Short-term Changes in Ambient Particulate Matter and Risk of Stroke: A Systematic Review and Meta-analysis

Background Stroke is a leading cause of death and long‐term disability in the United States. There is a well‐documented association between ambient particulate matter air pollution (PM) and cardiovascular disease morbidity and mortality. Given the pathophysiologic mechanisms of these effects, short‐term elevations in PM may also increase the risk of ischemic and/or hemorrhagic stroke morbidity and mortality, but the evidence has not been systematically reviewed. Methods and Results We provide a comprehensive review of all observational human studies (January 1966 to January 2014) on the association between short‐term changes in ambient PM levels and cerebrovascular events. We also performed meta‐analyses to evaluate the evidence for an association between each PM size fraction (PM2.5, PM10, PM2.5‐10) and each outcome (total cerebrovascular disease, ischemic stroke/transient ischemic attack, hemorrhagic stroke) separately for mortality and hospital admission. We used a random‐effects model to estimate the summary percent change in relative risk of the outcome per 10‐μg/m3 increase in PM. Conclusions We found that PM2.5 and PM10 are associated with a 1.4% (95% CI 0.9% to 1.9%) and 0.5% (95% CI 0.3% to 0.7%) higher total cerebrovascular disease mortality, respectively, with evidence of inconsistent, nonsignificant associations for hospital admission for total cerebrovascular disease or ischemic or hemorrhagic stroke. Current limited evidence does not suggest an association between PM2.5‐10 and cerebrovascular mortality or morbidity. We discuss the potential sources of variability in results across studies, highlight some observations, and identify gaps in literature and make recommendations for future studies

Residential proximity to major roadways and prevalent hypertension among postmenopausal women: results from the Women's Health Initiative San Diego Cohort.

BackgroundLiving near major roadways has been linked with increased risk of cardiovascular events and worse prognosis. Residential proximity to major roadways may also be associated with increased risk of hypertension, but few studies have evaluated this hypothesis.Methods and resultsWe examined the cross-sectional association between residential proximity to major roadways and prevalent hypertension among 5401 postmenopausal women enrolled into the San Diego cohort of the Women's Health Initiative. We used modified Poisson regression with robust error variance to estimate the association between prevalence of hypertension and residential distance to nearest major roadway, adjusting for participant demographics, medical history, indicators of individual and neighborhood socioeconomic status, and for local supermarket/grocery and fast food/convenience store density. The adjusted prevalence ratios for hypertension were 1.22 (95% CI: 1.07, 1.39), 1.13 (1.00, 1.27), and 1.05 (0.99, 1.12) for women living ≤100, >100 to 200, and >200 to 1000 versus >1000 m from a major roadway (P for trend=0.006). In a model treating the natural log of distance to major roadway as a continuous variable, a shift in distance from 1000 to 100 m from a major roadway was associated with a 9% (3%, 16%) higher prevalence of hypertension.ConclusionsIn this cohort of postmenopausal women, residential proximity to major roadways was positively associated with the prevalence of hypertension. If causal, these results suggest that living close to major roadways may be an important novel risk factor for hypertension

Assessing the causal effects of a stochastic intervention in time series data: Are heat alerts effective in preventing deaths and hospitalizations?

We introduce a new causal inference framework for time series data aimed at assessing the effectiveness of heat alerts in reducing mortality and hospitalization risks. We are interested in addressing the following question: how many deaths and hospitalizations could be averted if we were to increase the frequency of issuing heat alerts in a given location? In the context of time series data, the overlap assumption - each unit must have a positive probability of receiving the treatment - is often violated. This is because, in a given location, issuing a heat alert is a rare event on an average temperature day as heat alerts are almost always issued on extremely hot days. To overcome this challenge, first we introduce a new class of causal estimands under a stochastic intervention (i.e., increasing the odds of issuing a heat alert) for a single time series corresponding to a given location. We develop the theory to show that these causal estimands can be identified and estimated under a weaker version of the overlap assumption. Second, we propose nonparametric estimators based on time-varying propensity scores, and derive point-wise confidence bands for these estimators. Third, we extend this framework to multiple time series corresponding to multiple locations. Via simulations, we show that the proposed estimator has good performance with respect to bias and root mean squared error. We apply our proposed method to estimate the causal effects of increasing the odds of issuing heat alerts in reducing deaths and hospitalizations among Medicare enrollees in 2817 U.S. counties. We found weak evidence of a causal link between increasing the odds of issuing heat alerts during the warm seasons of 2006-2016 and a reduction in deaths and cause-specific hospitalizations across the 2817 counties.Comment: 31 pages, 5 figures, 2 table

Heat, Heat Waves, and Hospital Admissions among the Elderly in the United States, 1992–2006

Background: Heat-wave frequency, intensity, and duration are increasing with global climate change. The association between heat and mortality in the elderly is well documented, but less is known regarding associations with hospital admissions. Objectives: Our goal was to determine associations between moderate and extreme heat, heat waves, and hospital admissions for nonaccidental causes among Medicare beneficiaries ≥ 65 years of age in 114 cities across five U.S. climate zones. Methods: We used Medicare inpatient billing records and city-specific data on temperature, humidity, and ozone from 1992 through 2006 in a time-stratified case-crossover design to estimate the association between hospitalization and moderate [90th percentile of apparent temperature (AT)] and extreme (99th percentile of AT) heat and heat waves (AT above the 95th percentile over 2–8 days). In sensitivity analyses, we additionally considered confounding by ozone and holidays, different temperature metrics, and alternate models of the exposure–response relationship. Results: Associations between moderate heat and hospital admissions were minimal, but extreme heat was associated with a 3% (95% CI: 2%, 4%) increase in all-cause hospital admissions over the subsequent 8 days. In cause-specific analyses, extreme heat was associated with increased hospitalizations for renal (15%; 95% CI: 9%, 21%) and respiratory (4%; 95% CI: 2%, 7%) diseases, but not for cardiovascular diseases. An added heat-wave effect was observed for renal and respiratory admissions. Conclusion: Extreme heat is associated with increased hospital admissions, particularly for renal causes, among the elderly in the United States. Citation: Gronlund CJ, Zanobetti A, Schwartz JD, Wellenius GA, O’Neill MS. 2014. Heat, heat waves, and hospital admissions among the elderly in the United States, 1992–2006. Environ Health Perspect 122:1187–1192; http://dx.doi.org/10.1289/ehp.120613

Infectious Disease in a Warming World: How Weather Influenced West Nile Virus in the United States (2001–2005)

Background: The effects of weather on West Nile virus (WNV) mosquito populations in the United States have been widely reported, but few studies assess their overall impact on transmission to humans. Objectives: We investigated meteorologic conditions associated with reported human WNV cases in the United States. Methods: We conducted a case–crossover study to assess 16,298 human WNV cases reported to the Centers for Disease Control and Prevention from 2001 to 2005. The primary outcome measures were the incidence rate ratio of disease occurrence associated with mean weekly maximum temperature, cumulative weekly temperature, mean weekly dew point temperature, cumulative weekly precipitation, and the presence of ≥ 1 day of heavy rainfall (≥ 50 mm) during the month prior to symptom onset. Results: Increasing weekly maximum temperature and weekly cumulative temperature were similarly and significantly associated with a 35–83% higher incidence of reported WNV infection over the next month. An increase in mean weekly dew point temperature was significantly associated with a 9–38% higher incidence over the subsequent 3 weeks. The presence of at least 1 day of heavy rainfall within a week was associated with a 29–66% higher incidence during the same week and over the subsequent 2 weeks. A 20-mm increase in cumulative weekly precipitation was significantly associated with a 4–8% increase in incidence of reported WNV infection over the subsequent 2 weeks. Conclusions: Warmer temperatures, elevated humidity, and heavy precipitation increased the rate of human WNV infection in the United States independent of season and each others’ effects

Short-Term Changes in Ambient Temperature and Risk of Ischemic Stroke

Background: Despite consistent evidence of a higher short-term risk of cardiovascular mortality associated with ambient temperature, there have been discrepant findings on the association between temperature and ischemic stroke. Moreover, few studies have considered potential confounding by ambient fine particulate matter air pollution <2.5 μm in diameter (PM2.5) and none have examined the impact of temperature changes on stroke in the subsequent hours rather than days. The aim of this study was to evaluate whether changes in temperature trigger an ischemic stroke in the following hours and days and whether humid days are particularly harmful. Methods: We reviewed the medical records of 1,705 patients residing in the metropolitan region of Boston, Mass., USA, who were hospitalized with neurologist-confirmed ischemic stroke, and we abstracted data on the time of symptom onset and clinical characteristics. We obtained hourly meteorological data from the National Weather Service station and hourly PM2.5 data from the Harvard ambient monitoring station. We used the time-stratified case-crossover design to assess the association between ischemic stroke and apparent temperature averaged over 1-7 days prior to stroke onset adjusting for PM2.5. We assessed whether differences in apparent temperature trigger a stroke within shorter time periods by examining the association between stroke onset and apparent temperature levels averaged in 2-hour increments prior to stroke onset (0-2 h through 36-38 h). We tested whether the association varied by health characteristics or by PM2.5, ozone or relative humidity. Results: The incidence rate ratio of ischemic stroke was 1.09 (95% confidence interval 1.01-1.18) following a 5°C decrement in average apparent temperature over the 2 days preceding symptom onset. The higher risk associated with cooler temperatures peaked in the first 14-34 h. There was no statistically significant difference in the association between temperature and ischemic stroke across seasons. The risk of ischemic stroke was not meaningfully different across subgroups of patients defined by health characteristics. The association between ischemic stroke and ambient temperature was stronger on days with higher levels of relative humidity. Conclusions: Lower temperatures are associated with a higher risk of ischemic stroke onset in both warm and cool seasons, and the risk is higher on days with higher levels of relative humidity. Based on this study and the body of literature on ambient temperature and cardiovascular events, identifying methods for mitigating cardiovascular risk may be warranted

Structural equation modeling of parasympathetic and sympathetic response to traffic air pollution in a repeated measures study

Background: Traffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV). The association between traffic-related pollution and HRV, however, has varied by traffic-related or HRV marker as well as by study, suggesting the need for a more comprehensive and integrative approach to examining air pollution-mediated biological impacts on these outcomes. In a Bayesian framework, we examined the effect of traffic pollution on HRV using structural equation models (SEMs) and looked at effect modification by participant characteristics. Methods: We studied measurements of 5 HRV markers [high frequency (HF), low frequency (LF), 5-min standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive normal-to-normal intervals (rMSSD), and LF/HF ratio (LF/HF)] for 700 elderly men from the Normative Aging Study. Using SEMs, we fit a latent variable for traffic pollution that is reflected by levels of carbon monoxide, nitrogen monoxide, nitrogen dioxide, and black carbon (BC) to estimate its effect on latent variable for parasympathetic tone that included HF, SDNN and rMSSD, and the sympathetic tone marker, LF/HF. Exposure periods were assessed using 4-, 24-, 48-, 72-hour moving average pre-visit. We compared our main effect findings using SEMs with those obtained using linear mixed models. Results: Traffic pollution was not associated with mean parasympathetic tone and LF/HF for all examined moving averages. In Bayesian linear mixed models, however, BC was related to increased LF/HF, an inter quartile range (IQR) increase in BC was associated with a 6.5% (95% posterior interval (PI): -0.7%, 14.2%) increase in mean LF/HF 24-hours later. The strongest association observed was for the 4-hour moving average (10.1%; 95% PI: 3.0%, 17.6%). The effect of traffic on parasympathetic tone was stronger among diabetic as compared to non-diabetic participants. Specifically, an IQR increase in traffic pollution in the 48-hr prior to the clinic visit was associated with a 44.3% (95% PI: -67.7%, -4.2%) lower mean parasympathetic tone among diabetics, and a 7.7% (95% PI: -18.0%, 41.4%) higher mean parasympathetic tone among non-diabetics. Conclusions: BC was associated with adverse changes LF/HF in the elderly. Traffic pollution may decrease parasympathetic tone among diabetic elderly

Ambient Temperature and Biomarkers of Heart Failure: A Repeated Measures Analysis

Background: Extreme temperatures have been associated with hospitalization and death among individuals with heart failure, but few studies have explored the underlying mechanisms. Objectives: We hypothesized that outdoor temperature in the Boston, Massachusetts, area (1- to 4-day moving averages) would be associated with higher levels of biomarkers of inflammation and myocyte injury in a repeated-measures study of individuals with stable heart failure. Methods: We analyzed data from a completed clinical trial that randomized 100 patients to 12 weeks of tai chi classes or to time-matched education control. B-type natriuretic peptide (BNP), C-reactive protein (CRP), and tumor necrosis factor (TNF) were measured at baseline, 6 weeks, and 12 weeks. Endothelin-1 was measured at baseline and 12 weeks. We used fixed effects models to evaluate associations with measures of temperature that were adjusted for time-varying covariates. Results: Higher apparent temperature was associated with higher levels of BNP beginning with 2-day moving averages and reached statistical significance for 3- and 4-day moving averages. CRP results followed a similar pattern but were delayed by 1 day. A 5°C change in 3- and 4-day moving averages of apparent temperature was associated with 11.3% [95% confidence interval (CI): 1.1, 22.5; :p = 0.03) and 11.4% (95% CI: 1.2, 22.5; p = 0.03) higher BNP. A 5°C change in the 4-day moving average of apparent temperature was associated with 21.6% (95% CI: 2.5, 44.2; p = 0.03) higher CRP. No clear associations with TNF or endothelin-1 were observed. Conclusions: Among patients undergoing treatment for heart failure, we observed positive associations between temperature and both BNP and CRP—predictors of heart failure prognosis and severity

Long-term exposure to ambient air pollution and renal function in African Americans: the Jackson Heart Study

Renal dysfunction is prevalent in the US among African Americans. Air pollution is associated with renal dysfunction in mostly white American populations, but has not been studied among African Americans. We evaluated cross-sectional associations between 1-year and 3-year fine particulate matter (PM2.5) and ozone (O3) concentrations, and renal function among 5090 African American participants in the Jackson Heart Study. We used mixed-effect linear regression to estimate associations between 1-year and 3-year PM2.5 and O3 and estimated glomerular filtration rate (eGFR), urine albumin/creatinine ratio (UACR), serum creatinine, and serum cystatin C, adjusting for: sociodemographic factors, health behaviors, and medical history and accounting for clustering by census tract. At baseline, JHS participants had mean age 55.4 years, and 63.8% were female; mean 1-year and 3-year PM2.5 concentrations were 12.2 and 12.4 µg/m3, and mean 1-year and 3-year O3 concentrations were 40.2 and 40.7 ppb, respectively. Approximately 6.5% of participants had reduced eGFR ( 30 mg/g), both indicating impaired renal function. Annual and 3-year O3 concentrations were inversely associated with eGFR and positively associated with serum creatinine; annual and 3-year PM2.5 concentrations were inversely associated with UACR. We observed impaired renal function associated with increased O3 but not PM2.5 exposure among African Americans