Environmental research, health : ERH最新文献

North Carolina (NC) ranks third among US states in both hog production and hurricanes. NC's hogs are housed in concentrated animal feeding operations (CAFOs) in the eastern, hurricane-prone part of the state. Hurricanes can inundate hog waste lagoons, transporting fecal bacteria that may cause acute gastrointestinal illness (AGI). While CAFOs and hurricanes have separately been associated with AGI, few epidemiological studies have examined the joint effect of hurricanes and CAFOs. We examined the impacts of Hurricanes Matthew (2016) and Florence (2018) on the occurrence of post-storm AGI in areas with varying numbers of hog and poultry CAFOs. We used ZIP code-level disease surveillance data, 2016-2019, to calculate rates of AGI emergency department (ED) visits in NC. Using precipitation data, CAFO permit data, and interrupted time series methods, we assessed the change in AGI rate during the three weeks after Matthew and Florence in ZIP codes with heavy rain (>75th percentile of storm precipitation) and 0, 1-10, and >10 hog CAFOs. The AGI ED rate in ZIP codes with heavy storm rain and >10 hog CAFOs increased 15% (RR = 1.15, 95% CI: 1.04, 1.27) during the three weeks after Hurricane Florence, although there was little increase after Hurricane Matthew (RR = 1.05, 95% CI = 0.86, 1.24). The AGI ED rates in ZIP codes with heavy storm rain and no hog CAFOs exhibited no increase during these post-hurricane periods (Matthew: RR = 0.97, 95% CI: 0.80, 1.14; Florence: RR = 1.01, 95% CI: 0.89, 1.13). We also observed an increase in AGI ED rate in areas with both >10 hog CAFOs and >10 poultry CAFOs. Areas with heavy hurricane precipitation and many CAFOs had a higher proportion of Black, American Indian, and Hispanic residents and lower annual household incomes than the state averages. Heavy hurricane precipitation in areas with CAFOs may increase AGI rates, disproportionately affecting people of color in NC.

The threats to human health from wildfires and wildfire smoke (WFS) in the United States (US) are increasing due to continued climate change. A growing body of literature has documented important adverse health effects of WFS exposure, but there is insufficient evidence regarding how risk related to WFS exposure varies across individual or community level characteristics. To address this evidence gap, we utilized a large nationwide database of healthcare utilization claims for emergency department (ED) visits in California across multiple wildfire seasons (May through November, 2012-2019) and quantified the health impacts of fine particulate matter <2.5 μm (PM_2.5) air pollution attributable to WFS, overall and among subgroups of the population. We aggregated daily counts of ED visits to the level of the Zip Code Tabulation Area (ZCTA) and used a time-stratified case-crossover design and distributed lag non-linear models to estimate the association between WFS and relative risk of ED visits. We further assessed how the association with WFS varied across subgroups defined by age, race, social vulnerability, and residential air conditioning (AC) prevalence. Over a 7 day period, PM_2.5 from WFS was associated with elevated risk of ED visits for all causes (1.04% (0.32%, 1.71%)), non-accidental causes (2.93% (2.16%, 3.70%)), and respiratory disease (15.17% (12.86%, 17.52%)), but not with ED visits for cardiovascular diseases (1.06% (-1.88%, 4.08%)). Analysis across subgroups revealed potential differences in susceptibility by age, race, and AC prevalence, but not across subgroups defined by ZCTA-level Social Vulnerability Index scores. These results suggest that PM_2.5 from WFS is associated with higher rates of all cause, non-accidental, and respiratory ED visits with important heterogeneity across certain subgroups. Notably, lower availability of residential AC was associated with higher health risks related to wildfire activity.

Wildfires are impacting communities globally, with California wildfires often breaking records of size and destructiveness. Knowing how communities are affected by these wildfires is vital to understanding recovery. We sought to identify impacted communities' post-wildfire needs and characterize how those needs change over time. The WHAT-Now study deployed a survey that was made publicly available for communities affected by the October 2017 Northern California wildfires or the accompanying smoke at beginning approximately four months post-fire with the vast majority completed by nine months post-fire. Among other questions, the survey asked an adult household member to report on their households' greatest need both one-week post-fire and at the time of survey. A total of 1461 households responded to these questions. Households reported many types of needs, with 154 responses that did not directly name needs but rather described how their households had been affected, which we classified as impacts. Four major themes were identified: physical, health, air, and information, each representing an array of varied specific needs or impacts. Physical needs (e.g. housing, food) were the most common (cited by more than 50% during the fires and about a third at the time of survey). The need for clean air was strong during the fires, but not months later, at the time of survey. In contrast, health needs were reported by a quarter of households during the fires. Needs that were reported at both times were categorized as 'persistent', and there were more persistent mental health needs over time compared to other health themes. Understanding the needs and impacts that arise during wildfires, their diversity and duration, and how they change over time is crucial to identifying types of assistance that are most needed during recovery efforts and when they are needed. Results presented here along with other wildfire needs assessments can be utilized to improve disaster preparedness, including for wildfire recovery.

Background: In the 6 months following Hurricane Maria the number of people who died from the hurricane was much higher than was initially estimated from death certificates. Disruption of health care services and displacement led to the exacerbation of pre-existing chronic diseases. The objectives of this study were to (1) estimate the excess deaths in Puerto Rico in the 6 months following Maria, (2) identify geographical areas experiencing higher risk of chronic disease mortality following Maria and (3) identify community-level vulnerability characteristics associated with some communities being at higher risk of increased chronic disease mortality after Maria.

Methods: Death records were obtained from Puerto Rico's Department of Health Demographic Registry. Mortality risks per 100 000 were calculated for chronic disease categories and all-cause mortality for the 6 months following Maria and the same months in the year before. Geospatial analysis using Getis-Ord Gi* Statistic was used to determine if mortality clusters of 6 month mortality risk following hurricane Maria by census tract were statistically significant. Multinomial logistic regression was used to model the association between census tract level social vulnerability and being classified as higher or sustained risk of mortality in the 6 months following Hurricane Maria compared to the previous year's mortality risk. Odds ratios and 95% confidence intervals were estimated to measure associations between social vulnerability and mortality risk.

Results: In the 6 months following Maria there were increases in mortality risk for cardiovascular disease, Alzheimer's, diabetes, sepsis, chronic respiratory disease, hypertension and all-cause mortality. Examining community level characteristics associated with vulnerability to disasters, neighborhoods with higher proportion of people 65 and older, higher proportion of houses being multiunit structures and higher proportion of households with no vehicle, in comparison to other neighborhoods in Puerto Rico,were more likely to have sustained high risk for mortality before and after Maria or increased risk of being a hot spot for chronic disease mortality after Maria.

As wildfire frequency and severity increases, smoke exposures will cause increasingly more adverse respiratory effects. While acute respiratory effects of smoke exposure have been documented in children, longer term sequelae are largely unstudied. Our objective here was to examine the association between gestational and postnatal exposure to wildfire smoke and prolonged use of prescription medication for respiratory conditions in early childhood. Using Merative MarketScan claims data, we created cohorts of term children born in western states between 1 January 2010-31 December 2014 followed for at least three years. Using NOAA Hazard Mapping System data, we determined the average number of days a week that >25% of the population in a metropolitan statistical area (MSA) was covered by smoke within each exposure period. The exposure periods were defined by trimester and two 12 week postnatal periods. Medication use was based on respiratory indication (upper respiratory, lower respiratory, or any respiratory condition) and categorized into outcomes of prolonged use (⩾30 d use) (PU) and multiple prolonged uses (at least two prolonged uses) (MPU). We used logistic regression models with random intercepts for MSAs adjusted for child sex, birth season, and birth year. Associations differed by exposure period and respiratory outcome, with elevated risk of MPU of lower respiratory medications following exposure in the third trimester and the first 12 postnatal weeks (RR 1.15, 95% CI 0.98, 1.35; RR 1.21, 95% CI 1.05, 1.40, respectively). Exposure in the third trimester was associated with an increase in MPU of any respiratory among males infants only (male RR 1.22, 95% CI 1.00, 1.50; female RR 0.93, 95% CI 0.66, 1.31). Through novel use of prescription claims data, this work identifies critical developmental windows in the 3rd trimester and first 12 postnatal weeks during which environmental inhalational disaster events may impact longer-term respiratory health.

As temperatures defy heat records, it is difficult to ignore the implications of climate change for public health, including impacts on population health more specifically. In short, climate change is happening now and presents an immediate hazard to human health on a global scale. Age-related health effects are an inalienable truth; physiology is relatively universal, and so are the ways in which our bodies respond to different types and levels of exposures to environmental stressors at different lifestages. Children are uniquely vulnerable to climate change stressors not only due to their physical and developmental immaturity, but also because they generally rely on adult caretakers for the fundamentals of survival. This article is the summary piece accompanying a special issue of Environmental Research: Health. It compiles new studies on children's vulnerability to climate change as well as studies exploring climate adaptation strategies to promote and protect child health. In this special issue, we see how these concepts are reflected repeatedly in empirical data domestically and internationally. For example, the special issue includes articles investigating linkages between climate change and health hazards such as asthma, injuries, and malnutrition. While local context is extremely important, many of the health effects may be extrapolated to other communities around the world.

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (β: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (β:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.