Relationship of Time-Activity-Adjusted Particle Number Concentration with Blood Pressure

Methods in Public Health Environmental Justice Research: a Scoping Review from 2018 to 2021

PURPOSE OF REVIEW

The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods.

RECENT FINDINGS

We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods.

Ambient ultrafine particle (PM0.1): Sources, characteristics, measurements and exposure implications on human health

The problem of ultrafine particles (UFPs; PM_0.1) has been prevalent since the past decades. In addition to become easily inhaled by human respiratory system due to their ultrafine diameter (<100 nm), ambient UFPs possess various physicochemical properties which make it more toxic. These properties vary based on the emission source profile. The current development of UFPs studies is hindered by the problem of expensive instruments and the inexistence of standardized measurement method. This review provides detailed insights on ambient UFPs sources, physicochemical properties, measurements, and estimation models development. Implications on health impacts due to short-term and long-term exposure of ambient UFPs are also presented alongside the development progress of potentially low-cost UFPs sensors which can be used for future UFPs studies references. Current challenge and future outlook of ambient UFPs research are also discussed in this review. Based on the review results, ambient UFPs may originate from primary and secondary sources which include anthropogenic and natural activities. In addition to that, it is confirmed from various chemical content analysis that UFPs carry heavy metals, PAHs, BCs which are toxic in its nature. Measurement of ambient UFPs may be performed through stationary and mobile methods for environmental profiling and exposure assessment purposes. UFPs PNC estimation model (LUR) developed from measurement data could be deployed to support future epidemiological study of ambient UFPs. Low-cost sensors such as bipolar ion and ionization sensor from common smoke detector device may be further developed as affordable instrument to monitor ambient UFPs. Recent studies indicate that short-term exposure of UFPs can be associated with HRV change and increased cardiopulmonary effects. On the other hand, long-term UFPs exposure have positive association with COPD, CVD, CHF, pre-term birth, asthma, and also acute myocardial infarction cases.

Development and application of an evidence-based directed acyclic graph to evaluate the associations between metal mixtures and cardiometabolic outcomes

Objectives

Specifying causal models to assess relationships among metal mixtures and cardiometabolic outcomes requires evidence-based models of the causal structures; however, such models have not been previously published. The objective of this study was to develop and evaluate a directed acyclic graph (DAG) diagraming metal mixture exposure and cardiometabolic outcomes.

Methods

We conducted a literature search to develop the DAG of metal mixtures and cardiometabolic outcomes. To evaluate consistency of the DAG, we tested the suggested conditional independence statements using linear and logistic regression analyses with data from the San Luis Valley Diabetes Study (SLVDS; n=1795). We calculated the proportion of statements supported by the data and compared this to the proportion of conditional independence statements supported by 1,000 DAGs with the same structure but randomly permuted nodes. Next, we used our DAG to identify minimally sufficient adjustment sets needed to estimate the association between metal mixtures and cardiometabolic outcomes (i.e., cardiovascular disease, fasting glucose, and systolic blood pressure). We applied them to the SLVDS using Bayesian kernel machine regression, linear mixed effects, and Cox proportional hazards models.

Results

From the 42 articles included in the review, we developed an evidence-based DAG with 74 testable conditional independence statements (43 % supported by SLVDS data). We observed evidence for an association between As and Mn and fasting glucose.

Conclusions

We developed, tested, and applied an evidence-based approach to analyze associations between metal mixtures and cardiometabolic health.

Long-term exposure to PM2.5 constituents in relation to glucose levels and diabetes in middle-aged and older Chinese

BACKGROUND

Previous studies have indicated the associations between fine particulate matter (PM_2.5) exposure and diabetes or glucose levels. However, evidence linking PM_2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM_2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO₃^-], sulfate [SO₄^2-], and ammonium [NH₄⁺]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations.

METHODS

A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China's mainland. Health examination and questionnaire survey for each respondent were performed during 2011-2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA_1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM_2.5 mass and its five constituents (BC, OM, NO₃^-, SO₄^2-, and NH₄⁺) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM_2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age.

RESULTS

We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM_2.5, BC, OM, NO₃^-, SO₄^2-, and NH₄⁺ were 47.9 (27.4) µg/m³, 2.9 (2.2) µg/m³, 9.2 (6.6) µg/m³, 10.2 (9.4) µg/m³, 11.0 (5.2) µg/m³, and 7.1 (4.4) µg/m³, respectively. Per IQR rise in exposure to PM_2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048-0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012-0.181]), OM (0.160 mmol/L [0.065-0.256]), NO₃^- (0.145 mmol/L [0.039-0.251]), SO₄^2- (0.111 mmol/L [0.026-0.196]), and NH₄⁺ (0.135 mmol/L [0.041-0.230]). Under different diabetes definitions, PM_2.5 mass and selected constituents with the exception of SO₄^2- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097-1.270) for PM_2.5, 1.154 (1.079-1.235) for BC, 1.170 (1.079-1.270) for OM, 1.200 (1.098-1.312) for NO₃^-, and 1.123 (1.037-1.215) for NH₄⁺. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064-1.411]) than females (1.024 [0.923-1.136]) when exposed to PM_2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM_2.5 constituents exposure.

CONCLUSIONS

Exposures to PM_2.5 and its constituents (i.e., BC, OM, NO₃^-, and NH₄⁺) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

A new exposure metric for the cumulative effect of short-term exposure peaks of traffic-related ultrafine particles

INTRODUCTION

The adverse health outcomes of traffic-related ultrafine particles (UFPs) disproportionally impact near-highway neighborhoods. Current studies focus on either short-term health outcomes associated with short-term UFP exposures averaged over days or weeks, or long-term outcomes associated with long-term (yearly or longer) average UFP exposures. We hypothesized that frequent and repeated exposure to short-term UFP peaks that last for just hours could overwhelm or alter physiological defensive responses, resulting in long-term health issues. Herein, we propose a new exposure metric for measuring the cumulative effect of these peak exposures.

METHOD

We used UFP exposure data estimated by the Community Assessment of Freeway Exposure and Health (CAFEH) project, which recruited 704 participants from three pairs of near-highway/urban background neighborhoods in the Greater Boston Area between 2009 and 2012. CAFEH developed land use regression (LUR) models to estimate hourly averages of ambient UFP levels within the study areas based on mobile-monitored UFP data, and applied time-activity adjustment (TAA) to calculate adjusted final hourly estimates. Our alternative metric assigns cumulative peak exposure, which is determined as either the intensity (a high percentile of an individual's adjusted hourly UFP estimates) or the frequency (the number of hours with adjusted UFP estimates greater than a high percentile of all adjusted hourly UFP estimates of all participants in the study area) of UFP peaks.

RESULTS

After TAA was applied, for most of the time, our cumulative peak exposure metrics were not strongly correlated with the annual average. However, the level of correlation varied greatly from neighborhood to neighborhood (Spearman's R ranges from 0.39 to 0.97).

CONCLUSION

There was variation in UFP peak exposure that was not explained by the annual average, suggesting that our proposed peak metric distinct from annual average exposure metric.

Distributions and determinants of time spent outdoors among school-age children in China

BACKGROUND

The outdoor time is a key factor that determines children's exposure to environmental contaminants. Meanwhile, children reap numerous physical and mental health benefits from playing outdoors.

OBJECTIVE

This study aimed to characterize the distributions and identify determinants of the time spent outdoors among school-age children in China.

METHODS

The study recruited 41,439 children aged 6-17 years in Mainland China using a multi-stage cluster random sampling method. This sample was nationally representative with sample weights created to account for the complex survey design. Information on time-activity patterns were collected with a standard questionnaire through face-to-face interviews. Frequency distributions of time outdoors were created by age group, gender, region, and other sociodemographic factors with sample weights. The key factors influencing time outdoors were identified using multivariable linear regression models.

RESULTS

The grand mean (±standard deviation) time outdoors was 101 ± 51 min/day for all the study participants, 22.3% having <60 min/day. Children spent longer time outdoors in warm seasons and on weekends. Children's outdoor time was significantly influenced by gender, age, urbanicity, region, annual total household expenditure, building environment, and meteorological conditions (annual mean temperature, sunshine time, and precipitation). Girls, 15-17 year old, and urban children had 6 min/day, 8 min/day, and 13 min/day less outdoor time than boys, 6-8 year old, and rural children, respectively. Most significantly, urban girls and high school students had the shortest outdoor time. The cement ground was the most important type of ground for children playing outside.

SIGNIFICANCE

This was the first national-scale study that characterized the time outdoors and where is it spent among school-age children in China. It revealed that one-fifth of Chinese children spent less than one hour outdoors every day, and urban girls had particular "indoor tendencies". The findings provide bases for future interventions and guidelines aimed at promoting children's physical activities.

Distinct Ultrafine Particle Profiles Associated with Aircraft and Roadway Traffic

The Mobile ObserVations of Ultrafine Particles study was a two-year project to analyze potential air quality impacts of ultrafine particles (UFPs) from aircraft traffic for communities near an international airport. The study assessed UFP concentrations within 10 miles of the airport in the directions of aircraft flight. Over the course of four seasons, this study conducted a mobile sampling scheme to collect time-resolved measures of UFP, CO₂, and black carbon (BC) concentrations, as well as UFP size distributions. Primary findings were that UFPs were associated with both roadway traffic and aircraft sources, with the highest UFP counts found on the major roadway (I-5). Total concentrations of UFPs alone (10-1000 nm) did not distinguish roadway and aircraft features. However, key differences existed in the particle size distribution and the black carbon concentration for roadway and aircraft features. These differences can help distinguish between the spatial impact of roadway traffic and aircraft UFP emissions using a combination of mobile monitoring and standard statistical methods.

Cardiovascular effects of air pollution: current evidence from animal and human studies

Air pollution is a global health concern. Particulate matter (PM)_2.5, a component of ambient air pollution, has been identified by the World Health Organization as one of the pollutants that poses the greatest threat to public health. Cardiovascular health effects have been extensively documented, and these effects are still being researched to provide an overview of recent literature regarding air pollution-associated cardiovascular morbidity and mortality in humans. Additionally, potential mechanisms through which air pollutants affect the cardiovascular system are discussed based on human and additional animal studies. We used the strategy of a narrative review to summarize the scientific literature of studies that were published in the past 7 yr. Searches were carried out on PubMed and Web of Science using predefined search queries. We obtained an initial set of 800 publications that were filtered to 78 publications that were relevant to include in this review. Analysis of the literature showed significant associations between air pollution, especially PM_2.5, and the risk of elevated blood pressure (BP), acute coronary syndrome, myocardial infarction (MI), cardiac arrhythmia, and heart failure (HF). Prominent mechanisms that underlie the adverse effects of air pollution include oxidative stress, systemic inflammation, endothelial dysfunction, autonomic imbalance, and thrombogenicity. The current review underscores the relevance of air pollution as a global health concern that affects cardiovascular health. More rigorous standards are needed to reduce the cardiovascular disease burden imposed by air pollution. Continued research on the health impact of air pollution is needed to provide further insight.

Ultrafine Particle Number Concentration Model for Estimating Retrospective and Prospective Long-Term Ambient Exposures in Urban Neighborhoods

Short-term exposure to ultrafine particles (UFP; <100 nm in diameter), which are present at high concentrations near busy roadways, is associated with markers of cardiovascular and respiratory disease risk. To date, few long-term studies (months to years) have been conducted due to the challenges of long-term exposure assignment. To address this, we modified hybrid land-use regression models of particle number concentrations (PNCs; a proxy for UFP) for two study areas in Boston (MA) by replacing the measured PNC term with an hourly model and adjusting for overprediction. The hourly PNC models used covariates for meteorology, traffic, and sulfur dioxide concentrations (a marker of secondary particle formation). We compared model performance against long-term PNC data collected continuously from 9 years before and up to 3 years after the model-development period. Model predictions captured the major temporal variations in the data and model performance remained relatively stable retrospectively and prospectively. The Pearson correlation of modeled versus measured hourly log-transformed PNC at a long-term monitoring site for 9 years prior was 0.74. Our results demonstrate that highly resolved spatial-temporal PNC models are capable of estimating ambient concentrations retrospectively and prospectively with generally good accuracy, giving us confidence in using these models in epidemiological studies.

Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants. Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.