143 research outputs found

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

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    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

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

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    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

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

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    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

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

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    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