brain energy metabolism and mitochondrial respiratory functions, which we found to be associated with altered hippocampal synaptic functions. Additionally, we find that key mechanisms associated with impaired intestinal permeability and gut dysbiosis are affected, supporting the hypothesis that exposure to climate change communication may also disrupt the gut-brain axis, as in part evidenced in our study by peripheral changes in immune and inflammatory signaling. Moreover, despite significant disruptions in metabolic and immune-inflammatory pathways, we observed no acceleration of cognitive decline in the young asymptomatic EOAD mice subjected to short, repeated exposure to extreme heat and environmental PM2.5. These findings highlight the potential role of climate change in promoting risk factors like neuroinflammation and gut-brain axis dysfunction due to gut microbiome dysbiosis in the onset and progression of AD, particularly in asymptomatic individuals at risk for developing the condition.

Major Depressive Disorder (MDD) is a multifactorial disease which could be influenced by exposure to air pollution through disruption of sleep-wake cycles and other circadian-related behaviors. Our study aimed to investigate the interplay between air pollution exposure, DNA methylation of core clock genes involved in circadian rhythms, and MDD severity.

Four hundred sixteen MDD patients (64 % females) agreed to participate and donated a blood sample to measure DNA methylation of the core clock genes CRY1, PER1, PER2, CLOCK, BMAL1. MDD severity and functioning was assessed using five rating scales. Daily mean estimates of particulate matter with diameter ≤ 2.5 μm (PM2.5) and nitrogen dioxide (NO2) were assigned to study participants based on their residential address, and averaged to estimate different cumulative exposure windows. Multivariate regression models were applied to assess associations between air pollutants and core clock genes methylation and between DNA methylation of those same genes and MDD severity.

PM2.5 exposure in the six months preceding recruitment was associated with CLOCK hypomethylation (β=-0.11, 95 % confidence interval [CI]:0.20; -0.02) and CRY1 hypermethylation (β=0.32, 95 %CI: 0.06; 0.58). All NO2 exposure windows were associated with CRY1 hypermethylation. Increasing methylation of CLOCK was associated with lower MDD severity considering several scales (e.g., Hamilton Depression Rating Scale: β=-7.21, 95 %CI:3.97; -0.44).

Taken together our findings shed some light on the complex mechanism underlying the pathogenesis of MDD, with a potentially relevant role of the environment and of its impact on epigenetic mechanisms altering the expression of core clock genes.

Residential wood heating (RWH) is a known source of particulate matter (PM), hazardous air pollutants (HAPs), and greenhouse gases (GHGs). However, the influence of operating conditions on emissions from certified cordwood stoves in the United States (U.S.) remains poorly understood. This study analyzes emissions data from different operational phases, including start-up, high heat, and low heat, to improve indicators of real-world stove performance. We tested five commercially available U.S. stoves through the four distinct operational conditions or phases of the novel Integrated Duty Cycle (IDC) testing protocol, which simulates typical residential wood-burning patterns by incorporating start-up, high heat, medium (or "maintain") heat, and low heat ("overnight" burn) phases. We determined emissions factors (EFs) by IDC phase for criteria, GHG, and HAP compounds, including volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs). We also developed a multiple linear regression model to assess the effect of dry burn rate (DBR) and IDC phase on each pollutant EF by stove technology type. IDC phase significantly influenced (p < 0.01) pollutant EFs from uncertified stoves and most emissions from catalytic/hybrid stoves, while DBR played a more substantial role in emissions from non-catalytic stoves. Current stove certification methods rely on a single nominal load under steady-state combustion, which does not reflect typical residential use. Additionally, we found DBR to be an inconsistent predictor of emissions in cordwood stoves. These findings underscore the importance of stove technology and operating conditions in determining RWH emissions, with implications for air quality science and regulatory policy.Implications: We report cordwood stove emissions factors by operating condition using the novel Integrated Duty Cycle (IDC) protocol on various U.S. technologies meeting 2020 New Source Performance Standards (NSPS) and one pre-NSPS, circa 1980 stove. We determined significant effects from IDC operating phase on uncertified and catalytic/hybrid stove emissions, but not noncatalytic stoves. This has important implications for use of emissions factors in air quality science, policy, and stove design, as different U.S. climate zones will influence the number of stove start-ups, fuel loading patterns, and frequencies of other "real world" operating conditions such as "high heat" and "overnight burn."

Temperature is a time varying factor that is associated with blood pressure and has the potential to be a confounder in randomized crossover trials.

We assessed the effect of temperature on blood pressure within the Home Air Filtration for Traffic-Related Air Pollution study, a randomized crossover trial of air purifiers in homes. We assessed the association of blood pressure with both outdoor and indoor temperatures using 190 paired blood pressure measurements that were not affected by the presence of air purifiers in the preceding month.

Mean (standard error) peripheral systolic blood pressure was observed to change by +0.24 (0.09) mmHg per 1 °F colder outdoor temperature and by -0.28 (0.07) mmHg per 1 °F warmer (P < 0.001). Results were similar, although somewhat smaller for peripheral diastolic blood pressure. Associations were nearly identical for central blood pressures. We found much smaller effects for indoor temperatures, none of which approached statistical significance, as indoor temperatures were more stable and did not change as much over the study period.

Despite the cooling and warming of outdoor temperatures being associated with increases and decreases in blood pressure, we believe that outdoor temperature may also be a surrogate marker of particulate matter air pollution. Regardless of the underlying mechanism, randomized trials using blood pressure as outcomes would be well advised to measure temperature and consider it a potential time-varying confounder in the analyses.

Cardiovascular disease (CVD) remains the leading cause of death in China and worldwide. However, a large proportion of CVD can be prevented by regulating the levels of cardiovascular risk predictors. Despite the contribution of well-established factors to changes in cardiovascular risk predictors, the role of the regional environment and its combined effects with individual factors, which could affect health outcomes, remain unclear.

We included 10 308 middle-aged and older Chinese adults from the 2015 China Health and Retirement Longitudinal Study. High-sensitivity C-reactive protein (hs-CRP) is a cardiovascular risk predictor. Related potential factors including individual characteristics, regional air pollution, and regional socioeconomic status characteristics were also collected. The geographical detector method was used to quantify the explanatory power of individual and regional factors separately and in pairs in the hs-CRP levels according to regions (southern vs. northern China).

Blood triglyceride had the highest explanatory power for hs-CRP levels. Regional environment factors, including air pollution and socioeconomic status, significantly affected hs-CRP levels, and the results differed by region. Indoor air pollution and regional industrial structure had a stronger effect on hs-CRP levels in the south, whereas outdoor air pollution and economic level had a greater effect in the north. The interactions between any two of the paired factors enhanced the effects.

Spatial stratified heterogeneity of the leading risk factors for hs-CRP, a powerful cardiovascular risk predictor, was found. The combined effect of individual factors and regional environment enhanced the explanatory power of each risk factor. The results suggest that policymakers should choose different optimal approaches to regulate the cardiovascular risk predictor levels of middle-aged and older Chinese adults in different regions and the interaction effects between individual factors and the regional environment should be considered.

Biomass burning constitutes a significant source of fine particulate matter (PM2.5) in the atmosphere, particularly during winter due to residential wood heating. This source also emits substantial quantities of volatile and semi-volatile organic compounds, leading through (photo-)chemical and physical processes, to the formation of secondary organic aerosols (SOAs), accounting for a significant fraction of PM2.5. The current understanding of the biological effects of SOA resulting from the oxidation of major gaseous precursors emitted by biomass burning (e.g., polycyclic aromatic hydrocarbons (PAHs), phenols, furans) is still limited. Mechanism-based in vitro cellular bioassays targeting toxicologically relevant modes of action have proven valuable in assessing and quantifying the overall biological activity of complex mixtures like SOA, thereby revealing the presence of toxicologically relevant compounds. The main objective of this study was to investigate, using a battery of in vitro mechanism-based cellular bioassays, the aryl hydrocarbon (AhR), estrogen (ER), and androgen receptor (AR)-mediated activities of laboratory-generated SOA resulting from the oxidation of four PAHs and three furans. SOA was produced using an oxidation flow reactor (OFR) under either daytime (OH radicals) or nighttime (NO3 radicals) conditions. Furan-derived SOA did not exhibit any biological activity with the targeted endpoints. PAH-derived SOA, formed from AhR weakly or inactive PAHs, showed significant AhR-mediated activities. Notably, SOA resulting from naphthalene and acenaphthylene + acenaphthene demonstrated the highest AhR activation potency, with greater activities observed for SOA formed through NO3 radical oxidation. No endocrine-disrupting activity was observed for the PAH-derived SOA, similar to the individual parent PAHs (with the exception of fluorene and phenanthrene PAHs which were weekly anti-androgenic). These findings underscore the substantial contribution of PAH-derived SOA to the AhR-mediated activities of PM.

In this study, we investigated the impact of iron-rich nanoparticles derived from different locations in the subway on the innate immune system in blood. Nanoparticles were generated from Third Rail, Rail, and Wheel materials and characterized using several techniques. The response in a human whole-blood model was analyzed using ELISA and capillary immunoelectrophoresis. All nanoparticles were iron oxides, but Third Rail nanoparticles also contained Silicon and were highly thrombo-inflammatory, activating Factor XI-induced coagulation and pro-inflammatory kallikrein/kinin pathways. Wheel and Rail nanoparticles were less reactive, mainly activating the kallikrein/kinin pathway, leading to milder inflammatory reactions. The strong thrombo-inflammatory properties of Third Rail nanoparticles are attributed to their high Silicon content. None of the nanoparticles significantly activated the complement system. In conclusion, we found that the elemental composition of nanoparticles is crucial in determining whether activation leads to kallikrein/kinin system activation and bradykinin release or Factor XI activation and thrombosis.

Long-term exposure to PM2.5 and O3 is linked to various adverse health outcomes. However, many epidemiological studies on their health effects use single-pollutant models, leading to omitted variable bias (OVB). The percent bias, based on the classical OVB formula, depends on the PM2.5-O3 correlation and unobservable true effects. Data were sourced from two recent meta-analyses of the log-linear link between all-cause mortality and per-unit exposure to PM2.5 or O3. We then developed a new meta-regression method to correct biases, and its performance was verified through simulation. The OVB for PM2.5 or O3 can vary greatly from positive to negative across different spatial scales (like country, sub-national region, or city). By applying this method to 24 individual estimates, we found that a 10 μg/m³ increase in PM2.5 was linked to a 7.4 % increase in all-cause mortality risk, while O3's association with all-cause mortality was not significant, which implies that PM2.5 must be considered in epidemiological analyses to obtain reliable effect estimates for O3. Our findings offer novel methodologies for the systematic assessment of the health effects of multiple pollutants. This contribution holds significant potential in fortifying health intervention strategies and minimizing the health risks posed by air pollution to the public.

Air pollution has a detrimental effect on the risk of dementia and cataract. This study aimed to investigate the association of air pollution with the dynamic transitions of cataract and dementia.

We enrolled 409,608 participants (mean age: 56.4 years; 45.9% male) free of cataract and dementia at baseline from the UK Biobank with follow-up until 30 September 2023. We estimated the annual average concentrations of particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) at 2010. We employed multi-state models to assess the association between air pollution and the dynamic transitions of cataract and dementia after adjusting for potential confounders.

During a median follow-up of 14.5 years, 51,786 participants were diagnosed with cataracts, and 6068 with dementia. PM2.5 showed the strongest association with the transitions from healthy to cataract (hazard ratio [HR], 1.05; 95% confidence interval [CI], 1.04-1.06; p < 0.001), from healthy to dementia (HR, 1.05; 95% CI, 1.02-1.09; p = 0.002), from cataract to comorbidity (HR, 1.07; 95% CI, 1.00-1.15; p = 0.048), from healthy to death (HR, 1.03; 95% CI, 1.01-1.05; p < 0.001), and from cataract to death (HR, 1.06; 95% CI, 1.02-1.10; p = 0.007).

Our study suggested that the long-term exposure to air pollution was associated an increased risk of the transitions from health to incident cataract, dementia or the progression of both conditions. This implied the importance of implementing air pollution control strategies to prevent cataract and dementia.

Individuals with lower socioeconomic status (SES) are at a higher risk of being exposed to adverse environmental factors. Children are more vulnerable to the harmful effects of air pollutants. Therefore, this study examined socioeconomic inequalities in air pollution exposure among children in Flanders, Belgium.

Data were used from 298 children (age range: 9-12 years), and from their parents who participated in the COGNition and Air pollution in Children study. Socioeconomic status was measured using highest parental education at the individual level and median income at the neighborhood (aggregated) level. Annual average outdoor concentrations of particulate matter with diameters <2.5 μm (PM2.5) and <10.0 μm (PM10), nitrogen dioxide (NO2), and black carbon (BC) in μg/m3 were estimated at the residential address. Mixed regression models were applied to examine the associations.

Children from parents with a low education level were exposed to significantly higher levels of PM2.5, PM10, and BC compared to children from parents with a high education level. However, the associations were not significant when tested using regression models. Children who lived in areas with a lower median neighborhood income were exposed to significantly higher levels of air pollution; an interquartile range (IQR; €4505.00) decrease in income was associated with an increase in exposure to PM2.5 of 0.198 μg/m3, PM10 of 0.406 μg/m3, NO2 of 0.740 μg/m3, and BC of 0.063 μg/m3. Children of parents with a low/high education level had a higher exposure to PM2.5, PM10, NO2, and BC when living in a low income neighborhood. Exposure to all air pollutants was the highest for low parental education level and low neighborhood income.

Low neighborhood income was significantly associated with higher levels of air pollution, while parental education level was not significantly associated. Children from parents with a low education and low income were exposed to the highest levels of air pollution.

Ambient air pollution still represents a major health burden. While the link between short-term air pollution exposures and mortality has been well-documented globally, few studies have applied causal modeling approaches. Therefore, we aimed to quantify the relationship between day-to-day changes in ambient particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and nitrogen dioxide (NO2) levels and changes in daily natural, cardiovascular (including all-cardiovascular, cardiac, and stroke), as well as respiratory mortality rates using a causal modeling framework. Daily air pollution data and cause-specific death counts at the county, district, or municipality level from California (US), Jiangsu (China), Germany, and Lazio (Italy) were obtained for the years 2015-2019, including urban and rural populations. We used interactive fixed effects models to analyze the effects of air pollutants across different lag periods (0-2, 3-7, and 0-7 days after exposure) while accounting for both measured and unmeasured time-varying spatial unit-specific confounding factors. We observed increases in daily cardiovascular deaths (per 1 million people) per a 10 μg/m3 increase in daily NO2 at lag 0-7: 0.18 (95 % confidence interval: 0.02, 0.38) in California, 0.23 (0.14, 0.32) in Jiangsu, 0.48 (0.27, 0.70) in Germany, and -0.35 (-2.63, 1.92) in Lazio. For PM2.5, the related increases in cardiovascular mortality rates were 0.00 (-0.18, 0.18) in California, 0.04 (0.00, 0.09) in Jiangsu, 0.22 (0.06, 0.37) in Germany, and 1.96 (0.76, 3.16) in Lazio. Additionally, associations were seen for natural, cardiac, stroke, and respiratory mortality, particularly pronounced among individuals aged 75 and older. These associations were strongest with prolonged exposures and remained consistent even in two-pollutant models. This study, using a causal modeling approach and including urban and rural populations, contributes to the growing body of evidence linking increases in short-term exposure to NO2 and PM2.5 with increased cause-specific mortality rates.

Previous studies have indicated increased dementia risk associated with fine particulate matter (PM2.5) exposure; however, the findings are inconsistent. In this systematic review, we assessed the association between long-term PM2.5 exposure and dementia outcomes using the Burden of Proof meta-analytic framework, which relaxes log-linear assumptions to better characterize relative risk functions and quantify unexplained between-study heterogeneity (PROSPERO, ID CRD42023421869). Here we report a meta-analysis of 28 longitudinal cohort studies published up to June 2023 that investigated long-term PM2.5 exposure and dementia outcomes. We derived risk-outcome scores (ROSs), highly conservative measures of effect size and evidence strength, mapped onto a 1-5-star rating from 'weak and/or inconsistent evidence' to 'very strong and/or consistent evidence'. We identified a significant nonlinear relationship between PM2.5 exposure and dementia, with a minimum 14% increased risk averaged across PM2.5 levels between 4.5 and 26.9 µg m-3 (the 15th to 85th percentile exposure range across included studies), relative to a reference of 2.0 µg m-3 (n = 49, ROS = 0.13, two stars). We found a significant association of PM2.5 with Alzheimer's disease (n = 12, ROS = 0.32, three stars) but not with vascular dementia. Our findings highlight the potential impact of air pollution on brain aging.

Epidemiologic evidence underpinning current World Health Organization Air Quality Guidelines (WHO AQGs) is primarily derived from urban populations, which remains challenging for implementing the guidelines in low- and middle-income countries (LMICs) where most people reside in rural or less developed areas. Here, we aimed to characterize the associations between ambient air pollution and mortality in Chinese populations living in both urban and rural areas, where rural populations have not been studied previously at national level.

In this nationwide time-stratified case-crossover study, we extracted non-accidental death cases of all ages in both urban and rural areas during 2008-2020 from National Mortality Surveillance System, which covered 40,300 representative township-level administration units from 29 provinces, representing nearly 24 % of Chinese population. The urban-rural classification of participants' addresses was defined based on the China's National Bureau of Statistics. Daily township-level exposures to ambient particulate matter in diameter less than 10 μm and 2.5 μm (PM10 and PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and 8-h maximum ozone (O3) were estimated using the Nested Air Quality Prediction Modeling System. We applied conditional logistic regression models to characterize province-specific associations of mortality risks with air pollutants, and then combined the estimates using random-effects meta-analysis.

A total of 61,228,962 all-cause deaths were compiled in the analysis. During the study period, 87.3 % of the death cases had PM2.5 exposure on the same day of death above current short-term guideline level of 15 μg/m3, and 35.6 % had O3 exposure above guideline level of 100 μg/m3. In this analysis, significant morality risks were observed in associations with short-term exposures to all six criteria pollutants. In specific, each 10 μg/m3 increase in PM2.5 exposure levels on the same day of death was associated with increased mortality risks of 0.22 % (95 % confidence interval [95CI %], 0.13 to 0.31). Further, when exposure levels below the guidelines of 15 μg/m3, PM2.5 exposure attributed mortality risks increased to 1.59 % (95CI %, 0.84 to 2.35), which became largely comparable with the risks observed in high-income country studies. Notably, we derived the effects attributed to nationwide O3 exposure, with association estimate of 0.18 % (95CI %, 0.11 to 0.25), which is also comparable with global estimates. The mortality risks for major criteria pollutants PM2.5, PM10, NO2, SO2, and O3 were slightly greater among urban populations than those observed in rural populations.

This nationwide study for the first time showed increased and globally comparable mortality risks of PM2.5 exposure below current guideline level, as well as significant morality risks of O3 exposure, in Chinese populations of all ages from both urban and rural areas. Our timely findings highlight the importance of global implementation of AQGs and call for immediate air quality management actions, particularly in less developed areas.

To evaluate the relationship between short-term exposure to ambient air pollutants and cardiovascular disease (CVD) hospitalizations.

A time-series analysis was conducted using data from the Tehran Lipid and Glucose Study cohort of 3454 residents (1880 women) aged 50-70 from District 13 of Tehran. Follow-up data from January 1999 to March 2018 were analyzed. Daily mean temperatures and air pollution levels (CO, O3, PM10, NO2, and SO2) were recorded, and distributed lag non-linear models (DLNMs) assessed the lagged effects on outcome.

Over a median follow-up of 14.7 years, 2200 CVD hospitalizations occurred among 3454 participants (mean age 58.7 years, women = 1880). Among the general population, the DLNM models indicated that PM10 concentrations at 73 μg/m3 was associated with a 12 % increased risk of the outcome, with an RR of 1.12 (95 % CI: 1.01-1.24), and higher PM10 levels corresponded to increasing RRs. PM10 indicated a short-term exposure effect at 1-day lag on the outcome risk. SO2 concentrations reached significance at 24 μg/m3, with an RR of 1.06 (95 % CI: 1.04-1.07); the effect persisted up to 65 μg/m3, with an increased risk of the outcome observed at a 6-day lag. CO showed the highest RR of 1.92 (95 % CI: 1.65-2.23) for the concentration of 5 mg/m3. Exposure to CO was linked to an increased risk of the outcome with a 1-day lag. Sex as well as presence of metabolic syndrome and CKD did not modify the association between air pollutants with the outcome.

Short-term exposure to PM10, SO2 and CO significantly increased risk of CVD hospitalization.

Evidence on the combined impact of air pollution and lifestyle on cardiovascular disease (CVD) risk is limited. We employed the Space-Time Extra-Trees model, an ensemble learning method for spatiotemporal data, to estimate the annual average concentrations of five air pollutants from 2017 to 2019. Cox proportional hazards models were used to assess the associations between air pollutant exposure and CVD incidence. A lifestyle score, based on body mass index, waist circumference, diet, physical activity, alcohol consumption, and smoking, was developed to examine the moderating effect of lifestyle on the air pollution-CVD relationship. Among 5,838,833 baseline participants without CVD, 414,218 developed CVD during follow-up. Long-term exposure to particulate matter (PM1, PM2.5, PM10), ozone (O3), and carbon monoxide (CO) was significantly associated with increased CVD risk. Stratified analyses revealed that exercise had the most significant impact on this association, with exercisers showing a notable reduction in risk compared to non-exercisers. An interaction between air pollution and lifestyle was observed (P-interaction < 0.001). Compared to individuals with a relatively healthy lifestyle and low air pollution exposure, those with an unhealthy lifestyle and high exposure had the highest risk of developing CVD (PM1: HR = 1.660, PM2.5: HR = 1.891, PM10: HR = 1.755, O3: HR = 1.970, CO: HR = 1.426). Further analysis revealed a synergistic additive interaction between lifestyle and air pollution, leading to relative excess risks of 0.151, 0.154, 0.137, 0.171, and 0.095 in groups with relatively unhealthy lifestyles and high exposure to PM1, PM2.5, PM10, O3, and CO, respectively. Thus, in addition to controlling major air pollutant emissions, promoting healthy lifestyle adoption is crucial.

Particulate matter (PM), a ubiquitous significant component of the ambient air pollution mixture, significantly contributes to increased global risk for chronic cardiopulmonary diseases, acute hospitalizations, and deaths. One of the causes of this increased risk is because PM exposure increases the incidence and severity of respiratory infections. The respiratory system is particularly vulnerable to air pollution and its impact on infection as it is a key site for exposure both to inhaled pollutants and infectious microbes or viruses. This review examines the current understanding of how PM affects antiviral host defense responses and possible underlying mechanisms.

While numerous studies have associated adverse health outcomes with combined or sequential exposure to inhaled pollutants and viruses, defining causal relationships and mechanisms remains limited. Particularly limited, are contemporary data focuses on low- and middle-income countries, including heavily polluted regions such as Ulaanbaatar, Mongolia. This manuscript focuses on how (1) PM, serving as a carrier for viruses, enhances the transmission of viruses; (2) PM impairs immune defense to viruses; and (3) PM impacts epithelial cell functions to exacerbate viral infections. Given the significant public health hazards on PM, particularly in heavily polluted regions such as Southeast Asia, Middle East and Africa, it is critical to define specific mechanisms of PM on respiratory infection and how their impact may differ in these highly polluted regions. Ultimately, this could devise future public health measures and interventions to limit this substantial public health risk.

Cardiovascular disease (CVD) is the leading cause of deaths worldwide, with 80% occurring in low- and middle-income countries. These countries are characterized by rapid urbanization, poorly funded health systems, poor access to prevention and treatment strategies, and increasing age and a higher prevalence of chronic disease. Rapid urbanization has contributed to the significant environmental and societal changes affecting daily life habits and cardiovascular health. There is growing awareness that environmental and social exposures and policies can influence CVD directly or through behavioural risk factors. However, much of this knowledge comes from studies in high-income countries and is applied to low- and middle-income countries without evidence to indicate this is appropriate. This state-of-the-art review will present and synthesize key findings from the Prospective Urban Rural Epidemiology study and related studies that have aimed to understand the environmental, social, and policy determinants of cardiovascular health in countries across varying levels of economic development through an urban/rural lens. Emerging from these findings are future policy and research recommendations to accelerate the reduction of the global burden of CVD.

The knowledge of the causal relationship between exposure to airborne particulate matter (PM) and respiratory-related health issues remains unsatisfactory, owing to the complexities of physical and chemical characteristics in PM. One measure that greatly lifts the complexity is oxidative potential (OP), the overall production capacity of reactive oxygen species. We analyzed PM at different size fractions from three localities, exhibiting different source emission properties and photochemical aging states. We also investigated possible causes for their OPs, which were assessed using cellular and acellular assays. We found that higher PM mass did not always yield higher OP. Instead, chemical composition, modified by photochemical alteration (particle oxidation), played a critical role in the PM's reactivity. From a pollution hot spot to a downwind country town, the PM2.5 levels (mean ± SD) were 9.3 ± 4.5, 9.7 ± 4.9, and 6.6 ± 4.7 μg/m3, respectively. In contrast, the PM mass-normalized OP values in the downwind region were approximately 20 % higher than those in the upwind region based on the cellular assay and about three times higher from the acellular assay. Enhanced PM OP is associated with atmospheric oxidation, approximated by sulfur and nitrogen oxidation ratios. We further identified transition metals, particularly copper, a single most important species group, the primary determinant to the values of OP measured, contributing directly to OP and indirectly through metal-oxides enhanced photochemical alterations to PM.

PM2.5 pollution poses significant health risks in urban areas, yet the specific cardiovascular impacts of its hazardous components, especially transition metals, remain insufficiently understood. This study evaluated the associations of PM2.5 components on acute myocardial infarction (AMI) and acute aortic dissections (AAD) emergency hospitalizations (n = 9985) using a time-stratified case-crossover between 2017 and 2023 in Xiamen, China. We collected comprehensive data on daily air pollutants, PM2.5 components (water-soluble ions, carbon components, metals, and other elements), and meteorological variables. Conditional logistic regressions were used to estimate odds ratios (OR) per the interquartile range (IQR) of exposures. Our finding reveals significant short-term associations of exposures to air pollutants and PM2.5 components with increased cardiovascular emergency hospitalizations. The strongest associations were observed between cumulative 3-day lagged (lag 0-3) PM2.5 transition metals including Mn [odds ratio, OR = 1.106 (95% CI: 1.032-1.186)], Fe [OR = 1.078, (95% CI: 1.015-1.145)], V [OR = 1.117 (95% CI: 1.024-1.219)], and Zn [OR = 1.08, (95% CI: 1.005-1.161)] exposure with AMI. These associations were stronger among older (age >65 years), male patients, and during colder seasons. Our study highlights the underexplored subacute cardiovascular risks of PM2.5 transition metals, underscoring the need to integrate them into urban air quality management to promote environmental sustainability.

This study aims to investigate the impact of coal dust (silicon dioxide) exposure on dyslipidemia and its underlying mechanisms, with a focus on the association between coal dust exposure and hepatic metabolic disorders.

Clinical data were collected from 5433 coal mine workers to compare the incidence of dyslipidemia between the dust-exposed group and the non-exposed group. A mouse model of silicon dioxide exposure was established to observe hepatic fat accumulation and pathological changes. Liver tissue sequencing was performed to screen for key differential genes. In vitro cell experiments were utilized to identify the molecular mechanisms underlying hepatocyte metabolic abnormalities induced by silicon dioxide exposure.

Clinical data revealed that 69.2% of miners in the dust-exposed group developed dyslipidemia, which was higher than the 30.7% in the non-exposed group. Animal data showed that silicon dioxide exposure led to hepatic fat deposition and pathological damage, with the degree of injury positively correlated with exposure time. Liver sequencing identified a significant upregulation of the FMO3 (flavin monooxygenase 3) gene in mouse liver tissue following silicon dioxide exposure, accompanied by enhanced inflammatory responses. Mechanistic studies demonstrated that silicon dioxide activates Kupffer cells to secrete IL-6 (interleukin-6), which induces high expression of FMO3 in hepatocytes through the PKC/YY1 signaling pathway, thereby disrupting lipid metabolism.

Silicon dioxide exposure can promote the upregulation of FMO3 expression in hepatocytes by activating Kupffer cells to release IL-6 via the PKC/YY1 pathway, ultimately leading to lipid metabolic disorders and dyslipidemia.

This systematic review aimed to analyze the implications of endurance exercise in environments with certain levels of air pollution. This study was developed on the basis of the consensus of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The present review is supported by articles containing the main databases PubMed, Elsevier, and Web of Science (WoS), including scientific articles published in the last 20 years. This study highlights that exposure to air pollution during endurance activities, such as cycling and outdoor running, significantly affects cardiopulmonary health. In conclusion, while physical exercise in environments with high air pollution presents significant risks to cardiopulmonary health, implementing preventive measures and adopting public policies are crucial to minimizing these impacts and promoting safe exercise practices. Likewise, on the basis of these results, it is possible to motivate the creation of safe and natural spaces for sports practice.

Exposure to PM2.5 (particulate matter <2.5 μm) has been implicated in increasing the risk of endometriosis and worsening its symptoms. However, the molecular mechanisms and direct associations remain unclear. This study explored whether PM2.5 contributes to the onset or progression of endometriosis using in vitro and in vivo models. Endometrial (EM) cells from women without endometriosis were cultured to the second passages (P2) with or without exposure to PM2.5 at a concentration of 200 µg/ml (N = 5 for each group). Z-stack confocal imaging confirmed PM accumulation in the nucleus and cytoplasm of exposed EM cells. Initial PM exposure at the primary passage (P0) led to decreased proliferation, migration, anti-apoptosis, and oxidative stress, accompanied by downregulation of associated pathways. However, repeated PM exposure during subculturing to P2 led to increased proliferation, enhanced anti-apoptotic activity, and elevated oxidative stress. Given the similarity of these gene expression alterations to those observed in endometriosis, an endometriosis-induced mouse model was established to assess the potential of repeated PM exposure to exacerbate the condition in vivo. To investigate the in vivo effects, an endometriosis-induced mouse model was developed using female C57BL/6 mice exposed to low (10 mg/kg/day) or high (20 mg/kg/day) doses of PM2.5 for 4 weeks (n = 6 for each group). PM exposure significantly enlarged endometriotic lesions compared to controls (no PM exposure). Upregulated gene expression in endometriotic lesions included anti-apoptotic (Bcl2/Bax), proliferative (p-ERK), inflammatory (p-NF-κB, p-c-jun, IL-6, IL-1β), and migration (MMP-2, MMP-9) markers. PM exposure altered estrogen receptor (ER) expression, resulting in a decreased ERα/ERβ ratio in both dose groups. The control group exhibited a ratio of 1.03 ± 0.09, while the low-dose and high-dose mice had ratios of 0.57 ± 0.08 (P = 0.02) and 0.46 ± 0.26 (P = 0.03), respectively. In conclusion, PM2.5 exposure alters gene expression related to cell growth, survival, oxidative stress, and migration in EM cells and exacerbates endometriotic lesions in vivo, likely through ER modulation. These findings suggest PM2.5 may contribute to other estrogen-dependent conditions, such as leiomyoma or adenomyosis, by influencing ER pathways.

Long-term exposure to air pollution is associated with a higher incidence of various non-infectious diseases. However, not only air pollution, but also other risk factors, such as lifestyle, can play a role in the occurrence of these diseases or premature deaths from them. The study aimed to compare the lifestyle of residents of two differently air polluted regions and to determine how lifestyle is affected by socioeconomic variables.

In the framework of the project Healthy Aging in Industrial Environments, two cohorts of persons from an industrial area and a control area were established. The cohorts consisted of individuals aged 35 to 65 years. Lifestyle factors included diet, BMI, alcohol and cigarette consumption, duration of sleep, physical activity, and time spent doing hobbies. Influencing factors included region, sex, age, education, family status, and economic situation. Fully adjusted binary and ordinal logistic regression models were used for evaluation, and the output was the odds ratio (OR) with 95% confidence intervals (CI).

The effect of more air polluted industrial region was related to higher BMI (OR = 1.23; 95% CI: 1.08-1.4) and physical activity (OR = 1.31; 95% CI: 1.13-1.51) and surprisingly to lower smoking level (OR = 0.84; 95% CI: 0.74-0.99).

The results of our study are useful in targeting public health strategies and intervention programs to specific populations, and the results will be share with public awareness groups that focus on prevention and the physiological aspects of physical activity.

The honey bee Apis mellifera has long been recognized as an ideal bioindicator for environmental pollution. These insects are exposed to pollutants during their foraging activities, making them effective samplers of environmental contaminants, including heavy metals, pesticides, radionuclides, and volatile organic compounds. Recently, it has been demonstrated that honey bees can be a valuable tool for monitoring and studying airborne PM pollution, a complex mixture of particles suspended in the air, known to have detrimental effects on human health. Airborne particles attached to the bees can be characterised for their morphology, size, and chemical composition using a scanning electron microscopy coupled with X-ray spectroscopy, thus providing key information on the emission sources of the particles, their environmental fate, and the potential to elicit inflammatory injury, oxidative damage, and other health effects in living organisms. Here, we present a comprehensive summary of the studies involving the use of honey bees to monitor airborne PM, including the limits of this approach and possible perspectives. The use of honey bees as a model organism for ecotoxicological studies involving pollutant PM is also presented and discussed, further highlighting the role of the bees as a cornerstone of human, animal, and environmental health, according to the principles of the "One Health" approach.

Health is at the forefront of clean air and climate action. However, most existing studies of health impacts were based on additive single-exposure effects, which often oversimplify the relationships between atmospheric components and health outcomes. This review examines various atmospheric components' common sources and differential health effects, including greenhouse gases and major air pollutants such as fine particulate matter (PM2.5). It emphasizes the need for a comparative assessment of health impacts across various atmospheric components. We further highlight black carbon as an illustrative example, given its higher toxicity compared with other major PM2.5 components. By integrating the best available findings on the differential effects of particulate matter components with multiple gridded estimates of air pollution concentrations and population data, we conducted a risk assessment to quantify the health benefits of particulate matter reductions associated with China's clean air actions (2013-2020) and future climate mitigation scenarios (2020-2060). Our assessments indicate that, in regions or during periods where black carbon accounts for a higher proportion of exposure reduction relative to other PM2.5 components, reducing per-unit concentrations of PM2.5 can prevent more premature deaths. We propose a conceptual framework for a health-oriented strategy to enhance the effectiveness of clean air and climate initiatives.

Placental abruption, a rare disorder of unclear etiology, lacks evidence to illustrate its relationship with exposure to air pollution and temperature.

This study aimed to investigate the association between exposure to ambient pollutants and temperatures and placental abruption to identify susceptible time windows and subpopulations.

A nested case-control study was based on a live birth registration database in Chongqing, the largest Chinese municipality in China, from 2018 to 2022. The placental abruption cases were each matched with four controls by maternal age at delivery, gestational week, gravidity, parity, and delivery date. Six ambient pollutants [particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), PM with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , CO, O 3 , and SO 2 ] and temperature were estimated using machine learning algorithms. A conditional logistic regression model analyzed associations of exposure to air pollution and temperature with placental abruption in five time windows (prepregnancy, the entire pregnancy, and each of the 3 trimesters). Stratification analyses were applied to examine potential modifiers including gravidity, parity, mothers' residential area (urban/rural), pandemic experience, and delivery season.

After data quality control, 798 cases were identified and matched with 3,192 controls. An exposure relationship was identified between NO 2 during the pregnancy period and placental abruption (p < 0.001 ). In comparison with the first quartile level of NO 2 , the odds ratios (ORs) of abruption associated with exposure to the second, third, and fourth quartile levels of NO 2 were 1.42 [95% confidence interval (CI): 1.03, 1.96], 1.90 (95% CI: 1.30, 2.76), and 2.27 (95% CI: 1.39, 3.71), respectively. The association for NO 2 exposure existed in the 3 trimesters but not prepregnancy. Exposure to locally extreme low temperatures (< fifth percentile) in the third trimester was associated with increased risks of abruption (OR = 3.68 ; 95% CI: 1.67, 8.08) in comparison with locally moderate temperatures (25th-75th percentile). Stratified analysis showed no statistical significances within the effect modifiers.

Based on a large-scale live birth record, the study suggested that exposure to air pollutants, mainly NO 2 , during pregnancy may be a substantial risk factor for placental abruption. https://doi.org/10.1289/EHP14714.

Microsensors have been used for the high-resolution particulate matter (PM) monitoring.

This study applies PM and health microsensors with the objective of assessing the peak exposure, sources, and immediate health impacts of PM2.5 and PM1 in two Asian countries.

Exposure assessment and health evaluation were carried out for 50 subjects in 2018 and 2019 in Bandung, Indonesia and for 55 subjects in 2019 and 2020 in Kaohsiung, Taiwan. Calibrated AS-LUNG sets and medical-certified RootiRx® sensors were used to assess PM and heart-rate variability (HRV), respectively.

Overall, the 5-min mean exposure of PM2.5 and PM1 was 30.4 ± 20.0 and 27.0 ± 15.7 µg/m3 in Indonesia and 14.9 ± 11.2 and 13.9 ± 9.8 µg/m3 in Taiwan, respectively. The maximum 5-min peak PM2.5 and PM1 exposures were 473.6 and 154.0 µg/m3 in Indonesia and 467.4 and 217.7 µg/m3 in Taiwan, respectively. Community factories and mosquito coil burning are the two most important exposure sources, resulting in, on average, 4.73 and 5.82 µg/m3 higher PM2.5 exposure increments for Indonesian subjects and 10.1 and 9.82 µg/m3 higher PM2.5 exposure for Taiwanese subjects compared to non-exposure periods, respectively. Moreover, agricultural waste burning and incense burning were another two important exposure sources, but only in Taiwan. Furthermore, 5-min PM2.5 and PM1 exposure had statistically significantly immediate impacts on the HRV indices and heart rates of all subjects in Taiwan and the scooter subjects in Indonesia with generalized additive mixed models. The HRV change for a 10 µg/m3 increase in PM2.5 and PM1 ranged from -0.9% to -2.5% except for ratio of low-high frequency, with greater impacts associated with PM1 than PM2.5 in both countries.

This work highlights the ability of microsensors to capture high peaks of PM2.5 and PM1, to identify exposure sources through the integration of activity records, and to assess immediate changes in heart rate variability for a panel of approximately 50 subjects in Indonesia and Taiwan. This study stands out as one of the few to demonstrate the immediate health impacts of peak PM, complementing to the short-term (days or weeks) or long-term effects (months or longer) assessed in most epidemiological studies. The technology/methodology employed offer great potential for researchers in the resource-limited countries with high PM2.5 and PM1 levels.

Metabolism-disrupting agents (MDAs) are chemical, infectious or physical agents that increase the risk of metabolic disorders. Examples include pharmaceuticals, such as antidepressants, and environmental agents, such as bisphenol A. Various types of studies can provide evidence to identify MDAs, yet a systematic method is needed to integrate these data to help to identify such hazards. Inspired by work to improve hazard identification of carcinogens using key characteristics (KCs), we developed 12 KCs of MDAs based on our knowledge of processes underlying metabolic diseases and the effects of their causal agents: (1) alters function of the endocrine pancreas; (2) impairs function of adipose tissue; (3) alters nervous system control of metabolic function; (4) promotes insulin resistance; (5) disrupts metabolic signalling pathways; (6) alters development and fate of metabolic cell types; (7) alters energy homeostasis; (8) causes inappropriate nutrient handling and partitioning; (9) promotes chronic inflammation and immune dysregulation in metabolic tissues; (10) disrupts gastrointestinal tract function; (11) induces cellular stress pathways; and (12) disrupts circadian rhythms. In this Consensus Statement, we present the logic that revealed the KCs of MDAs and highlight evidence that supports the identification of KCs. We use chemical, infectious and physical agents as examples to illustrate how the KCs can be used to organize and use mechanistic data to help to identify MDAs.

Air pollution presents a growing, significant threat to health among the general population. Athletes and individuals participating in recreational exercise are particularly vulnerable due to increased ventilation during physical activity. The detrimental impacts of various pollutants on cardiorespiratory function, cognition, and sport-specific metrics have been investigated. Therefore, focus within the sports community has shifted to both personal and organizational strategies to mitigate or even prevent these effects. Limited evidence supports reducing exposure time and proximity, transition to indoor activity, precompetition acclimation, monitoring air quality when choosing location, and the use of masks and supplements. In addition, special considerations should be made for the unique exposures and challenges faced by populations, such as warfighters, para-athletes, or those living in disadvantaged communities. There remains a need for detailed and evidence-driven guidelines on air pollution for those participating in sports.

Evidence on the impacts of PM1, PM2.5, and PM10 on the hospital admissions, length of hospital stays (LOS), and hospital expenses among patients with cardiovascular disease (CVD) is still limited in China, especially in rural areas. This study was performed in eight counties of Fuyang from 1 January 2015 to 30 June 2017. We use a three-stage time-series analysis to explore the effects of short-term exposure to PM1, PM2.5, and PM10 on hospital admissions, LOS, and hospital expenses for CVDs. An increment of 10 ug/m3 in PM1, PM2.5, and PM10 corresponded to an increment of 1.82% (95% CI: 1.34, 2.30), 0.96% (95% CI: 0.44, 1.48), and 0.79% (95% CI: 0.63%, 0.95%) in CVD hospital admissions, respectively. We observed that daily concentrations of PMs were associated with an increase in hospital admissions, LOS, and expenses for CVDs. Sustained endeavors are required to reduce air pollution so as to attenuate disease burdens from CVDs.

Metals and nonmetals in drinking water could potentially influence cardiovascular health. The relationship between poor-quality drinking water, major adverse cardiovascular events (MACE), and diet is not well studied.

The aim of this study was to determine whether long-term exposure to metals (copper, manganese, aluminum, zinc, and cadmium) and nonmetals (selenium, sulfate, and nitrate-nitrogen) in drinking water was associated with MACE outcomes, and whether the dietary patterns could modify the association between long-term exposure to low-quality drinking water and MACE.

Data from a prospective population-based cohort from Yinzhou District, Ningbo (follow-up between 2016 and 2022) were linked to Yinzhou Health Information System. MACE endpoints included acute myocardial infarction (AMI), heart failure, stroke, angina, and cardiovascular death. Effect modification of the associations between exposure and MACE by dietary factors was determined.

In the final cohort of 24,212 participants, 57 had an AMI; 886 developed heart failure; 733 had a stroke; 23 had angina; and 134 had a cardiovascular death. An increased risk of: 1) AMI was seen with exposure to copper, aluminum, cadmium, and selenium; 2) stroke with exposure to zinc, copper, and selenium; 3) angina with exposure to zinc and copper; and 4) cardiovascular death with exposure to zinc and aluminum in drinking water. Consuming fish, white meat, and grain products attenuated MACE outcomes induced by metals and nonmetals in drinking water.

In this study, long-term exposure to higher metallic and nonmetallic elements in drinking water was associated with an increased risk of MACE. Specific dietary patterns modified the associations. Further studies are needed in this area.

Extreme heat and air pollution is associated with increased mortality. Recent evidence suggests the combined effects of both is greater than the effects of each individual exposure. Low neighborhood socioeconomic status ("socioeconomic burden") has also been associated with increased exposure and vulnerability to both heat and air pollution. We investigated if neighborhood socioeconomic burden or the combination of socioeconomic and environmental exposures ("socioenvironmental burden") modified the effect of combined exposure to extreme heat and particulate air pollution on mortality in California.

We used a time-stratified case-crossover design to assess the impact of daily exposure to extreme particulate matter <2.5 μm (PM2.5) and heat on cardiovascular, respiratory, and all-cause mortality in California 2014-2019. Daily average PM2.5 and maximum temperatures based on decedent's residential census tract were dichotomized as extreme or not. Census tract-level socioenvironmental and socioeconomic burden was assessed with the CalEnviroScreen (CES) score and a social deprivation index (SDI), and individual educational attainment was derived from death certificates. Conditional logistic regression was used to estimate associations of heat and PM2.5 with mortality with a product term used to evaluate effect measure modification.

During the study period 1,514,292 all-cause deaths could be assigned residential exposures. Extreme heat and air pollution alone and combined were associated with increased mortality, matching prior reports. Decedents in census tracts with higher socioenvironmental and socioeconomic burden experienced more days with extreme PM2.5 exposure. However, we found no consistent effect measure modification by CES or SDI on combined or separate extreme heat and PM2.5 exposure on odds of total, cardiovascular or respiratory mortality. No effect measure modification was observed for individual education attainment.

We did not find evidence that neighborhood socioenvironmental- or socioeconomic burden significantly influenced the individual or combined impact of extreme exposures to heat and PM2.5 on mortality in California.

We investigated the effect measure modification by socioeconomic and socioenvironmental of the co-occurrence of heat and PM2.5, which adds support to the limited previous literature on effect measure modification by socioeconomic and socioenvironmental burden of heat alone and PM2.5 alone. We found no consistent effect measure modification by neighborhood socioenvironmental and socioeconomic burden or individual level SES of the mortality association with extreme heat and PM2.5 co-exposure. However, we did find increased number of days with extreme PM2.5 exposure in neighborhoods with high socioenvironmental and socioeconomic burden. We evaluated multiple area-level and an individual-level SES and socioenvironmental burden metrics, each estimating socioenvironmental factors differently, making our conclusion more robust.

Several factors, including environmental degradation, air pollution, intense urbanization, excessive agriculture, and climate change, endanger the well-being of animals and plants. One of the major issues with an increasingly negative impact is agricultural contamination with pesticides and antibiotics. Seed coatings with neonicotinoid insecticides used as a protective layer against pests are shown to exceed the permissible limits in most cases. Neonicotinoid compounds bind to nicotinic acetylcholine receptors, therefore affecting the honey bees' brain. Heavy metals in higher concentrations are lethal for honey bees, and the residue in bee products might pose a threat to human health. Highly effective acaricides used to treat Varroa destructor infestations in honey bee colonies have negative effects on honey bee reproduction, olfaction, and honey production. Furthermore, amitraz and fluvalinate are mostly found in the highest amounts and lead to decreased honey production and reduced colony reproduction, along with decreased learning ability and memory. However, scientific studies have shown that honey bees act as a reliable bio-indicator of environmental pollution. In response to the growing demand for bee products, the effects of adulteration and improper storage conditions have gotten worse and represent a new risk factor. In light of the shifting global economy, it is important to analyze consumer expectations and adjust manufacturing accordingly. By ensuring the manufacture of high-quality, traceable products devoid of drug residues, consumers will be better protected from subsequent health problems. This review's objectives are based on the necessity of identifying the risks associated with honey bees and bee products.

Existing studies have found the health implications of greenness on cardiovascular health, but largely focus on greenspace rather than visible greenness. We aimed to investigate the relationship between visible greenness within the community life circle and atrial fibrillation (AF). Our study included 11,539 permanent residents from a large prospective cohort in a megacity of southern China from 2015 to 2017. We generated 15-minute walking isochrone for each study participant as the community life circle and combined it with green view index (GVI) to estimate corresponding exposure to residential greenness. GVI was calculated utilizing street view images and a fully convolutional neural network tailored for evaluating urban environments. We combined logistic regression model and a doubly-robust approach to explore the relationship between GVI and AF. Mediation analyses were used to assess the mediating role of air pollution, body mass index (BMI) and exercise time on the relationship between GVI and AF. We found that each IQR increase in GVI exposure was associated with a 22.6 % (95 % CI: 8.7 %, 34.1 %) reduction in the risk of AF. The mediation effect of PM1 on the relationship between GVI and AF was also identified. Higher visible greenness exposure within community life circle was associated with reduced risk of AF among urban residents. Visible greenness within urban community areas should be emphasized as a solution to promote cardiovascular health.