Heat-Related Emergency Department Visits - United States, May-September 2023

Unprecedented heat waves can affect all persons, but some are more sensitive to the effects of heat, including children and adults with underlying health conditions, pregnant women, and outdoor workers. Many regions of the United States experienced record-breaking high temperatures in 2023, with populations exposed to extremely high temperatures for prolonged periods. CDC examined emergency department (ED) visits associated with heat-related illness (HRI) from the National Syndromic Surveillance Program and compared daily HRI ED visit rates during the warm-season months (May-September) of 2023 with those during 2018-2022. In the 2023 warm-season months, daily HRI ED visit rates peaked in several regions and remained elevated for a prolonged duration. More males than females sought care in EDs for HRI, especially males aged 18-64 years. CDC issued multiple public health alerts using the Epidemic Information Exchange system to bring attention to increases in ED utilization for HRI. Deaths and illnesses associated with heat exposure are a continuing public health concern as climate change results in longer, hotter, and more frequent episodes of extreme heat. Near real-time monitoring of weather conditions and adverse health outcomes can guide public health practitioners' timing of risk communication and implementation of prevention measures associated with extreme heat.

Psychotropic Medication Prescriptions and Large California Wildfires

Importance

Wildfires, intensified by climate change, have known effects on physical health but their effects on mental health are less well characterized. It has been hypothesized that the residential proximity to a large wildfire can exacerbate underlying mental health conditions as evidenced by increased prescriptions of psychotropic medications.

Objective

To evaluate the association between the occurrence of large wildfires and the prescription rates of psychotropic medications immediately following the start of the fire.

Design, Setting, and Participants

This cohortstudy used an interrupted time-series analysis to compare psychotropic medication prescriptions in the 6 weeks before and after each of 25 wildfires. The setting was California counties within metropolitan statistical areas (MSAs) experiencing large wildfires from 2011 through 2018. Participants included individuals residing in California MSAs with prescriptions of psychotropic medications recorded in the Merative MarketScan Research Database (MarketScan) during the study period. Statistical analysis was performed for these 25 large wildfires occurring between September 2011 and November 2018.

Exposure

Residential proximity to large wildfires that burned more than 25 000 acres occurring in a California county within an MSA.

Main Outcomes and Measures

Prescriptions of psychotropic medications, including antidepressants, antipsychotics, anxiolytics, hypnotics, and mood-stabilizers, with statins as a negative control outcome.

Results

For the study period, prescription data and patient-level attributes were extracted for 7 115 690 unique individuals (annual mean [range]: 889 461 [455 705-1 426 928] individuals) enrolled in MarketScan and residing in fire-affected MSAs. This study found a statistically significant increase in prescriptions of antidepressants (rate ratio [RR], 1.04 [95% CI, 1.01-1.07]), anxiolytics (RR, 1.05 [95% CI, 1.02-1.09]), and mood-stabilizing medications (RR, 1.06 [95% CI, 1.01-1.13]) in the fire period compared with the prefire baseline. However, the prescriptions of antipsychotics, hypnotics, and the negative control outcome, statins, showed no significant association.

Conclusions and Relevance

In this cohort study of large California wildfires, the occurrence of wildfire was associated with increased mental health burden as reflected in increased prescription rates of certain psychotropic medications. The findings underscore the need for further scientific examination into the mental health effects of wildfires and the allocation of mental health resources in disaster responses. California experienced a substantial burden of wildfires from 2011 to 2018, and as wildfires become more intense and frequent in the context of anthropogenic climate change, it is increasingly important to understand and address their mental health effects.

Ambient Air Quality and Fatal Asthma Exacerbations among Children in North Carolina

BACKGROUND

Little is known about the role of air quality in fatal asthma exacerbations among children.

METHODS

We collected information about 80 deaths that occurred in North Carolina from 2001 through 2016, among children aged 5-17 years, with asthma identified as the primary cause of death. We linked information about each death with county-level estimates of particulate matter ≤2.5 µm (PM2.5) and ozone (O3). Using the linked data, we conducted a case-crossover analysis of associations between PM2.5 and O3 lagged by 3-5 days with the odds of fatal asthma exacerbations.

RESULTS

In the highest tertile of PM2.5 lag(3-5), the odds of a fatal exacerbation of asthma were more than twice the odds in the lowest tertile (odds ratio = 2.2; 95% confidence interval = 1.1, 4.6).

CONCLUSION

These findings from North Carolina provide evidence to support the hypothesis that ambient air pollution increases the risk of fatal exacerbations of asthma among children.

Large-scale agricultural burning and cardiorespiratory emergency department visits in the U.S. state of Kansas

BACKGROUND

Prescribed agricultural burning is a common land management practice, but little is known about the health effects from the resulting smoke exposure.

OBJECTIVE

To examine the association between smoke from prescribed burning and cardiorespiratory outcomes in the U.S. state of Kansas.

METHODS

We analyzed a zip code-level, daily time series of primary cardiorespiratory emergency department (ED) visits for February-May (months when prescribed burning is common in Kansas) in the years 2009-2011 (n = 109,220). Given limited monitoring data, we formulated a measure of smoke exposure using non-traditional datasets, including fire radiative power and locational attributes from remote sensing data sources. We then assigned a population-weighted potential smoke impact factor (PSIF) to each zip code, based on fire intensity, smoke transport, and fire proximity. We used Poisson generalized linear models to estimate the association between PSIF on the same day and in the past 3 days and asthma, respiratory including asthma, and cardiovascular ED visits.

RESULTS

During the study period, prescribed burning took place on approximately 8 million acres in Kansas. Same-day PSIF was associated with a 7% increase in the rate of asthma ED visits when adjusting for month, year, zip code, meteorology, day of week, holidays, and correlation within zip codes (rate ratio [RR]: 1.07; 95% confidence interval [CI]: 1.01, 1.13). Same-day PSIF was not associated with a combined outcome of respiratory ED visits (RR [95% CI]: 0.99 [0.97, 1.02]), or cardiovascular ED visits (RR [95% CI]: 1.01 [0.98, 1.04]). There was no consistent association between PSIF during the past 3 days and any of the outcomes.

SIGNIFICANCE

These results suggest an association between smoke exposure and asthma ED visits on the same day. Elucidating these associations will help guide public health programs that address population-level exposure to smoke from prescribed burning.

Wildfire smoke and symptoms affecting mental health among adults in the U.S. state of Oregon

The physical and mental health impacts of wildfires are wide-ranging. We assessed associations between exposure to wildfire smoke and self-reported symptoms affecting mental health among adults living in Oregon. We linked by interview date and county of residence survey responses from 5807 adults who responded to the 2018 Behavioral Risk Factor Surveillance System's depression and anxiety module with smoke plume density, a proxy for wildfires and wildfire smoke exposure. Associations between weeks in the past year with medium and heavy smoke plume densities and symptoms affecting mental health during the two weeks before the interview date were estimated using predicted marginal probabilities from logistic regression models. In the year before completing the interview, 100% of respondents experienced ≥2 weeks of medium or heavy smoke, with an average exposure duration of 32 days. Nearly 10% reported being unable to stop or control their worrying more than half the time over the past two weeks. Medium or heavy smoke for 6 or more weeks in the past year, compared to ≤4 weeks in the past year, was associated with a 30% higher prevalence of being unable to stop or control worrying more than half the time during the past two weeks (prevalence ratio: 1.30, 95% confidence interval: 1.03, 1.65). Among adults in Oregon, selected symptoms affecting mental health were associated with extended durations of medium and heavy smoke. These findings highlight the burden of such symptoms among adults living in communities affected by wildfires and wildfire smoke.

Extreme Heat Exposure: Access and Barriers to Cooling Centers - Maricopa and Yuma Counties, Arizona, 2010-2020

Extreme heat exposure increases the risk for heat-related illnesses (HRIs) and deaths, and comprehensive strategies to prevent HRIs are increasingly important in a warming climate (1). An estimated 702 HRI-associated deaths and 67,512 HRI-associated emergency department visits occur in the United States each year (2,3). In 2020, Phoenix and Yuma, Arizona, experienced a record 145 and 148 days, respectively, of temperatures >100°F (37.8°C), and a record 522 heat-related deaths occurred in the state. HRIs are preventable through individual and community-based strategies*^,†; cooling centers,^§ typically air-conditioned or cooled buildings designated as sites to provide respite and safety during extreme heat, have been established in Maricopa and Yuma counties to reduce HRIs among at-risk populations, such as older adults. This analysis examined trends in HRIs by age during 2010-2020 for Maricopa and Yuma counties and data from a survey of older adults related to cooling center availability and use in Yuma County during 2018-2019. Data from CDC's Social Vulnerability Index (SVI) were also used to overlay cooling center locations with SVI scores. During 2010-2020, heat days, defined as days with an excessive heat warning issued by the National Weather Service Phoenix Office,^¶ for any part of Maricopa and Yuma counties (4), increased in both Maricopa County (1.18 days per year) and Yuma County (1.71 days per year) on average. Adults aged ≥65 years had higher rates of HRI hospitalization compared with those aged <65 years. In a survey of 39 adults aged ≥65 years in Yuma County, 44% reported recent HRI symptoms, and 18% reported electricity cost always or sometimes constrained their use of air conditioning. Barriers to cooling center access among older adults include awareness of location and transportation. Collaboration among diverse community sectors and health profession education programs is important to better prepare for rising heat exposure and HRIs. States and communities can implement adaptation and evaluation strategies to mitigate and assess heat risk, such as the use of cooling centers to protect communities disproportionately affected by HRI during periods of high temperatures.

Short term physician visits and medication prescriptions for allergic disease associated with seasonal tree, grass, and weed pollen exposure across the United States

BACKGROUND

While year-round exposure to pollen is linked to a large burden of allergic diseases, location-specific risk information on pollen types and allergy outcomes are limited. We characterize the relationship between acute exposure to tree, grass and weed pollen taxa and two allergy outcomes (allergic rhinitis physician visit and prescription allergy medication fill) across 28 metropolitan statistical areas (MSA) in the United States.

METHODS

We obtained daily pollen data from National Allergy Bureau (NAB) monitors at these 28 MSAs for 2008-2015. We revised the NAB guidelines to classify taxa-specific pollen severity each day. Daily information on allergic rhinitis and prescribed allergy medications for individuals with employer-based health insurance from the IBM MarketScan Research database for these MSAs. We combined the daily pollen and health data for each MSA into a longitudinal dataset. We conducted a MSA-specific conditional quasi-Poisson regression analysis to assess how different levels of pollen concentration impact the health outcomes, controlling for local air pollution, meteorology and Influenza-like illness (ILI). We used a random effects meta-analysis to produce an overall risk estimate for each pollen type and health outcome.

RESULTS

The seasonal distribution of pollen taxa and associated health impacts varied across the MSAs. Relative risk of allergic rhinitis visits increased as concentrations increased for all pollen types; relative risk of medication fills increased for tree and weed pollen only. We observed an increase in health risk even on days with moderate levels of pollen concentration. 7-day average concentration of pollen had stronger association with the health outcomes compared to the same-day measure. Controlling for air pollution and ILI had little impact on effect estimates.

CONCLUSION

This analysis expands the catalogue of associations between different pollen taxa and allergy-related outcomes across multiple MSAs. The effect estimates we present can be used to project the burden of allergic disease in specific locations in the future as well inform patients with allergies on impending pollen exposure.

Long-Term Air Pollution and Blood Pressure in an African American Cohort: the Jackson Heart Study

INTRODUCTION

African Americans are disproportionately affected by high blood pressure, which may be associated with exposure to air pollutants, such as fine particulate matter and ozone.

METHODS

Among African American Jackson Heart Study participants, this study examined associations between 1-year and 3-year mean fine particulate matter and ozone concentrations with prevalent and incident hypertension at Visits 1 (2000-2004, n=5,191) and 2 (2005-2008, n=4,105) using log binomial regression. Investigators examined associations with systolic blood pressure, diastolic blood pressure, pulse pressure, and mean arterial pressure using linear regression and hierarchical linear models, adjusting for sociodemographic, behavioral, and clinical characteristics. Analyses were conducted in 2017-2019.

RESULTS

No associations were observed between fine particulate matter or ozone concentration and prevalent or incident hypertension. In linear models, an IQR increase in 1-year ozone concentration was associated with 0.67 mmHg higher systolic blood pressure (95% CI=0.27, 1.06), 0.42 mmHg higher diastolic blood pressure (95% CI=0.20, 0.63), and 0.50 mmHg higher mean arterial pressure (95% CI=0.26, 0.74). In hierarchical models, fine particulate matter was inversely associated with systolic blood pressure (-0.72, 95% CI= -1.31, -0.13), diastolic blood pressure (-0.69, 95% CI= -1.02, -0.36), and mean arterial pressure (-0.71, 95% CI= -1.08, -0.33). Attenuated associations were observed with 1-year concentrations and at Visit 1.

CONCLUSIONS

Positive associations were observed between ozone and systolic blood pressure, diastolic blood pressure, and mean arterial pressure, and inverse associations between fine particulate matter and systolic blood pressure, diastolic blood pressure, and mean arterial pressure in an African American population with high (56%) prevalence of hypertension. Effect sizes were small and may not be clinically relevant.

Association Between Work-Related Hyperthermia Emergency Department Visits and Ambient Heat in Five Southeastern States, 2010-2012-A Case-Crossover Study

The objective of this study is to assess ambient temperatures' and extreme heat events' contribution to work-related emergency department (ED) visits for hyperthermia in the southeastern United States to inform prevention. Through a collaborative network and established data framework, work-related ED hyperthermia visits in five participating southeastern U.S. states were analyzed using a time stratified case-crossover design. For exposure metrics, day- and location-specific measures of ambient temperatures and county-specific identification of extreme heat events were used. From 2010 to 2012, 5,017 work-related hyperthermia ED visits were seen; 2,298 (~46%) of these visits occurred on days when the daily maximum heat index was at temperatures the Occupational Safety and Health Administration designates as having "lower" or "moderate" heat risk. A 14% increase in risk of ED visit was seen for a 1°F increase in average daily mean temperature, modeled as linear predictor across all temperatures. A 54% increase in risk was seen for work-related hyperthermia ED visits during extreme heat events (two or more consecutive days of unusually high temperatures) when controlling for average daily mean temperature. Despite ambient heat being a well-known risk to workers' health, this study's findings indicate ambient heat contributed to work-related ED hyperthermia visits in these five states. Used alone, existing OSHA heat-risk levels for ambient temperatures did not appear to successfully communicate workers' risk for hyperthermia in this study. Findings should inform future heat-alert communications and policies, heat prevention efforts, and heat-illness prevention research for workers in the southeastern United States.

Internet searches offer insight into early-season pollen patterns in observation-free zones

Tracking concentrations of regional airborne pollen is valuable for a variety of fields including plant and animal ecology as well as human health. However, current methods for directly measuring regional pollen concentrations are labor-intensive, requiring special equipment and manual counting by professionals leading to sparse data availability in select locations. Here, we use publicly available Google Trends data to evaluate whether searches for the term "pollen" can be used to approximate local observed early-season pollen concentrations as reported by the National Allergy Bureau across 25 U.S. regions from 2012-2017, in the context of site-specific characteristics. Our findings reveal that two major factors impact the ability of internet search data to approximate observed pollen: (1) volume/availability of internet search data, which is tied to local population size and media use; and (2) signal intensity of the seasonal peak in searches. Notably, in regions and years where internet search data was abundant, we found strong correlations between local search patterns and observed pollen, thus revealing a potential source of daily pollen data across the U.S. where observational pollen data are not reliably available.

The association between wildfire smoke exposure and asthma-specific medical care utilization in Oregon during the 2013 wildfire season

Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter ≤ 2.5 μm in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 µg/m3. A 10 µg/m3 increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.

Age-Specific Associations of Ozone and Fine Particulate Matter with Respiratory Emergency Department Visits in the United States

RATIONALE

Whereas associations between air pollution and respiratory morbidity for adults 65 years and older are well documented in the United States, the evidence for people under 65 is less extensive. To address this gap, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program collected respiratory emergency department (ED) data from 17 states.

OBJECTIVES

To estimate age-specific acute effects of ozone and fine particulate matter (particulate matter ≤2.5 mm in aerodynamic diameter [PM_2.5]) on respiratory ED visits.

METHODS

We conducted time-series analyses in 894 counties by linking daily respiratory ED visits with estimated ozone and PM_2.5 concentrations during the week before the date of the visit. Overall effect estimates were obtained with a Bayesian hierarchical model to combine county estimates for each pollutant by age group (children, 0-18; adults, 19-64; adults ≥ 65, and all ages) and by outcome group (acute respiratory infection, asthma, chronic obstructive pulmonary disease, pneumonia, and all respiratory ED visits).

MEASUREMENTS AND MAIN RESULTS

Rate ratios (95% credible interval) per 10-μg/m³ increase in PM_2.5 and all respiratory ED visits were 1.024 (1.018-1.029) among children, 1.008 (1.004-1.012) among adults younger than 65 years, and 1.002 (0.996-1.007) among adults 65 and older. Per 20-ppb increase in ozone, rate ratios were 1.017 (1.011-1.023) among children, 1.051 (1.046-1.056) among adults younger than 65, and 1.033 (1.026-1.040) among adults 65 and older. Associations varied in magnitude by age group for each outcome group.

CONCLUSIONS

These results address a gap in the evidence used to ensure adequate public health protection under national air pollution policies.

Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models

Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.Implications: Fine particulate matter (PM2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

Community drinking water data on the National Environmental Public Health Tracking Network: a surveillance summary of data from 2000 to 2010

This report describes the available drinking water quality monitoring data on the Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network (Tracking Network). This surveillance summary serves to identify the degree to which ten drinking water contaminants are present in finished water delivered to populations served by community water systems (CWS) in 24 states from 2000 to 2010. For each state, data were collected from every CWS. CWS are sampled on a monitoring schedule established by the Environmental Protection Agency (EPA) for each contaminant monitored. Annual mean and maximum concentrations by CWS for ten water contaminants were summarized from 2000 to 2010 for 24 states. For each contaminant, we calculated the number and percent of CWS with mean and maximum concentrations above the maximum contaminant level (MCL) and the number and percent of population served by CWS with mean and maximum concentrations above the MCL by year and then calculated the median number of those exceedances for the 11-year period. We also summarized these measures by CWS size and by state and identified the source water used by those CWS with exceedances of the MCL. The contaminants that occur more frequently in CWS with annual mean and annual maximum concentrations greater than the MCL include the disinfection byproducts, total trihalomethanes (TTHM), and haloacetic acids (HAA5); arsenic; nitrate; radium and uranium. A very high proportion of exceedances based on MCLs occurred mostly in very small and small CWS, which serve a year-round population of 3,300 or less. Arsenic in New Mexico and disinfection byproducts HAA5 and TTHM, represent the greatest health risk in terms of exposure to regulated drinking water contaminants. Very small and small CWS are the systems' greatest difficulty in achieving compliance.

Assessment of extreme heat and hospitalizations to inform early warning systems

Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat-health early warning systems. We used a two-stage analysis to estimate heat-health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003-2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat-health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure-response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat-health early warning systems.

TAIGA: results and perspectives

In this talk, we describe the status and the perspectives of the hybrid Air Shower Array TAIGA (Tunka Advanced Instrument for cosmic rays and Gamma Astronomy) which is currently under construction in the Tunka Valley close to Lake Baikal and is taking data in its initial configurations. TAIGA is designed for the study of gamma rays and charged cosmic rays in the energy range of 1013 eV - 1018 eV. It has the potential to play an important role in the search for Galactic Pevatrons and within a multi-messenger approach to explore the high-energy sky.

Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence

Most epidemiological studies of high temperature effects on mortality have focused on urban settings, while heat-related health risks in rural areas remain underexplored. To date there has been no meta-analysis of epidemiologic literature concerning heat-related mortality in rural settings. This study aims to systematically review the current literature for assessing heat-related mortality risk among rural populations. We conducted a comprehensive literature search using PubMed, Web of Science, and Google Scholar to identify articles published up to April 2018. Key selection criteria included study location, health endpoints, and study design. Fourteen studies conducted in rural areas in seven countries on four continents met the selection criteria, and eleven were included in the meta-analysis. Using the random effects model, the pooled estimates of relative risks (RRs) for all-cause and cardiovascular mortality were 1.030 (95% CI: 1.013, 1.048) and 1.111 (95% CI: 1.045, 1.181) per 1 °C increase in daily mean temperature, respectively. We found excess risks in rural settings not to be smaller than risks in urban settings. Our results suggest that rural populations, like urban populations, are also vulnerable to heat-related mortality. Further evaluation of heat-related mortality among rural populations is warranted to develop public health interventions in rural communities.

Emergency Department Visits and Ambient Temperature: Evaluating the Connection and Projecting Future Outcomes

The U.S. Global Climate Change Research Program has identified climate change as a growing public health threat. We investigated the potential effects of changes in ambient daily maximum temperature on hyperthermia and cardiovascular emergency department (ED) visits using records for patients age 64 and younger from a private insurance database for the May-September period for 2005-2012. We found a strong positive relationship between daily maximum temperatures and ED visits for hyperthermia but not for cardiovascular conditions. Using the fitted relationship from 136 metropolitan areas, we calculated the number and rate of hyperthermia ED visits for climates representative of year 1995 (baseline period), as well as years 2050 and 2090 (future periods), for two climate change scenarios based on outcomes from five global climate models. Without considering potential adaptation or population growth and movement, we calculate that climate change alone will result in an additional 21,000-28,000 hyperthermia ED visits for May to September, with associated treatment costs between $6 million and $52 million (2015 U.S. dollars) by 2050; this increases to approximately 28,000-65,000 additional hyperthermia ED visits with treatment costs between $9 million and $118 million (2015 U.S. dollars) by 2090. The range in projected additional hyperthermia visits reflects the difference between alternative climate scenarios, and the additional range in valuation reflects different assumptions about per-case valuation.

Particulate Matter Air Pollution Exposure and Heart Disease Mortality Risks by Race and Ethnicity in the United States: 1997 to 2009 National Health Interview Survey With Mortality Follow-Up Through 2011

BACKGROUND

Most US studies of mortality and air pollution have been conducted on largely non-Hispanic white study populations. However, many health and mortality outcomes differ by race and ethnicity, and non-Hispanic white persons experience lower air pollution exposure than those who are non-Hispanic black or Hispanic. This study examines whether associations between air pollution and heart disease mortality differ by race/ethnicity.

METHODS

We used data from the 1997 to 2009 National Health Interview Survey linked to mortality records through December 2011 and annual estimates of fine particulate matter (PM2.5) by census tract. Proportional hazards models were used to estimate hazard ratios and 95% confidence intervals between PM2.5 (per 10 µg/m3) and heart disease mortality using the full sample and the sample adults, which have information on additional health variables. Interaction terms were used to examine differences in the PM2.5-mortality association by race/ethnicity.

RESULTS

Overall, 65 936 of the full sample died during follow-up, and 22 152 died from heart disease. After adjustment for several factors, we found a significant positive association between PM2.5 and heart disease mortality (hazard ratio, 1.16; 95% confidence interval, 1.08-1.25). This association was similar in sample adults with adjustment for smoking and body mass index (hazard ratio, 1.18; 95% confidence interval, 1.06-1.31). Interaction terms for non-Hispanic black and Hispanic groups compared with the non-Hispanic white group were not statistically significant.

CONCLUSIONS

Using a nationally representative sample, the association between PM2.5 and heart disease mortality was elevated and similar to previous estimates. Associations for non-Hispanic black and Hispanic adults were not statistically significantly different from those for non-Hispanic white adults.

Differences in Heat-Related Mortality by Citizenship Status: United States, 2005-2014

OBJECTIVES

To determine whether non-US citizens have a higher mortality risk of heat-related deaths than do US citizens.

METHODS

We used place of residence reported in mortality data from the National Vital Statistics System from 2005 to 2014 as a proxy for citizenship to examine differences in heat-related deaths between non-US and US citizens. Estimates from the US Census Bureau American Community Survey of self-reported citizenship status and place of birth provided the numbers for the study population. We calculated the standardized mortality ratio and relative risk for heat-related deaths between non-US and US citizens nationally.

RESULTS

Heat-related deaths accounted for 2.23% (n = 999) of deaths among non-US citizens and 0.02% (n = 4196) of deaths among US citizens. The age-adjusted standardized mortality ratio for non-US citizens compared with US citizens was 3.4 (95% confidence ratio [CI] = 3.2, 3.6). This risk was higher for Hispanic non-US citizens (risk ratio [RR] = 3.6; 95% CI = 3.2, 3.9) and non-US citizens aged 18 to 24 years (RR = 20.6; 95% CI = 16.5, 25.7).

CONCLUSIONS

We found an increased mortality risk among non-US citizens compared with US citizens for heat-related deaths, especially those younger and of Hispanic ethnicity.

Developing an online tool for identifying at-risk populations to wildfire smoke hazards

Wildfire episodes pose a significant public health threat in the United States. Adverse health impacts associated with wildfires occur near the burn area as well as in places far downwind due to wildfire smoke exposures. Health effects associated with exposure to particulate matter arising from wildfires can range from mild eye and respiratory tract irritation to more serious outcomes such as asthma exacerbation, bronchitis, and decreased lung function. Real-time operational forecasts of wildfire smoke concentrations are available but they are not readily integrated with information on vulnerable populations necessary to identify at-risk communities during wildfire smoke episodes. Efforts are currently underway at the Centers for Disease Control and Prevention (CDC) to develop an online tool that utilizes short-term predictions and forecasts of smoke concentrations and integrates them with measures of population-level vulnerability for identifying at-risk populations to wildfire smoke hazards. The tool will be operationalized on a national scale, seeking input and assistance from several academic, federal, state, local, Tribal, and Territorial partners. The final product will then be incorporated into CDC's National Environmental Public Health Tracking Network (http://ephtracking.cdc.gov), providing users with access to a suite of mapping and display functionalities. A real-time vulnerability assessment tool incorporating standardized health and exposure datasets, and prevention guidelines related to wildfire smoke hazards is currently unavailable for public health practitioners and emergency responders. This tool could strengthen existing situational awareness competencies, and expedite future response and recovery efforts during wildfire episodes.

Electronic health record case studies to advance environmental public health tracking

Data from traditional public health surveillance systems can have some limitations, e.g., timeliness, geographic level, and amount of data accessible. Electronic health records (EHRs) could present an opportunity to supplement current sources of routinely collected surveillance data. The National Environmental Public Health Tracking Program (Tracking Program) sought to explore the use of EHRs for advancing environmental public health surveillance practices. The Tracking Program funded four state/local health departments to obtain and pilot the use of EHR data to address several issues including the challenges and technical requirements for accessing EHR data, and the core data elements required to integrate EHR data within their departments' Tracking Programs. The results of these pilot projects highlighted the potential of EHR data for public health surveillance of rare diseases that may lack comprehensive registries, and surveillance of prevalent health conditions or risk factors for health outcomes at a finer geographic level. EHRs therefore, may have potential to supplement traditional sources of public health surveillance data.

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions

Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM2.5) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM2.5. A 10 μg/m3 increase in GWR smoke PM2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019-1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM2.5 exposure method: a 10 μg/m3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026-1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931-1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.

Outdoor PM2.5, Ambient Air Temperature, and Asthma Symptoms in the Past 14 Days among Adults with Active Asthma

BACKGROUND

Relationships between air quality and health are well-described, but little information is available about the joint associations between particulate air pollution, ambient temperature, and respiratory morbidity.

OBJECTIVES

We evaluated associations between concentrations of particulate matter ≤ 2.5 μm in diameter (PM2.5) and exacerbation of existing asthma and modification of the associations by ambient air temperature.

METHODS

Data from 50,356 adult respondents to the Asthma Call-back Survey from 2006-2010 were linked by interview date and county of residence to estimates of daily averages of PM2.5 and maximum air temperature. Associations between 14-day average PM2.5 and the presence of any asthma symptoms during the 14 days leading up to and including the interview date were evaluated using binomial regression. We explored variation by air temperature using similar models, stratified into quintiles of the 14-day average maximum temperature.

RESULTS

Among adults with active asthma, 57.1% reported asthma symptoms within the past 14 days, and 14-day average PM2.5 ≥ 7.07 μg/m3 was associated with an estimated 4-5% higher asthma symptom prevalence. In the range of 4.00-7.06 μg/m3 of PM2.5, each 1-μg/m3 increase was associated with a 3.4% [95% confidence interval (CI): 1.1, 5.7] increase in symptom prevalence; across categories of temperature from 1.1 to 80.5°F, each 1-μg/m3 increase was associated with increased symptom prevalence (1.1-44.4°F: 7.9%; 44.5-58.6°F: 6.9%; 58.7-70.1°F: 2.9%; 70.2-80.5°F: 7.3%).

CONCLUSIONS

These results suggest that each unit increase in PM2.5 may be associated with an increase in the prevalence of asthma symptoms, even at levels as low as 4.00-7.06 μg/m3. Citation: Mirabelli MC, Vaidyanathan A, Flanders WD, Qin X, Garbe P. 2016. Outdoor PM2.5, ambient air temperature, and asthma symptoms in the past 14 days among adults with active asthma. Environ Health Perspect 124:1882-1890; http://dx.doi.org/10.1289/EHP92.

Heat Stress Illness Emergency Department Visits in National Environmental Public Health Tracking States, 2005-2010

Variability of heat stress illness (HSI) by urbanicity and climate region has rarely been considered in previous HSI studies. We investigated temporal and geographic trends in HSI emergency department (ED) visits in CDC Environmental Public Health Tracking Network (Tracking) states for 2005-2010. We obtained county-level HSI ED visit data for 14 Tracking states. We used the National Center for Health Statistics Urban-Rural Classification Scheme to categorize counties by urbanicity as (1) large central metropolitan (LCM), (2) large fringe metropolitan, (3) small-medium metropolitan, or (4) nonmetropolitan (NM). We also assigned counties to one of six US climate regions. Negative binomial regression was used to examine trends in HSI ED visits over time across all counties and by urbanicity for each climate region, adjusting for pertinent variables. During 2005-2010, there were 98,462 HSI ED visits in the 14 states. ED visits for HSI decreased 3.0% (p < 0.01) per year. Age-adjusted incidence rates of HSI ED visits increased from most urban to most rural. Overall, ED visits were significantly higher for NM areas (IRR = 1.41, p < 0.01) than for LCM areas. The same pattern was observed in all six climate regions; compared with LCM, NM areas had from 14 to 90% more ED visits for HSI. These findings of significantly increased HSI ED visit rates in more rural settings suggest a need to consider HSI ED visit variability by county urbanicity and climate region when designing and implementing local HSI preventive measures and interventions.

A Statistical Framework to Evaluate Extreme Weather Definitions from A Health Perspective: A Demonstration Based on Extreme Heat Events

A statistical framework for evaluating definitions of extreme weather phenomena can help weather agencies and health departments identify the definition(s) most applicable for alerts nd other preparedness operations related to extreme weather episodes.

Long-Term Exposure to Ozone and Life Expectancy in the United States, 2002 to 2008

Long-term exposure to ground-level ozone is associated with increased risk of morbidity and mortality. The association remains uncertain between long-term exposure to ozone and life expectancy. We assessed the associations between seasonal mean daily 8-hour maximum (8-hr max) ozone concentrations measured during the ozone monitoring seasons and life expectancy at birth in 3109 counties of the conterminous U.S. during 2002 to 2008. We used latent class growth analysis to identify latent classes of counties that had distinct mean levels and rates of change in ozone concentrations over the 7-year period and used linear regression analysis to determine differences in life expectancy by ozone levels. We identified 3 classes of counties with distinct seasonal mean daily 8-hr max ozone concentrations and rates of change. When compared with the counties with the lowest ozone concentrations, the counties with the highest ozone concentrations had 1.7- and 1.4-year lower mean life expectancy in males and females (both P < 0.0001), respectively. The associations remained statistically significant after controlling for potential confounding effects of seasonal mean PM2.5 concentrations and other selected environmental, demographic, socio-economic, and health-related factors (both P < 0.0001). A 5 ppb higher ozone concentration was associated with 0.25 year lower life expectancy in males (95% CI: -0.30 to -0.19) and 0.21 year in females (95% CI: -0.25 to -0.17). We identified 3 classes of counties with distinct mean levels and rates of change in ozone concentrations. Our findings suggest that long-term exposure to a higher ozone concentration may be associated with a lower life expectancy.

Short-term effects of ambient air pollutants on asthma-related emergency department visits in Indianapolis, Indiana, 2007-2011

OBJECTIVE

We estimate the short-term associations between daily changes in ambient air pollutants and daily asthma-related emergency department (ED) visits in Indianapolis, IN.

METHODS

We identified asthma-related ED visits among Indianapolis residents aged ≥5 years. We used Poisson regression in a time-series framework to estimate the increased risk for asthma-related ED visits from exposure to ambient SO2, PM2.5 and ozone during the warm season (April-September) and SO2 and PM2.5 during the cold (October-March) season, from 2007 to 2011. Our models controlled for measured confounders, including weather and respiratory infections, as well as unmeasured confounders using a natural cubic spline to account for long-term seasonal trends.

RESULTS

During 2007-2011 in Indianapolis, 165,056 asthma-related ED visits occurred. We found statistically significant positive associations (p < 0.05) between ambient air pollutants and ED visits during the warm season for persons aged 5-44 years. Interquartile range increases in daily ozone concentrations with same day, 2-day lagged, and 3-day moving average were associated with increased risks for ED visits of 3.2% (95% CI: 0.2%, 6.3%), 4.4% (0.1%, 8.9%) and 4.8% (0.2%, 9.6%), respectively. Interquartile range increases in 3-day moving averages for SO2 were associated with an increased risk of 3.3% (95% CI: 0.2%, 6.5%). We identified statistically significant associations (p < 0.05) between increased SO2 and PM2.5 levels and decreased ED visits among some age groups, primarily during the cold season, and no significant positive associations between changes in PM2.5 concentration and asthma-related ED visits.

CONCLUSIONS

During the warm season, increases in ozone and SO2 concentrations were associated with increased asthma morbidity in children and young adults in Indianapolis. These results will enable reliable estimation of the health impacts of increases in these pollutants on asthma-related ED visits in Indianapolis and similar communities.

Spatial variation in hyperthermia emergency department visits among those with employer-based insurance in the United States - a case-crossover analysis

BACKGROUND

Predictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes.

METHODS

Hyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan(®) Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions.

RESULTS

Examination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4°F in 'South' and 81.9°F in the 'Northwest' climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest.

CONCLUSION

The results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat.

Heat stress illness hospitalizations--environmental public health tracking program, 20 States, 2001-2010

PROBLEM/CONDITION

Heat stress illness (HSI), also known as heat-related illness, comprises mild heat edema, heat syncope, heat cramps, heat exhaustion (the most common type of HSI), and heat stroke (the most severe form). CDC's Environmental Public Health Tracking Program receives annual hospitalization discharge data from 23 states that are used to assess and monitor trends of HSI hospitalization over time.

REPORTING PERIOD

May-September, 2001-2010.

DESCRIPTION OF SYSTEM

The Environmental Public Health Tracking Program is a comprehensive surveillance system implemented in 25 states and one city health department. The core of the system is the Tracking Network, which collects data on environmental hazards, health effects, exposures, and population. The Tracking Network provides nationally consistent environmental and health outcome data that enable federal, state, and local public health agencies to assess trends, explore associations, and generate hypotheses using these data. For HSI surveillance, the Tracking Network uses state-based hospital discharge data.

RESULTS

During 2001-2010, approximately 28,000 HSI hospitalizations occurred in 20 states participating in the Tracking Program. Data from three states were not included in this report because of missing data for ≥3 years. Two states joined the Tracking Program after the study period and also are not included in this report. The majority of HSI hospitalizations occurred among males and persons aged ≥65 years. The highest rates of hospitalizations were in the Midwest and the South. During this period, an overall 2%-5% increase in the rate of HSI hospitalizations occurred in all 20 states compared with the 2001 rate. The correlation between the average number of HSI hospitalizations and the average monthly maximum temperature/heat index was statistically significant (at p<0.0001) in all 20 states.

INTERPRETATION

Consistent with previous studies, age and sex were identified as major risk factors for HSI hospitalizations. Certain Tracking states that experienced high temperatures during summer months showed an increase in rate of HSI hospitalizations over the 10-year study period.

PUBLIC HEALTH ACTION

HSIs are preventable and an important focus of public health interventions at state and local health departments. Federal, state, and local public health agencies can use data on HSI hospitalizations for surveillance purposes to estimate trends over time and to design targeted intervention to reduce heat stress morbidity among at-risk populations.

Statistical air quality predictions for public health surveillance: evaluation and generation of county level metrics of PM2.5 for the environmental public health tracking network

Background

The Centers for Disease Control and Prevention (CDC) developed county level metrics for the Environmental Public Health Tracking Network (Tracking Network) to characterize potential population exposure to airborne particles with an aerodynamic diameter of 2.5 μm or less (PM_2.5). These metrics are based on Federal Reference Method (FRM) air monitor data in the Environmental Protection Agency (EPA) Air Quality System (AQS); however, monitor data are limited in space and time. In order to understand air quality in all areas and on days without monitor data, the CDC collaborated with the EPA in the development of hierarchical Bayesian (HB) based predictions of PM_2.5 concentrations. This paper describes the generation and evaluation of HB-based county level estimates of PM_2.5.

Methods

We used three geo-imputation approaches to convert grid-level predictions to county level estimates. We used Pearson (r) and Kendall Tau-B (τ) correlation coefficients to assess the consistency of the relationship, and examined the direct differences (by county) between HB-based estimates and AQS-based concentrations at the daily level. We further compared the annual averages using Tukey mean-difference plots.

Results

During the year 2005, fewer than 20% of the counties in the conterminous United States (U.S.) had PM_2.5 monitoring and 32% of the conterminous U.S. population resided in counties with no AQS monitors. County level estimates resulting from population-weighted centroid containment approach were correlated more strongly with monitor-based concentrations (r = 0.9; τ = 0.8) than were estimates from other geo-imputation approaches. The median daily difference was −0.2 μg/m³ with an interquartile range (IQR) of 1.9 μg/m³ and the median relative daily difference was −2.2% with an IQR of 17.2%. Under-prediction was more prevalent at higher concentrations and for counties in the western U.S.

Conclusions

While the relationship between county level HB-based estimates and AQS-based concentrations is generally good, there are clear variations in the strength of this relationship for different regions of the U.S. and at various concentrations of PM_2.5. This evaluation suggests that population-weighted county centroid containment method is an appropriate geo-imputation approach, and using the HB-based PM_2.5 estimates to augment gaps in AQS data provides a more spatially and temporally consistent basis for calculating the metrics deployed on the Tracking Network.

Screening for lead poisoning: a geospatial approach to determine testing of children in at-risk neighborhoods

OBJECTIVE

To develop a spatial strategy to assess neighborhood risk for lead exposure and neighborhood-level blood lead testing of young children living in the city of Atlanta, Georgia.

STUDY DESIGN

This ecologic study used existing blood lead results of children aged <or=36 months tested and living in one of Atlanta's 236 neighborhoods in 2005. Geographic information systems used Census, land parcel, and neighborhood spatial data to create a neighborhood priority testing index on the basis of proxies for poverty (Special Supplemental Nutrition Program for Women, Infants and Children [WIC] enrollment) and lead in house paint (year housing built).

RESULTS

In 2005, only 11.9% of Atlanta's 18,627 children aged <or=36 months living in the city had blood lead tests, despite a high prevalence of risk factors: 75,286 (89.6%) residential properties were built before 1978, and 44% of children were enrolled in WIC. Linear regression analysis indicated testing was significantly associated with WIC status (P < .001) but not with old housing.

CONCLUSIONS

This neighborhood spatial approach provided smaller geographic areas to assign risk and assess testing in a city that has a high prevalence of risk factors for lead exposure. Testing may be improved by collaboration between pediatricians and public health practitioners.

Characterization of fuel gas products from the treatment of solid waste streams with a plasma arc torch

This work addresses the plasma treatment of two solid waste streams and production of fuel gases from the process. In this study, carpet waste and simulated solid wastes generated by a United States Air Force Basic Expeditionary Airfield Resources Base deployment were used. Waste was treated in a furnace fitted with a 100kW plasma arc torch. The off gas was analyzed to determine its composition. The product gas was composed primarily of carbon monoxide and hydrogen, with small amounts of methane, benzene and toluene also detected. These experiments demonstrate the feasibility of producing fuel gases by plasma treatment of the solid waste streams. While the thermal energy value of the fuel gas produced in these experiments was less than the energy input, a higher waste-to-fuel gas conversion efficiency is expected in full-scale application.

Three-photon absorption in direct-gap crystals

Third-order time-dependent perturbation theory, utilizing parabolic and nonparabolic energy bands and calculated (from band structure) higher bands as intermediate levels, and a Keldysh first-order model are used to calculate three-photon-absorption coefficients of several direct-gap crystals. Third-order perturbation results for CdS at 1.06 microm agree well with the experimental data.

Nonlinear absorption in direct-gap semiconductors

Nonlinear absorption coefficients have been calculated for certain direct-bandgap semiconductors at 0.694-microm, 1.06-microm, 1.318-microm, and 10.6-microm wavelengths and compared with experimental results. The second- order perturbation theories of Braunstein and Basov yield underestimates and overestimates, respectively, of the nonlinear absorption constants. The numerical values are dependent upon the use of appropriate effective band masses, dielectric constants, and electron spin degeneracy factors. However, the Keldysh model gives second-order absorption constants that are intermediate between the two perturbation calculations. Although the Keldysh model often underestimates the value, in general, it yields the estimate of the magnitude of the two-photon absorption coefficient. The one-photon band-edge absorption in GaAs and InSb is predicted surprisingly well by the Keldysh model.