Long-term effects of air pollution on ankle-brachial index

Long-term associations of PM1 versus PM2.5 and PM10 with asthma and asthma-related respiratory symptoms in the middle-aged and elderly population

Background

Few studies have compared the associations between long-term exposures to particulate matters (aerodynamic diameter ≤1, ≤2.5 and ≤10 µm: PM1, PM2.5 and PM10, respectively) and asthma and asthma-related respiratory symptoms. The objective of the present study was to compare the strength of the aforementioned associations in middle-aged and elderly adults.

Methods

We calculated the mean 722-day personal exposure estimates of PM1, PM2.5 and PM10 at 1 km×1 km spatial resolution between 2013 and 2019 at individual levels from China High Air Pollutants (CHAP) datasets. Using logistic regression models, we presented the associations as odds ratios and 95% confidence intervals, for each interquartile range (IQR) increase in PM1/PM2.5/PM10 concentration. Asthma denoted a self-reported history of physician-diagnosed asthma or wheezing in the preceding 12 months.

Results

We included 7371 participants in COPD surveillance from Guangdong, China. Each IQR increase in PM1, PM2.5 and PM10 was associated with a greater odds (OR (95% CI)) of asthma (PM1: 1.22 (1.02-1.45); PM2.5: 1.24 (1.04-1.48); PM10: 1.30 (1.07-1.57)), wheeze (PM1: 1.27 (1.11-1.44); PM2.5: 1.30 (1.14-1.48); PM10: 1.34 (1.17-1.55)), persistent cough (PM1: 1.33 (1.06-1.66); PM2.5: 1.36 (1.09-1.71); PM10: 1.31 (1.02-1.68)) and dyspnoea (PM1: 2.10 (1.84-2.41); PM2.5: 2.17 (1.90-2.48); PM10: 2.29 (1.96-2.66)). Sensitivity analysis results were robust after excluding individuals with a family history of allergy. Associations of PM1, PM2.5 and PM10 with asthma and asthma-related respiratory symptoms were slightly stronger in males.

Conclusion

Long-term exposure to PM is associated with increased risks of asthma and asthma-related respiratory symptoms.

Understanding the Cardiovascular and Metabolic Health Effects of Air Pollution in the Context of Cumulative Exposomic Impacts

Poor air quality accounts for more than 9 million deaths a year globally according to recent estimates. A large portion of these deaths are attributable to cardiovascular causes, with evidence indicating that air pollution may also play an important role in the genesis of key cardiometabolic risk factors. Air pollution is not experienced in isolation but is part of a complex system, influenced by a host of other external environmental exposures, and interacting with intrinsic biologic factors and susceptibility to ultimately determine cardiovascular and metabolic outcomes. Given that the same fossil fuel emission sources that cause climate change also result in air pollution, there is a need for robust approaches that can not only limit climate change but also eliminate air pollution health effects, with an emphasis of protecting the most susceptible but also targeting interventions at the most vulnerable populations. In this review, we summarize the current state of epidemiologic and mechanistic evidence underpinning the association of air pollution with cardiometabolic disease and how complex interactions with other exposures and individual characteristics may modify these associations. We identify gaps in the current literature and suggest emerging approaches for policy makers to holistically approach cardiometabolic health risk and impact assessment.

Long-Term Exposure to Fine Particulate Constituents and Vascular Damage in a Population with Metabolic Abnormality in China

AIM

To date, PM2.5-associated vascular damage in metabolic abnormalities has remained controversial. We knew little about the vascular damage of PM2.5 constituents. Thus, this study aimed to investigate the relationship between long-term exposure to PM2.5 and its constituents and vascular damage in metabolic abnormalities.

METHODS

A total of 124,387 participants with metabolic abnormalities (defined as at least one metabolic disorder, such as obesity, elevated blood pressure, elevated triglyceride level, elevated fasting glucose level, or low HDL cholesterol level) were recruited in this study from 11 representative centers in China between January 2011 and December 2017. PM2.5 and its constituents (black carbon [BC], organic matter [OM], sulfate [SO42-], nitrate [NO3-], and ammonium salts [NH4＋]) were extracted. Elevated brachial-ankle pulse wave velocity (baPWV) (≥ 1,400 cm/s) and declined ankle-brachial index (ABI) (＜0.9) indicated vascular damage. Multivariable logistic regression and Quantile g-Computation models were utilized to explore the impact on outcomes.

RESULTS

Of the 124,387 participants (median age, 49 years), 87,870 (70.64%) were men. One-year lag exposure to PM2.5 and its constituents was significantly associated with vascular damage in single pollutant models. The adjusted odds ratios (OR) for each 1-µg/m3 increase in PM2.5 was 1.013 (95% CI, 1.012-1.015) and 1.031 (95% CI, 1.025-1.037) for elevated baPWV and decreased ABI, respectively. PM2.5 constituents were also associated with vascular damage in multi-pollutant models. Among the PM2.5 constituents, BC (47.17%), SO42- (33.59%), and NH4＋ (19.23%) have the highest contribution to elevated baPWV and NO3- (47.89%) and BC (23.50%) to declined ABI.

CONCLUSION

Chronic exposure to PM2.5 and PM2.5 constituents was related to vascular damage in the abnormal metabolic population in China. The heterogeneous contribution of different PM2.5 constituents to vessel bed damage is worthy of attention when developing targeted strategies.

The Impact of Fine Particulate Matter 2.5 on the Cardiovascular System: A Review of the Invisible Killer

Air pollution exerts several deleterious effects on the cardiovascular system, with cardiovascular disease (CVD) accounting for 80% of all premature deaths caused by air pollution. Short-term exposure to particulate matter 2.5 (PM_2.5) leads to acute CVD-associated deaths and nonfatal events, whereas long-term exposure increases CVD-associated risk of death and reduces longevity. Here, we summarize published data illustrating how PM_2.5 may impact the cardiovascular system to provide information on the mechanisms by which it may contribute to CVDs. We provide an overview of PM_2.5, its associated health risks, global statistics, mechanistic underpinnings related to mitochondria, and hazardous biological effects. We elaborate on the association between PM_2.5 exposure and CVD development and examine preventive PM_2.5 exposure measures and future strategies for combating PM_2.5-related adverse health effects. The insights gained can provide critical guidelines for preventing pollution-related CVDs through governmental, societal, and personal measures, thereby benefitting humanity and slowing climate change.

Recent Insights into Particulate Matter (PM2.5)-Mediated Toxicity in Humans: An Overview

Several epidemiologic and toxicological studies have commonly viewed ambient fine particulate matter (PM_2.5), defined as particles having an aerodynamic diameter of less than 2.5 µm, as a significant potential danger to human health. PM_2.5 is mostly absorbed through the respiratory system, where it can infiltrate the lung alveoli and reach the bloodstream. In the respiratory system, reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress stimulate the generation of mediators of pulmonary inflammation and begin or promote numerous illnesses. According to the most recent data, fine particulate matter, or PM_2.5, is responsible for nearly 4 million deaths globally from cardiopulmonary illnesses such as heart disease, respiratory infections, chronic lung disease, cancers, preterm births, and other illnesses. There has been increased worry in recent years about the negative impacts of this worldwide danger. The causal associations between PM_2.5 and human health, the toxic effects and potential mechanisms of PM_2.5, and molecular pathways have been described in this review.

Beyond air pollution at home: Assessment of personal exposure to PM2.5 using activity-based travel demand model and low-cost air sensor network data

Assessing personal exposure to air pollution is challenging due to the limited availability of human movement data and the complexity of modeling air pollution at high spatiotemporal resolution. Most health studies rely on residential estimates of outdoor air pollution instead which introduces exposure measurement error. Personal exposure for 100,784 individuals in Los Angeles County was estimated by integrating human movement data simulated from the Southern California Association of Governments (SCAG) activity-based travel demand model with hourly PM_2.5 predictions from my 500 m gridded model incorporating low-cost sensor monitoring data. Individual exposures were assigned considering PM_2.5 levels at homes, workplaces, and other activity locations. These dynamic exposures were compared to the residence-based exposures, which do not consider human movement, to examine the degree of exposure estimation bias. The results suggest that exposures were underestimated by 13% (range 5-22%) on average when human movement was not considered, and much of the error was eliminated by accounting for work location. Exposure estimation bias increased for people who exhibited higher mobility levels, especially for workers with long commute distances. Overall, the personal exposures of workers were underestimated by 22% (5-61%) relative to their residence-based exposures. For workers who commute >20 miles, their exposure levels can be at most underestimated by 61%. Omitting mobility resulted in underestimating exposures for people who reside in areas with cleaner air but work in more polluted areas. Similarly, exposures were overestimated for people living in areas with poorer air quality and working in cleaner areas. These could lead to differential estimation biases across racial, ethnic and socioeconomic lines that typically correlate with where people live and work and lead to important exposure and health disparities. This study demonstrates that ignoring human movement and spatiotemporal variability of air pollution could lead to differential exposure misclassification potentially biasing health risk assessments. These improved dynamic approaches can help planners and policymakers identify disadvantaged populations for which exposures are typically misrepresented and might lead to targeted policy and planning implications.

Effects of long-term air pollution exposure on ankle-brachial index and cardio-ankle vascular index: A longitudinal cohort study using data from the Electricity Generating Authority of Thailand study

BACKGROUND

Ankle-brachial index (ABI) and cardio-ankle vascular index (CAVI) are surrogate measures of atherosclerosis based on the functional performance of vessels, and are highly related to cardiovascular events. However, only a few longitudinal studies have been conducted on their associations with long-term air pollution exposure.

OBJECTIVE

This study aimed to examine whether long-term air pollution exposure is associated with ABI and CAVI in workers of the Electricity Generating Authority of Thailand (EGAT) in the Bangkok Metropolitan Region (BMR).

METHODS

This longitudinal study included 1261 participants (age range, 57-76 years as of 2007) of the EGAT study (2007-2017). ABI and CAVI were measured in 2007, 2012, and 2017. Annual mean concentrations of particulate matter ≤10 μm in diameter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO) were estimated by ordinary kriging using data from 22 background and 7 traffic monitoring stations in BMR between 2002 and 2017. Linear mixed-effects models were used to assess associations between air pollution (expressed as 1-year, 3-year, and 5-year average concentration) and ABI and CAVI (expressed as percent changes per interquartile range (IQR) increase in PM₁₀, O₃, NO₂, SO_2, and CO). We also applied the mixed-effect ordinal logistic models to calculate odds ratios (ORs) of having high or moderate CAVI per an IQR increase in air pollution.

RESULTS

After controlling for potential confounders, 1-year average CO was negatively associated with ABI, but not significantly (-0.48%, 95% CI: -1.03, 0.07). Three-year average NO₂ was positively associated with CAVI (6.67%, 95% CI: 0.21, 13.1). In contrast, 1-year average PM₁₀ was inversely associated with CAVI although the association was not significant. Although not significantly, 1-year average NO₂ and CO were positively associated with prevalence of high or moderate CAVI.

CONCLUSIONS

Although not statistically significant, long-term NO₂ and CO exposure was associated with ABI and CAVI in the participants of the EGAT study.

Systematic review and meta-analysis of cohort studies of long term outdoor nitrogen dioxide exposure and mortality

Objective

To determine whether long term exposure to outdoor nitrogen dioxide (NO₂) is associated with all-cause or cause-specific mortality.

Methods

MEDLINE, Embase, CENTRAL, Global Health and Toxline databases were searched using terms developed by a librarian. Screening, data extraction and risk of bias assessment were completed independently by two reviewers. Conflicts were resolved through consensus and/or involvement of a third reviewer. Pooling of results across studies was conducted using random effects models, heterogeneity among included studies was assessed using Cochran’s Q and I² measures, and sources of heterogeneity were evaluated using meta-regression. Sensitivity of pooled estimates to individual studies was examined and publication bias was evaluated using Funnel plots, Begg’s and Egger’s tests, and trim and fill.

Results

Seventy-nine studies based on 47 cohorts, plus one set of pooled analyses of multiple European cohorts, met inclusion criteria. There was a consistently high degree of heterogeneity. After excluding studies with probably high or high risk of bias in the confounding domain (n = 12), pooled hazard ratios (HR) indicated that long term exposure to NO₂ was significantly associated with mortality from all/ natural causes (pooled HR 1.047, 95% confidence interval (CI), 1.023–1.072 per 10 ppb), cardiovascular disease (pooled HR 1.058, 95%CI 1.026–1.091), lung cancer (pooled HR 1.083, 95%CI 1.041–1.126), respiratory disease (pooled HR 1.062, 95%CI1.035–1.089), and ischemic heart disease (pooled HR 1.111, 95%CI 1.079–1.144). Pooled estimates based on multi-pollutant models were consistently smaller than those from single pollutant models and mostly non-significant.

Conclusions

For all causes of death other than cerebrovascular disease, the overall quality of the evidence is moderate, and the strength of evidence is limited, while for cerebrovascular disease, overall quality is low and strength of evidence is inadequate. Important uncertainties remain, including potential confounding by co-pollutants or other concomitant exposures, and limited supporting mechanistic evidence. (PROSPERO registration number CRD42018084497)

Long-term effects of fine particulate matter exposure on the progression of arterial stiffness

BACKGROUND

Prior studies have investigated the association of PM_2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM_2.5 exposure on the arterial stiffness index.

METHODS

We used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM_2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM_2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively.

RESULTS

The association between PM_2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82-1.50, P = 0.497). There was - 0.16% (95% CI: - 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72-1.37%) increase in baPWV annually with each increment of 10 μg/m³ average PM_2.5 concentration.

CONCLUSIONS

Long-term exposure to PM_2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness.

Environmental determinants of cardiovascular disease: lessons learned from air pollution

Air pollution is well recognized as a major risk factor for chronic non-communicable diseases and has been estimated to contribute more to global morbidity and mortality than all other known environmental risk factors combined. Although air pollution contains a heterogeneous mixture of gases, the most robust evidence for detrimental effects on health is for fine particulate matter (particles ≤2.5 µm in diameter (PM2.5)) and ozone gas and, therefore, these species have been the main focus of environmental health research and regulatory standards. The evidence to date supports a strong link between the risk of cardiovascular events and all-cause mortality with PM2.5 across a range of exposure levels, including to levels below current regulatory standards, with no 'safe' lower exposure levels at the population level. In this comprehensive Review, the empirical evidence supporting the effects of air pollution on cardiovascular health are examined, potential mechanisms that lead to increased cardiovascular risk are described, and measures to reduce this risk and identify key gaps in our knowledge that could help address the increasing cardiovascular morbidity and mortality associated with air pollution are discussed.

Air pollution and cardiovascular disease: car sick

The cardiovascular effects of inhaled particle matter (PM) are responsible for a substantial morbidity and mortality attributed to air pollution. Ultrafine particles, like those in diesel exhaust emissions, are a major source of nanoparticles in urban environments, and it is these particles that have the capacity to induce the most significant health effects. Research has shown that diesel exhaust exposure can have many detrimental effects on the cardiovascular system both acutely and chronically. This review provides an overview of the cardiovascular effects on PM in air pollution, with an emphasis on ultrafine particles in vehicle exhaust. We consider the biological mechanisms underlying these cardiovascular effects of PM and postulate that cardiovascular dysfunction may be implicated in the effects of PM in other organ systems. The employment of multiple strategies to tackle air pollution, and especially ultrafine particles from vehicles, is likely to be accompanied by improvements in cardiovascular health.

Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location data

One major source of uncertainty in accurately estimating human exposure to air pollution is that human subjects move spatiotemporally, and such mobility is usually not considered in exposure estimation. How such mobility impacts exposure estimates at the population and individual level, particularly for subjects with different levels of mobility, remains under-investigated. In addition, a wide range of methods have been used in the past to develop air pollutant concentration fields for related health studies. How the choices of methods impact results of exposure estimation, especially when detailed mobility information is considered, is still largely unknown. In this study, by using a publicly available large cell phone location dataset containing over 35 million location records collected from 310,989 subjects, we investigated the impact of individual subjects' mobility on their estimated exposures for five chosen ambient pollutants (CO, NO₂, SO₂, O₃ and PM_2.5). We also estimated exposures separately for 10 groups of subjects with different levels of mobility to explore how increased mobility impacted their exposure estimates. Further, we applied and compared two methods to develop concentration fields for exposure estimation, including one based on Community Multiscale Air Quality (CMAQ) model outputs, and the other based on the interpolated observed pollutant concentrations using the inverse distance weighting (IDW) method. Our results suggest that detailed mobility information does not have a significant influence on mean population exposure estimate in our sample population, although impacts can be substantial at the individual level. Additionally, exposure classification error due to the use of home-location data increased for subjects that exhibited higher levels of mobility. Omitting mobility could result in underestimation of exposures to traffic-related pollutants particularly during afternoon rush-hour, and overestimate exposures to ozone especially during mid-afternoon. Between CMAQ and IDW, we found that the IDW method generates smooth concentration fields that were not suitable for exposure estimation with detailed mobility data. Therefore, the method for developing air pollution concentration fields when detailed mobility data were to be applied should be chosen carefully. Our findings have important implications for future air pollution health studies.

Transparent thermoplastic polyurethane air filters for efficient electrostatic capture of particulate matter pollutants

Particulate matter (PM) air pollution has been established as a significant threat to public health and a destructive factor to the climate and eco-systems. In order to eliminate the effects of PM air pollution, various air filtering strategies based on electrospun nanofibers have recently been developed. However, to date, almost none of the existing nanofibers based air filters can meet the requirements of high-performance air PM filtering, including high PM removal efficiency, low resistance to airflow, and long service life, etc. For the first time, we report a fabrication process using the electrospinning method for air filters based on thermoplastic polyurethane (TPU) nanofibers. The average diameters of TPU nanofibers are tunable from 0.14 ± 0.06 μm to 0.82 ± 0.22 μm by changing the TPU concentrations in polymeric solutions. The optimized TPU nanofibers based air filters demonstrate the attractive attributes of high PM_2.5 removal efficiency up to 98.92%, good optical transparency of ∼60%, low pressure drop of ∼10 Pa, high quality factor of 0.45 Pa^-1, and long service life under the flow rate of 200 ml min^-1, which is ground-breaking compared with the existing nanofibers based air filters. These TPU nanofibers based air filters, with the excellent filtration performance and light transmittance, will shed light on the future research of nanofibers for various filtration applications and greatly benefit the public health by reducing the effects of PM air pollution.