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BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) have been linked to adverse birth outcomes that have been reported to be induced by oxidative stress, but few epidemiological studies to date have evaluated associations between urinary PAH metabolites and oxidative stress biomarkers in pregnancy and identified critical periods for these outcomes and PAH exposures in pregnancy. METHODS: A cohort of pregnant women was recruited early in pregnancy from antenatal clinics at the University of California Los Angeles during 2016-2019. We collected urine samples up to three times during pregnancy in a total of 159 women enrolled in the cohort. A total of 7 PAH metabolites and 2 oxidative stress biomarkers [malondialdehyde (MDA), 8-hydroxy-2-deoxyguanosine (8-OHdG)] were measured in all available urine samples. 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. Furthermore, we used linear mixed models with a random intercept for participant to estimate the associations between PAH metabolite and oxidative stress biomarker concentrations across multiple time points in pregnancy. 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. A doubling of each urinary PAH metabolite concentration increased MDA concentrations by 5.8-41.1% and 8-OHdG concentrations by 13.8-49.7%. Linear mixed model results were consistent with those from linear regression models for each gestational sampling period. CONCLUSION: Urinary PAH metabolites are associated with increases in oxidative stress biomarkers during pregnancy, especially in early and late pregnancy.

California faces several serious direct and indirect climate exposures that can adversely affect public health, some of which are already occurring. The public health burden now and in the future will depend on atmospheric greenhouse gas concentrations, underlying population vulnerabilities, and adaptation efforts. Here, we present a structured review of recent literature to examine the leading climate risks to public health in California, including extreme heat, extreme precipitation, wildfires, air pollution, and infectious diseases. Comparisons among different climate-health pathways are difficult due to inconsistencies in study design regarding spatial and temporal scales and health outcomes examined. We find, however, that the current public health burden likely affects thousands of Californians each year, depending on the exposure pathway and health outcome. Further, while more evidence exists for direct and indirect proximal health effects that are the focus of this review, distal pathways (e.g., impacts of drought on nutrition) are more uncertain but could add to this burden. We find that climate adaptation measures can provide significant health benefits, particularly in disadvantaged communities. We conclude with priority recommendations for future analyses and solution-driven policy actions.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

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..

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.

BACKGROUND: Although many studies have linked prenatal exposure to PM2.5 to adverse birth outcomes, little is known about the effects of exposure to specific constituents of PM2.5 or mechanisms that contribute to these outcomes. OBJECTIVES: Our objective was to investigate effects of oxidative potential and PM2.5 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 PM2.5 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 (OPOH), and dithiothreitol (DTT) loss (OPDTT). Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for PTB and TLBW with speciated PM2.5 exposures and PM2.5 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 PM2.5 mass. Associations for PM2.5 mass, black carbon, metal components, and oxidative potential (especially ROS and OPOH) with adverse birth outcomes were stronger in Hispanic, Black, and mixed-race or Native American women. DISCUSSION: Our results indicate that exposure to PM2.5 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 PM2.5 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.

BackgroundTracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures. ObjectiveThe objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern. MethodsAdults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants’ geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1). ResultsThe mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P

BackgroundBoth 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).MethodsWe 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.ResultsIn 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 (

BackgroundRecent 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.MethodsWe 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 (PM2.5). We also derived estimates of pollutant exposures from ultra-fine particulate matter (PM0.1), 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.FindingsWe found significant associations between COVID-19 death and several air pollution exposures, including: PM2.5 mass, PM0.1 mass, PM2.5 nitrates, PM2.5 elemental carbon, PM2.5 on-road diesel, and PM2.5 on-road gasoline. Based on the interquartile (IQR) exposure increment, effect sizes ranged from hazard ratios (HR) = 1.12 for PM2.5 mass and PM2.5 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.InterpretationAir 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.

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM2.5) 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 (OPOH), dithiothreitol loss (OPDTT), black carbon, and 52 metals and elements for 54 total PM2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OPOH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OPOH, followed by 21% from brake and tire wear. Similar results were observed for the OPDTT source apportionment. Furthermore, by linking measured PM2.5 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. OPOH exhibited the largest inverse social gradients, followed by OPDTT and PM2.5 mass. Finally, OPOH was the metric most strongly correlated with adverse health outcome indicators.

Electrification of gas appliances in residential buildings will be necessary to rapidly decarbonize the energy system. In California however, recent rates of adoption of electric appliances, especially within disadvantaged and vulnerable communities (DVCs), have been insufficient to meet the state's ambitious GHG emissions abatement targets. In this study we use an integrated assessment modeling framework to quantify the holistic benefits of different electrification pathways within a representative study area DVC. Results indicate that aggressive electrification retrofits can deliver significant net reductions in GHG emissions, even when future grid emissions from increased electric loads are factored in. We also find that these measures can also create significant net public health benefits, in terms of overall avoided impacts from particulate matter (PM-2.5μ) exposures. However, the realization of these net benefits requires tradeoffs between local improvements in air quality in the areas where electrification occurs, for smaller, but still significant, reductions in air quality, in areas where fossil fueled electricity generators remain active. We conclude with a discussion of some of the persistent barriers to electrification within DVCs and the import role of electrification within broader efforts to combat climate change and improve equity within the energy system.

BackgroundEpidemiological studies on physical activity often lack inexpensive, objective, valid, and reproducible tools for measuring physical activity levels of participants. Novel sensing technologies built into smartphones offer the potential to fill this gap. ObjectiveWe sought to validate estimates of physical activity and determine the usability for large population-based studies of the smartphone-based CalFit software. MethodsA sample of 36 participants from Barcelona, Spain, wore a smartphone with CalFit software and an Actigraph GT3X accelerometer for 5 days. The ease of use (usability) and physical activity measures from both devices were compared, including vertical axis counts (VT) and duration and energy expenditure predictions for light, moderate, and vigorous intensity from Freedson’s algorithm. Statistical analyses included (1) Kruskal-Wallis rank sum test for usability measures, (2) Spearman correlation and linear regression for VT counts, (3) concordance correlation coefficient (CCC), and (4) Bland-Altman plots for duration and energy expenditure measures. ResultsApproximately 64% (23/36) of participants were women. Mean age was 31 years (SD 8) and mean body mass index was 22 kg/m2 (SD 2). In total, 25/36 (69%) participants recorded at least 3 days with at least 10 recorded hours of physical activity using CalFit. The linear association and correlations for VT counts were high (adjusted R2=0.85; correlation coefficient .932, 95% CI 0.931-0.933). CCCs showed high agreement for duration and energy expenditure measures (from 0.83 to 0.91). ConclusionsThe CalFit system had lower usability than the Actigraph GT3X because the application lacked a means to turn itself on each time the smartphone was powered on. The CalFit system may provide valid estimates to quantify and classify physical activity. CalFit may prove to be more cost-effective and easily deployed for large-scale population health studies than other specialized instruments because cell phones are already carried by many people.

BackgroundType 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes.ObjectiveWe studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association.MethodsWe 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.ResultsIn 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].ConclusionsOur 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.

Poor air quality affects the health and wellbeing of large populations around the globe. Although source controls are the most effective approaches for improving air quality and reducing health risks, individuals can also take actions to reduce their personal exposure by staying indoors, reducing physical activity, altering modes of transportation, filtering indoor air, and using respirators and other types of face masks. A synthesis of available evidence on the efficacy, effectiveness, and potential adverse effects or unintended consequences of personal interventions for air pollution is needed by clinicians to assist patients and the public in making informed decisions about use of these interventions. To address this need, the American Thoracic Society convened a workshop in May of 2018 to bring together a multidisciplinary group of international experts to review the current state of knowledge about personal interventions for air pollution and important considerations when helping patients and the general public to make decisions about how best to protect themselves. From these discussions, recommendations were made regarding when, where, how, and for whom to consider personal interventions. In addition to the efficacy and safety of the various interventions, the committee considered evidence regarding the identification of patients at greatest risk, the reliability of air quality indices, the communication challenges, and the ethical and equity considerations that arise when discussing personal interventions to reduce exposure and risk from outdoor air pollution.

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).MethodsFor 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.ResultsThe 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.ConclusionsExposure 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.

Fine particulate air pollution

BackgroundRecently, it has been suggested that environmental exposures from traffic sources including noise may play a role in cognitive impairment in the elderly. The objective of the study was to investigate the association between local traffic-related noise pollution and incident dementia or cognitive impairment without dementia (CIND) during a 10-year follow-up period.Methods1612 Mexican-American participants from the Sacramento Area Latino Study on Aging (SALSA) were followed every 12-15 months via home visits from 1998 to 2007. We used the SoundPLAN software package to estimate noise originating from local traffic with the input of Annual Average Daily Traffic (AADT) data from Metropolitan Planning Organizations (MPO) based on geocoded residential addresses at baseline (1998-1999). We estimated the risks of incident dementia or CIND from 24-hour and nighttime noise exposure using Cox proportional hazard models.ResultsDuring the follow-up, we identified 159 incident dementia or CIND cases in total. Per 11.6 dB (interquartile range width) increase in 24-hour noise, the hazard of developing dementia or CIND increased (hazard ratio = 1.3 [1.0, 1.6]) during follow-up; estimates were slightly lower (hazard ratio = 1.2 [0.97, 1.6]) when adjusting for modeled local air pollution exposure from traffic sources. Overall, the risk of dementia/CIND was elevated when 24-hour and nighttime noise were higher than 75 and 65 dB respectively. See video Abstract: http://links.lww.com/EDE/B728.ConclusionsIn our study, traffic-related noise exposure was associated with increased risk of dementia or CIND in elderly Mexican-Americans. Future studies taking into account other noise sources and occupational noise exposure before retirement are needed.

BackgroundEpidemiological 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.ObjectivesWe evaluated the associations between long-term exposure to road traffic noise and the incidence of AMI and CHF.MethodsOur 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].ResultsDuring 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.ConclusionIn 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.

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

BackgroundAmbient 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.MethodsWe 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).ResultsEach 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

BackgroundUrban trails are a useful resource to promote physical activity. This study identified features of urban trails that correlated with trail use.MethodsMultiuse 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.ResultsPositive 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.ConclusionsThese correlates should be confirmed in other studies and, if supported, should be considered in the promotion and design of urban trails.

BackgroundAmbient 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.ObjectiveTo 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).MethodsIn 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.ResultsHigher 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.ConclusionOur 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.

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.

BackgroundPrevious 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.MethodsA 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.ResultsEach 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).ConclusionPolicies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

Limited research has been conducted on the contributions of local and nonlocal emission sources to ambient fine particulate matter (PM2.5) and ozone (O3) and their associated mortality. In this study, we estimated the total mortality resulting from long-term PM2.5 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 PM2.5-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.

Conventional regulatory air quality monitoring sites tend to be sparsely located. The availability of lower-cost air pollution sensors, however, allows for their use in spatially dense community monitoring networks, which can be operated by various stakeholders, including concerned residents, organizations, academics, or government agencies. Networks of many community monitors have the potential to fill the spatial gaps between existing government-operated monitoring sites. One potential benefit of finer scale monitoring might be the ability to discern elevated air pollution episodes in locations that have not been identified by government-operated monitoring sites, which might improve public health warnings for populations sensitive to high levels of air pollution. In the Imperial Air study, a large network of low-cost particle monitors was deployed in the Imperial Valley in Southeastern California. Data from the new monitors is validated against regulatory air monitoring. Neighborhood-level air pollution episodes, which are defined as periods in which the PM2.5 (airborne particles with sizes less than 2.5 μm in diameter) hourly average concentration is equal to or greater than 35 μg m-3, are identified and corroborate with other sites in the network and against the small number of government monitors in the region. During the period from October 2016 to February 2017, a total of 116 episodes were identified among six government monitors in the study region; however, more than 10 times as many episodes are identified among the 38 community air monitors. Of the 1426 episodes identified by the community sensors, 723 (51%) were not observed by the government monitors. These findings suggest that the dense network of community air monitors could be useful for addressing current limitations in the spatial coverage of government air monitoring to provide real-time warnings of high pollution episodes to vulnerable populations.

Environmental triggers is part of five focus areas of the Challenges in IBD research document, which also includes preclinical human IBD mechanisms, novel technologies, precision medicine and pragmatic clinical research. The Challenges in IBD research document provides a comprehensive overview of current gaps in inflammatory bowel diseases (IBD) research and delivers actionable approaches to address them. It is the result of a multidisciplinary input from scientists, clinicians, patients, and funders, and represents a valuable resource for patient centric research prioritization. In particular, the environmental triggers section is focused on the main research gaps in elucidating causality of environmental factors in IBD. Research gaps were identified in: 1) epidemiology of exposures; 2) identification of signatures of biological response to exposures; and 3) mechanisms of how environmental exposures drive IBD. To address these gaps, the implementation of longitudinal prospective studies to determine disease evolution and identify sub-clinical changes in response to exposures is proposed. This can help define critical windows of vulnerability and risk prediction. In addition, systems biology analysis and in silico modeling were proposed as approaches to integrate the IBD exposome for the identification of biological signatures of response to exposures, and to develop prediction models of the effects of environmental factors in driving disease activity and response to therapy. This research could lead to identification of biomarkers of exposures and new modalities for therapeutic intervention. Finally, hypothesis-driven mechanistic studies to understand gene-environment interactions and to validate causality of priority factors should be performed to determine how environment influences clinical outcomes.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Purpose of reviewA number of studies over the past two decades have suggested that type 2 diabetes mellitus (T2DM) patients are at an increased risk of Alzheimer's disease (AD). Several common molecular pathways to cellular and metabolic dysfunction have been implicated in the etiology of both diseases. Here, we review the emerging evidence from observational studies that investigate the relationship between T2DM and AD, and of shared environmental risk factors, specifically air pollution and pesticides, associated with both chronic disorders.Recent findingsParticulate matter and traffic-related air pollution have been widely associated with T2DM, and multiple studies have associated exposures with AD or cognitive function. Organochlorine (OC) and organophosphate (OP) pesticides have been associated with T2DM in multiple independent populations. Two populations have observed increased risks for OC and OP exposures and AD. Other studies, limited in exposure assessment, have reported increased risk of AD with any pesticide exposure assessments. This may suggest shared pathogenic pathways between environmental risk factors, T2DM, and AD. Research focusing on exposures related to both T2DM and AD could provide new disease insights on shared mechanisms and help shape innovative preventative measures and policy decisions.

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM2.5 and PM10 (particulate matter with aerodynamic diameters

BackgroundLittle is known about the long-term health effects of ambient ultrafine particles (

This study investigated whether residential availability of natural outdoor environments (NOE) was associated with contact with NOE, overall physical activity and physical activity in NOE, in four different European cities using objective measures. A nested cross-sectional study was conducted in Barcelona (Spain); Stoke-on-Trent (United Kingdom); Doetinchem (The Netherlands); and Kaunas (Lithuania). Smartphones were used to collect information on the location and physical activity (overall and NOE) of around 100 residents of each city over seven days. We used Geographic Information Systems (GIS) to determine residential NOE availability (presence/absence of NOE within 300 m buffer from residence), contact with NOE (time spent in NOE), overall PA (total physical activity), NOE PA (total physical activity in NOE). Potential effect modifiers were investigated. Participants spent around 40 min in NOE and 80 min doing overall PA daily, of which 11% was in NOE. Having residential NOE availability was consistently linked with higher NOE contact during weekdays, but not to overall PA. Having residential NOE availability was related to NOE PA, especially for our Barcelona participants, people that lived in a city with low NOE availability.