Assessment of extreme heat and hospitalizations to inform early warning systems

Impacts of the 2021 heat dome on emergency department visits, hospitalizations, and health system operations in three hospitals in Seattle, Washington

Objectives

Extreme heat events (EHEs) are associated with excess healthcare utilization but specific impacts on emergency department (ED) operations and throughput are unknown. In 2021, the Pacific Northwest experienced an unprecedented heat dome that resulted in substantial regional morbidity and mortality. The aim of this study was to examine its impact on ED utilization, unplanned hospitalization, and hospital operations in a large academic healthcare system.

Methods

Retrospective electronic medical records from three Seattle-area hospitals were used to compare healthcare utilization during the EHE compared to a pre-event reference period within the same month. Interrupted time series analysis was used to evaluate the association between EHE exposure and ED visits and hospitalizations. Metrics of ED crowding for the EHE were compared to the reference period using Student's t-tests and chi-squared tests. Additionally, multivariable Poisson regression was used to identify risk factors for heat-related illness and hospital admission.

Results

Interrupted time series analysis showed an increase of 21.7 ED visits per day (95% confidence interval [CI] = 14.7, 28.6) and 9.9 unplanned hospitalizations per day (95% CI = 8.3, 11.5) during the EHE, as compared to the reference period. ED crowding and process measures also displayed significant increases, becoming the most pronounced by day 3 of the EHE; the EHE was associated with delays in ED length of stay of 1.0 h (95% CI = 0.4, 1.6) compared to the reference period. Higher incidence rate ratios for heat-related illness were observed for patients who were older (incidence rate ratio [IRR] = 1.02; 95% CI = 1.01,1.03), female (IRR = 1.47; 95% CI = 1.06, 2.04), or who had pre-existing diabetes (IRR = 3.19; 95% CI = 1.47, 6.94).

Conclusions

The 2021 heat dome was associated with a significant increase in healthcare utilization including ED visits and unplanned hospitalizations. Substantial impacts on ED and hospital throughput were also noted. These findings contribute to the understanding of the role extreme heat events play on impacting patient outcomes and healthcare system function.

Protecting vulnerable patient populations from climate hazards: the role of the nation's cancer centers

Individuals diagnosed with cancer are a vulnerable population during disasters. Emergency preparedness efforts are crucial for meeting the health and safety needs of patients, health-care professionals, health-care facilities, and communities before, during, and after a disaster. Recognizing the importance of advancing emergency preparedness expertise to cancer control efforts nationwide, especially in the era of climate change, we searched National Cancer Institute-designated cancer centers' websites to examine emergency preparedness information sharing and evidence of research efforts focused on disaster preparedness. Of 71 centers, 56 (78.9%) presented some emergency preparedness information, and 36 (50.7%) presented information specific to individuals diagnosed with cancer. Only 17 (23.9%) centers provided emergency preparedness information for climate-driven disasters. Informed by these data, this commentary describes an opportunity for cancer centers to lead knowledge advancement on an important aspect of climate change adaptation: disaster preparedness.

Measuring Nurses' Knowledge and Awareness of Climate Change and Climate-Associated Diseases: Protocol for a Systematic Review of Existing Instruments

BACKGROUND

Climate change is a health emergency. Each year, it is estimated to cost more than 230 million years of life expectancy, with 4-9 million premature deaths associated with air pollution, and 9 million excess deaths due to non-optimal temperatures, representing 7% more temperature-related deaths since 2015 and 66% more since 2000.

OBJECTIVE

Identify and evaluate the reliability, fidelity, and validity of instruments measuring nurses' knowledge and awareness of climate change and climate-associated diseases.

METHODS

A systematic literature review will retrieve and assess studies examining instruments measuring nurses' knowledge and awareness of climate change and climate-associated diseases. Using predefined search terms for nurses, climate change, literacy and scales or tools, we will search for published articles recorded in the following electronic databases, with no language or date restrictions, from their inception until 31 October 2023: Medline Ovid SP (from 1946), PubMed (NOT Medline[sb], from 1996), Embase.com (from 1947), CINAHL Ebesco (from 1937), the Cochrane Library Wiley (from 1992), Web of Science Core Collection (from 1900), the Trip Database (from 1997), JBI OVID SP (from 1998), and the GreenFILE EBSCO. We will also hand-search relevant articles' bibliographies and search for unpublished studies using Google Scholar, ProQuest Dissertations and Theses Global, and DART-EUrope.eu. This will be completed by exploring the gray literature in OpenGrey and the Grey Literature Report, from inception until 31 October 2023, in collaboration with a librarian. Twelve bibliographic databases will be searched for publications up to 31 October 2023. The papers selected will be assessed for their quality.

RESULTS

The electronic database searches were completed in May 2023. Retrieved articles are being screened, and the study will be completed by October 2023. After removing duplicates, our search strategy has retrieved 3449 references.

CONCLUSIONS

This systematic review will provide specific knowledge about instruments to measure nurses' knowledge, awareness, motivation, attitudes, behaviors, beliefs, skills, and competencies regarding climate change and climate-associated diseases.

Heat is associated with short-term increases in household food insecurity in 150 countries and this is mediated by income

Rising temperatures are expected to stall progress on food insecurity by reducing agricultural yields in the coming decades. But hot periods may also increase food insecurity within days when it gets too hot to work and earn an income, thus limiting households' capability to purchase food. Here I exploit variations in heat levels during a household survey spanning 150 countries in a quasi-natural experiment to show that particularly hot weeks are associated with higher chances of food insecurity among households (0.5767, 95% confidence interval 0.2958-0.8576, t = 4.024, d.f. = 427,816, P < 0.001). This association is mediated by reductions in income and health for households and the effects are stronger in countries with lower incomes and more agricultural or precarious forms of employment. The results highlight the importance of labour market disruptions for food insecurity and suggest integration of these concerns into heat action plans and food programmes.

A nationwide analysis of the outcomes in hospitalized patients with atrial fibrillation and temperature-related illnesses

OBJECTIVES

The authors evaluated mortality and indices of cost of care among inpatients with Atrial Fibrillation (AF) and a diagnosis of a Temperature-Related Illness (TRI). The authors also assessed trends in the prevalence of TRIs among AF hospitalizations.

METHODS

In this cross-sectional study, the authors used discharge data from the Nationwide Inpatient Sample (NIS) collected between January 2005 and September 2015 to identify patients with a diagnosis of AF and TRI. Outcomes of interest included in-hospital mortality, invasive mechanical ventilation, hospital length of stay, and cost of hospitalization.

RESULTS

A total of 37,933 encounters were included. The median age was 79 years. Males were slightly overrepresented relative to females (54.2% vs. 45.8%, respectively). Although Blacks were only 6.6% of the cohort, they represented 12.2% of the TRI cases. Compared to non-TRI-related hospitalizations, a diagnosis of a TRI was associated with an increased likelihood of invasive mechanical ventilation (16.5% vs. 4.1%, p < 0.001), longer length-of-stay (5 vs. 4 days, p < 0.001), higher cost of care (10,082 vs. 8,607, in US dollars p < 0.001), and increased mortality (18.6% vs. 5.1%, p < 0.001). Compared to non-TRI, cold-related illness portends higher odds of mortality 4.68, 95% Confidence Interval (4.35-5.04), p < 0.001, and heat-related illness was associated with less odds of mortality, but this was not statistically significant 0.77 (0.57-1.03), p = 0.88.

CONCLUSION

The occurrence of TRI among hospitalized AF patients is small but there is an increasing trend in the prevalence, which more than doubled over the decade in this study. Individuals with AF who are admitted with a TRI face significantly poorer outcomes than those admitted without a TRI including higher mortality. Cold-related illness is associated with higher odds of mortality. Further research is required to elucidate the pathogenic mechanisms underlying these findings and identify strategies to prevent TRIs in AF patients.

Heat-related first cardiovascular event incidence in the city of Madrid (Spain): Vulnerability assessment by demographic, socioeconomic, and health indicators

While climate change and population ageing are expected to increase the exposure and vulnerability to extreme heat events, there is emerging evidence suggesting that social inequalities would additionally magnify the projected health impacts. However, limited evidence exists on how social determinants modify heat-related cardiovascular morbidity. This study aims to explore the association between heat and the incidence of first acute cardiovascular event (CVE) in adults in Madrid between 2015 and 2018, and to assess how social context and other individual characteristics modify the estimated association. We performed a case-crossover study using the individual information collected from electronic medical records of 6514 adults aged 40-75 living in Madrid city that suffered a first CVE during summer (June-September) between 2015 and 2018. We applied conditional logistic regression with a distributed lag non-linear model to analyse the heat-CVE association. Estimates were expressed as Odds Ratio (OR) for extreme heat (at 97.5th percentile of daily maximum temperature distribution), compared to the minimum risk temperature. We performed stratified analyses by specific diagnosis, sex, age (40-64, 65-75), country of origin, area-level deprivation, and presence of comorbidities. Overall, the risk of suffering CVE increased by 15.3% (OR: 1.153 [95%CI 1.010-1.317]) during extreme heat. Males were particularly more affected (1.248, [1.059-1.471]), vs 1.039 [0.810-1.331] in females), and non-Spanish population (1.869 [1.28-2.728]), vs 1.084 [0.940-1.250] in Spanish). Similar estimates were found by age groups. We observed a dose-response pattern across deprivation levels, with larger risks in populations with higher deprivation (1.228 [1.031-1.462]) and almost null association in the lowest deprivation group (1.062 [0.836-1.349]). No clear patterns of larger vulnerability were found by presence of comorbidity. We found that heat unequally increased the risk of suffering CVE in adults in Madrid, affecting mainly males and deprived populations. Local measures should pay special attention to vulnerable populations.

Association of Temperature Thresholds with Heat Illness- and Cardiorespiratory-Related Emergency Visits during Summer Months in Alaska

BACKGROUND

Recent record-breaking hot temperatures in Alaska have raised concerns about the potential human health implications of heat exposure among this unacclimated population.

OBJECTIVES

We estimated cardiorespiratory morbidity associated with days above summer (June-August) heat index (HI, apparent temperature) thresholds in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) for the years 2015-2019.

METHODS

We implemented time-stratified case-crossover analyses of emergency department (ED) visits for International Classification of Diseases, 10^th Revision codes indicative of heat illness and major cardiorespiratory diagnostic codes using data from the Alaska Health Facilities Data Reporting Program. Using conditional logistic regression models, we tested maximum hourly HI temperature thresholds between 21.1°C (70°F) and 30°C (86°F) for a single day, 2 consecutive days, and the absolute number of previous consecutive days above the threshold, adjusting for the daily average concentration of particulate matter ≤2.5μg.

RESULTS

There were increased odds of ED visits for heat illness above a HI threshold as low as 21.1°C (70°F) [odds ratio (OR)=13.84; 95% confidence interval (CI): 4.05, 47.29], and this increased risk continued for up to 4 d (OR=2.43; 95% CI: 1.15, 5.10). Asthma and pneumonia were the only respiratory outcomes positively associated with the HI: ED visits for both were highest the day after a heat event (Asthma: HI>27°C(80°F) OR=1.18; 95% CI: 1.00, 1.39; Pneumonia: HI>28°C(82°F) OR=1.40; 95% CI: 1.06, 1.84). There was a decreased odds of bronchitis-related ED visits when the HI was above thresholds of 21.1-28°C (70-82°F) across all lag days. We found stronger effects for ischemia and myocardial infarction (MI) than for respiratory outcomes. Multiple days of warm weather were associated with an increased risk of health impacts. For each additional preceding day above a HI of 22°C (72°F), the odds of ED visits related to ischemia increased 6% (95% CI: 1%, 12%); for each additional preceding day above a HI of 21.1°C (70°F), the odds of ED visits related to MI increased 7% (95% CI: 1%, 14%).

DISCUSSION

This study demonstrates the importance of planning for extreme heat events and developing local guidance for heat warnings, even in areas with historically mild summertime climates. https://doi.org/10.1289/EHP11363.

Human Health and Well-being in a Warming World

Policy Points After decades of scientific progress and growth in academic literature, there is a recognition that climate change poses a substantial threat to the health and well-being of individuals and communities both in the United States and globally. Solutions to mitigate and adapt to climate change can have important health cobenefits. A vital component of these policy solutions is that they must also take into consideration historic issues of environmental justice and racism, and implementation of these policies must have a strong equity lens.

Comparison of various heat waves definitions and the burden of heat-related mortality in France: Implications for existing early warning systems

INTRODUCTION

In France, a heat warning system (HWS) has been implemented almost two decades ago and rely on some official heat wave (HW) definitions. However, no study has compared the burden associated with a large set of alternative HW definitions to the official definitions. Such comparison could be particularly helpful to identify HW conditions for which effective HWS would minimize the health burden across various geographical contexts and possibly update thresholds to trigger HWS. The aim of this study is to identify (and rank) definitions that drive the highest health burden in terms of mortality to inform future HWS across multiple cities in France.

METHODS

Based on weather data for 16 French cities, we compared the two official definitions used in France to: i) the Excess Heat Factor (EHF) used in Australia, and ii) 18 alternative hypothetical HW definitions based on various combinations of temperature metrics, intensity, and duration. Propensity score matching and Poisson regressions were used to estimate the effect of each HW exposure on non-accidental mortality for the May-September period from 2000 to 2015.

RESULTS

The associations between HW and mortality differed greatly depending on the definition. The greatest burden of heat was 1,055 (95% confidence interval "CI": [856; 1,302]) deaths per summer and was obtained with the EHF. The EHF identified HW with 2.46 (95% CI: [1.92; 3.58]) or 8.18 (95% CI: [6.63; 10.61]) times the global burden at the national level obtained with the climatological indicator of the French national weather service and the HW indicator of the French national HWS, respectively and was the most impactful definition pattern for both temperate oceanic and Mediterranean climate types.

CONCLUSION

Identifying the set of extreme heat conditions that drive the highest health burden in a given geographical context is particularly helpful when designing or updating heat early warning systems.

A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States

As climate change increases the frequency and intensity of devastating and unpredictable extreme heat events, developments to the built environment should consider instigating practices that minimize the likelihood of indoor overheating during hot weather. Heatwaves are the leading cause of death among weather-related causes worldwide, including in developed and developing countries. In this empirical study, a four-step approach was used to collect, extract and analyze data from twenty-seven states in the United States. Three housing characteristic categories (i.e., general housing conditions, living conditions, and housing thermal inertia) and eight variables were extracted from the American Housing Survey database, ResStock database and CDC's National Environmental Public Health Tracking Network. Multivariable regression models were used to understand the influential variables, a multicollinearity test was used to determine the dependence of those variables, and then a logistic model was used to verify the results. Three variables-housing age (HA), housing crowding ratio (HCR), and roof condition (RC)-were found to be correlated with the risk of heat-related illness (HRI) indexes. Then, a logistic regression model was generated using the three variables to predict the risk of heat-related emergency department visits (EDV) and heat-related mortality (MORD) on a state level. The results indicate that the proposed logistic regression model correctly predicted 100% of the high-risk states for MORD for the eight states tested. Overall, this analysis provides additional evidence about the housing character variables that influence HRI. The outcomes also reinforce the concept of the built environment determined health and demonstrate that the built environment, especially housing, should be considered in techniques for mitigating climate change-exacerbated health conditions.

Emergency Department Visits for Heat-Related Emergency Conditions in the United States from 2008-2020

Exposure to high temperatures is detrimental to human health. As climate change is expected to increase the frequency of extreme heat events, and raise ambient temperatures, an investigation into the trend of heat-related emergency department (ED) visits over the past decade is necessary to assess the human health impact of this growing public health crisis. ED visits were examined using the Nationwide Emergency Department Sample. Visits were included if the diagnostic field contained an ICD-9-CM or ICD-10-CM code specific to heat-related emergency conditions. Weighted counts were generated using the study design and weighting variables, to estimate the national burden of heat-related ED visits. A total of 1,078,432 weighted visits were included in this study. The annual incidence rate per 100,000 population increased by an average of 2.85% per year, ranging from 18.21 in 2009, to 32.34 in 2018. The total visit burden was greatest in the South (51.55%), with visits increasing to the greatest degree in the Midwest (8.52%). ED visit volume was greatest in July (29.79%), with visits increasing to the greatest degree in July (15.59%) and March (13.18%). An overall increase in heat-related ED visits for heat-related emergency conditions was found during the past decade across the United States, affecting patients in all regions and during all seasons.

The association of indoor heat exposure with diabetes and respiratory 9-1-1 calls through emergency medical dispatch and services documentation

BACKGROUND

People with pre-existing medical conditions, who spend a large proportion of their time indoors, are at risk of emergent morbidities from elevated indoor heat exposures. In this study, indoor heat of structures wherein exposed people received Grady Emergency Services based care in Atlanta, GA, U.S., was measured from May to September 2016.

METHOD

ology: In this case-control study, analyses were conducted to investigate the effect of indoor heat on the odds of 9-1-1 calls for diabetic (n = 90 cases) and separately, for respiratory (n = 126 cases), conditions versus heat-insensitive emergencies (n = 698 controls). Generalized Additive Models considered both linear and non-linear indoor heat and health outcome associations using thin-plate regression splines.

RESULTS

Hotter and more humid indoor conditions were non-linearly associated with an increasing likelihood of receiving emergency care for complications of diabetes and severe respiratory distress. Higher heat indices were associated with increased odds of a diabetes (odds ratio for change from 30 to 31 °C: 1.12, 95% CI: 1.08-1.16) or respiratory 9-1-1 medical call versus control (odds ratio for change from 34 to 35 °C: 1.18, 95% CI: 1.09-1.28) call. Both diabetic and respiratory distress patients were more likely to be African-American and/or have comorbidities.

CONCLUSIONS

In this study, the statistical association of indoor heat exposure with emergency morbidities (diabetic, respiratory) was demonstrated. The study also showcased the value and utility of data gathered by emergency medical dispatch and services from inaccessible private indoor sources (i.e., domiciles) for environmental health.

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Evaluations of heat action plans for reducing the health impacts of extreme heat: methodological developments (2012-2021) and remaining challenges

The recent report of the Intergovernmental Panel on Climate Change is stark in its warnings about the changing climate, including future increases in the frequency and intensity of extremely hot weather. The well-established impacts of extreme heat on human health have led to widespread implementation of national and city-wide heat plans for mitigating such impacts. Evaluations of the effectiveness of some heat plans have been published, with previous reviews highlighting key methodological challenges. This article reviews methods used since and that address those challenges, so helping to set an agenda for improving evaluations of heat plans in terms of their effectiveness in reducing heat-health impacts. We examined the reviews that identified the methodological challenges and systematically searched the literature to find evaluations that had since been conducted. We found 11 evaluations. Their methods help address the key challenge of identifying study control groups and address other challenges to a limited extent. For future evaluations, we recommend: utilising recent evaluation methodologies, such as difference-in-differences quasi-experimental designs where appropriate; cross-agency working to utilise data on morbidity and confounders; adoption of a proposed universal heat index; and greater publication of evaluations. More evaluations should assess morbidity outcomes and be conducted in low- and middle-income countries. Evaluations of heat plans globally should employ robust methodologies, as demonstrated in existing studies and potentially transferrable from other fields. Publication of such evaluations will advance the field and thus help address some of the health challenges resulting from our changing climate.

Impact of extreme temperatures on emergency hospital admissions by age and socio-economic deprivation in England

Climate change poses an unprecedented challenge to population health and health systems' resilience, with increasing fluctuations in extreme temperatures through pressures on hospital capacity. While earlier studies have estimated morbidity attributable to hot or cold weather across cities, we provide the first large-scale, population-wide assessment of extreme temperatures on inequalities in excess emergency hospital admissions in England. We used the universe of emergency hospital admissions between 2001 and 2012 combined with meteorological data to exploit daily variation in temperature experienced by hospitals (N = 29,371,084). We used a distributed lag model with multiple fixed-effects, controlling for seasonal factors, to examine hospitalisation effects across temperature-sensitive diseases, and further heterogeneous impacts across age and deprivation. We identified larger hospitalisation impacts associated with extreme cold temperatures than with extreme hot temperatures. The less extreme temperatures produce admission patterns like their extreme counterparts, but at lower magnitudes. Results also showed an increase in admissions with extreme temperatures that were more prominent among older and socioeconomically-deprived populations - particularly across admissions for metabolic diseases and injuries.

Wet-Bulb Globe Temperature, Universal Thermal Climate Index, and Other Heat Metrics for US Counties, 2000-2020

Epidemiologic research on extreme heat consistently finds significant impacts on human morbidity and mortality. However, most of these analyses do not use spatially explicit measures of heat (typically assessing exposures at major cities using the nearest weather station), and they frequently consider only ambient temperature or heat index. The field is moving toward more expansive analyses that use spatially resolved gridded meteorological datasets and alternative assessments of heat, such as wet-bulb globe temperature (WBGT) and universal thermal climate index (UTCI), both of which require technical geoscientific skills that may be inaccessible to many public health researchers. To facilitate research in this domain, we created a database of population-weighted, spatially explicit daily heat metrics - including WBGT, UTCI, heat index, dewpoint temperature, net effective temperature, and humidex - for counties in the conterminous United States derived from the ERA5-Land gridded data set and using previously validated equations and algorithms. We also provide an R package to calculate these metrics, including gold-standard algorithms for estimating WBGT and UTCI, to facilitate replication.

Attributing hypertensive life expectancy loss to ambient heat exposure: A multicenter study in eastern China

Ambient high temperature is a worldwide trigger for hypertension events. However, the effects of heat exposure on hypertension and years of life lost (YLL) due to heat remain largely unknown. We conducted a multicenter study in 13 cities in Jiangsu Province, China, to investigate 9727 individuals who died from hypertension during the summer months (May to September) between 2016 and 2017. Meteorological observation data (temperature and rainfall) and air pollutants (fine particulate matter and ozone) were obtained for each decedent by geocoding the residential addresses. A time-stratified case-crossover design was used to quantify the association between heat and different types of hypertension and further explore the modification effect of individual and hospital characteristics. Meanwhile, the YLL associated with heat exposure was estimated. Our results show that summer heat exposure shortens the YLL of hypertensive patients by a total of 14,74 years per month. Of these, 77.9% of YLL was mainly due to hypertensive heart disease. YLL due to heat was pronounced for essential hypertension (5.1 years (95% empirical confidence intervals (eCI): 4.1-5.8)), hypertensive heart and renal disease with heart failure (4.4 years (95% eCI: 0.9-5.9)), and hypertensive heart and renal disease (unspecified, 3.5 years (95% eCI: 1.8-4.5)). Moderate heat was associated with a larger YLL than extreme heat. The distance between hospitals and patients and the number of local first-class hospitals can significantly mitigate the adverse effect of heat exposure on longevity. Besides, unmarried people and those under 65 years of age were potentially susceptible groups, with average reduced YLL of 3.5 and 3.9 years, respectively. Our study reveals that heat exposure increases the mortality risk from many types of hypertension and YLL. In the context of climate change, if effective measures are not taken, hot weather may bring a greater burden of disease to hypertension due to premature death.

Understanding current and projected emergency department presentations and associated healthcare costs in a changing thermal climate in Adelaide, South Australia

Background

Exposure to extreme temperatures is associated with increased emergency department (ED) presentations. The resulting burden on health service costs and the potential impact of climate change is largely unknown. This study examines the temperature-EDs/cost relationships in Adelaide, South Australia and how this may be impacted by increasing temperatures.

Methods

A time series analysis using a distributed lag nonlinear model was used to explore the exposure–response relationships. The net-attributable, cold-attributable and heat-attributable ED presentations for temperature-related diseases and costs were calculated for the baseline (2014–2017) and future periods (2034–2037 and 2054–2057) under three climate representative concentration pathways (RCPs).

Results

The baseline heat-attributable ED presentations were estimated to be 3600 (95% empirical CI (eCI) 700 to 6500) with associated cost of $A4.7 million (95% eCI 1.8 to 7.5). Heat-attributable ED presentations and costs were projected to increase during 2030s and 2050s with no change in the cold-attributable burden. Under RCP8.5 and population growth, the increase in heat-attributable burden would be 1.9% (95% eCI 0.8% to 3.0%) for ED presentations and 2.5% (95% eCI 1.3% to 3.7%) for ED costs during 2030s. Under the same conditions, the heat effect is expected to increase by 3.7% (95% eCI 1.7% to 5.6%) for ED presentations and 5.0% (95% eCI 2.6% to 7.1%) for ED costs during 2050s.

Conclusions

Projected climate change is likely to increase heat-attributable emergency presentations and the associated costs in Adelaide. Planning health service resources to meet these changes will be necessary as part of broader risk mitigation strategies and public health adaptation actions.

Hot weather as a risk factor for kidney disease outcomes: A systematic review and meta-analysis of epidemiological evidence

BACKGROUND

The occurrence or exacerbation of kidney disease has been documented as a growing problem associated with hot weather. The implementation of effective prevention measures requires a better understanding of the risk factors that increase susceptibility. To fill gaps in knowledge, this study reviews the current literature on the effects of heat on kidney-disease outcomes (ICD-10 N00-N39), including morbidity and mortality.

METHODS

Databases were systematically searched for relevant literature published between 1990 and 2020 and the quality of evidence evaluated. We performed random effects meta-analysis to calculate the pooled relative risks (RRs) of the association between high temperatures (and heatwaves) and kidney disease outcomes. We further evaluated vulnerability concerning contextual population characteristics.

RESULTS

Of 2739 studies identified, 91 were reviewed and 82 of these studies met the criteria for inclusion in a meta-analysis. Findings showed that with a 1 °C increase in temperature, the risk of kidney-related morbidity increased by 1% (RR 1.010; 95% CI: 1.009-1.011), with the greatest risk for urolithiasis. Heatwaves were also associated with increased morbidity with a trend observed with heatwave intensity. During low-intensity heatwaves, there was an increase of 5.9% in morbidity, while during high-intensity heatwaves there was a 7.7% increase. There were greater RRs for males, people aged ≤64 years, and those living in temperate climate zones. Similarly, for every 1 °C temperature increase, there was a 3% (RR 1.031; 95% CI: 1.018-1.045) increase in the risk of kidney-related mortality, which also increased during heatwaves.

CONCLUSIONS

High temperatures (and heatwaves) are associated with an elevated risk of kidney disease outcomes, particularly urolithiasis. Preventive measures that may minimize risks in vulnerable individuals during hot spells are discussed.

Environmental Heat Exposure Among Pet Dogs in Rural and Urban Settings in the Southern United States

With advancing global climate change, heat-related illnesses and injuries are anticipated to become more prevalent for humans and other species. Canine hyperthermia is already considered an important seasonal emergency. Studies have been performed on the risk factors for heat stroke in canine athletes and military working dogs; however there is limited knowledge on environmental risk factors for the average pet dog. This observational study explores variation in individually experienced environmental temperatures of pet dogs (N = 30) in rural and urban environments in central Alabama. Temperature data from dogs and their owners was collected using wearable personal thermometers. Demographic data on the dogs was collected using a brief survey instrument completed by their owners. Dogs included in the study varied in signalment, activity level, and home environment. Linear mixed effects regression models were used to analyze repeated measure temperature and heat index values from canine thermometers to explore the effect of environmental factors on the overall heat exposure risk of canine pets. Specifically, the heat exposures of dogs were modeled considering their owner's experienced temperatures, as well as neighborhood and local weather station measurements, to identify factors that contribute to the heat exposure of individual dogs, and therefore potentially contribute to heat stress in the average pet dog. Results show hourly averaged temperatures for dogs followed a diurnal pattern consistent with both owner and ambient temperature measurements, except for indoor dogs whose recordings remained stable throughout the day. Heat index calculations showed that owners, in general, had more hours categorized into the National Weather Station safe category compared to their dogs, and that indoor dogs had a greater proportion of hours categorized as safe compared to outdoor dogs. Our results suggest that the risk of the average pet dog to high environmental heat exposure may be greater than traditional measures indicate, emphasizing that more localized considerations of temperature are important when assessing a dog's environmental risk for heat-related injury or illness.

Keeping Each Other Safe: Who Checks on Their Neighbors During Weather Extremes in Summer and Winter?

OBJECTIVE

Weather extremes are increasing with climate change and associated with higher morbidity and mortality. Promotion of social connections is an emerging area of research and practice for risk reduction during weather extremes. This study examines the practice of checking on neighbors during extreme summer heat and extreme winter weather. Objectives are to (1) describe the extent of neighbor checking during these extremes, and (2) examine factors associated with neighbor checking.

METHODS

We analyze survey data (n = 442) from a primarily low- and moderate- income study sample in a Southeastern U.S. city, using descriptive statistics and logistic regression.

RESULTS

About 17.6% of participants checked on neighbors during extreme summer heat, and 25.2% did so during extreme winter weather. Being middle or older aged and having more adverse physical health impacts were positively associated with neighbor checking, for both extremes. For winter only, having less education was positively associated with neighbor checking.

CONCLUSIONS

Community-based partnerships for reducing risk during weather extremes may consider people who are older or have experienced their own adverse health impacts as initial target groups for promoting neighbor checking. Future research should also examine the motivations for, details about, and impacts of neighbor checking in greater depth.

Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products

BACKGROUND

Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error.

METHODS

We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1 km spatial resolution.

RESULTS

Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center.

CONCLUSION

Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.

Impact of Extreme Weather on Healthcare Utilization by People with HIV in Metropolitan Miami

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990-2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017-2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients' 'no-show' status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of 'no-show' was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population's utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.

Evidence-Based Heatstroke Management in the Emergency Department

Introduction

Climate change is causing an increase in the frequency and intensity of extreme heat events, which disproportionately impact the health of vulnerable populations. Heatstroke, the most serious heat-related illness, is a medical emergency that causes multiorgan failure and death without intervention. Rapid recognition and aggressive early treatment are essential to reduce morbidity and mortality. The objective of this study was to evaluate current standards of care for the emergent management of heatstroke and propose an evidence-based algorithm to expedite care.

Methods

We systematically searched PubMed, Embase, and key journals, and reviewed bibliographies. Original research articles, including case studies, were selected if they specifically addressed the recognition and management of heatstroke in any prehospital, emergency department (ED), or intensive care unit population. Reviewers evaluated study quality and abstracted information regarding demographics, scenario, management, and outcome.

Results

In total, 63 articles met full inclusion criteria after full-text review and were included for analysis. Three key themes identified during the qualitative review process included recognition, rapid cooling, and supportive care. Rapid recognition and expedited external or internal cooling methods coupled with multidisciplinary management were associated with improved outcomes. Delays in care are associated with adverse outcomes. We found no current scalable ED alert process to expedite early goal-directed therapies.

Conclusion

Given the increased risk of exposure to heat waves and the time-sensitivity of the condition, EDs and healthcare systems should adopt processes for rapid recognition and management of heatstroke. This study proposes an evidence-based prehospital and ED heat alert pathway to improve early diagnosis and resource mobilization. We also provide an evidence-based treatment pathway to facilitate efficient patient cooling. It is hoped that this protocol will improve care and help healthcare systems adapt to changing environmental conditions.

Adding A Climate Lens To Health Policy In The United States

Climate change increasingly threatens the ability of the US health care system to deliver safe, effective, and efficient care to the American people. The existing health care system has key vulnerabilities that will grow more problematic as the effects of climate change on Americans' lives become stronger. Thus, health care policy makers must integrate a climate lens as they develop health system interventions. Applying a climate lens means assessing climate change-driven health risks and integrating them into policies and other actions to improve the nation's health. This lens can be applied to rethinking how to take a more population-based approach to health care delivery, prioritize health care system decarbonization and resilience, adapt data infrastructure, develop a climate-ready workforce, and pay for care. Our recommendations outline how to include climate-informed assessments into health care decision making and health policy, ultimately leading to a more resilient and equitable health care system that is better able to meet the needs of patients today and in the future.

Physiological factors characterizing heat-vulnerable older adults: A narrative review

More frequent and intense periods of extreme heat (heatwaves) represent the most direct challenge to human health posed by climate change. Older adults are particularly vulnerable, especially those with common age-associated chronic health conditions (e.g., cardiovascular disease, hypertension, obesity, type 2 diabetes, chronic kidney disease). In parallel, the global population is aging and age-associated disease rates are on the rise. Impairments in the physiological responses tasked with maintaining homeostasis during heat exposure have long been thought to contribute to increased risk of health disorders in older adults during heatwaves. As such, a comprehensive overview of the provisional links between age-related physiological dysfunction and elevated risk of heat-related injury in older adults would be of great value to healthcare officials and policy makers concerned with protecting heat-vulnerable sectors of the population from the adverse health impacts of heatwaves. In this narrative review, we therefore summarize our current understanding of the physiological mechanisms by which aging impairs the regulation of body temperature, hemodynamic stability and hydration status. We then examine how these impairments may contribute to acute pathophysiological events common during heatwaves (e.g., heatstroke, major adverse cardiovascular events, acute kidney injury) and discuss how age-associated chronic health conditions may exacerbate those impairments. Finally, we briefly consider the importance of physiological research in the development of climate-health programs aimed at protecting heat-vulnerable individuals.

Mapping Human Vulnerability to Extreme Heat: A Critical Assessment of Heat Vulnerability Indices Created Using Principal Components Analysis

BACKGROUND

Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping.

OBJECTIVE

We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA.

METHODS

We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) "unsupervised"-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) "supervised"-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles).

RESULTS

Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups.

DISCUSSION

HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.

Defining heat waves and extreme heat events using sub-regional meteorological data to maximize benefits of early warning systems to population health

BACKGROUND

Extreme heat events have been consistently associated with an increased risk of hospitalization for various hospital diagnoses. Classifying heat events is particularly relevant for identifying the criteria to activate early warning systems. Heat event classifications may also differ due to heterogeneity in climates among different geographic regions, which may occur at a small scale. Using local meteorological data, we identified heat waves and extreme heat events that were associated with the highest burden of excess hospitalizations within the County of San Diego and quantified discrepancies using county-level meteorological criteria.

METHODS

Eighteen event classifications were created using various combinations of temperature metric, percentile, and duration for both county-level and climate zone level meteorological data within San Diego County. Propensity score matching and Poisson regressions were utilized to ascertain the association between heat wave exposure and risk of hospitalization for heat-related illness and dehydration for the 1999-2013 period. We estimated both relative and absolute risks for each heat event classification in order to identify optimal definitions of heat waves and extreme heat events for the whole city and in each climate zone to target health impacts.

RESULTS

Heat-related illness differs vastly by level (county or zone-specific), definition, and risk measure. We found the county-level definitions to be systematically biased when compared to climate zone definitions with the largest discrepancy of 56 attributable hospitalizations. The relative and attributable risks were often minimally correlated, which exemplified that relative risks alone are not adequate to optimize heat waves definitions.

CONCLUSIONS

Definitions based on county-level defined thresholds do not provide an accurate picture of the observed health effects and will fail to maximize the potential effectiveness of heat warning systems. Absolute rather than relative risks are a more appropriate measure to define the set of criteria to activate early warnings systems and thus maximize public health benefits.

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.

Heatwave Events and Mortality Outcomes in Memphis, Tennessee: Testing Effect Modification by Socioeconomic Status and Urbanicity

Heatwave studies typically estimate heat-related mortality and morbidity risks at the city level; few have addressed the heterogeneous risks by socioeconomic status (SES) and location within a city. This study aimed to examine the impacts of heatwaves on mortality outcomes in Memphis, Tennessee, a Mid-South metropolitan area top-ranked in morbidity and poverty rates, and to investigate the effects of SES and urbanicity. Mortality data were retrieved from the death records in 2008-2017, and temperature data from the Applied Climate Information System. Heatwave days were defined based on four temperature metrics. Heatwave effects on daily total-cause, cardiovascular, and respiratory mortality were evaluated using Poisson regression, accounting for temporal trends, sociodemographic factors, urbanicity, and air pollution. We found higher cardiovascular mortality risk (cumulative RR (relative risk) = 1.25, 95% CI (confidence interval): 1.01-1.55) in heatwave days defined as those with maximum daily temperature >95th percentile for more than two consecutive days. The effects of heatwaves on mortality did not differ by SES, race, or urbanicity. The findings of this study provided evidence to support future heatwave planning and studies of heatwave and health impacts at a coarser geographic resolution.