Urinary polycyclic aromatic hydrocarbon metabolites and their association with oxidative stress among pregnant women in Los Angeles

Background

Polycyclic aromatic hydrocarbons (PAHs) have been linked to adverse birth outcomes, but few epidemiological studies to date have evaluated associations between urinary PAH metabolites and oxidative stress biomarkers in pregnancy.

Methods

We measured a total of 7 PAH metabolites and 2 oxidative stress biomarkers (malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG)) in urine samples collected up to three times during pregnancy in 159 women enrolled at antenatal clinics at the University of California Los Angeles during 2016-2019. Using multiple linear regression models, we estimated the percentage change (%) and 95% confidence interval (CI) in 8-OHdG and MDA measured at each sample collection time per doubling of PAH metabolite concentrations.

Results

Most PAH metabolites were positively associated with both urinary oxidative stress biomarkers, MDA and 8-OHdG, with stronger associations in early and late pregnancy. Women pregnant with male fetuses exhibited slightly larger increases in both MDA and 8-OHdG in association with PAH exposures in early and late pregnancy.

Conclusion

Urinary OH-PAH biomarkers are associated with increases in oxidative stress during pregnancy, especially in early and late pregnancy. Sex differences in associations between PAH exposures and oxidative stress need to be further explored in the future.

Associations between brake and tire wear-related PM2.5 metal components, particulate oxidative stress potential, and autism spectrum disorder in Southern California

BACKGROUND

Air pollution is a global health concern, with fine particulate matter (PM2.5) constituents posing potential risks to human health, including children's neurodevelopment. Here we investigated associations between exposure during pregnancy and infancy to specific traffic-related PM2.5 components with Autism Spectrum Disorder (ASD) diagnosis.

METHODS

For exposure assessment, we estimated PM2.5 components related to traffic exposure (Barium [Ba] as a marker of brake dust and Zinc [Zn] as a tire wear marker, Black Carbon [BC]) and oxidative stress potential (OSP) markers (Hydroxyl Radical [OPOH] formation, Dithiothreitol activity [OPDTT], reactive oxygen species [ROS]) modeled with land use regression with co-kriging based on an intensive air monitoring campaign. We assigned exposures to a cohort of 444,651 children born in Southern California between 2016 and 2019, among whom 11,466 ASD cases were diagnosed between 2018 and 2022, Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained with logistic regression for single pollutant and PM2.5 mass co-adjusted models, also adjusting for sociodemographic characteristics.

RESULTS

Among PM2.5 components, we found the strongest positive association with ASD for our brake wear marker Ba (ORper IQR = 1.29, 95 % CI: 1.24, 1.34). This was followed by an increased risk for all PM2.5 oxidative stress potential markers; the strongest association was with ROS formation (ORper IQR = 1.22, 95 % CI: 1.18, 1.25). PM2.5 mass was linked to ASD in Hispanic and Black children, but not White children, while traffic-related PM2.5 and OSP markers increased ASD risk across all groups. In neighborhoods with the lowest socioeconomic status (SES), associations with ASD were stronger for all examined pollutants compared to higher SES areas.

CONCLUSIONS

Our findings suggest that brake wear-related PM2.5 and PM2.5 OSP are associated with ASD diagnosis in Southern California. These results suggest that strategies aimed at reducing the public health impacts of PM2.5 need to consider specific sources.

Neighborhood greenness and participation in specific types of recreational physical activities in the Sister Study

BACKGROUND

Urban green spaces have been consistently shown to have important human health benefits across a range of outcomes. These benefits are thought to be achieved, in part, because urban greenness provides opportunities for participation in recreational activity. However, the findings from studies that have assessed links between exposure to greenness and physical activity have been mixed. To date, few studies have examined association between greenness and specific types of recreational physical activities.

OBJECTIVE

We evaluated associations between measures of greenness and specific types of recreational physical activities. Moreover, we explored the extent to which these associations were modified by socioeconomic conditions, and regionally.

METHODS

We analyzed cross-sectional data from 49,649 women in the Sister Study and assigned three residentially-based measures of greenness based on national land cover data at buffer distances of 250 m and 500 m. Data on participation in up to ten specific recreational physical activities, including time spent in each activity were collected. Logistic regression was used to estimate odds ratios (OR) and their 95% confidence intervals (CI) controlling for confounders.

RESULTS

Compared to those in the lowest tertile of greenness, participants in the upper tertile of greenness within a 500 m buffer, were more likely to garden (OR = 1.46, 95% CI = 1.25,1.69), participate in sports (OR = 1.28, 95% CI = 1.19,1.38), run (OR = 1.15, 95% CI = 1.04,1.27), walk (OR = 1.11, 95% CI = 1.06,1.16), and engage in conditioning exercises (OR = 1.10, 95% CI = 1.05,1.16) at least once a week for at least one month over the past year. These associations were modified by household income and US region.

DISCUSSION

Our findings suggest a beneficial effect of greenness on physical activity and provide additional information to inform planning of green environments that contribute to better health and wellbeing.

Chronic respiratory symptoms following deployment-related occupational and environmental exposures among US veterans

OBJECTIVES

Characterise inhalational exposures during deployment to Afghanistan and Southwest Asia and associations with postdeployment respiratory symptoms.

METHODS

Participants (n=1960) in this cross-sectional study of US Veterans (Veterans Affairs Cooperative Study 'Service and Health Among Deployed Veterans') completed an interviewer-administered questionnaire regarding 32 deployment exposures, grouped a priori into six categories: burn pit smoke; other combustion sources; engine exhaust; mechanical and desert dusts; toxicants; and military job-related vapours gas, dusts or fumes (VGDF). Responses were scored ordinally (0, 1, 2) according to exposure frequency. Factor analysis supported item reduction and category consolidation yielding 28 exposure items in 5 categories. Generalised linear models with a logit link tested associations with symptoms (by respiratory health questionnaire) adjusting for other covariates. OR were scaled per 20-point score increment (normalised maximum=100).

RESULTS

The cohort mean age was 40.7 years with a median deployment duration of 11.7 months. Heavy exposures to multiple inhalational exposures were commonly reported, including burn pit smoke (72.7%) and VGDF (72.0%). The prevalence of dyspnoea, chronic bronchitis and wheeze in the past 12 months was 7.3%, 8.2% and 15.6%, respectively. Burn pit smoke exposure was associated with dyspnoea (OR 1.22; 95% CI 1.06 to 1.47) and chronic bronchitis (OR 1.22; 95% CI 1.13 to 1.44). Exposure to VGDF was associated with dyspnoea (OR 1.29; 95% CI 1.14 to 1.58) and wheeze (OR 1.18; 95% CI 1.02 to 1.35).

CONCLUSION

Exposures to burn pit smoke and military occupational VGDF during deployment were associated with an increased odds of chronic respiratory symptoms among US Veterans.

BAYESIAN HIERARCHICAL MODELING AND ANALYSIS FOR ACTIGRAPH DATA FROM WEARABLE DEVICES

The majority of Americans fail to achieve recommended levels of physical activity, which leads to numerous preventable health problems such as diabetes, hypertension, and heart diseases. This has generated substantial interest in monitoring human activity to gear interventions toward environmental features that may relate to higher physical activity. Wearable devices, such as wrist-worn sensors that monitor gross motor activity (actigraph units) continuously record the activity levels of a subject, producing massive amounts of high-resolution measurements. Analyzing actigraph data needs to account for spatial and temporal information on trajectories or paths traversed by subjects wearing such devices. Inferential objectives include estimating a subject's physical activity levels along a given trajectory; identifying trajectories that are more likely to produce higher levels of physical activity for a given subject; and predicting expected levels of physical activity in any proposed new trajectory for a given set of health attributes. Here, we devise a Bayesian hierarchical modeling framework for spatial-temporal actigraphy data to deliver fully model-based inference on trajectories while accounting for subject-level health attributes and spatial-temporal dependencies. We undertake a comprehensive analysis of an original dataset from the Physical Activity through Sustainable Transport Approaches in Los Angeles (PASTA-LA) study to ascertain spatial zones and trajectories exhibiting significantly higher levels of physical activity while accounting for various sources of heterogeneity.

Air pollution and the sequelae of COVID-19 patients: A multistate analysis

IMPORTANCE

Recent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data.

OBJECTIVE

To assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information.

DESIGN AND OUTCOMES

We used a cohort design that followed patients admitted to hospital in the Kaiser Permanente Southern California (KPSC) Health System, which has 4.7 million members with characteristics similar to the general population. Enrollment began on 06/01/2020 and ran until 01/30/2021 for all patients admitted to hospital while ill with COVID-19. All possible states of sequelae were considered, including deterioration to intensive care, to death, discharge to recovery, or discharge to death. Transition risks were estimated with a multistate model. We assessed exposure using chemical transport model that predicted ambient concentrations of nitrogen dioxide, ozone, and fine particulate matter (PM2.5) at a 1 km scale.

RESULTS

Each increase in PM2.5 concentration equivalent to the interquartile range was associated with increased risk of deterioration to intensive care (HR of 1.16; 95% CI: 1.12-1.20) and deterioration to death (HR of 1.11; 95% CI: 1.04-1.17). Results for ozone were consistent with PM2.5 effects, but ozone also affected the transition from recovery to death: HR of 1.24 (95% CI: 1.01-1.51). NO2 had weaker effects but displayed some elevated risks.

CONCLUSIONS

PM2.5 and ozone were significantly associated with transitions to more severe states while in hospital and to death after discharge from hospital. Reducing air pollution could therefore lead to improved prognosis for COVID-19 patients and a sustainable means of reducing the health impacts of coronaviruses now and in the future.

Fine Particulate Matter Metal Composition, Oxidative Potential, and Adverse Birth Outcomes in Los Angeles

BACKGROUND

Although many studies have linked prenatal exposure to PM 2.5 to adverse birth outcomes, little is known about the effects of exposure to specific constituents of PM 2.5 or mechanisms that contribute to these outcomes.

OBJECTIVES

Our objective was to investigate effects of oxidative potential and PM 2.5 metal components from non-exhaust traffic emissions, such as brake and tire wear, on the risk of preterm birth (PTB) and term low birth weight (TLBW).

METHODS

For a birth cohort of 285,614 singletons born in Los Angeles County, California, in the period 2017-2019, we estimated speciated PM 2.5 exposures modeled from land use regression with cokriging, including brake and tire wear related metals (barium and zinc), black carbon, and three markers of oxidative potential (OP), including modeled reactive oxygen species based on measured iron and copper (ROS), OH formation (OP OH ), and dithiothreitol (DTT) loss (OP DTT ). Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for PTB and TLBW with speciated PM 2.5 exposures and PM 2.5 mass as continuous variables scaled by their interquartile range (IQR).

RESULTS

For both metals and oxidative potential metrics, we estimated increased risks for PTB (ORs ranging from 1.01 to 1.03) and TLBW (ORs ranging from 1.02 to 1.05) per IQR exposure increment that were robust to adjustment for PM 2.5 mass. Associations for PM 2.5 mass, black carbon, metal components, and oxidative potential (especially ROS and OP OH ) with adverse birth outcomes were stronger in Hispanic, Black, and mixed-race or Native American women.

DISCUSSION

Our results indicate that exposure to PM 2.5 metals from brake and tire wear and particle components that contribute to oxidative potential were associated with an increased risk of PTB and TLBW in Los Angeles County, particularly among Hispanic, Black, and mixed-race or Native American women. Thus, reduction of PM 2.5 mass only may not be sufficient to protect the most vulnerable pregnant women and children from adverse effects due to traffic source exposures. https://doi.org/10.1289/EHP12196.

Short-Term total and wildfire fine particulate matter exposure and work loss in California

BACKGROUND

Few studies investigated the impact of particulate matter (PM2.5) on some symptom exacerbations that are not perceived as severe enough to search for medical assistance. We aimed to study the association of short-term daily total PM2.5 exposure with work loss due to sickness among adults living in California.

METHODS

We included 44,544 adult respondents in the workforce from 2015 to 2018 California Health Interview Survey data. Daily total PM2.5 concentrations were linked to respondents' home addresses from continuous spatial surfaces of PM2.5 generated by a geostatistical surfacing algorithm. We estimated the effect of a 2-week average of daily total PM2.5 exposure on work loss using logistic regression models.

RESULTS

About 1.69% (weighted percentage) of adult respondents reported work loss in the week before the survey interview. The odds ratio of work loss was 1.45 (odds ratio [OR] = 1.45, 95% confidence interval [CI]: 1.03, 2.03) when a 2-week average of daily total PM2.5 exposure was higher than 12 µg/m3. The OR for work loss was 1.05 (95% CI: 0.98, 1.13) for each 2.56ug/m3 increase in the 2-week average of daily total PM2.5 exposure, and became stronger among those who were highly exposed to wildfire smoke (OR = 1.06, 95% CI: 1.00, 1.13), compared to those with lower wildfire smoke exposure (OR = 1.04, 95% CI: 0.79, 1.39).

CONCLUSIONS

Our findings suggest that short-term ambient PM2.5 exposure is positively associated with work loss due to sickness and the association was stronger among those with higher wildfire smoke exposure. It also indicated that the current federal and state PM2.5 standards (annual average of 12 µg/m3) could be further strengthened to protect the health of the citizens of California.

Health benefits of Open Streets programmes in Latin America: a quantitative health impact assessment

BACKGROUND

To improve physical activity in Latin American cities, several interventions have been promoted, such as Open Streets programmes. Our study aims to quantify the health and economic effects of Open Streets-related physical activity in 15 Latin American cities.

METHODS

We used a quantitative health impact assessment approach to estimate annual premature deaths and disease incidence (ischaemic heart disease, ischaemic stroke, type 2 diabetes, colon cancer, breast cancer, and dementia) avoided, the disability-adjusted life-years (DALYs) gained, and the cost saving (from reduced premature mortality) related to increased physical activity from Open Streets programmes in 15 Latin American cities. Input data were obtained from scientific publications, reports, and open street city surveys spanning 2017 to 2019. Physical activity data were converted to metabolic equivalent of the task. Exposure-response relationship functions were applied to estimate relative risk and population-attributable fraction, enabling the assessment of premature deaths and disease incidence.

FINDINGS

The percentage of male users of the Open Streets programmes ranged from 55% (27 500 of 50 000 in Guatemala) to 75% (2250 of 3000 in El Alto, Bolivia), and female users ranged from 25% (750; El Alto) to 45% (22 500; Guatemala). We estimated that the current Open Streets programmes in the 15 Latin American cities studied could prevent 363 (95% CI 271-494) annual premature deaths due to increased physical activity, with an annual economic impact of US$194·1 million (144·9 million-263·9 million) saved and an annual reduction of 1036·7 DALYs (346·7-1778·3). If one Open Streets event is added per week in each of those cities, the potential benefit could increase to 496 (370 to 677) premature deaths prevented each year.

INTERPRETATION

Open Streets programmes in Latin America can provide health and economic benefits related to increased physical activity and can be used as a health promotion and disease prevention tool.

FUNDING

EU's Horizon 2020 research and innovation programme.

Effect modification of the association between fine particulate air pollution during a wildfire event and respiratory health by area-level measures of socio-economic status, race/ethnicity, and smoking prevalence

Fine particulate air pollution (PM2.5) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities.

Air pollution and traffic noise interact to affect cognitive health in older Mexican Americans

BACKGROUND

Both air pollution and noise exposures have separately been shown to affect cognitive impairment. Here, we examine how air pollution and noise exposures interact to influence the development of incident dementia or cognitive impairment without dementia (CIND).

METHODS

We used 1,612 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Air pollution (nitrogen dioxides, particulate matter, ozone) and noise exposure levels were modeled with a land-use regression and via the SoundPLAN software package implemented with the Traffic Noise Model applied to the greater Sacramento area, respectively. Using Cox proportional hazard models, we estimated the hazard of incident dementia or CIND from air pollution exposure at the residence up to 5-years prior to diagnosis for the members of each risk set at event time. Further, we investigated whether noise exposure modified the association between air pollution exposure and dementia or CIND.

RESULTS

In total, 104 incident dementia and 159 incident dementia/CIND cases were identified during the 10 years of follow-up. For each ∼2 µg/m3 increase in time-varying 1- and 5-year average PM2.5 exposure, the hazard of dementia increased 33% (HR = 1.33, 95%CI: 1.00, 1.76). The hazard ratios for NO2-related dementia/CIND and PM2.5-related dementia were stronger in high-noise (≥65 dB) exposed than low-noise (<65 dB) exposed participants.

CONCLUSION

Our study indicates that PM2.5 and NO2 air pollution adversely affect cognition in elderly Mexican Americans. Our findings also suggest that air pollutants may interact with traffic-related noise exposure to affect cognitive function in vulnerable populations.

The association of green space, tree canopy and parks with life expectancy in neighborhoods of Los Angeles

Substantial evidence suggests that access to urban green spaces and parks is associated with positive health outcomes, including decreased mortality. Few existing studies have investigated the association between green spaces and life expectancy (LE), and none have used small-area data in the U.S. Here we used the recently released U.S. Small-Area Life Expectancy Estimates Project data to quantify the relationship between LE and green space in Los Angeles County, a large diverse region with inequities in park access. We developed a model to quantify the association between green space and LE at the census tract level. We evaluated three green space metrics: normalized difference vegetation index (NDVI, 0.6-meter scale), percent tree canopy cover, and accessible park acres. We statistically adjusted for 15 other determinants of LE. We also developed conditional autoregressive models to account for spatial dependence. Tree canopy and NDVI were both significantly associated with higher LE. For an interquartile range (IQR) increase in each metric respectively, the spatial models demonstrated a 0.24 to 0.33-year increase in LE. Tree canopy and NDVI also modified the effect of park acreage on LE. ln areas with tree canopy levels below the county median, an IQR increase in park acreage was associated with an increase of 0.12 years. Although on an individual level these effects were modest, we predicted 155,300 years of LE gains across the population in LA County if all areas below median tree canopy were brought to the county median of park acres. If tree canopy or NDVI were brought to median levels, between 570,300 and 908,800 years of LE could be gained. The majority of potential gains are in areas with predominantly Hispanic/Latinx and Black populations. These findings suggest that equitable access to green spaces could result in substantial population health benefits.

Air pollution and meteorology as risk factors for COVID-19 death in a cohort from Southern California

BACKGROUND

Recent evidence links ambient air pollution to COVID-19 incidence, severity, and death, but few studies have analyzed individual-level mortality data with high quality exposure models.

METHODS

We sought to assess whether higher air pollution exposures led to greater risk of death during or after hospitalization in confirmed COVID-19 cases among patients who were members of the Kaiser Permanente Southern California (KPSC) healthcare system (N=21,415 between 06-01-2020 and 01-31-2022 of whom 99.85 % were unvaccinated during the study period). We used 1 km resolution chemical transport models to estimate ambient concentrations of several common air pollutants, including ozone, nitrogen dioxide, and fine particle matter (PM_2.5). We also derived estimates of pollutant exposures from ultra-fine particulate matter (PM_0.1), PM chemical species, and PM sources. We employed Cox proportional hazards models to assess associations between air pollution exposures and death from COVID-19 among hospitalized patients.

FINDINGS

We found significant associations between COVID-19 death and several air pollution exposures, including: PM_2.5 mass, PM_0.1 mass, PM_2.5 nitrates, PM_2.5 elemental carbon, PM_2.5 on-road diesel, and PM_2.5 on-road gasoline. Based on the interquartile (IQR) exposure increment, effect sizes ranged from hazard ratios (HR) = 1.12 for PM_2.5 mass and PM_2.5 nitrate to HR ∼ 1.06-1.07 for other species or source markers. Humidity and temperature in the month of diagnosis were also significant negative predictors of COVID-19 death and negative modifiers of the air pollution effects.

INTERPRETATION

Air pollution exposures and meteorology were associated the risk of COVID-19 death in a cohort of patients from Southern California. These findings have implications for prevention of death from COVID-19 and for future pandemics.

Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM_2.5) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OP^OH), dithiothreitol loss (OP^DTT), black carbon, and 52 metals and elements for 54 total PM_2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OP^OH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OP^OH, followed by 21% from brake and tire wear. Similar results were observed for the OP^DTT source apportionment. Furthermore, by linking measured PM_2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OP^OH exhibited the largest inverse social gradients, followed by OP^DTT and PM_2.5 mass. Finally, OP^OH was the metric most strongly correlated with adverse health outcome indicators.

A Description of the Imaging Innovations for Placental Assessment in Response to Environmental Pollution Study

OBJECTIVE

 The aim of Placental Assessment in Response to Environmental Pollution Study (PARENTs) was to determine whether imaging of the placenta by novel multiparametric magnetic resonance imaging (MRI) techniques in early pregnancy could help predict adverse pregnancy outcomes (APOs) due to ischemic placental disease (IPD). Additionally, we sought to determine maternal characteristics and environmental risk factors that contribute to IPD and secondary APOs.

STUDY DESIGN

 Potential patients in their first trimester of pregnancy, who agreed to MRI of the placenta and measures of assessment of environmental pollution, were recruited into PARENTs, a prospective population-based cohort study. Participants were seen at three study visits during pregnancy and again at their delivery from 2015 to 2019. We collected data from interviews, chart abstractions, and imaging. Maternal biospecimens (serum, plasma, and urine) at antepartum study visits and delivery specimens (placenta, cord, and maternal blood) were collected, processed, and stored. The primary outcome was a composite of IPD, which included any of the following: placental abruption, hypertensive disease of pregnancy, fetal growth restriction, or a newborn of small for gestational age.

RESULTS

 In this pilot cohort, of the 190 patients who completed pregnancy to viable delivery, 50 (26%) developed IPD. Among demographic characteristics, having a history of prior IPD in multiparous women was associated with the development of IPD. In the multiple novel perfusion measurements taken of the in vivo placenta using MRI, decreased high placental blood flow (mL/100 g/min) in early pregnancy (between 14 and 16 weeks) was found to be significantly associated with the later development of IPD.

CONCLUSION

 Successful recruitment of the PARENTs prospective cohort demonstrated the feasibility and acceptability of the use of MRI in human pregnancy to study the placenta in vivo and at the same time collect environmental exposure data. Analysis is ongoing and we hope these methods will assist researchers in the design of prospective imaging studies of pregnancy.

KEY POINTS

· MRI was acceptable and feasible for the study of the human placenta in vivo.. · Functional imaging of the placenta by MRI showed a significant decrease in high placental blood flow.. · Measures of environmental exposures are further being analyzed to predict IPD..

Reductions in NO2 and emergency room visits associated with California's goods movement policies: A quasi-experimental study

INTRODUCTION

This study examines whether the "Emission Reduction Plan for Ports and Goods Movement" in California reduced air pollution exposures and emergency room visits among California Medicaid enrollees with asthma and/or chronic obstructive pulmonary disease.

METHOD

We created a retrospective cohort of 5608 Medicaid enrollees from ten counties in California with data from 2004 to 2010. We grouped the patients into two groups: those living within 500 m of goods movement corridors (ports and truck-permitted freeways), and control areas (away from the busy truck or car permitted highways). We created annual air pollution surfaces for nitrogen dioxide and assigned them to enrollees' home addresses. We used a quasi-experimental design with a difference-in-differences method to examine changes before and after the policy for cohort beneficiaries in the two groups.

RESULTS

The reductions in nitrogen dioxide exposures and emergency room visits were greater for enrollees in goods movement corridors than those in control areas in post-policy years. We found that the goods movement actions were associated with 14.8% (95% CI, -24.0% to -4.4%; P = 0.006) and 11.8% (95% CI, -21.2% to -1.2%; P = 0.030) greater reduction in emergency room visits for the beneficiaries with asthma and chronic obstructive pulmonary disease, respectively, in the third year after California's emission reduction plan.

CONCLUSION

These findings indicate remarkable health benefits via reduced emergency room visits from the significantly improved air quality due to public policy interventions for disadvantaged and susceptible populations.

Co-kriging with a low-cost sensor network to estimate spatial variation of brake and tire-wear metals and oxidative stress potential in Southern California

Due to regulations and technological advancements reducing tailpipe emissions, an increasing proportion of emissions arise from brake and tire wear particulate matter (PM). PM from these non-tailpipe sources contains heavy metals capable of generating oxidative stress in the lung. Although important, these particles remain understudied because the high cost of actively collecting filter samples. Improvements in electrical engineering, internet connectivity, and an increased public concern over air pollution have led to a proliferation of dense low-cost air sensor networks such as the PurpleAir monitors, which primarily measure unspeciated fine particulate matter (PM2.5). In this study, we model the concentrations of Ba, Zn, black carbon, reactive oxygen species concentration in the epithelial lining fluid, dithiothreitol (DTT) loss, and OH formation. We use a co-kriging approach, incorporating data from the PurpleAir network as a secondary predictor variable and a land-use regression (LUR) as an external drift. For most pollutant species, co-kriging models produced more accurate predictions than an LUR model, which did not incorporate data from the PurpleAir monitors. This finding suggests that low-cost sensors can enhance predictions of pollutants that are costly to measure extensively in the field.

Up in smoke: California's greenhouse gas reductions could be wiped out by 2020 wildfires

In this short communication, we estimate that California's wildfire carbon dioxide equivalent (CO₂e) emissions from 2020 are approximately two times higher than California's total greenhouse gas (GHG) emission reductions since 2003. Without considering future vegetation regrowth, CO₂e emissions from the 2020 wildfires could be the second most important source in the state above either industry or electrical power generation. Regrowth may partly of fully occur over a long period, but due to exigencies of the climate crisis most of the regrowth will not occur quickly enough to avert greater than 1.5 degrees of warming. Global monetized damages caused by CO₂e from in 2020 wildfire emissions amount to some $7.1 billion USD. Our analysis suggests that significant societal benefits could accrue from larger investments in improved forest management and stricter controls on new development in fire-prone areas at the wildland-urban interface.

Principles of risk decision-making

Risk management decisions in public health require consideration of a number of complex, often conflicting factors. The aim of this review was to propose a set of 10 fundamental principles to guide risk decision-making. Although each of these principles is sound in its own right, the guidance provided by different principles might lead the decision-maker in different directions. For example, where the precautionary principle advocates for preemptive risk management action under situations of scientific uncertainty and potentially catastrophic consequences, the principle of risk-based decision-making encourages decision-makers to focus on established and modifiable risks, where a return on the investment in risk management is all but guaranteed in the near term. To evaluate the applicability of the 10 principles in practice, one needs to consider 10 diverse risk issues of broad concern and explore which of these principles are most appropriate in different contexts. The 10 principles presented here afford substantive insight into the process of risk management decision-making, although decision-makers will ultimately need to exercise judgment in reaching appropriate risk decisions, accounting for all of the scientific and extra-scientific factors relevant to the risk decision at hand.

The influence of early-life residential exposure to different vegetation types and paved surfaces on early childhood development: A population-based birth cohort study

BACKGROUND

Growing evidence suggests that exposure to green space is associated with improved childhood health and development, but the influence of different green space types remains relatively unexplored. In the present study, we investigated the association between early-life residential exposure to vegetation and early childhood development and evaluated whether associations differed according to land cover types, including paved land.

METHODS

Early childhood development was assessed via kindergarten teacher-ratings on the Early Development Instrument (EDI) in a large population-based birth cohort (n = 27,539) in Metro Vancouver, Canada. The residential surrounding environment was characterized using a high spatial resolution land cover map that was linked to children by six-digit residential postal codes. Early-life residential exposure (from birth to time of EDI assessment, mean age = 5.6 years) was calculated as the mean of annual percentage values of different land cover classes (i.e., total vegetation, tree cover, grass cover, paved surfaces) within a 250 m buffer zone of postal code centroids. Multilevel models were used to analyze associations between respective land cover classes and early childhood development.

RESULTS

In adjusted models, one interquartile range increase in total vegetation percentage was associated with a 0.33 increase in total EDI score (95% CI: 0.21, 0.45). Similar positive associations were observed for tree cover (β-coefficient: 0.26, 95% CI: 0.15, 0.37) and grass cover (β-coefficient: 0.12, 95% CI: 0.02, 0.22), while negative associations were observed for paved surfaces (β-coefficient: -0.35, 95% CI: -0.47, -0.23).

CONCLUSIONS

Our findings indicate that increased early-life residential exposure to vegetation is positively associated with early childhood developmental outcomes, and that associations may be stronger for residential exposure to tree cover relative to grass cover. Our results further indicate that childhood development may be negatively associated with residential exposure to paved surfaces. These findings can inform urban planning to support early childhood developmental health.

Residential proximity to greenness and adverse birth outcomes in urban areas: Findings from a national Canadian population-based study

BACKGROUND

Over the last decade, several studies have reported that residential proximity to vegetation, or 'greenness', is associated with improved birth outcomes, including for term birth weight (TBW), preterm birth (PTB), and small for gestational age (SGA). However, there remain several uncertainties about these possible benefits including the role of air pollution, and the extent to they are influenced socioeconomic status.

METHODS

We addressed these gaps using a national population-based study of 2.2 million singleton live births in Canadian metropolitan areas between 1999 and 2008. Exposures to greenness, fine particulate matter (PM_2.5), and nitrogen dioxide (NO₂) were assigned to infants using the postal code of their mother's residence at the time of birth. The Normalized Difference Vegetation Index (NDVI) was used to characterize greenness, while estimates of ambient PM_2.5 and NO₂ were estimated using remote sensing, and a national land-use regression surface, respectively. Multivariable regression analysis was performed to describe associations between residential greenness and the birth outcomes. Stratified analyses explored whether these associations were modified by neighbourhood measures of socioeconomic status.

RESULTS

Mothers who lived in greener areas had a lower risk of low TBW, PTB, and SGA babies. These associations persisted after adjustment for ambient NO₂ and PM_2.5. Specifically, in fully adjusted models, an interquartile range (IQR = 0.16) increase in the NDVI within a residential buffer of 250 m yielded odds ratios of 0.93 (95% confidence interval (CI): 0.92, 0.94), 0.94 (95% CI: 0.92, 0.95), and 0.94 (95% CI: 0.93, 0.95) for the outcomes of PTB, low TBW, and SGA, respectively. Similarly, an IQR increase in greenness was associated with a 16.3 g (95% CI: 15.3, 17.4) increase in TBW. We found inverse associations between greenness and the occurrence of adverse birth outcomes regardless of the socioeconomic status of the neighbourhood.

INTERPRETATION

Our findings support the hypothesis that residential greenness contributes to healthier pregnancies, that these associations are independent from exposure to air pollution. , and that proximity to greenness benefits all mothers regardless of socioeconomic status.

Neighborhood environmental exposures and incidence of attention deficit/hyperactivity disorder: A population-based cohort study

BACKGROUND

Emerging studies have associated low greenspace and high air pollution exposure with risk of child attention deficit/hyperactivity disorder (ADHD). Population-based studies are limited, however, and joint effects are rarely evaluated. We investigated associations of ADHD incidence with greenspace, air pollution, and noise in a population-based birth cohort.

METHODS

We assembled a cohort from administrative data of births from 2000 to 2001 (N ∼ 37,000) in Metro Vancouver, Canada. ADHD was identified by hospital records, physician visits, and prescriptions. Cox proportional hazards models were applied to assess associations between environmental exposures and ADHD incidence adjusting for available covariates. Greenspace was estimated using vegetation percentage derived from linear spectral unmixing of Landsat imagery. Fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were estimated using land use regression models; noise was estimated using a deterministic model. Exposure period was from birth until the age of three. Joint effects of greenspace and PM_2.5 were analysed in two-exposure models and by categorizing values into quintiles.

RESULTS

During seven-year follow-up, 1217 ADHD cases were diagnosed. Greenspace was associated with lower incidence of ADHD (hazard ratio, HR: 0.90 [0.81-0.99] per interquartile range increment), while PM_2.5 was associated with increased incidence (HR: 1.11 [1.06-1.17] per interquartile range increment). NO₂ (HR: 1.01 [0.96, 1.07]) and noise (HR: 1.00 [0.95, 1.05]) were not associated with ADHD. There was a 50% decrease in the HR for ADHD in locations with the lowest PM_2.5 and highest greenspace exposure, compared to a 62% increase in HR in locations with the highest PM_2.5 and lowest greenspace exposure. Effects of PM_2.5 were attenuated by greenspace in two-exposure models.

CONCLUSIONS

We found evidence suggesting environmental inequalities where children living in greener neighborhoods with low air pollution had substantially lower risk of ADHD compared to those with higher air pollution and lower greenspace exposure.

Elemental composition of fine and coarse particles across the greater Los Angeles area: Spatial variation and contributing sources

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM_2.5) and coarse (PM_2.5-10) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM_2.5 and PM_2.5-10, while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM_2.5. The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6-4.6. Both PM_2.5 and PM_2.5-10 elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM_2.5 elemental concentrations, and three sources that explained 86% of the variance in the PM_2.5-10 elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM_2.5 was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM_2.5-10 with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area.

Air Quality in Africa: Public Health Implications

This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and (a) rapid urbanization, (b) social problems, (c) health impacts, (d) climate change, (e) policies, and (f) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.

Identifying impacts of air pollution on subacute asthma symptoms using digital medication sensors

BACKGROUND

Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities.

METHODS

We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique.

RESULTS

The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed.

CONCLUSIONS

Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach.

Assessing the association between lifetime exposure to greenspace and early childhood development and the mediation effects of air pollution and noise in Canada: a population-based birth cohort study

BACKGROUND

Exposure to greenspace is associated with improved childhood development, but the pathways behind this relationship are insufficiently understood. Therefore, we aimed to investigate the association between lifetime residential exposure to greenspace and early childhood development and evaluate the extent to which this association is mediated by reductions in traffic-related air pollution and noise.

METHODS

This population-based birth cohort study comprised singleton births in Metro Vancouver, BC, Canada, between April 1, 2000, and Dec 31, 2005. Children and mothers had to be registered with the mandatory provincial health insurance programme, Medical Services Plan, and have lived within the study area from the child's birth to the time of outcome assessment. Early childhood development was assessed via teacher ratings on the Early Development Instrument (EDI), and we used the total EDI score as the primary outcome variable. We estimated greenspace using percentage vegetation derived from spectral unmixing of annual Landsat satellite image composites. Lifetime residential exposure to greenspace was estimated as the mean of annual percentage vegetation values within 250 m of participants' residential postal codes. Multilevel modelling, adjusted for eight covariates, was used to investigate associations between greenspace exposure and EDI scores. We estimated the mediation effects of nitrogen dioxide (NO₂), fine particulate matter (PM_2·5), and noise levels using causal mediation analyses.

FINDINGS

Of the 37 745 children born in Metro Vancouver between April 1, 2000, and Dec 31, 2005, 27 372 were included in our final study sample. In the adjusted model, 1 IQR increase in percentage vegetation was associated with a 0·16 (95% CI 0·04-0·28; p=0·0073) increase in total EDI score, indicating small improvements in early childhood development. We estimated that 97·1% (95% CI 43·0-396·0), 29·5% (12·0-117·0), and 35·2% (17·9-139·0) of the association was mediated through reductions in NO₂, PM_2·5, and noise, respectively.

INTERPRETATION

Increased exposure to residential greenspace might improve childhood development by reducing the adverse developmental effects of traffic-related exposures, especially NO₂ air pollution. Our study supports the implementation of healthy urban planning and green infrastructure interventions.

FUNDING

Canadian Institutes of Health Research.

Ozone Exposure, Outdoor Physical Activity, and Incident Type 2 Diabetes in the SALSA Cohort of Older Mexican Americans

BACKGROUND

Type 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes.

OBJECTIVE

We studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association.

METHODS

We selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O3 exposure and diabetes.

RESULTS

In total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [hazard ratio (HR)=0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O3 exposure; also, this association was stronger among those physically active outdoors [HR=1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [HR=1.04 (95% CI: 0.90, 1.20), pinteraction=0.01].

CONCLUSIONS

Our findings suggest that ambient O3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.

A prospective cohort study of ambient air pollution exposure and risk of uterine leiomyomata

STUDY QUESTION

To what extent are ambient concentrations of particulate matter <2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) associated with risk of self-reported physician-diagnosed uterine leiomyomata (UL)?

SUMMARY ANSWER

In this large prospective cohort study of Black women, ambient concentrations of O3, but not PM2.5 or NO2, were associated with increased risk of UL.

WHAT IS KNOWN ALREADY

UL are benign tumors of the myometrium that are the leading cause of gynecologic inpatient care among reproductive-aged women. Black women are clinically diagnosed at two to three times the rate of white women and tend to exhibit earlier onset and more severe disease. Two epidemiologic studies have found positive associations between air pollution exposure and UL risk, but neither included large numbers of Black women.

STUDY DESIGN, SIZE, DURATION

We conducted a prospective cohort study of 21 998 premenopausal Black women residing in 56 US metropolitan areas from 1997 to 2011.

PARTICIPANTS/MATERIAL, SETTING, METHODS

Women reported incident UL diagnosis and method of confirmation (i.e. ultrasound, surgery) on biennial follow-up questionnaires. We modeled annual residential concentrations of PM2.5, NO2 and O3 throughout the study period. We used Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for a one-interquartile range (IQR) increase in air pollutant concentrations, adjusting for confounders and co-pollutants.

MAIN RESULTS AND THE ROLE OF CHANCE

During 196 685 person-years of follow-up, 6238 participants (28.4%) reported physician-diagnosed UL confirmed by ultrasound or surgery. Although concentrations of PM2.5 and NO2 were not appreciably associated with UL (HRs for a one-IQR increase: 1.01 (95% CI: 0.93, 1.10) and 1.05 (95% CI: 0.95, 1.16), respectively), O3 concentrations were associated with increased UL risk (HR for a one-IQR increase: 1.19, 95% CI: 1.07, 1.32). The association was stronger among women age <35 years (HR: 1.26, 95% CI: 0.98, 1.62) and parous women (HR: 1.28, 95% CI: 1.11, 1.48).

LIMITATIONS, REASONS FOR CAUTION

Our measurement of air pollution is subject to misclassification, as monitoring data are not equally spatially distributed and we did not account for time-activity patterns. Our outcome measure was based on self-report of a physician diagnosis, likely resulting in under-ascertainment of UL. Although we controlled for several individual- and neighborhood-level confounding variables, residual confounding remains a possibility.

WIDER IMPLICATIONS OF THE FINDINGS

Inequitable burden of air pollution exposure has important implications for racial health disparities, and may be related to disparities in UL. Our results emphasize the need for additional research focused on environmental causes of UL.

STUDY FUNDING/COMPETING INTEREST(S)

This research was funded by the National Cancer Institute (U01-CAA164974) and the National Institute of Environmental Health Sciences (R01-ES019573). L.A.W. is a fibroid consultant for AbbVie, Inc. and accepts in-kind donations from Swiss Precision Diagnostics, Sandstone Diagnostics, FertilityFriend.com and Kindara.com for primary data collection in Pregnancy Study Online (PRESTO). M.J. declares consultancy fees from the Health Effects Institute (as a member of the review committee). The remaining authors declare they have no actual or potential competing financial interests.

TRIAL REGISTRATION NUMBER

N/A.

Does exposure to air pollution increase the risk of acute care in young children with asthma? An Ontario, Canada study

Owing to their greater outdoor activity and ongoing lung development, children are particularly vulnerable to the harmful effects of exposure to fine particulate matter (PM_2.5)_. However, the effects of PM_2.5 components are poorly understood. This study aimed to use a longitudinal birth cohort of children with physician-diagnosed incident asthma to investigate the effect of PM_2.5 components at birth on morbidity measured by health services utilization. Of 1277 Toronto Child Health Evaluation Questionnaire (T-CHEQ) participants, the study population included 362 children diagnosed with asthma who were followed for a mean of 13 years from birth until March 31, 2016, or loss-to-follow-up. Concentrations of PM_2.5 and its components were assigned based on participants' postal codes at birth. Study outcomes included counts of asthma, asthma-related, and all-cause health services use. Poisson regression in single-, two-, and multi-pollutant models was used to estimate rate ratios (RR) per interquartile range (IQR) increase of exposures. Covariates were included in all models to further adjust for potential confounding. The adjusted RR for sulfate (SO₄) and all-cause hospitalizations was statistically significant with RR = 2.23 (95% confidence interval [CI]: 1.25-3.96) in a multi-pollutant model with nitrogen dioxide (NO₂) and ozone (O₃). In multi-pollutant models with oxidants, the adjusted RRs for SO₄ of all-cause hospitalizations and emergency department (ED) visits were also statistically significant with RR = 2.31 (95% CI: 1.32-4.03) and RR = 1.39 (95% CI: 1.02-1.90), respectively. While unadjusted single-pollutant RRs for asthma-specific and asthma-related health services use with the SO₄ component of PM_2.5 were above one, none were statistically significant. This study found significant associations with exposure to SO₄ in PM_2.5 and all-cause acute care, chiefly for hospitalizations, in children with asthma.

Long-term exposure to iron and copper in fine particulate air pollution and their combined impact on reactive oxygen species concentration in lung fluid: a population-based cohort study of cardiovascular disease incidence and mortality in Toronto, Canada

BACKGROUND

Exposure to fine particulate (PM2.5) air pollution is associated with increased cardiovascular disease (CVD), but less is known about its specific components, such as metals originating from non-tailpipe emissions. We investigated the associations of long-term exposure to metal components [iron (Fe) and copper (Cu)] in PM2.5 with CVD incidence.

METHODS

We conducted a population-based cohort study in Toronto, Canada. Exposures to Fe and Cu in PM2.5 and their combined impact on the concentration of reactive oxygen species (ROS) in lung fluid were estimated using land use regression models. Incidence of acute myocardial infarction (AMI), congestive heart failure (CHF) and CVD death was ascertained using health administrative datasets. We used mixed-effects Cox regression models to examine the associations between the exposures and health outcomes. A series of sensitivity analyses were conducted, including indirect adjustment for individual-level cardiovascular risk factors (e.g. smoking), and adjustment for PM2.5 and nitrogen dioxide (NO2).

RESULTS

In single-pollutant models, we found positive associations between the three exposures and all three outcomes, with the strongest associations detected for the estimated ROS. The associations of AMI and CHF were sensitive to indirect adjustment, but remained robust for CVD death in all sensitivity analyses. In multi-pollutant models, the associations of the three exposures generally remained unaltered. Interestingly, adjustment for ROS did not substantially change the associations between PM2.5 and CVD, but attenuated the associations of NO2.

CONCLUSIONS

Long-term exposure to Fe and Cu in PM2.5 and their combined impact on ROS were consistently associated with increased CVD death.

Traffic-Related Air Pollution and Incident Dementia: Direct and Indirect Pathways Through Metabolic Dysfunction

BACKGROUND

Ambient air pollution exposure has been associated with dementia. Additionally, epidemiologic evidence supports associations between air pollution and diabetes as well as diabetes and dementia. Thus, an indirect pathway between air pollution and dementia may exist through metabolic dysfunction.

OBJECTIVE

To investigate whether local traffic-related air pollution (TRAP) influences incident dementia and cognitive impairment, non-dementia (CIND) in a cohort of older Mexican Americans. We also assess how much of this estimated effect might be mediated through type 2 diabetes (T2DM).

METHODS

In a 10-year, prospective study of Latinos (n = 1,564), we generated TRAP-NOx as a surrogate for pollution from local traffic sources at participants' residences during the year prior to enrollment. We used Cox proportional hazards modeling and mediation analysis to estimate the effects of TRAP-NOx on dementia and/or CIND and indirect pathways operating through T2DM.

RESULTS

Higher TRAP-NOx was associated with incident dementia (HR = 1.55 for the highest versus lower tertiles, 95% CI = 1.04, 2.55). Higher TRAP-NOx was also associated with T2DM (OR = 1.62, 95% CI = 1.27, 2.05); furthermore, T2DM was associated with dementia (HR = 1.94, 95% CI = 1.42, 2.66). Mediation analysis indicated that 20% of the estimated effect of TRAP-NOx on dementia/CIND was mediated through T2DM.

CONCLUSION

Our results suggest that exposure to local traffic-related air pollution is associated with incident dementia. We also estimated that 20% of this effect is mediated through T2DM. Thus, ambient air pollution might affect brain health via direct damage as well as through indirect pathways related to diabetes and metabolic dysfunction.

Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project

BACKGROUND

Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity.

METHODS

Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables.

RESULTS

We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in three of four cities, aside from the coastal city of Barcelona. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). Significant linear effects were found for higher levels of surrounding greenness in Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET.

CONCLUSION

Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across three of four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design.

The association between natural environments and childhood mental health and development: A systematic review and assessment of different exposure measurements

BACKGROUND

Several studies have assessed the relationship between exposure to natural environments (NEs) and childhood mental health and development. In most cases, a positive association has been found, but results are inconsistent, and the strength of association is unclear. This inconsistency may reflect the heterogeneity in measurements used to assess NE.

OBJECTIVES

This systematic review aims to identify the most common NE metrics used in childhood mental health and development research. Our second aim is to identify the metrics that are most consistently associated with health and assess the relative strength of association depending on type of NE exposure measurement, in terms of metric used (i.e., measurement technique, such as remote sensing), but also rate (i.e., spatial and temporal exposure).

METHODS

We used the PRISMA protocol to identify eligible studies, following a set of pre-defined inclusion criteria based on the PECOS strategy. A number of keywords were used for retrieving relevant articles from Medline, Embase, PsychINFO, and Web of Science databases between January 2000-November 2020. From these, we extracted data on type of NE measurement and relative association to a number of indicators of childhood mental health and development. We conducted a systematic assessment of quality and risk of bias in the included articles to evaluate the level of evidence. Case studies and qualitative studies were excluded.

RESULTS

After screening of title (283 studies included), abstract, and full article, 45 studies were included in our review. A majority of which were conducted in North America and Europe (n = 36; 80%). The majority of studies used land use or land covers (LULC, n = 24; 35%) to determine exposures to NEs. Other metrics included the normalized difference vegetation index (NDVI), expert measures (e.g., surveys of data collection done by experts), surveys (e.g., self-reported assessments), and use of NE (e.g., measures of a participant's use of NE such as through GPS tracts or parent reports). Rate was most commonly determined by buffer zones around residential addresses or postal codes. The most consistent association to health outcomes was found for buffers of 100 m, 250 m, 500 m, and within polygons boundaries (e.g., census tracts). Six health categories, academic achievement, prevalence of doctor diagnosed disorders, emotional and behavioral functioning, well-being, social functioning, and cognitive skills, were created post hoc. We found sufficient evidence between NDVI (Landsat) and emotional and behavioral well-being. Additionally, we found limited evidence between LULC datasets and academic achievement; use of NE, parent/guardian reported greenness, and expert measures of greenness and emotional and behavioral functioning; and use of NE and social functioning.

DISCUSSION

This review demonstrates that several NE measurements must be evaluated further before sufficient evidence for a potential association between distinct NE exposure metrics and childhood mental health and development can be established. Further, we suggest increased coordination between research efforts, for example, by replication of studies and comparing different NE measurements systematically, so that effect sizes can be confirmed for various health outcomes. Finally, we recommend implementing research designs that assess underlying pathways of nature-health relations and utilize measurement techniques that adequately assess exposure, access, use, and perception of NEs in order to contribute to a better understanding of health impacts of surrounding natural environments.

Improvements in Air Quality and Health Outcomes Among California Medicaid Enrollees Due to Goods Movement Actions

INTRODUCTION

In 2006, the California Air Resources Board (CARB) and local air quality management districts implemented an Emission Reduction Plan for Ports and Goods Movement program (referred to hereinafter as GM policy actions) (CARB 2006). The GM policy actions comprise approximately 200 actions with an estimated investment value of $6 to $10 billion. These actions targeted the major sources and polluters related to goods movements, such as highways; ports and railyard trucks; ship fuel and shore power; cargo equipment; and locomotives. These actions aimed to reduce total statewide domestic GM emissions to 2001 levels or lower by the year 2010; to reduce the statewide diesel particulate matter (DPM) health risk from GM by 85% by the year 2020; and to reduce the nitrogen oxides (NOx) emissions from international GM in the South Coast Air Basin by 30% from projected 2015 levels and 50% from projected 2020 levels. The years 2006 and 2007 marked an important milestone in starting to regulate GM polluters and adopting stricter standards for traffic-related air pollution.

This project aimed to examine the impact of the GM policy actions on reductions in ambient air pollution and subsequent improvements in health outcomes of Medi-Cal fee-for-service (FFS) beneficiaries with chronic conditions in 10 counties in California. Specifically, we examined whether the GM policy actions reduced air pollution near GMC corridors more than in control areas. We subsequently assessed whether there were greater decreases in emergency room (ER) visits and hospitalizations for enrollees with chronic conditions who lived in the GM corridors (GMCs) than for those who lived in other areas.

METHODS

The study used a quasi-experimental design. We defined areas within 500 m of truck-permitted freeways and ports as GMCs. We further defined non-goods movement corridors (NGMCs) as locations within 500 m of truck-prohibited freeways or 300 m of a connecting roadway, and areas out of GMCs and NGMCs as controls (CTRLs). We defined years 2004-2007 as the pre-policy period and years 2008-2010 as the post-policy period. We developed linear mixed-effects land use regression models and created annual air pollution surfaces for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California for years 2004-2010 at a spatial resolution of 30 m, then assigned them to enrollees' home addresses.

We used a retrospective cohort of 23,000 California Medicaid (Medi-Cal) FFS adult beneficiaries living in 10 California counties with six years of data (September 1, 2004, to August 31, 2010). Cohort beneficiaries had at least one of four chronic conditions, including asthma, chronic obstructive pulmonary disease (COPD), diabetes, and heart disease.

We used a difference-in-differences (DiD) model to assess whether air pollutant concentration and health care utilization (ER visits and hospitalizations) for cohort beneficiaries declined more for those living in intervention corridors (GMCs, NGMCs) than those living in CTRLs. All the models controlled for age, sex, language spoken, race/ethnicity, number of comorbidities in baseline years, county, time-varying health indicator variables, and several neighborhood variables.

To facilitate interpretation, we calculated the DiD estimates in each of the three years after the policy intervention. The DiD was used to assess the causal impact of regulatory policy on reductions of air pollution, as well as for the improvements in health outcomes.

We explored whether improvements in health outcomes were due to the air pollution reduction by using a multi- level mediation model, in which the effect of GM actions on health outcomes was mediated through the effect of actual air pollution reductions in the post-policy years. We used the Generalized Structural Equation Models for the estimation and combined the effects of NO2 and PM2.5 in the model. To further verify the causal inferences of the GM actions on reductions of exposures and improvements in health outcomes, we performed sensitivity analyses with propensity score weighting.

RESULTS

We observed statistically significant reductions in pollutant NO2 and PM2.5 concentrations for enrollees in all 10 counties. The enrollees in GMCs experienced greater reductions in NO2 and PM2.5 from the pre- to the post-policy periods than those in CTRLs. Greater reductions were also observed among beneficiaries living in NGMCs versus those in CTRLs, but those reductions were smaller than among beneficiaries living in GMCs. For O3 concentrations, an opposite trend was observed.

Furthermore, we observed significantly greater reductions in ER visits for patients with asthma and COPD living in GMCs than those in CTRLS in the post-policy years. For example, we saw in the DiD modeling results there were 170 fewer ER visits for 1,000 beneficiaries with asthma per year in GMCs if the regionwide trend in the CTRL group was considered not related to the GM policy. Similarly, among the beneficiaries with COPD, there were 180 fewer ER visits per 1,000 patients estimated in the GMCs for the third year after the implementation of the policy.

We also observed greater reductions in ER visits among those with asthma, when comparing NGMCs with CTRLs, but reductions were smaller than comparisons between GMCs and CTRLs. The ER visits for those with COPD, diabetes, and the total sample in NGMCs also had downward trends in the post-policy year in comparison with those in CTRLs but the differences were not statistically significant; similar phenomena were also observed for the ER visits among those with diabetes and heart diseases and in the total sample when GMCs versus CTRLs and GMCs versus NGMCs were compared. Although hospitalizations also decreased more in GMCs than in NGMCs and more in NGMCs than in CTRLs in the post-policy period, results were not statistically significant.

Using the mediation models, we observed 0.129 more reductions in the expected number of ER visits among individuals with asthma for a composite reduction in one unit NO2 and one unit PM2.5 (DiD = -0.129, P < 0.05) from the pre-policy years to the post-policy years. The reductions in NO2 and PM2.5 due to policy change estimated by the mediation model are essentially the same as shown in the respective DiD models. Mediation analyses suggested that the effects of GM policy interventions on health improvements were largely due to exposure reductions. Finally, sensitivity analyses with propensity scores produced similar DiD results.

CONCLUSIONS

This project has produced empirical evidence that air pollution control actions reduced pollution exposures among disadvantaged and susceptible populations. More importantly, our findings suggest that the reductions in air pollution led to health outcome improvements among low-income people with chronic conditions. Our investigation also contributed to scientific methods for assessing the health effects of long-term, large-scale, and complex regulatory actions with routinely collected pollutants and medical claims data. Therefore, the results strongly support both short-term and long-term efforts to improve air quality for all members of society and future studies on the impact of air pollution control policies.

A Population-Based Cohort Study of Respiratory Disease and Long-Term Exposure to Iron and Copper in Fine Particulate Air Pollution and Their Combined Impact on Reactive Oxygen Species Generation in Human Lungs

Metal components in fine particulate matter (PM_2.5) from nontailpipe emissions may play an important role in underlying the adverse respiratory effects of PM_2.5. We investigated the associations between long-term exposure to iron (Fe) and copper (Cu) in PM_2.5 and their combined impact on reactive oxygen species (ROS) generation in human lungs, and the incidence of asthma, chronic obstructive pulmonary disease (COPD), COPD mortality, pneumonia mortality, and respiratory mortality. We conducted a population-based cohort study of ∼0.8 million adults in Toronto, Canada. Land-use regression models were used to estimate the concentrations of Fe, Cu, and ROS. Outcomes were ascertained using validated health administrative databases. We found positive associations between long-term exposure to Fe, Cu, and ROS and the risks of all five respiratory outcomes. The associations were more robust for COPD, pneumonia mortality, and respiratory mortality than for asthma incidence and COPD mortality. Stronger associations were observed for ROS than for either Fe or Cu. In two-pollutant models, adjustment for nitrogen dioxide somewhat attenuated the associations while adjustment for PM_2.5 had little influence. Long-term exposure to Fe and Cu in PM_2.5 and estimated ROS concentration in lung fluid was associated with increased incidence of respiratory diseases, suggesting the adverse respiratory effects of nontailpipe emissions.

Cardiopulmonary Impact of Particulate Air Pollution in High-Risk Populations: JACC State-of-the-Art Review

Fine particulate air pollution <2.5 μm in diameter (PM2.5) is a major environmental threat to global public health. Multiple national and international medical and governmental organizations have recognized PM2.5 as a risk factor for cardiopulmonary diseases. A growing body of evidence indicates that several personal-level approaches that reduce exposures to PM2.5 can lead to improvements in health endpoints. Novel and forward-thinking strategies including randomized clinical trials are important to validate key aspects (e.g., feasibility, efficacy, health benefits, risks, burden, costs) of the various protective interventions, in particular among real-world susceptible and vulnerable populations. This paper summarizes the discussions and conclusions from an expert workshop, Reducing the Cardiopulmonary Impact of Particulate Matter Air Pollution in High Risk Populations, held on May 29 to 30, 2019, and convened by the National Institutes of Health, the U.S. Environmental Protection Agency, and the U.S. Centers for Disease Control and Prevention.

Metabolic dysfunction modifies the influence of traffic-related air pollution and noise exposure on late-life dementia and cognitive impairment: A cohort study of older Mexican-Americans

Supplemental Digital Content is available in the text.

Cognitive impairment has been linked to traffic-related air pollution and noise exposure as well as to metabolic syndrome or some of its individual components. Here, we investigate whether the presence of metabolic dysfunction modifies associations between air pollution or noise exposures and incident dementia or cognitive impairment without dementia (CIND).

Metabolic dysfunction modifies the influence of traffic-related air pollution and noise exposure on late-life dementia and cognitive impairment: A cohort study of older Mexican-Americans

Cognitive impairment has been linked to traffic-related air pollution and noise exposure as well as to metabolic syndrome or some of its individual components. Here, we investigate whether the presence of metabolic dysfunction modifies associations between air pollution or noise exposures and incident dementia or cognitive impairment without dementia (CIND).

METHODS

For 1,612 elderly Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) followed for up to 10 years, we estimated residential-based local traffic-related exposures relying on the California Line Source Dispersion Model version 4 (CALINE4) for nitrogen oxides (NOx) and the SoundPLAN software package (Version 8.0; NAVCON, Fullerton, CA) that implements the Federal Highway Administration Traffic Noise Model (TNM) for noise, respectively. We used Cox proportional hazard models to estimate the joint effects of NOx or noise exposures and obesity, hyperglycemia, or low high-density lipoprotein (HDL) cholesterol.

RESULTS

The risk of developing dementia/CIND among participants with hyperglycemia who also were exposed to high levels of NOx (≥3.44 parts per billion [ppb] [75th percentile]) or noise (≥65 dB) was 2.4 (1.4, 4.0) and 2.2 (1.7, 3.9), respectively. For participants with low HDL-cholesterol, the estimated hazard ratios for dementia/CIND were 2.5 (1.4, 4.3) and 1.8 (1.0, 3.0) for those also exposed to high levels of NOx (≥3.44 ppb) or noise (≥65 dB), respectively, compared with those without metabolic dysfunction exposed to low traffic-related air pollution or noise levels.

CONCLUSIONS

Exposure to traffic-related air pollution or noise most strongly increases the risk of dementia/CIND among older Mexican-Americans living in California who also exhibit hyperglycemia or low HDL-cholesterol.

Predicting differential improvements in annual pollutant concentrations and exposures for regulatory policy assessment

Over the past decade, researchers and policy-makers have become increasingly interested in regulatory and policy interventions to reduce air pollution concentrations and improve human health. Studies have typically relied on relatively sparse environmental monitoring data that lack the spatial resolution to assess small-area improvements in air quality and health. Few studies have integrated multiple types of measures of an air pollutant into one single modeling framework that combines spatially- and temporally-rich monitoring data. In this paper, we investigated the differential effects of California emissions reduction plan on reducing air pollution between those living in the goods movement corridors (GMC) that are within 500 m of major highways that serve as truck routes to those farther away or adjacent to routes that prohibit trucks. A mixed effects Deletion/Substitution/Addition (D/S/A) machine learning algorithm was developed to model annual pollutant concentrations of nitrogen dioxide (NO₂) by taking repeated measures into consideration and by integrating multiple types of NO₂ measurements, including those through government regulatory and research-oriented saturation monitoring into a single modeling framework. Difference-in-difference analysis was conducted to identify whether those living in GMC demonstrated statistically larger reductions in air pollution exposure. The mixed effects D/S/A machine learning modeling result indicated that GMC had 2 ppb greater reductions in NO₂ concentrations from pre- to post-policy period than far away areas. The difference-in-difference analysis demonstrated that the subjects living in GMC experienced statistically significant greater reductions in NO₂ exposure than those living in the far away areas. This study contributes to scientific knowledge by providing empirical evidence that improvements in air quality via the emissions reductions plan policies impacted traffic-related air pollutant concentrations and associated exposures most among low-income Californians with chronic conditions living in GMC. The identified differences in pollutant reductions across different location domains may be applicable to other states or other countries if similar policies are enacted.

Exposure to Road Traffic Noise and Incidence of Acute Myocardial Infarction and Congestive Heart Failure: A Population-Based Cohort Study in Toronto, Canada

BACKGROUND

Epidemiological evidence for the association between traffic-related noise and the incidence of major cardiovascular events such as acute myocardial infarction (AMI) and congestive heart failure (CHF) is inconclusive, especially in North America.

OBJECTIVES

We evaluated the associations between long-term exposure to road traffic noise and the incidence of AMI and CHF.

METHODS

Our study population comprised ∼1 million people 30-100 years of age who lived in Toronto, Canada, from 2001 to 2015 and were free of AMI (referred to as the AMI cohort) or CHF (the CHF cohort) at baseline. Outcomes were ascertained from health administrative databases using validated algorithms. Annual average noise levels were estimated as the A-weighted equivalent sound pressure level over the 24-h period (LAeq24) and during nighttime (LAeqNight), respectively, using propagation modeling, and assigned to participants' annual six-digit postal code addresses during follow-up. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for incident AMI and CHF in relation to LAeq24 and LAeqNight using random-effects Cox proportional hazards models adjusting for individual- and census tract-level covariates, including traffic-related air pollutants [e.g., ultrafine particles (UFPs) and nitrogen dioxide].

RESULTS

During follow-up, there were 37,441 AMI incident cases and 95,138 CHF incident cases. Each interquartile range change in LAeq24 was associated with an increased risk of incident AMI (HR=1.07; 95% CI: 1.06, 1.08) and CHF (HR=1.07; 95% CI: 1.06, 1.09). Similarly, LAeqNight was associated with incident AMI (HR=1.07; 95% CI: 1.05, 1.08) and CHF (HR=1.06; 95% CI: 1.05, 1.07). These results were robust to various sensitivity analyses and remained elevated after controlling for long-term exposure to UFPs and nitrogen dioxide. We found near-linear relationships between noise and the incidence of AMI and CHF with no evidence of threshold values.

CONCLUSION

In this large cohort study in Toronto, Canada, chronic exposure to road traffic noise was associated with elevated risks for AMI and CHF incidence. https://doi.org/10.1289/EHP5809.

PM2.5 air pollution and cause-specific cardiovascular disease mortality

BACKGROUND

Ambient air pollution is a modifiable risk factor for cardiovascular disease, yet uncertainty remains about the size of risks at lower levels of fine particulate matter (PM2.5) exposure which now occur in the USA and elsewhere.

METHODS

We investigated the relationship of ambient PM2.5 exposure with cause-specific cardiovascular disease mortality in 565 477 men and women, aged 50 to 71 years, from the National Institutes of Health-AARP Diet and Health Study. During 7.5 x 106 person-years of follow up, 41 286 cardiovascular disease deaths, including 23 328 ischaemic heart disease (IHD) and 5894 stroke deaths, were ascertained using the National Death Index. PM2.5 was estimated using a hybrid land use regression (LUR) geostatistical model. Multivariate Cox regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CI).

RESULTS

Each increase of 10  μg/m3 PM2.5 (overall range, 2.9-28.0  μg/m3) was associated, in fully adjusted models, with a 16% increase in mortality from ischaemic heart disease [hazard ratio (HR) 1.16; 95% CI 1.09-1.22] and a 14% increase in mortality from stroke (HR 1.14; CI 1.02-1.27). Compared with PM2.5 exposure <8  μg/m3 (referent), risks for CVD were increased in relation to PM2.5 exposures in the range of 8-12  μg/m3 (CVD: HR 1.04; 95% CI 1.00-1.08), in the range 12-20  μg/m3 (CVD: HR 1.08; 95% CI 1.03-1.13) and in the range 20+ μg/m3 (CVD: HR 1.19; 95% CI 1.10-1.28). Results were robust to alternative approaches to PM2.5 exposure assessment and statistical analysis.

CONCLUSIONS

Long-term exposure to fine particulate air pollution is associated with ischaemic heart disease and stroke mortality, with excess risks occurring in the range of and below the present US long-term standard for ambient exposure to PM2.5 (12  µg/m3), indicating the need for continued improvements in air pollution abatement for CVD prevention.

Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA

Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015-2018) on a network-wide basis. Annual mean levels of PM10 did not differ statistically from regulatory annual means, but did for PM2.5 for two out of the 4 years. R2s from ordinary least square regression results ranged from 0.16 to 0.67 for PM10, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.

The Association of Trail Features With Self-Report Trail Use by Neighborhood Residents

BACKGROUND

Urban trails are a useful resource to promote physical activity. This study identified features of urban trails that correlated with trail use.

METHODS

Multiuse urban trails were selected in Chicago, Dallas, and Los Angeles. An audit of each trail was completed using the Systematic Pedestrian and Cyclist Environmental Scan for Trails instrument, identifying built environmental features. A self-report of trail use was obtained from trailside residents (N = 331) living within 1 mile of each trail. Univariate and multivariate Poisson regressions controlled for trail time from home and motivation for physical activity.

RESULTS

Positive associations with the past month's hours on the trail were observed for the presence of distance signs, vegetation height, vegetation maintenance, and trail crowding, and a negative association was observed for the presence of crossings on the trail. Positive associations with dichotomous trail use were observed for the presence of distance signs, vegetation height, and vegetation maintenance, and a negative association was observed for the presence of crossings on the trail.

CONCLUSIONS

These correlates should be confirmed in other studies and, if supported, should be considered in the promotion and design of urban trails.

Association Between Road Traffic Noise and Incidence of Diabetes Mellitus and Hypertension in Toronto, Canada: A Population-Based Cohort Study

Background Exposure to road traffic noise has been linked to cardiometabolic complications, such as elevated blood pressure and glucose dysregulation. However, epidemiologic evidence linking road traffic noise to diabetes mellitus and hypertension remains scarce. We examined associations between road traffic noise and the incidence of diabetes mellitus and hypertension in Toronto, Canada. Methods and Results Using the Ontario Population Health and Environment Cohort, we conducted a retrospective, population-based cohort study of long-term residents of Toronto, aged 35 to 100 years, who were registered for provincial publicly funded health insurance, and were without a history of hypertension (n=701 174) or diabetes mellitus (n=914 607). Road traffic noise exposure levels were assessed by the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day and the equivalent continuous A-weighted sound pressure level for the night (11 pm-7am). Noise exposures were assigned to subjects according to their annual residential postal codes during the 15-year follow-up. We used random-effect Cox proportional hazards models adjusting for personal and area-level characteristics. From 2001 to 2015, each interquartile range increase in the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day (10.0 dBA) was associated with an 8% increase in incident diabetes mellitus (95% CI, 1.07-1.09) and a 2% increase in hypertension (95% CI, 1.01-1.03). We obtained similar estimates with the equivalent continuous A-weighted sound pressure level for the night (11 pm-7am). These results were robust to all sensitivity analyses conducted, including further adjusting for traffic-related air pollutants (ultrafine particles and nitrogen dioxide). For both hypertension and diabetes mellitus, we observed stronger associations with the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day among women and younger adults (aged <60 years). Conclusions Long-term exposure to road traffic noise was associated with an increased incidence of diabetes mellitus and hypertension in Toronto.

Early life exposure to air pollution and incidence of childhood asthma, allergic rhinitis and eczema

Rationale

There is growing evidence that air pollution may contribute to the development of childhood asthma and other allergic diseases. In this follow-up of the Toronto Child Health Evaluation Questionnaire (T-CHEQ) study, we examined associations between early life exposures to air pollution and incidence of asthma, allergic rhinitis and eczema from birth through adolescence.

Methods

1286 T-CHEQ participants were followed from birth until outcome (March 31, 2016) or loss to follow-up, with a mean of 17 years of follow-up. Concentrations of nitrogen dioxide (NO₂), ozone (O₃) and particulate matter with a 50% cut-off aerodynamic diameter of 2.5 µm (PM_2.5) from January 1, 1999 to December 31, 2012 were assigned to participants based on their postal codes at birth using ground observations, chemical/meteorological models, remote sensing and land-use regression models. Study outcomes included incidence of physician-diagnosed asthma, allergic rhinitis and eczema. Cox proportional hazard regression models were used to estimate hazard ratios per interquartile range of exposures and outcomes, adjusting for potential confounders.

Results

Hazard ratios of 1.17 (95% CI 1.05–1.31) for asthma and 1.07 (95% CI 0.99–1.15) for eczema were observed for total oxidants (O₃ and NO₂) at birth. No significant increase in risk was found for PM_2.5.

Conclusions

Exposures to oxidant air pollutants (O₃ and NO₂) but not PM_2.5 were associated with an increased risk of incident asthma and eczema in children. This suggests that improving air quality may contribute to the prevention of asthma and other allergic disease in childhood and adolescence.

This study found that exposure to total oxidants at birth increased the risk of developing asthma by 17% and eczema by 7%. Adverse impacts of exposure to air pollutants, particularly ozone and nitrogen dioxide, may have their origins in early life.http://bit.ly/33PClYN

Momentary mood response to natural outdoor environments in four European cities

Exposure to natural outdoor environments (NOE) has been shown in population-level studies to reduce anxiety and psychological distress. This study investigated how exposure to one's everyday natural outdoor environments over one week influenced mood among residents of four European cities including Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands) and Kaunas (Lithuania). Participants (n = 368) wore a smartphone equipped with software applications to track location and mood (using mobile ecological momentary assessment (EMA) software), for seven consecutive days. We estimated random-effects ordered logistic regression models to examine the association between mood (positive and negative affect), and exposure to green space, represented by two binary variables indicating exposure versus no exposure to NOE using GPS tracking and satellite and aerial imagery, 10 and 30 min prior to participants' completing the EMA. Models were adjusted for home city, day of the week, hour of the day, EMA survey type, residential NOE exposure, and sex, age, education level, mental health status and neighbourhood socioeconomic status. In addition, we tested for heterogeneity of effect by city, sex, age, residential NOE exposure and mental health status. Within 10 min of NOE exposure, compared to non-exposure, we found that overall there was a positive relationship with positive affect (OR: 1.39, 95% CI: 1.06, 1.81) of EMA surveys, and non-significant negative association with negative affect (OR: 0.80, 95% CI: 0.58, 1.10). When stratifying, associations were consistently found for Stoke-on-Trent inhabitants and men, while findings by age group were inconsistent. Weaker and less consistent associations were found for exposure 30 min prior to EMA. Our findings support increasing evidence of psychological and mental health benefits of exposure to natural outdoor environments, especially among urban populations such as those included in our study.

Air pollution, noise exposure, and metabolic syndrome - A cohort study in elderly Mexican-Americans in Sacramento area

BACKGROUND

Previous studies suggested that air pollutants may increase the incidence of metabolic syndrome, but the potential impact from traffic sources is not well-understood. This study aimed to investigate associations between traffic-related nitrogen oxides (NOx) or noise pollution and risk of incident metabolic syndrome and its components in an elderly Mexican-American population.

METHODS

A total of 1,554 Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) cohort were followed from 1998 to 2007. We used anthropometric measures and biomarkers to define metabolic syndrome according to the recommendations of the Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP ATP III). Based on participants' residential addresses at baseline, estimates of local traffic-related NOx were generated using the California Line Source Dispersion Model version 4 (CALINE4), and of noise employing the SoundPLAN software package. We used Cox regression models with calendar time as the underlying time scale to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of air pollution or noise with metabolic syndrome or its components.

RESULTS

Each per unit increase of traffic-related NOx (2.29 parts per billion (ppb)) was associated with a 15% (HR = 1.15, 95% CI: 1.04-1.28) lower level of high-density lipoprotein cholesterol (HDL-cholesterol), and each 11.6 decibels (dB) increase in noise increased the risk of developing metabolic syndrome by 17% (HR = 1.17, 95% CI: 1.01-1.35).

CONCLUSION

Policies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

Mortality burdens in California due to air pollution attributable to local and nonlocal emissions

Limited research has been conducted on the contributions of local and nonlocal emission sources to ambient fine particulate matter (PM_2.5) and ozone (O₃) and their associated mortality. In this study, we estimated the total mortality resulting from long-term PM_2.5 and O₃ exposures in California in 2012 using multiple concentration response functions (CRFs) and attributed the estimated mortality to different emission groups. The point estimates of PM_2.5-associated mortality in California ranged from 12,700 to 26,700, of which 53% were attributable to in-state anthropogenic emissions. Based on new epidemiological evidence, we estimated that O₃ could be associated with up to 13,700 deaths from diseases of both the respiratory and cardiovascular systems in California. In addition, 75% of the ambient O₃ in California was due to distant emissions outside the western United States, leading to 92% of the O₃-associated mortality. Overall, distant emissions lead to greater mortality burdens of air pollution in California than local anthropogenic emissions.