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Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.
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Poluentes Atmosféricos/toxicidade , Calor Extremo , Hospitalização/estatística & dados numéricos , Ozônio/toxicidade , Sistema Respiratório/fisiopatologia , Poluentes Atmosféricos/análise , Teorema de Bayes , California , Humanos , Ozônio/análise , RiscoRESUMO
BACKGROUND: This study capitalized on coal and oil facility retirements to quantify their potential effects on fine particulate matter (PM2.5) concentrations and cardiorespiratory hospitalizations in affected areas using a generalized synthetic control method. METHODS: We identified 11 coal and oil facilities in California that retired between 2006 and 2013. We classified zip code tabulation areas (ZCTA) as exposed or unexposed to a facility retirement using emissions information, distance, and a dispersion model. We calculated weekly ZCTA-specific PM2.5 concentrations based on previously estimated daily time-series PM2.5 concentrations from an ensemble model, and weekly cardiorespiratory hospitalization rates based on hospitalization data collected by the California Department of Health Care Access and Information. We estimated the average differences in weekly average PM2.5 concentrations and cardiorespiratory hospitalization rates in four weeks after each facility retirement between the exposed ZCTAs and the synthetic control using all unexposed ZCTAs (i.e., the average treatment effect among the treated [ATT]) and pooled ATTs using meta-analysis. We conducted sensitivity analyses to consider different classification schemes to distinguish exposed from unexposed ZCTAs, including aggregating outcomes with different time intervals and including a subset of facilities with reported retirement date confirmed via emission record. RESULTS: The pooled ATTs were 0.02 µg/m3 (95% confidence interval (CI): -0.25 to 0.29 µg/m3) and 0.34 per 10,000 person-weeks (95%CI: -0.08 to 0.75 per 10,000 person-weeks) following the facility closure for weekly PM2.5 and cardiorespiratory hospitalization rates, respectively. Our inferences remained the same after conducting sensitivity analyses. CONCLUSIONS: We demonstrated a novel approach to study the potential benefits associated with industrial facility retirements. The declining contribution of industrial emissions to ambient air pollution in California may explain our null findings. We encourage future research to replicate this work in regions with different industrial activities.
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Poluentes Atmosféricos , Poluição do Ar , Humanos , Poluentes Atmosféricos/análise , Aposentadoria , Carvão Mineral , Poluição do Ar/análise , Material Particulado/análise , California , Centrais ElétricasRESUMO
BACKGROUND: Although slow gait speed is an established risk factor for falls, few studies have evaluated change in gait speed as a predictor of falls or considered variability in effects by cognitive status. Change in gait speed may be a more useful metric because of its potential to identify decline in function. In addition, older adults with mild cognitive impairment are at an elevated risk of falls. The purpose of this research was to quantify the association between 12-month change in gait speed and falls in the subsequent 6 months among older adults with and without mild cognitive impairment. METHODS: Falls were self-reported every six months, and gait speed was ascertained annually among 2,776 participants in the Ginkgo Evaluation of Memory Study (2000-2008). Adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for fall risk relative to a 12-month change in gait speed. RESULTS: Slowing gait speed over 12 months was associated with increased risk of one or more falls (HR:1.13; 95% CI: 1.02 to 1.25) and multiple falls (HR:1.44; 95% CI: 1.18 to 1.75). Quickening gait speed was not associated with risk of one or more falls (HR 0.97; 95% CI: 0.87 to 1.08) or multiple falls (HR 1.04; 95% CI: 0.84 to 1.28), relative to those with a less than 0.10 m/s change in gait speed. Associations did not vary by cognitive status (pinteraction = 0.95 all falls, 0.25 multiple falls). CONCLUSIONS: Decline in gait speed over 12 months is associated with an increased likelihood of falls among community-dwelling older adults, regardless of cognitive status. Routine checks of gait speed at outpatient visits may be warranted as a means to focus fall risk reduction efforts.
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Disfunção Cognitiva , Vida Independente , Humanos , Idoso , Estudos Retrospectivos , Marcha , Estudos de Coortes , Velocidade de Caminhada , Disfunção Cognitiva/diagnóstico , Disfunção Cognitiva/epidemiologiaRESUMO
INTRODUCTION: Growing evidence implicates air pollution as a risk factor for dementia, but prior work is limited by challenges in diagnostic accuracy and assessing exposures in the decades prior to disease development. We evaluated the impact of long-term fine particulate matter (PM2.5 ) exposures on incident dementia (all-cause, Alzheimer's disease [AD], and vascular dementia [VaD]) in older adults. METHODS: A panel of neurologists adjudicated dementia cases based on extensive neuropsychological testing and magnetic resonance imaging. We applied validated fine-scale air pollutant models to reconstructed residential histories to assess exposures. RESULTS: An interquartile range increase in 20-year PM2.5 was associated with a 20% higher risk of dementia (95% confidence interval [CI]: 5%, 37%) and an increased risk of mixed VaD/AD but not AD alone. DISCUSSION: Our findings suggest that air pollutant exposures over decades contribute to dementia and that effects of current exposures may be experienced years into the future.
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Poluentes Atmosféricos , Poluição do Ar , Doença de Alzheimer , Demência Vascular , Humanos , Idoso , Ginkgo biloba , Poluição do Ar/efeitos adversos , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Doença de Alzheimer/epidemiologia , Doença de Alzheimer/induzido quimicamente , Material Particulado/efeitos adversos , Material Particulado/análise , Demência Vascular/epidemiologiaRESUMO
This study aimed to investigate the role of cardiovascular health (CVH) and vascular events as potential contributors to socioeconomic inequalities in dementia using causal mediation analyses. We used data from the Three-City Cohort, a French population-based study with 12 years of follow-up, with active search of dementia cases and validated diagnosis. Individual socioeconomic status was assessed using education, occupation and income. A CVH score as defined by the American Heart Association and incident vascular events were considered separately as mediators. We performed multi-level Cox proportional and Aalen additive hazard regression models to estimate the total effects of socioeconomic status on dementia risk. To estimate natural direct and indirect effects through CVH and vascular events, we applied two distinct weighting methods to quantify the role of CVH and vascular events: Inverse Odds Ratio Weighting (IORW) and Marginal Structural Models (MSM) respectively. Among 5581 participants, the risk of dementia was higher among participants with primary education (HR 1.60, 95%CI 1.44-1.78), blue-collar workers (HR 1.62, 95%CI 1.43-1.84) and with lower income (HR 1.23, 95%CI 1.09-1.29). Using additive models, 571 (95% CI 288-782) and 634 (95% CI 246-1020) additional cases of dementia per 100 000 person and year were estimated for primary education and blue-collar occupation, respectively. Using IORW, the CVH score mediate the relationship between education or income, and dementia (proportion mediated 17% and 26%, respectively). Yet, considering vascular events as mediator, MSM generated indirect effects that were smaller and more imprecise. Socioeconomic inequalities in dementia risk were observed but marginally explained by CVH or vascular events mediators.
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Doenças Cardiovasculares/complicações , Demência/diagnóstico , Comportamentos Relacionados com a Saúde , Classe Social , Determinantes Sociais da Saúde , Idoso , Doenças Cardiovasculares/epidemiologia , Demência/epidemiologia , Demência/etiologia , Feminino , Disparidades nos Níveis de Saúde , Indicadores Básicos de Saúde , Humanos , Masculino , Análise de Mediação , Características de Residência/estatística & dados numéricosRESUMO
BACKGROUND: Falls contribute to impairments in activities of daily living (ADLs), resulting in significant declines in the quality of life, safety, and functioning of older adults. Understanding the magnitude and duration of the effect of falls on ADLs, as well as identifying the characteristics of older adults more likely to have post-fall ADL impairment is critical to inform fall prevention and post-fall intervention. The purpose of this study is to 1) Quantify the association between falls and post-fall ADL impairment and 2) Model trajectories of ADL impairment pre- and post-fall to estimate the long-term impact of falls and identify characteristics of older adults most likely to have impairment. METHOD: Study participants were from the Ginkgo Evaluation of Memory Study, a randomized controlled trial in older adults (age 75+) in the United States. Self-reported incident falls and ADL scores were ascertained every 6 months over a 7-year study period. We used Cox proportional hazards analyses (n = 2091) to quantify the association between falls and ADL impairment and latent class trajectory modeling (n = 748) to visualize trajectories of ADL impairment pre-and post-fall. RESULTS: Falls reported in the previous 6 months were associated with impairment in ADLs (HR: 1.42; 95% CI 1.32, 1.52) in fully adjusted models. Based on trajectory modeling (n = 748), 19% (n = 139) of participants had increased, persistent ADL impairment after falling. Participants who were female, lived in a neighborhood with higher deprivation, or experienced polypharmacy were more likely to have ADL impairment post-fall. CONCLUSIONS: Falls are associated with increased ADL impairment, and this impairment can persist over time. It is crucial that all older adults, and particularly those at higher risk of post-fall ADL impairment have access to comprehensive fall risk assessment and evidence-based fall prevention interventions, to help mitigate the negative impacts on ADL function.
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Atividades Cotidianas , Qualidade de Vida , Idoso , Feminino , Humanos , Masculino , Estudos de Coortes , Estudos Retrospectivos , Ensaios Clínicos Controlados Aleatórios como AssuntoRESUMO
Background: Growing evidence links air pollution exposure to the risk of dementia. We hypothesized that hypertension may partially mediate this effect. Methods: We previously documented an association between air pollution and dementia in the Ginkgo Evaluation of Memory Study, a randomized, placebo-controlled trial of 3069 adults ≥75 years across four US sites who were evaluated for dementia every 6 months from 2000-2008. We utilized a two-stage regression approach for causal mediation analysis to decompose the total effect of air pollution on dementia into its natural direct and indirect effect through prevalent hypertension. Exposure to air pollution in the 10 or 20 years before enrollment was assigned using estimates from fine-scale spatial-temporal models for PM2.5, PM10, and NO2. We used Poisson regression models for hypertension and Cox proportional hazard models for time-to-incident all-cause dementia, adjusting for a priori confounders. Results: Participants were free of mild cognitive impairment at baseline (n = 2564 included in analyses); 69% had prevalent hypertension at baseline. During follow-up, 12% developed all-cause dementia (Alzheimer's disease [AD] = 212; vascular dementia with or without AD [VaD/AD mixed] = 97). We did not find an adverse effect of any air pollutant on hypertension. Hypertension was associated with VaD/AD mixed (HR, 1.92 [95% CI = 1.14, 3.24]) but not AD. We did not observe mediation through hypertension for the effect of any pollutant on dementia outcomes. Conclusions: The lack of mediated effect may be due to other mechanistic pathways and the minimal effect of air pollution on hypertension in this cohort of older adults.
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Air pollution has been linked to Alzheimer's disease and related dementias (ADRD), but the mechanisms connecting air pollution to ADRD have not been firmly established. Air pollution may cause oxidative stress and neuroinflammation and contribute to the deposition of amyloid beta (Aß) in the brain. We examined the association between fine particulate matter<2.5 µm in diameter (PM2.5), particulate matter<10 µm in diameter (PM10), nitrogen dioxide (NO2), and plasma based measures of Aß1-40, Aß1-42 and Aß1-42/Aß1-40 using data from 3044 dementia-free participants of the Ginkgo Evaluation of Memory Study (GEMS). Air pollution exposures were estimated at residential addresses that incorporated address histories dating back to 1980, resulting in one-, five-, 10- and 20- year exposure averages. Aß was measured at baseline (2000-2002) and then again at the end of the study (2007-2008) allowing for linear regression models to assess cross-sectional associations and linear random effects models to evaluate repeated measures. After adjustment for socio-demographic and behavioral covariates, we found small positive associations between each air pollutant and Aß1-40 but no association with Aß1-42 or the ratio measures in cross sectional analysis. In repeat measures analysis, we found larger positive associations between each air pollutant and all three outcomes. We observed a 4.43% (95% CI 3.26%, 5.60%) higher Aß1-40 level, 9.73% (6.20%, 13.38%) higher Aß1-42 and 1.57% (95% CI: 0.94%, 2.20%) higher Aß1-42/Aß1-40 ratio associated with a 2 µg/m3 higher 20-year average PM2.5. Associations with other air pollutants were similar. Our study contributes to the broader evidence base on air pollution and ADRD biomarkers by evaluating longer air pollution exposure averaging periods to better mimic disease progression and provides a modifiable target for ADRD prevention.
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Poluentes Atmosféricos , Poluição do Ar , Humanos , Idoso , Peptídeos beta-Amiloides/análise , Estudos Transversais , Ginkgo biloba , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Material Particulado/efeitos adversos , Material Particulado/análise , Dióxido de Nitrogênio/efeitos adversos , Dióxido de Nitrogênio/análise , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análiseRESUMO
Evidence suggests exposure to air pollution increases the risk of dementia. Cognitively stimulating activities and social interactions, made available through the social environment, may slow cognitive decline. We examined whether the social environment buffers the adverse effect of air pollution on dementia in a cohort of older adults. Methods: This study draws from the Ginkgo Evaluation of Memory Study. Participants aged 75 years and older were enrolled between 2000 and 2002 and evaluated for dementia semi-annually through 2008. Long-term exposure to particulate matter and nitrogen dioxide was assigned from spatial and spatiotemporal models. Census tract-level measures of the social environment and individual measures of social activity were used as measures of the social environment. We generated Cox proportional hazard models with census tract as a random effect and adjusted for demographic and study visit characteristics. Relative excess risk due to interaction was estimated as a qualitative measure of additive interaction. Results: This study included 2,564 individuals. We observed associations between increased risk of dementia and fine particulate matter (µg/m3), coarse particulate matter (µg/m3), and nitrogen dioxide (ppb); HRs per 5 unit increase were 1.55 (1.01, 2.18), 1.31 (1.07, 1.60), and 1.18 (1.02, 1.37), respectively. We found no evidence of additive interaction between air pollution and the neighborhood social environment. Conclusions: We found no consistent evidence to suggest a synergistic effect between exposure to air pollution and measures of the social environment. Given the many qualities of the social environment that may reduce dementia pathology, further examination is encouraged.
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Introduction: Research focusing on cognitive aging and dementia is a global endeavor. However, cross-national differences in cognition are embedded in other sociocultural differences, precluding direct comparisons of test scores. Such comparisons can be facilitated by co-calibration using item response theory (IRT). The goal of this study was to explore, using simulation, the necessary conditions for accurate harmonization of cognitive data. Method: Neuropsychological test scores from the US Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS) were subjected to IRT analysis to estimate item parameters and sample means and standard deviations. These estimates were used to generate simulated item response patterns under 10 scenarios that adjusted the quality and quantity of linking items used in harmonization. IRT-derived factor scores were compared to the known population values to assess bias, efficiency, accuracy, and reliability of the harmonized data. Results: The current configuration of HRS and MHAS data was not suitable for harmonization, as poor linking item quality led to large bias in both cohorts. Scenarios with more numerous and higher quality linking items led to less biased and more accurate harmonization. Discussion: Linking items must possess low measurement error across the range of latent ability for co-calibration to be successful. HIGHLIGHTS: We developed a statistical simulation platform to evaluate the degree to which cross-sample harmonization accuracy varies as a function of the quality and quantity of linking items.Two large studies of aging-one in Mexico and one in the United States-use three common items to measure cognition.These three common items have weak correspondence with the ability being measured and are all low in difficulty.Harmonized scores derived from the three common linking items will provide biased and inaccurate estimates of cognitive ability.Harmonization accuracy is greatest when linking items vary in difficulty and are strongly related to the ability being measured.
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Typically, progressive supranuclear palsy (PSP) is clinically characterized by slow vertical saccades or supranuclear gaze palsy, levodopa-resistant parkinsonism with predominant axial symptoms, and cognitive executive impairment. Over the past decades, various PSP phenotypes, including PSP with predominant parkinsonism, PSP with corticobasal syndrome, PSP with progressive gait freezing, and PSP with predominant frontal dysfunction, have been identified from pathologically confirmed cases. Expanding knowledge led to new diagnostic criteria for PSP that with increased disease awareness led to increased PSP prevalence estimates. The identification of environmental and modifiable risk factors creates an opportunity to intervene and delay the onset of PSP or slow disease progression. To date, despite the increasing number of publications assessing risk factors for PSP, few articles have focused on environmental and lifestyle risk factors for this disorder. In this article, we reviewed the literature investigating the relationship between PSP and several environmental and other modifiable lifestyle risk factors. In our review, we found that exposures to toxins related to diet, metals, well water, and hypertension were associated with increased PSP risk. In contrast, higher education and statins may be protective. Further case-control studies are encouraged to determine the exact role of these factors in the etiopathogenesis of PSP, which in turn would inform strategies to prevent and reduce the burden of PSP.
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Air pollution may increase risk of Alzheimer's disease and related dementias (ADRD) in the U.S., but the extent of this relationship is unclear. Here, we constructed two national U.S. population-based cohorts of those aged ≥65 from the Medicare Chronic Conditions Warehouse (2000-2018), combined with high-resolution air pollution datasets, to investigate the association of long-term exposure to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with dementia and AD incidence, respectively. We identified ~2.0 million incident dementia cases (N = 12,233,371; dementia cohort) and ~0.8 million incident AD cases (N = 12,456,447; AD cohort). Per interquartile range (IQR) increase in the 5-year average PM2.5 (3.2 µg/m3), NO2 (11.6 ppb), and warm-season O3 (5.3 ppb) over the past 5 years prior to diagnosis, the hazard ratios (HRs) were 1.060 (95% confidence interval [CI]: 1.054, 1.066), 1.019 (95% CI: 1.012, 1.026), and 0.990 (95% CI: 0.987, 0.993) for incident dementias, and 1.078 (95% CI: 1.070, 1.086), 1.031 (95% CI: 1.023, 1.039), and 0.982 (95%CI: 0.977, 0.986) for incident AD, respectively, for the three pollutants. For both outcomes, concentration-response relationships for PM2.5 and NO2 were approximately linear. Our study suggests that exposures to PM2.5 and NO2 are associated with incidence of dementia and AD.
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Poluição do Ar/efeitos adversos , Demência/epidemiologia , Exposição Ambiental/efeitos adversos , Idoso , Idoso de 80 Anos ou mais , Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/estatística & dados numéricos , Demência/etiologia , Exposição Ambiental/estatística & dados numéricos , Monitoramento Ambiental/estatística & dados numéricos , Feminino , Seguimentos , Humanos , Incidência , Masculino , Material Particulado/efeitos adversos , Fatores de Risco , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: Hispanics/Latinos in the United States are more likely to live in neighborhoods with greater exposure to air pollution and are projected to have the largest increase in dementia among race/ethnic minority groups. OBJECTIVE: We examined the associations of air pollution with performance on cognitive function tests in Hispanic/Latino adults. METHODS: We used data from the San Diego site of the Hispanic Community Health Study/Study of Latinos, an ongoing cohort of Hispanics/Latinos. This analysis focused on individuals ≥45 years of age who completed a neurocognitive battery examining overall mental status, verbal learning, memory, verbal fluency, and executive function (nâ=â2,089). Air pollution (PM2.5 and O3) before study baseline was assigned to participants' zip code. Logistic and linear regression were used to estimate the associations of air pollution on overall mental status and domain-specific standardized test scores. Models accounted for complex survey design, demographic, and socioeconomic characteristics. RESULTS: We found that for every 10µg/m3 increase in PM2.5, verbal fluency worsened (ß: -0.21 [95%CI: -0.68, 0.25]). For every 10 ppb increase in O3, verbal fluency and executive function worsened (ß: -0.19 [95%CI: -0.34, -0.03]; ß: -0.01 [95%CI: -0.01, 0.09], respectively). We did not identify any detrimental effect of pollutants on other domains. CONCLUSION: Although we found suggestions that air pollution may impact verbal fluency and executive function, we observed no consistent or precise evidence to suggest an adverse impact of air pollution on cognitive level among this cohort of Hispanic/Latino adults.
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Poluição do Ar/efeitos adversos , Cognição , Exposição Ambiental/efeitos adversos , Adulto , Idoso , California , Estudos de Coortes , Feminino , Hispânico ou Latino , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
Wildfire smoke adversely impacts respiratory health as fine particles can penetrate deeply into the lungs. Epidemiological studies of differential impacts typically target population subgroups in terms of vulnerability to wildfire smoke. Such information is useful to customize smoke warnings and mitigation actions for specific groups of individuals. In addition to individual vulnerability, it is also important to assess spatial patterns of health impacts to identify vulnerable communities and tailor public health actions during wildfire smoke events. METHODS: We assess the spatiotemporal variation in respiratory hospitalizations in San Diego County during a set of major wildfires in 2007, which led to a substantial public health burden. We propose a spatial within-community matched design analysis, adapted to the study of wildfire impacts, coupled with a Bayesian Hierarchical Model, that explicitly considers the spatial variation of respiratory health associated with smoke exposure, compared to reference periods before and after wildfires. We estimate the signal-to-noise ratio to ultimately gauge the precision of the Bayesian model output. RESULTS: We find the highest excess hospitalizations in areas covered by smoke, mainly ZIP codes contained by and immediately downwind of wildfire perimeters, and that excess hospitalizations tend to follow the distribution of smoke plumes across space (ZIP codes) and time (days). CONCLUSIONS: Analyzing the spatiotemporal evolution of exposure to wildfire smoke is necessary due to variations in smoke plume extent, particularly in this region where the most damaging wildfires are associated with strong wind conditions.
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Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region's most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures.
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BACKGROUND: Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy. OBJECTIVES: To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB. METHODS: California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB. RESULTS: In total, 1,967,300 births were included in this study. For PM2.5, PM10 and O3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e., shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves. CONCLUSION: This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
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BACKGROUND: Preterm birth is a leading cause of infant morbidity and mortality. Identifying potentially modifiable triggers toward the end of gestation, such as extreme heat, can improve understanding of the role of acute stress on early deliveries and inform warning systems. In this study we examined the association between extreme heat, variously defined during the last week of gestation, and risk of preterm birth among mothers in California. METHODS: We created a population-based cohort comprised of 1,967,300 mothers who had live, singleton births in California, from May through September 2005-2013. Daily temperature data estimated at the maternal zip code of residence was used to create 12 definitions of extreme heat with varying relative temperatures (75th, 90th, 95th, and 98th percentiles) and durations (at least 2, 3, or 4 consecutive days). We estimated risk of preterm birth (<37 gestational weeks) in relation to exposure to extreme heat during the last week of gestation with multi-level Cox proportional hazard regression models, adjusting for maternal characteristics, sex of neonate, and seasonality. We also included randomly generated data, SAS code, and estimates for reproducibility purposes. RESULTS: Approximately 7% of the cohort had a preterm birth. For all definitions of extreme heat, the risk of preterm birth was consistently higher among mothers who experienced an extreme heat episode during their last week of gestation. Hazard ratios ranged from 1.008 (95% CI: 0.997, 1.021) to 1.128 (95% CI: 1.052, 1.210), with increasing associations as the relative temperature and duration of extreme heat episode increased. CONCLUSION: This study adds to the previous literature by considering multiple definitions of extreme heat and applying a time-to-event framework. Findings suggest that acute exposure to extreme heat during the last week of gestation may trigger an earlier delivery. Implementing heat warning systems targeted toward pregnant women may improve birth outcomes.
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Calor Extremo , Nascimento Prematuro , California/epidemiologia , Calor Extremo/efeitos adversos , Feminino , Humanos , Recém-Nascido , Gravidez , Terceiro Trimestre da Gravidez , Nascimento Prematuro/epidemiologia , Reprodutibilidade dos Testes , TemperaturaRESUMO
BACKGROUND: Evidence suggests a link between air pollution and dementia. Cardiovascular disease (CVD) may be a potential determinant of dementia. This motivated us to quantify the contribution of CVD to the association between air pollution and dementia. METHODS: A cohort of Canadian-born residents of Ontario, who participated in the 1996-2003 Canadian Community Health Surveys, was followed through 2013 or until dementia diagnosis. Exposure to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) was estimated with a 3-year average and 5-year lag before dementia diagnosis. Incident CVD was evaluated as a mediator. We used multi-level Cox proportional and Aalen additive hazard regression models, adjusting for individual- and neighbourhood-level risk factors to estimate associations with NO2 and PM2.5. We estimated the total, direct and indirect effects of air pollution on dementia through cardiovascular disease. RESULTS: This study included 34 391 older adults. At baseline, the mean age of this cohort was 59 years. The risk of dementia was moderately higher among those more exposed to NO2 (hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.99-1.19; and 100 additional cases per 100 000 [standard error (SE) <100x10-5]) and PM2.5 [(HR 1.29, 95% CI 0.99-1.64; 200 additional cases per 100 000] [SE 100x10-5]) after adjusting for covariates; however, these estimates are imprecise. A greater proportion of the relationship between PM2.5 and dementia was mediated through CVD than NO2 for both scales. CONCLUSIONS: These results suggest some of the association between air pollution and dementia is mediated through CVD, indicating that improving cardiovascular health may prevent dementia in areas with higher exposure to air pollution.
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Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Doenças Cardiovasculares/epidemiologia , Demência/epidemiologia , Exposição Ambiental/estatística & dados numéricos , Material Particulado/efeitos adversos , Idoso , Poluição do Ar/estatística & dados numéricos , Estudos de Coortes , Demência/diagnóstico , Exposição Ambiental/efeitos adversos , Feminino , Inquéritos Epidemiológicos , Humanos , Masculino , Pessoa de Meia-Idade , Ontário/epidemiologia , Avaliação de Resultados em Cuidados de Saúde , Ozônio/análise , Material Particulado/análise , Vigilância da PopulaçãoRESUMO
BACKGROUND: Living in greener areas of cities was linked to increased physical activity levels, improved mental well-being, and lowered harmful environmental exposures, all of which may affect human health. However, whether living in greener areas may be associated with lower risk of cardiovascular disease incidence, progression, and premature mortality is unclear. OBJECTIVES: We conducted a cohort study to examine the associations between residential green spaces and the incidence of acute myocardial infarction (AMI) and heart failure (HF), post-AMI and HF hospital readmissions, and mortality. METHODS: We simultaneously followed four large population-based cohorts in Ontario, Canada, including the entire adult population, adults free of AMI and HF, and survivors of AMI or HF from 2000 to 2014. We estimated residential exposure to green spaces using satellite-derived observations and ascertained health outcomes using validated disease registries. We estimated the associations using spatial random-effects Cox proportional hazards models. We conducted various sensitivity analyses, including further adjusting for property values and performing exploratory mediation analysis. RESULTS: Each interquartile range increase in residential greenness was associated with a 7% [95% confidence interval (CI): 4%, 9%] decrease in incident AMI and a 6% (95% CI: 4%, 7%) decrease in incident HF. Residential greenness was linked to a â¼10% decrease in cardiovascular mortality in both adults free of AMI and HF and the entire adult population. These associations remained consistent in sensitivity analyses and were accentuated among younger adults. Additionally, we estimated that the decreases in AMI and HF incidence associated with residential greenness explained â¼53% of the protective association between residential greenness and cardiovascular mortality. Conversely, residential greenness was not associated with any delay in readmission or mortality among AMI and HF patients. CONCLUSIONS: Living in urban areas with more green spaces was associated with improved cardiovascular health in people free of AMI and HF but not among individuals who have already developed these conditions. https://doi.org/10.1289/EHP6161.
Assuntos
Ambiente Construído , Doenças Cardiovasculares/epidemiologia , Exposição Ambiental/estatística & dados numéricos , Adulto , Cidades , Estudos de Coortes , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Ontário/epidemiologia , Readmissão do Paciente , Modelos de Riscos Proporcionais , Características de ResidênciaRESUMO
BACKGROUND: Exposure to fine particulate matter (PM2.5) during pregnancy has been shown to be associated with reduced birth weight and racial/ethnic minorities have been found to be more vulnerable. Previous studies have focused on the mean value of birth weight associated with PM2.5, which may mask meaningful differences. We applied a quantile regression approach to investigate the variation by percentile of birth weight and compared non-Hispanic (NH) Black, NH White, and Hispanic mothers. METHODS: Data for singleton births in California from October 24, 2005 to February 27, 2010 were collected from the birth records accessed from the California Department of Public Health. Air pollution monitoring data collected by the California Air Resources Board and interpolated for each zip code using an inverse-distance weighting approach, and linked to maternal zip code of residence reported on the birth certificate. Multilevel linear regression models were conducted with mother's residential zip code tabulation area as a random effect. Multilevel quantile regression models were used to analyze the association at different percentiles of birth weight (5th, 10th, 25th, 50th, 75th, 90th, 95th), as well as examine the heterogeneity in this association between racial/ethnic groups. RESULTS: Linear regression revealed that a 10 µg/m3 increase in PM2.5 exposure during pregnancy is associated with a mean birth weight decrease of 7.31 g [95% confidence interval (CI): 8.10, 6.51] and NH Black mothers are the most vulnerable. Results of the quantile regression are not constant across quantiles. For NH Black mothers whose infants had the lowest birthweight of less than 2673 g (5th percentile), a 10 µg/m3 increase in PM2.5 exposure is associated with a decrease of 18.57 g [95% CI: 22.23, 14.91], while it is associated with a decrease of 7.77 g [95% CI: 8.73, 6.79] for NH White mothers and 7.76 [8.52, 7.00] decrease for Hispanic mothers at the same quantile. CONCLUSION: Results of the quantile regression revealed greater disparities, particularly for infants with the lowest birth weight. By identifying vulnerable populations, we can promote and implement policies to confront these health disparities.