Effect Modification by Environmental Quality on the Association between Heatwaves and Mortality in Alabama, United States.
Ontology highlight
ABSTRACT:
SUBMITTER: Jian Y
PROVIDER: S-EPMC5664644 | biostudies-literature | 2017 Sep
REPOSITORIES: biostudies-literature
Publications
Effect Modification by Environmental Quality on the Association between Heatwaves and Mortality in Alabama, United States.
Jian Yun Y Wu Connor Y H CYH Gohlke Julia M JM
International journal of environmental research and public health 20170928 10
<i>Background</i>: Previous studies have shown that heatwaves are associated with increased mortality. However, it remains unclear whether the associations between heatwaves and mortality are modified by the environmental quality. <i>Methods</i>: We used the United States (US) Environmental Protection Agency's Environmental Quality Index (EQI) and its five domain indices (air, water, land, built, and sociodemographic) to represent the cumulative environmental quality. We applied a time-stratifie ...[more]
Similar Datasets
Project description:Heatwaves are divided between moderate, more common heatwaves and rare "high-mortality" heatwaves that have extremely large health effects per day, which we define as heatwaves with a 20% or higher increase in mortality risk. Better projections of the expected frequency of and exposure to these separate types of heatwaves could help communities optimize heat mitigation and response plans and gauge the potential benefits of limiting climate change. Whether a heatwave is high-mortality or moderate could depend on multiple heatwave characteristics, including intensity, length, and timing. We created heatwave classification models using a heatwave training dataset created using recent (1987-2005) health and weather data from 82 large US urban communities. We built twenty potential classification models and used Monte Carlo cross-validations to evaluate these models. We ultimately identified several models that can adequately classify high-mortality heatwaves. These models can be used to project future trends in high-mortality heatwaves under different scenarios of a changing future (e.g., climate change, population change). Further, these models are novel in the way they allow exploration of different scenarios of adaptation to heat, as they include, as predictive variables, heatwave characteristics that are measured relative to a community's temperature distribution, allowing different adaptation scenarios to be explored by selecting alternative community temperature distributions. The three selected models have been placed on GitHub for use by other researchers, and we use them in a companion paper to project trends in high-mortality heatwaves under different climate, population, and adaptation scenarios.
| S-EPMC5881918 | biostudies-literature
Project description:BackgroundAssessing cumulative effects of the multiple environmental factors influencing mortality remains a challenging task.ObjectivesThis study aimed to examine the associations between cumulative environmental quality and all-cause and leading cause-specific (heart disease, cancer, and stroke) mortality rates.MethodsWe used the overall Environmental Quality Index (EQI) and its five domain indices (air, water, land, built, and sociodemographic) to represent environmental exposure. Associations between the EQI and mortality rates (CDC WONDER) for counties in the contiguous United States (n = 3,109) were investigated using multiple linear regression models and random intercept and random slope hierarchical models. Urbanicity, climate, and a combination of the two were used to explore the spatial patterns in the associations.ResultsWe found 1 standard deviation increase in the overall EQI (worse environment) was associated with a mean 3.22% (95% CI: 2.80%, 3.64%) increase in all-cause mortality, a 0.54% (95% CI: -0.17%, 1.25%) increase in heart disease mortality, a 2.71% (95% CI: 2.21%, 3.22%) increase in cancer mortality, and a 2.25% (95% CI: 1.11%, 3.39%) increase in stroke mortality. Among the environmental domains, the associations ranged from -1.27% (95% CI: -1.70%, -0.84%) to 3.37% (95% CI: 2.90%, 3.84%) for all-cause mortality, -2.62% (95% CI: -3.52%, -1.73%) to 4.50% (95% CI: 3.73%, 5.27%) for heart disease mortality, -0.88% (95% CI: -2.12%, 0.36%) to 3.72% (95% CI: 2.38%, 5.06%) for stroke mortality, and -0.68% (95% CI: -1.19%, -0.18%) to 3.01% (95% CI: 2.46%, 3.56%) for cancer mortality. Air had the largest associations with all-cause, heart disease, and cancer mortality, whereas the sociodemographic index had the largest association with stroke mortality. Across the urbanicity gradient, no consistent trend was found. Across climate regions, the associations ranged from 2.29% (95% CI: 1.87%, 2.72%) to 5.30% (95% CI: 4.30%, 6.30%) for overall EQI, and larger associations were generally found in dry areas for both overall EQI and domain indices.ConclusionsThese results suggest that poor environmental quality, particularly poor air quality, was associated with increased mortality and that associations vary by urbanicity and climate region. Citation: Jian Y, Messer LC, Jagai JS, Rappazzo KM, Gray CL, Grabich SC, Lobdell DT. 2017. Associations between environmental quality and mortality in the contiguous United States, 2000-2005. Environ Health Perspect 125:355-362;?http://dx.doi.org/10.1289/EHP119.
| S-EPMC5332172 | biostudies-literature
Project description:BackgroundThe United States (U.S.) suffers from high infant mortality (IM) rates and there are significant racial/ethnic differences in these rates. Prior studies on the environment and infant mortality are generally limited to singular exposures. We utilize the Environmental Quality Index (EQI), a measure of cumulative environmental exposure (across air, water, land, sociodemographic, and land domains) for U.S. counties from 2000 to 2005, to investigate associations between ambient environment and IM across maternal race/ethnicity.MethodsWe linked 2000-2005 infant data from the U.S. Centers for Disease Control and Prevention to the EQI (n = 22,702,529; 144,741 deaths). We utilized multi-level regression to estimate associations between quartiles of county-level EQI and IM. We also considered associations between quartiles of county level domain specific indices with IM. We controlled for rural-urban status (RUCC1: urban, metropolitan; RUCC2: urban, non-metropolitan; RUCC3: less urbanized; RUCC4: thinly populated), maternal age, maternal education, marital status, infant sex, and stratified on race/ethnicity. Additionally, we estimated associations for linear combinations of environmental quality and rural-urban status.ResultsWe found a mix of positive, negative, and null associations and our findings varied across domain and race/ethnicity. Poorer overall environmental quality was associated with decreased odds among Non-Hispanic whites (OR and 95% CI: EQIQ4 (ref. EQIQ1): 0.84[0.80,0.89]). For Non-Hispanic blacks and Hispanics, some increased odds were observed. Poorer air quality was monotonically associated with increased odds among Non-Hispanic whites (airQ4 (ref. airQ1): 1.05[0.99,1.11]) and blacks (airQ4 (ref. airQ1): 1.09 [0.9,1.31]). Rural status was associated with increased IM odds among Hispanics (RUCC4-Q4:1.36[1.04,1.78]; RUCC1-Q4: 1.04[0.92,1.16], ref. for both RUCC1-Q1).ConclusionsThis study is the first to report on associations between ambient environmental quality and IM across the United States. It corroborates prior research suggesting an association between air pollution and IM and identifies residence in thinly populated (rural) areas as a potential risk factor towards IM amongst Hispanics. Some of the counterintuitive findings highlight the need for additional research into potentially differential drivers of environmental quality across the rural-urban continuum, especially with regards to the sociodemographic environment.
| S-EPMC6191999 | biostudies-literature
Project description:Air pollution is responsible for a wide range of health effects in exposed populations. Variations in local air pollution can affect local population health outcomes. The strict regulations imposed during the peak of the COVID-19 pandemic ('lockdowns') resulted in a unique situation where human mobility was limited significantly, resulting in improved air quality in several major cities. The main goal of this study was to investigate if lockdowns during the COVID-19 pandemic significantly impacted air quality in Birmingham, Alabama-a city with a history of high air pollution levels-with a focus on PM2.5 (Particulate Matter with an aerodynamic diameter ≤2.5 µm) and NO2 (Nitrogen dioxide). Daily air pollutant and traffic data were obtained for the Birmingham Metropolitan Area for the period January to October 2020, and previous years. Mean PM2.5 and NO2 concentrations and traffic volumes during the official city/state lockdown period (24 March to 30 April 2020) were compared to pre- and post-lockdown means. The mean PM2.5 and NO2 concentrations during the lockdown did not significantly differ from that of the pre- or post-lockdown periods. However, NO2 significantly decreased even after the lockdown order was removed, with the mean decreasing significantly compared to pre-lockdown and lockdown periods. Both PM2.5 and NO2 annual means in 2020 were significantly lower than the annual means in 2019, indicating the occurrence of significant changes over the longer term that were not limited by defined lockdown periods. Traffic significantly increased after the lockdown order was removed but did not correlate with the two pollutants studied. Therefore, we conclude that the Stay at Home/lockdown regulations and other COVID-19 restrictions had an impact on the air quality of Birmingham Alabama; although these lockdown impacts varied for each pollutant and were not limited only by the official lockdown dates/periods.
| S-EPMC8951610 | biostudies-literature
Project description:A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data.
| S-EPMC4577202 | biostudies-other
Project description:ImportanceSelf-injury mortality (SIM) combines suicides and the preponderance of drug misuse-related overdose fatalities. Identifying social and environmental factors associated with SIM and suicide may inform etiologic understanding and intervention design.ObjectiveTo identify factors associated with interstate SIM and suicide rate variation and to assess potential for differential suicide misclassification.Design, setting, and participantsThis cross-sectional study used a partial panel time series with underlying cause-of-death data from 50 US states and the District of Columbia for 1999-2000, 2007-2008, 2013-2014 and 2018-2019. Applying data from the Centers for Disease Control and Prevention, SIM includes all suicides and the preponderance of unintentional and undetermined drug intoxication deaths, reflecting self-harm behaviors. Data were analyzed from February to June 2021.ExposuresExposures included inequity, isolation, demographic characteristics, injury mechanism, health care access, and medicolegal death investigation system type.Main outcomes and measuresThe main outcome, SIM, was assessed using unstandardized regression coefficients of interstate variation associations, identified by the least absolute shrinkage and selection operator; ratios of crude SIM to suicide rates per 100 000 population were assessed for potential differential suicide misclassification.ResultsA total of 101 325 SIMs were identified, including 74 506 (73.5%) among males and 26 819 (26.5%) among females. SIM to suicide rate ratios trended upwards, with an accelerating increase in overdose fatalities classified as unintentional or undetermined (SIM to suicide rate ratio, 1999-2000: 1.39; 95% CI, 1.38-1.41; 2018-2019: 2.12; 95% CI, 2.11-2.14). Eight states recorded a SIM to suicide rate ratio less than 1.50 in 2018-2019 vs 39 states in 1999-2000. Northeastern states concentrated in the highest category (range, 2.10-6.00); only the West remained unrepresented. Least absolute shrinkage and selection operator identified 8 factors associated with the SIM rate in 2018-2019: centralized medical examiner system (β = 4.362), labor underutilization rate (β = 0.728), manufacturing employment (β = -0.056), homelessness rate (β = -0.125), percentage nonreligious (β = 0.041), non-Hispanic White race and ethnicity (β = 0.087), prescribed opioids for 30 days or more (β = 0.117), and percentage without health insurance (β = -0.013) and 5 factors associated with the suicide rate: percentage male (β = 1.046), military veteran (β = 0.747), rural (β = 0.031), firearm ownership (β = 0.030), and pain reliever misuse (β = 1.131).Conclusions and relevanceThese findings suggest that SIM rates were associated with modifiable, upstream factors. Although embedded in SIM, suicide unexpectedly deviated in proposed social and environmental determinants. Heterogeneity in medicolegal death investigation processes and data assurance needs further characterization, with the goal of providing the highest-quality reports for developing and tracking public health policies and practices.
| S-EPMC8829661 | biostudies-literature
Project description:BackgroundHeatwaves are becoming more frequent and may acutely increase the risk of stillbirth, a rare and severe pregnancy outcome.ObjectivesExamine the association between multiple heatwave metrics and stillbirth in six U.S. states.MethodsData were collected from fetal death and birth records in California (1996-2017), Florida (1991-2017), Georgia (1994-2017), Kansas (1991-2017), New Jersey (1991-2015), and Oregon (1991-2017). Cases were matched to controls 1:4 based on maternal race/ethnicity, maternal education, and county, and exposure windows were aligned (gestational week prior to stillbirth). County-level temperature data were obtained from Daymet and linked to cases and controls by residential county and the exposure window. Five heatwave metrics (1 categorical, 3 dichotomous, 1 continuous) were created using different combinations of the duration and intensity of hot days (mean daily temperature exceeding the county-specific 97.5th percentile) during the exposure window, as well as a continuous measure of mean temperature during the exposure window modeled using natural splines to allow for nonlinear associations. State-specific odds ratios (ORs) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. State-specific results were pooled using a fixed-effects meta-analysis.ResultsIn our data set of 140,428 stillbirths (553,928 live birth controls), three of the five heatwave metrics examined were not associated with stillbirth. However, four consecutive hot days during the previous week was associated with a 3% increase in stillbirth risk (CI: 1.01, 1.06), and a 1 °C average increase over the threshold was associated with a 10% increase in stillbirth risk (CI: 1.04, 1.17). In continuous temperature analyses, there was a slight increased risk of stillbirth associated with extremely hot temperatures (≥ 35 °C).DiscussionMost heat wave definitions examined were not associated with acute changes in stillbirth risk; however, the most extreme heatwave durations and temperatures were associated with a modest increase in stillbirth risk.
| S-EPMC9202158 | biostudies-literature
Project description:ImportanceCardiovascular disease (CVD) is a leading cause of morbidity and mortality in the United States. Despite substantial declines in CVD mortality rates during past decades, progress against cardiovascular deaths in midlife has stagnated, with rates increased in some US racial/ethnic groups.ObjectiveTo examine the trends in premature (ages 25-64 years) mortality from CVD from 2000 to 2015 by demographics and county-level factors, including education, rurality, and the prevalence of smoking, obesity, and diabetes.Design, setting, and participantsThis descriptive study used US national mortality data from the Surveillance, Epidemiology, and End Results data set and included all CVD deaths among individuals ages 25 to 64 years from January 2000 to December 2015. The data analysis began in February 2018.ExposuresAge, sex, race/ethnicity, and county-level factors.Main outcomes and measuresAge-standardized mortality rates and average annual percent change (AAPC) in rates by age, sex, race/ethnicity, and county-level factors (in quintiles) and relative risks of CVD mortality across quintiles of each county-level factor.ResultsIn 2000 to 2015, 2.3 million CVD deaths occurred among individuals age 25 to 64 years in the United States. There were significant declines in CVD mortality for black, Latinx, and Asian and Pacific Islander individuals (AAPC: range, -1.7 to -3.2%), although black people continued to have the highest CVD mortality rates. Mortality rates were second highest for American Indian/Alaskan Native individuals and increased significantly among those aged 25 to 49 years (AAPC: women, 2.1%; men, 1.3%). For white individuals, mortality rates plateaued among women age 25 to 49 years (AAPC, 0.05%). Declines in mortality rates were observed for most major CVD subtypes except for ischemic heart disease, which was stable in white women and increased in American Indian/Alaska Native women, hypertensive heart disease, for which significant increases in rates were observed in most racial/ethnic groups, and endocarditis, for which rates increased in white individuals and American Indian/Alaska Native men. Counties with the highest prevalence of diabetes (quintile 5 vs quintile 1: relative risk range 1.6-1.8 for white individuals and 1.4-1.6 for black individuals) had the most risk of CVD mortality.Conclusions and relevanceThere have been substantial declines in premature CVD mortality in much of the US population. However, increases in CVD mortality before age 50 years among American Indian/Alaska Native individuals, flattening rates in white people, and overall increases in deaths from hypertensive disease suggest that targeted public health interventions are needed to prevent these premature deaths.
| S-EPMC6802055 | biostudies-literature
Project description:BackgroundThis study seeks to answer two questions about the impacts of the 2020 Environmental Protection Agency's enforcement regulation rollbacks: is this suspension bolstering the economic viability of industries as oil and manufacturing executives claim they will and are these regulations upholding the agency's mission of protecting the environment?ResultsTo answer the former question, we utilized 6 months of state employment level data from California, United States, as a method of gauging the economic health of agency-regulated industries. We implemented a machine learning model to predict weekly employment data and a t-test to indicate any significant changes in employment. We found that, following California's state-issued stay-at-home order and the agency's regulation suspension, oil and certain manufacturing industries had statistically significant lower employment values.To answer the latter question, we used 10 years of PM2.5 levels in California, United States, as a metric for local air quality and treatment-control county pairs to isolate the impact of regulation rollbacks from the impacts of the state lockdown. Using the agency's data, we performed a t-test to determine whether treatment-control county pairs experienced a significant change in PM2.5 levels. Even with the statewide lockdown-a measure we hypothesized would correlate with decreased mobility and pollution levels-in place, counties with oil refineries experienced the same air pollution levels when compared to historical data averaged from the years 2009 to 2019.ConclusionsIn contrast to the expectation that the suspension would improve the financial health of the oil and manufacturing industry, we can conclude that these industries are not witnessing economic growth with the suspension and state shutdown in place. Additionally, counties with oil refineries could be taking advantage of these rollbacks to continue emitting the same amount of PM2.5, in spite of state lockdowns. For these reasons, we ask international policymakers to reconsider the suspension of enforcement regulations as these actions do not fulfill their initial expectations. We recommend the creation and maintenance of pollution control and prevention programs that develop emission baselines, mandate the construction of pollution databases, and update records of pollution emissions.Supplementary informationThe online version contains supplementary material available at 10.1186/s12302-021-00489-9.
| S-EPMC8058586 | biostudies-literature
Project description:Introduction: Fine wool production is an important source of revenue, accounting for up to 13% of total revenue in extensively managed wool sheep production systems of the United States. The Rambouillet are a predominant breed that excels in wool quality characteristics. Understanding the genetic basis of wool quality characteristics would aid in the development of genomic breeding strategies to facilitate genetic improvement. Methods: Wool characteristics and DNA were collected for rams enrolled in the North Dakota State University and University of Wyoming annual central performance ram tests over a three-year period (2019–2021, N = 313). The relationships of wool quality characteristics including grease fleece weight adjusted 365 days (wt. 365 adj.), clean fleece wt. 365 adj., staple length 365 adj., average fiber diameter, face wool cover, amount of skin wrinkles and belly wool were evaluated through genome-wide association studies (GWAS), Pearson correlation and ANOVA. Results: The GWAS identified four genome-wide significant genetic markers (p-value <1.19e-06) and five chromosome-wide significant markers (p-value <1.13e-05) on chromosomes 1, 2, 4, 15, and 19. Significant markers were associated with genes notable for relevant wool biological functions, including the gene ABCC8 which codes for SUR1, an ATP-sensitive potassium channel known to affect hair growth and 60S ribosomal protein L17-like, previously found to be expressed during follicle formation. The strongest Pearson correlation coefficients were identified between clean fleece wt. 365 adj. and grease fleece wt. 365 adj. (r = 0.83) and between clean fleece wt. 365 adj. and staple length 365 adj. (r = 0.53). Additionally, clean fleece wt. 365 adj. was correlated with final body weight (r = 0.35) and scrotal circumference (r = 0.16). Staple length 365 adj. (p-value = 5e-04), average fiber diameter (p-value = .0053) and clean fleece wt. 365 adj. (p-value = .014) were significantly associated with belly wool score. Discussion: The results of this study provide important insight into the relationships between wool quality characteristics and report specific markers that Rambouillet sheep producers may use to help inform selection and breeding decisions for improved wool quality.
| S-EPMC9901206 | biostudies-literature