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2.
Environ Int ; 158: 106897, 2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34601393

RESUMO

High-resolution, high-quality exposure modeling is critical for assessing the health effects of ambient PM2.5 in epidemiological studies. Using sparse regulatory PM2.5 measurements as principal model inputs may result in two issues in exposure prediction: (1) they may affect the models' accuracy in predicting PM2.5 spatial distribution; (2) the internal validation based on these measurements may not reliably reflect the model performance at locations of interest (e.g., a cohort's residential locations). In this study, we used the PM2.5 measurements from a publicly available commercial low-cost PM2.5 network, PurpleAir, with an external validation dataset at the residential locations of a representative sample of participants from the Adult Changes in Thought - Air Pollution (ACT-AP) study, to improve the accuracy of exposure prediction at the cohort participant locations. We also proposed a metric based on principal component analysis (PCA) - the PCA distance - to assess the similarity between monitor and cohort locations to guide monitor deployment and data selection. The analysis was based on a spatiotemporal modeling framework with 51 "gold-standard" monitors and 58 PurpleAir monitors for model development, as well as 105 home monitors at the cohort locations for model validation, in the Puget Sound region of Washington State from June 2017 to March 2019. After including calibrated PurpleAir measurements as part of the dependent variable, the external spatiotemporal validation R2 and root-mean-square error, RMSE, for two-week concentration averages improved from 0.84 and 2.22 µg/m3 to 0.92 and 1.63 µg/m3, respectively. The external spatial validation R2 and RMSE for long-term averages over the modeling period improved from 0.72 and 1.01 µg/m3 to 0.79 and 0.88 µg/m3, respectively. The exposure predictions incorporating PurpleAir measurements demonstrated sharper urban-suburban concentration gradients. The PurpleAir monitors with shorter PCA distances improved the model's prediction accuracy more substantially than the monitors with longer PCA distances, supporting the use of this similarity metric.

3.
Environ Health Perspect ; 129(9): 97009, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34516296

RESUMO

BACKGROUND: Episodic memory decline varies by age and underlying neuropathology. Whether ambient air pollution contributes to the heterogeneity of episodic memory decline in older populations remains unclear. OBJECTIVES: We estimated associations between air pollution exposures and episodic memory decline according to pollutant, exposure time window, age, and latent class subgroups defined by episodic memory trajectories. METHODS: Participants were from the Women's Health Initiative Memory Study-Epidemiology of Cognitive Health Outcomes. Older women (n=2,056; 74-92 years of age) completed annual (2008-2018) episodic memory assessments using the telephone-based California Verbal Learning Test (CVLT). We estimated 3-y average fine particulate matter [PM with an aerodynamic diameter of ≤2.5µm (PM2.5)] and nitrogen dioxide (NO2) exposures at baseline and 10 y earlier (recent and remote exposures, respectively), using regionalized national universal kriging. Separate latent class mixed models were used to estimate associations between interquartile range increases in exposures and CVLT trajectories in women ≤80 and >80 years of age, adjusting for covariates. RESULTS: Two latent classes were identified for women ≤80 years of age (n=828), "slow-decliners" {slope=-0.12/y [95% confidence interval (CI): -0.23, -0.01] and "fast-decliners" [slope=-1.79/y (95% CI: -2.08, -1.50)]}. In the slow-decliner class, but not the fast-decliner class, PM2.5 exposures were associated with a greater decline in CVLT scores over time, with a stronger association for recent vs. remote exposures [-0.16/y (95% CI: -2.08, -0.03) per 2.88 µg/m3 and -0.11/y (95% CI: -0.22, 0.01) per 3.27 µg/m3, respectively]. Among women ≥80 years of age (n=1,128), the largest latent class comprised "steady-decliners" [slope=-1.35/y (95% CI: -1.53, -1.17)], whereas the second class, "cognitively resilient", had no decline in CVLT on average. PM2.5 was not associated with episodic memory decline in either class. A 6.25-ppb increase in recent NO2 was associated with nonsignificant acceleration of episodic memory decline in the ≤80-y-old fast-decliner class [-0.21/y (95% CI: -0.45, 0.04)], and in the >80-y-old cognitively resilient class [-0.10/y (95% CI: -0.24, 0.03)] and steady-decliner class [-0.11/y (95% CI: -0.27, 0.05)]. Associations with recent NO2 exposure in women >80 years of age were stronger and statistically significant when 267 women with incident probable dementia were excluded [e.g., -0.12/y (95% CI: -0.22, -0.02) for the cognitively resilient class]. In contrast with changes in CVLT over time, there were no associations between exposures and CVLT scores during follow-up in any subgroup. DISCUSSION: In a community-dwelling U.S. population of older women, associations between late-life exposure to ambient air pollution and episodic memory decline varied by age-related cognitive trajectories, exposure time windows, and pollutants. https://doi.org/10.1289/EHP7668.

4.
Environ Res ; 204(Pt B): 112087, 2021 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-34562475

RESUMO

BACKGROUND: PM2.5 have been associated with weight change in animal models and non-pregnant populations. Evidence of associations between PM2.5 and gestational weight gain (GWG), an important determinant of course and outcomes of pregnancy, and subsequent birth outcomes is limited. METHODS: The study was conducted among a subset of participants from the Omega Study, a prospective pregnancy cohort. Exposure to PM2.5 (µg/m3) was ascertained for participants (N = 855) based on their residential address using a validated national spatiotemporal model. Adjusted multivariable linear regression models were used to estimate associations of trimester-specific and pregnancy-month PM2.5 exposures with early (<20 weeks gestation), late (≥20 weeks gestation), and total GWG and infant birth weight. Stratified models and product terms were used to examine whether pre-pregnancy BMI (ppBMI) and infant sex modified the associations. RESULTS: Average monthly PM2.5 exposure during the first, second, and third trimesters were 7.3 µg/m3, 7.9 µg/m3, and 7.7 µg/m3, respectively. Higher third trimester PM2.5 exposure was associated with higher late (0.40 kg per 5 µg/m (McDowell et al., 2018); 95%CI: 0.12, 0.67) and total (0.35 kg; 95%CI: 0.01, 0.70) GWG among participants with normal ppBMI. Higher second month PM2.5 exposure was associated with lower early (-0.70 kg; 95%CI: 1.22, -0.18), late (-0.84 kg; 95% CI: 1.54, -0.14), and total (-1.70 kg; 95%CI: 2.57, -0.82) GWG among participants with overweight/obese ppBMI. Product terms between PM2.5 and ppBMI were significant for second month PM2.5 exposure and early (p-value = 0.01) and total GWG (p-value<0.01). Higher third trimester PM2.5 exposure was associated with higher birth weight, though higher fourth month PM2.5 exposure was associated with lower birth weight, particularly among those with normal ppBMI and male infants. CONCLUSIONS: Associations of PM2.5 with GWG vary by exposure window and ppBMI, while associations of PM2.5 with birth weight potentially vary by exposure window, ppBMI and infant sex. Further exploration of associations between PM2.5 and maternal/child health outcomes are needed.

5.
Artigo em Inglês | MEDLINE | ID: mdl-34360264

RESUMO

Few studies have examined associations between neighborhood built environments (BE) and longitudinally measured cognition. We examined whether four BE characteristics were associated with six-year change in global cognition and processing speed. We obtained data on 1816 participants without dementia from the Multi-Ethnic Study of Atherosclerosis. BE measures included social destination density, walking destination density, proportion of land dedicated to retail, and network ratio (street connectivity). Global cognition was measured with the Cognitive Abilities Screening Instrument (CASI) and processing speed with the Digit Symbol Coding test (DSC). Multivariable random intercept logistic models tested associations between neighborhood BE at 2010-2012 and maintained/improved cognition (versus decline) from 2010-2018, and mediation by minutes of physical activity (PA)/week. The sample was an average of 67 years old (standard deviation = 8.2) (first cognitive measurement) and racially/ethnically diverse (29% African American, 11% Chinese, 17% Hispanic, 44% White). Compared to individuals with no walking destinations in the 1-mile surrounding their residence, those with 716 walking destinations (maximum observed) were 1.24 times more likely to have maintain/improved DSC score (Odds ratio: 1.24; 95% confidence interval: 1.03-1.45). No other associations were observed between BE and cognition, and PA minutes/week did not mediate the association between walking destination density and DSC change. This study provides limited evidence for an association between greater neighborhood walking destinations and maintained/improved processing speed in older age and no evidence for associations between the other BE characteristics and cognition. Future studies with finer grained BE and cognitive measures and longer-term follow up may be required.


Assuntos
Aterosclerose , Ambiente Construído , Idoso , Cognição , Estudos Transversais , Planejamento Ambiental , Humanos , Características de Residência , Caminhada
6.
Environ Health Perspect ; 129(8): 87001, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34347531

RESUMO

BACKGROUND: Air pollution may be associated with elevated dementia risk. Prior research has limitations that may affect reliability, and no studies have evaluated this question in a population-based cohort of men and women in the United States. OBJECTIVES: We evaluated the association between time-varying, 10-y average fine particulate matter (PM2.5) exposure and hazard of all-cause dementia. An additional goal was to understand how to adequately control for age and calendar-time-related confounding through choice of the time axis and covariate adjustment. METHODS: Using the Adult Changes in Thought (ACT) population-based prospective cohort study in Seattle, we linked spatiotemporal model-based PM2.5 exposures to participant addresses from 1978 to 2018. Dementia diagnoses were made using high-quality, standardized, consensus-based protocols at biennial follow-ups. We conducted multivariable Cox proportional hazards regression to evaluate the association between time-varying, 10-y average PM2.5 exposure and time to event in a model with age as the time axis, stratified by apolipoprotein E (APOE) genotype, and adjusted for sex, education, race, neighborhood median household income, and calendar time. Alternative models used calendar time as the time axis. RESULTS: We report 1,136 cases of incident dementia among 4,166 individuals with nonmissing APOE status. Mean [mean ± standard deviation (SD)] 10-y average PM2.5 was 10.1 (±2.9) µg/m3. Each 1-µg/m3 increase in the moving average of 10-y PM2.5 was associated with a 16% greater hazard of all-cause dementia [1.16 (95% confidence interval: 1.03, 1.31)]. Results using calendar time as the time axis were similar. DISCUSSION: In this prospective cohort study with extensive exposure data and consensus-based outcome ascertainment, elevated long-term exposure to PM2.5 was associated with increased hazard of all-cause dementia. We found that optimal control of age and time confounding could be achieved through use of either age or calendar time as the time axis in our study. Our results strengthen evidence on the neurodegenerative effects of PM2.5. https://doi.org/10.1289/EHP9018.

7.
Sensors (Basel) ; 21(12)2021 Jun 19.
Artigo em Inglês | MEDLINE | ID: mdl-34205429

RESUMO

We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO2; NO2-B43F), and oxidizing gases (OX-B431)-which refers to ozone (O3) and NO2. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019. Monitors were rotated throughout the region, including at two Puget Sound Clean Air Agency monitoring sites for calibration purposes, and over 100 residences, including the homes of epidemiological study participants, with the goal of improving long-term pollutant exposure predictions at participant locations. Calibration models improved when accounting for individual sensor performance, ambient temperature and humidity, and concentrations of co-pollutants as measured by other low-cost sensors in the monitors. Predictions from the final daily models for CO and NO performed the best considering agreement with regulatory monitors in cross-validated root-mean-square error (RMSE) and R2 measures (CO: RMSE = 18 ppb, R2 = 0.97; NO: RMSE = 2 ppb, R2 = 0.97). Performance measures for NO2 and O3 were somewhat lower (NO2: RMSE = 3 ppb, R2 = 0.79; O3: RMSE = 4 ppb, R2 = 0.81). These high levels of calibration performance add confidence that low-cost sensor measurements collected at the homes of epidemiological study participants can be integrated into spatiotemporal models of pollutant concentrations, improving exposure assessment for epidemiological inference.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Calibragem , Monóxido de Carbono/análise , Monitoramento Ambiental , Estudos Epidemiológicos , Humanos , Óxido Nítrico/análise , Dióxido de Nitrogênio/análise , Ozônio/análise , Material Particulado/análise
8.
Curr Environ Health Rep ; 8(2): 113-126, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34086258

RESUMO

PURPOSE OF REVIEW: Epidemiological studies of short- and long-term health impacts of ambient air pollutants require accurate exposure estimates. We describe the evolution in exposure assessment and assignment in air pollution epidemiology, with a focus on spatiotemporal techniques first developed to meet the needs of the Multi-ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Initially designed to capture the substantial variation in pollutant levels and potential health impacts that can occur over small spatial and temporal scales in metropolitan areas, these methods have now matured to permit fine-scale exposure characterization across the contiguous USA and can be used for understanding long- and short-term health effects of exposure across the lifespan. For context, we highlight how the MESA Air models compare to other available exposure models. RECENT FINDINGS: Newer model-based exposure assessment techniques provide predictions of pollutant concentrations with fine spatial and temporal resolution. These validated models can predict concentrations of several pollutants, including particulate matter less than 2.5 µm in diameter (PM2.5), oxides of nitrogen, and ozone, at specific locations (such as at residential addresses) over short time intervals (such as 2 weeks) across the contiguous USA between 1980 and the present. Advances in statistical methods, incorporation of supplemental pollutant monitoring campaigns, improved geographic information systems, and integration of more complete satellite and chemical transport model outputs have contributed to the increasing validity and refined spatiotemporal spans of available models. Modern models for predicting levels of outdoor concentrations of air pollutants can explain a substantial amount of the spatiotemporal variation in observations and are being used to provide critical insights into effects of air pollutants on the prevalence, incidence, progression, and prognosis of diseases across the lifespan. Additional enhancements in model inputs and model design, such as incorporation of better traffic data, novel monitoring platforms, and deployment of machine learning techniques, will allow even further improvements in the performance of pollutant prediction models.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Aterosclerose , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Aterosclerose/epidemiologia , Exposição Ambiental/efeitos adversos , Monitoramento Ambiental , Estudos Epidemiológicos , Humanos , Material Particulado/análise
9.
J Alzheimers Dis ; 82(1): 221-233, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34024841

RESUMO

BACKGROUND: Preliminary evidence suggests associations between neighborhood park access and better late-life cognition and reduced Alzheimer's disease (AD) risk. OBJECTIVE: Examine associations between neighborhood park access and longitudinal change in cognition among U.S. older adults without dementia. METHODS: We used 2000-2018 observational data from the population-based, multi-site Multi-Ethnic Study of Atherosclerosis (n = 1,733). Measures included proportion of neighborhood park space (park access), distance to nearest park, and 6-year dichotomous and continuous change in scores on the Cognitive Abilities Screening Instrument (CASI; global cognition) and Digit Symbol Coding task (processing speed). Multivariable random intercept models tested main associations and mediation by depressive symptoms, physical activity, and PM2.5 exposure. Effect modification by race (African Americans/Blacks versus Whites) was tested using interaction terms. RESULTS: Greater park access (equivalent to 10%more in 1/2-mile around home) was associated with maintained/improved CASI score over six years independent of several covariates including individual- and neighborhood-level socioeconomic status (Odds ratio: 1.04; 95%confidence interval: 1.00-1.08). No other associations were observed with the dichotomous or continuous measures of cognitive change and no mediators were found. While a borderline association was seen between greater park access and maintained/improved CASI for African Americans/Blacks but not for Whites, effect modification was not confirmed by testing interaction terms. CONCLUSION: Neighborhood park access may help maintain/improve late-life global cognition. However, our findings need replication in other population-based studies and regions. Additionally, studies are needed to determine if associations between park access and change in cognition vary by race/ethnicity to inform intervention efforts.


Assuntos
Cognição/fisiologia , Grupos Étnicos/estatística & dados numéricos , Parques Recreativos , Características de Residência , Idoso , Exercício Físico/fisiologia , Feminino , Humanos , Estudos Longitudinais , Masculino , Estados Unidos
10.
Environ Health Perspect ; 129(5): 51001, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-34014764
11.
Am J Respir Crit Care Med ; 204(5): 536-545, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-33971109

RESUMO

Rationale: Racial residential segregation has been associated with worse health outcomes, but the link with chronic obstructive pulmonary disease (COPD) morbidity has not been established.Objectives: To investigate whether racial residential segregation is associated with COPD morbidity among urban Black adults with or at risk of COPD.Methods: Racial residential segregation was assessed using isolation index, based on 2010 decennial census and baseline address, for Black former and current smokers in the multicenter SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), a study of adults with or at risk for COPD. We tested the association between isolation index and respiratory symptoms, physiologic outcomes, imaging parameters, and exacerbation risk among urban Black residents, adjusting for established COPD risk factors, including smoking. Additional mediation analyses were conducted for factors that could lie on the pathway between segregation and COPD outcomes, including individual and neighborhood socioeconomic status, comorbidity burden, depression/anxiety, and ambient pollution.Measurements and Main Results: Among 515 Black participants, those residing in segregated neighborhoods (i.e., isolation index ⩾0.6) had worse COPD Assessment Test score (ß = 2.4; 95% confidence interval [CI], 0.7 to 4.0), dyspnea (modified Medical Research Council scale; ß = 0.29; 95% CI, 0.10 to 0.47), quality of life (St. George's Respiratory Questionnaire; ß = 6.1; 95% CI, 2.3 to 9.9), and cough and sputum (ß = 0.8; 95% CI, 0.1 to 1.5); lower FEV1% predicted (ß = -7.3; 95% CI, -10.9 to -3.6); higher rate of any and severe exacerbations; and higher percentage emphysema (ß = 2.3; 95% CI, 0.7 to 3.9) and air trapping (ß = 3.8; 95% CI, 0.6 to 7.1). Adverse associations attenuated with adjustment for potential mediators but remained robust for several outcomes, including dyspnea, FEV1% predicted, percentage emphysema, and air trapping.Conclusions: Racial residential segregation was adversely associated with COPD morbidity among urban Black participants and supports the hypothesis that racial segregation plays a role in explaining health inequities affecting Black communities.


Assuntos
Afro-Americanos/estatística & dados numéricos , Disparidades nos Níveis de Saúde , Doença Pulmonar Obstrutiva Crônica/etnologia , Doença Pulmonar Obstrutiva Crônica/mortalidade , Doença Pulmonar Obstrutiva Crônica/fisiopatologia , Segregação Social , População Urbana/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Características de Residência , Classe Social , Inquéritos e Questionários , Estados Unidos/etnologia
12.
Sleep ; 44(10)2021 Oct 11.
Artigo em Inglês | MEDLINE | ID: mdl-33987669

RESUMO

STUDY OBJECTIVES: To quantify the gender-specific associations between insomnia symptoms and subclinical atherosclerosis, measured by coronary artery calcium (CAC) scores, which has strong predictive value for incident cardiovascular disease. METHODS: We analyzed data from 1,429 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Participants completed standardized questionnaires and underwent polysomnography (PSG) and 7-day actigraphy. Insomnia symptoms were defined as: self-reported trouble falling, staying or returning to sleep, early-morning awakenings, or hypnotic use, for ≥5 nights/week. MESA assessed CAC using computed tomography. We employed multivariable linear regression to model the probability of CAC >0 overall and to model the linear continuous effect among those with nonzero CAC. RESULTS: Our sample was a mean age of 68.1 ± 9.1 years, 53.9% female, and 36.2% white, 28.0% black, 24.2% Hispanic, and 11.5% Chinese-American. Insomnia symptoms were present in 49.7% of men and 47.2% of women. In multivariable-adjusted analyses, insomnia symptoms was associated with an 18% higher prevalence of CAC (PR 1.18, 95% CI 1.04, 1.33) among females, but no association was observed among males (PR 1.00, 95% CI 0.91, 1.08). There was no evidence that the association between insomnia symptoms and prevalence of CAC >0 differed by objective sleep duration status (by single-night PSG or multi-night actigraphy) in females or males. CONCLUSIONS: We found that among women, insomnia symptoms were associated with an 18% higher prevalence of CAC compared to no insomnia. Insomnia symptoms were not associated with CAC prevalence in men. Additionally, there was no evidence that the association between insomnia symptoms and CAC score >0 differed by objective short sleep duration status.

13.
BMC Pulm Med ; 21(1): 139, 2021 Apr 27.
Artigo em Inglês | MEDLINE | ID: mdl-33906617

RESUMO

BACKGROUND: Millions of Americans are living in food deserts in the United States, however the role of the local food environment on COPD has not been studied. The aim of this study is to determine the association between food deserts and COPD-related outcomes. METHOD: In this cross-sectional analysis we linked data collected from SPIROMICS (SubPopulations and InteRmediate Outcome Measures in COPD Study) between 2010 and 2015 and food desert data, defined as an underserved area that lacks access to affordable healthy foods, from the Food Access Research Atlas. COPD outcomes include percentage of predicted forced expiratory volume in one second (FEV1%), St. George's Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT), 6-min walk distance test (6MWD), exacerbations, and air trapping. We used generalized linear mixed models to evaluate the association between living in food deserts and respiratory outcomes, adjusting for age, gender, race, education, income, marital status, BMI, smoking status, pack years, and urban status RESULTS: Among 2713 participants, 22% lived in food deserts. Participants living in food deserts were less likely to be white and more likely to have a lower income than those who did not live in food deserts. In the adjusted model controlling for demographics and individual income, living in food deserts was associated lower FEV1% (ß = - 2.51, P = 0.046), higher air trapping (ß = 2.47, P = 0.008), worse SGRQ (ß = 3.48, P = 0.001) and CAT (ß = 1.20, P = 0.003) scores, and 56% greater odds of severe exacerbations (P = 0.004). Results were consistent when looking at food access alone, regardless of whether participants lived in low income areas. CONCLUSIONS: Findings suggest an independent association between food desert and food access alone with COPD outcomes. Health program planning may benefit from addressing disparities in access to food.

14.
Environ Pollut ; 279: 116893, 2021 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-33765506

RESUMO

To help understand the pathophysiologic mechanisms linking air pollutants and cardiovascular disease (CVD), we employed a repeated measures design to investigate the associations of four short-term air pollution exposures - particulate matter less than 2.5 µm in diameter (PM2.5), nitrogen dioxide (NO2), ozone (O3) and sulfur dioxide (SO2), with two blood markers involved in vascular effects of oxidative stress, soluble lectin-like oxidized LDL receptor-1 (sLOX-1) and nitrite, using data from the Multi-Ethnic Study of Atherosclerosis (MESA). Seven hundred and forty participants with plasma sLOX-1 and nitrite measurements at three exams between 2002 and 2007 were included. Daily PM2.5, NO2, O3 and SO2 zero to seven days prior to blood draw were estimated from central monitors in six MESA regions, pre-adjusted using site-specific splines of meteorology and temporal trends, and an indicator for day of the week. Unconstrained distributed lag generalized estimating equations were used to estimate net effects over eight days with adjustment for sociodemographic and behavioral factors. The results showed that higher short-term concentrations of PM2.5, but not other pollutants, were associated with increased sLOX-1 analyzed both as a continuous outcome (percent change per interquartile increase: 16.36%, 95%CI: 0.1-35.26%) and dichotomized at the median (odds ratio per interquartile increase: 1.21, 95%CI: 1.01-1.44). The findings were not meaningfully changed after adjustment for additional covariates or in several sensitivity analyses. Pollutant concentrations were not associated with nitrite levels. This study extends earlier experimental findings of increased sLOX-1 levels following PM inhalation to a much larger population and at ambient concentrations. In light of its known mechanistic role in promoting vascular disease, sLOX-1 may be a suitable translational biomarker linking air pollutant exposures and cardiovascular outcomes.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Biomarcadores , Exposição Ambiental/análise , Humanos , Dióxido de Nitrogênio/análise , Ozônio/análise , Material Particulado/análise
15.
BMJ Open Respir Res ; 8(1)2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33664125

RESUMO

BACKGROUND: Air pollution may affect the risk of respiratory infection, though research has focused on uncommon infections or infections in children. Whether ambient air pollutants increase the risk of common acute respiratory infections among adults is uncertain, yet this may help understand whether pollutants influence spread of pandemic respiratory infections like COVID-19. OBJECTIVE: To estimate the association between ambient air pollutant exposures and respiratory infections in adults. METHODS: During five study examinations over 12 years, 6536 participants in the multiethnic study of atherosclerosis (MESA) reported upper respiratory tract infections, bronchitis, pneumonia or febrile illness in the preceding 2 weeks. Using a validated spatiotemporal model, we estimated residential concentrations of ambient PM2.5, NOx and NO2 for the 2-6 weeks (short-term) and year (long-term) prior to each examination. RESULTS: In this population aged 44-84 years at baseline, 10%-32% of participants reported a recent respiratory infection, depending on month of examination and study region. PM2.5, NOx and NO2 concentrations over the prior 2-6 weeks were associated with increased reporting of recent respiratory infection, with risk ratios (95% CIs) of 1.04 (1.00 to 1.09), 1.15 (1.10 to 1.20) and 1.21 (1.10 to 1.33), respectively, per increase from 25th to 75th percentile in residential pollutant concentration. CONCLUSION: Higher short-term exposure to PM2.5 and traffic-related pollutants are associated with increased risk of symptomatic acute respiratory infections among adults. These findings may provide an insight into the epidemiology of COVID-19.


Assuntos
Poluição do Ar/efeitos adversos , Poluição do Ar/estatística & dados numéricos , Aterosclerose/etnologia , Aterosclerose/epidemiologia , COVID-19/etnologia , COVID-19/epidemiologia , Comparação Transcultural , Grupos Étnicos/estatística & dados numéricos , Infecções Respiratórias/etnologia , Infecções Respiratórias/epidemiologia , Doença Aguda , Adulto , Idoso , Idoso de 80 Anos ou mais , Bronquite/epidemiologia , Bronquite/etnologia , Correlação de Dados , Estudos Transversais , Feminino , Febre/epidemiologia , Febre/etnologia , Humanos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Pneumonia/epidemiologia , Pneumonia/etnologia , Risco , Análise Espaço-Temporal , Estados Unidos
16.
Environ Sci Technol ; 55(6): 3530-3538, 2021 03 16.
Artigo em Inglês | MEDLINE | ID: mdl-33635626

RESUMO

Mobile monitoring is increasingly employed to measure fine spatial-scale variation in air pollutant concentrations. However, mobile measurement campaigns are typically conducted over periods much shorter than the decadal periods used for modeling chronic exposure for use in air pollution epidemiology. Using the regions of Los Angeles and Baltimore and the time period from 2005 to 2014 as our modeling domain, we investigate whether including mobile or stationary passive sampling device (PSD) monitoring data collected over a single 2-week period in one or two seasons using a unified spatio-temporal air pollution model can improve model performance in predicting NO2 and NOx concentrations throughout the 9-year study period beyond what is possible using only routine monitoring data. In this initial study, we use data from mobile measurement campaigns conducted contemporaneously with deployments of stationary PSDs and only use mobile data collected within 300 m of a stationary PSD location for inclusion in the model. We find that including either mobile or PSD data substantially improves model performance for pollutants and locations where model performance was initially the worst (with the most-improved R2 changing from 0.40 to 0.82) but does not meaningfully change performance in cases where performance was already very good. Results indicate that in many cases, additional spatial information from mobile monitoring and personal sampling is potentially cost-efficient inexpensive way of improving exposure predictions at both 2-week and decadal averaging periods, especially for the predictions that are located closer to features such as roadways targeted by the mobile short-term monitoring campaign.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Baltimore , Monitoramento Ambiental , Los Angeles , Material Particulado/análise
17.
J Alzheimers Dis ; 79(4): 1761-1773, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33459717

RESUMO

BACKGROUND: Evidence links fine particulate matter (PM2.5) to Alzheimer's disease (AD), but no community-based prospective cohort studies in older adults have evaluated the association between long-term exposure to PM2.5 and markers of AD neuropathology at autopsy. OBJECTIVE: Using a well-established autopsy cohort and new spatiotemporal predictions of air pollution, we evaluated associations of 10-year PM2.5 exposure prior to death with Braak stage, Consortium to Establish a Registry for AD (CERAD) score, and combined AD neuropathologic change (ABC score). METHODS: We used autopsy specimens (N = 832) from the Adult Changes in Thought (ACT) study, with enrollment ongoing since 1994. We assigned long-term exposure at residential address based on two-week average concentrations from a newly developed spatiotemporal model. To account for potential selection bias, we conducted inverse probability weighting. Adjusting for covariates with tiered models, we performed ordinal regression for Braak and CERAD and logistic regression for dichotomized ABC score. RESULTS: 10-year average (SD) PM2.5 from death across the autopsy cohort was 8.2 (1.9) µg/m3. Average age (SD) at death was 89 (7) years. Each 1µg/m3 increase in 10-year average PM2.5 prior to death was associated with a suggestive increase in the odds of worse neuropathology as indicated by CERAD score (OR: 1.35 (0.90, 1.90)) but a suggestive decreased odds of neuropathology as defined by the ABC score (OR: 0.79 (0.49, 1.19)). There was no association with Braak stage (OR: 0.99 (0.64, 1.47)). CONCLUSION: We report inconclusive associations between PM2.5 and AD neuropathology at autopsy among a cohort where 94% of individuals experienced 10-year exposures below the current EPA standard. Prior studies of AD risk factors and AD neuropathology are similarly inconclusive, suggesting alternative mechanistic pathways for disease or residual confounding.


Assuntos
Poluição do Ar/efeitos adversos , Doença de Alzheimer/patologia , Material Particulado/efeitos adversos , Idoso de 80 Anos ou mais , Autopsia , Encéfalo/patologia , Estudos de Coortes , Exposição Ambiental/efeitos adversos , Feminino , Humanos , Masculino , Fatores de Risco
18.
Environ Pollut ; 271: 116282, 2021 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-33385889

RESUMO

The interrelationships among long-term ambient air pollution exposure, emotional distress and cognitive decline in older adulthood remain unclear. Long-term exposure may impact cognitive performance and subsequently impact emotional health. Conversely, exposure may initially be associated with emotional distress followed by declines in cognitive performance. Here we tested the inter-relationship between global cognitive ability, emotional distress, and exposure to PM2.5 (particulate matter with aerodynamic diameter <2.5 µm) and NO2 (nitrogen dioxide) in 6118 older women (aged 70.6 ± 3.8 years) from the Women's Health Initiative Memory Study. Annual exposure to PM2.5 (interquartile range [IQR] = 3.37 µg/m3) and NO2 (IQR = 9.00 ppb) was estimated at the participant's residence using regionalized national universal kriging models and averaged over the 3-year period before the baseline assessment. Using structural equation mediation models, a latent factor capturing emotional distress was constructed using item-level data from the 6-item Center for Epidemiological Studies Depression Scale and the Short Form Health Survey Emotional Well-Being scale at baseline and one-year follow-up. Trajectories of global cognitive performance, assessed by the Modified-Mini Mental State Examination (3MS) annually up to 12 years, were estimated. All effects reported were adjusted for important confounders. Increases in PM2.5 (ß = -0.144 per IQR; 95% CI = -0.261; -0.028) and NO2 (ß = -0.157 per IQR; 95% CI = -0.291; -0.022) were associated with lower initial 3MS performance. Lower 3MS performance was associated with increased emotional distress (ß = -0.008; 95% CI = -0.015; -0.002) over the subsequent year. Significant indirect effect of both exposures on increases in emotional distress mediated by exposure effects on worse global cognitive performance were present. No statistically significant indirect associations were found between exposures and 3MS trajectories putatively mediated by baseline emotional distress. Our study findings support cognitive aging processes as a mediator of the association between PM2.5 and NO2 exposure and emotional distress in later-life.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Adulto , Idoso , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Cognição , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Feminino , Humanos , Dióxido de Nitrogênio/análise , Material Particulado/análise , Angústia Psicológica
19.
Environ Health Perspect ; 129(1): 11001, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33400597
20.
Indoor Air ; 31(3): 702-716, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33037695

RESUMO

Increased outdoor concentrations of fine particulate matter (PM2.5 ) and oxides of nitrogen (NO2 , NOx ) are associated with respiratory and cardiovascular morbidity in adults and children. However, people spend most of their time indoors and this is particularly true for individuals with chronic obstructive pulmonary disease (COPD). Both outdoor and indoor air pollution may accelerate lung function loss in individuals with COPD, but it is not feasible to measure indoor pollutant concentrations in all participants in large cohort studies. We aimed to understand indoor exposures in a cohort of adults (SPIROMICS Air, the SubPopulations and Intermediate Outcome Measures in COPD Study of Air pollution). We developed models for the entire cohort based on monitoring in a subset of homes, to predict mean 2-week-measured concentrations of PM2.5 , NO2 , NOx , and nicotine, using home and behavioral questionnaire responses available in the full cohort. Models incorporating socioeconomic, meteorological, behavioral, and residential information together explained about 60% of the variation in indoor concentration of each pollutant. Cross-validated R2 for best indoor prediction models ranged from 0.43 (NOx ) to 0.51 (NO2 ). Models based on questionnaire responses and estimated outdoor concentrations successfully explained most variation in indoor PM2.5 , NO2 , NOx , and nicotine concentrations.

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