Comparison of health risks by heat wave definition: Applicability of wet-bulb globe temperature for heat wave criteria

Existing Challenges and Opportunities for Advancing Drought and Health Research

PURPOSE OF REVIEW

Drought is one of the most far-reaching natural disasters, yet drought and health research is sparse. This may be attributed to the challenge of quantifying drought exposure, something complicated by multiple drought indices without any designed for health research. The purpose of this general review is to evaluate current drought and health literature and highlight challenges or scientific considerations when performing drought exposure and health assessments.

RECENT FINDINGS

The literature revealed a small, but growing, number of drought and health studies primarily emphasizing Australian, western European, and US populations. The selection of drought indices and definitions of drought are inconsistent. Rural and agricultural populations have been identified as vulnerable cohorts, particularly for mental health outcomes. Using relevant examples, we discuss the importance of characterizing drought and explore why health outcomes, populations of interest, and compound environmental hazards are crucial considerations for drought and health assessments. As climate and health research is prioritized, we propose guidance for investigators performing drought-focused analyses.

Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes

The wet bulb temperature (Tw) has gained considerable attention as a crucial indicator of heat-related health risks. Here we report south-to-north spatially heterogeneous trends of Tw in China over 1979-2018. We find that actual water vapor pressure (Ea) changes play a dominant role in determining the different trend of Tw in southern and northern China, which is attributed to the faster warming of high-latitude regions of East Asia as a response to climate change. This warming effect regulates large-scale atmospheric features and leads to extended impacts of the South Asia high (SAH) and the western Pacific subtropical high (WPSH) over southern China and to suppressed moisture transport. Attribution analysis using climate model simulations confirms these findings. We further find that the entire eastern China, that accommodates 94% of the country's population, is likely to experience widespread and uniform elevated thermal stress the end of this century. Our findings highlight the necessity for development of adaptation measures in eastern China to avoid adverse impacts of heat stress, suggesting similar implications for other regions as well.

Health risks from extreme heat in China: Evidence from health insurance

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change.

A nationwide time-series analysis for short-term effects of ambient temperature on violent crime in South Korea

Psychological theories on heat-aggression relationship have existed for decades and recent models suggest climate change will increase violence through varying pathways. Although observational studies have examined the impact of temperature on violent crime, the evidence for associations is primarily limited to coarse temporal resolution of weather and crime (e.g., yearly/monthly) and results from a few Western communities, warranting studies based on higher temporal resolution data of modern systemic crime statistics for various regions. This observational study examined short-term temperature impacts on violent crime using national crime data for the warm months (Jun.-Sep.) across South Korea (2016-2020). Distributed lag non-linear models assessed relative risks (RRs) of daily violent crime counts at the 70th, 90th, and 99th summer temperature percentiles compared to the reference temperature (10th percentile), with adjustments for long-term trends, seasonality, weather, and air pollution. Results indicate potentially non-linear relationships between daily summer temperature (lag0-lag10) and violent crime counts. Violent crimes consistently increased from the lowest temperature and showed the highest risk at the 70th temperature (~ 28.0 °C). The RR at the 70th and 90th percentiles of daily mean temperature (lag0-lag10), compared to the reference, was 1.11 (95% CI 1.09, 1.15) and 1.04 (95% CI 1.01, 1.07), indicating significant associations. Stratified analysis showed significant increases in assault and domestic violence for increases in temperature. The lagged effects, the influences of heat on subsequent crime incidence, did not persist 21 days after the exposure, possibly due to the displacement phenomenon. We found curvilinear exposure-response relationships, which provide empirical evidence to support the psychological theories for heat and violence. Lower public safety through increased violent crime may be an additional public health harm of climate change.

Hourly values of an advanced human-biometeorological index for diverse populations from 1991 to 2020 in Greece

Existing assessments of the thermal-related impact of the environment on humans are often limited by the use of data that are not representative of the population exposure and/or not consider a human centred approach. Here, we combine high resolution regional retrospective analysis (reanalysis), population data and human energy balance modelling, in order to produce a human thermal bioclimate dataset capable of addressing the above limitations. The dataset consists of hourly, population-weighted values of an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), at fine-scale administrative level and for 10 different population groups. It also includes the main environmental drivers of mPET at the same spatiotemporal resolution, covering the period from 1991 to 2020. The study area is Greece, but the provided code allows for the ease replication of the dataset in countries included in the domains of the climate reanalysis and population data, which focus over Europe. Thus, the presented data and code can be exploited for human-biometeorological and environmental epidemiological studies in the European continent.

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 3: Heat and cold tolerance during exercise

In this third installment of our four-part historical series, we evaluate contributions that shaped our understanding of heat and cold stress during occupational and athletic pursuits. Our first topic concerns how we tolerate, and sometimes fail to tolerate, exercise-heat stress. By 1900, physical activity with clothing- and climate-induced evaporative impediments led to an extraordinarily high incidence of heat stroke within the military. Fortunately, deep-body temperatures > 40 °C were not always fatal. Thirty years later, water immersion and patient treatments mimicking sweat evaporation were found to be effective, with the adage of cool first, transport later being adopted. We gradually acquired an understanding of thermoeffector function during heat storage, and learned about challenges to other regulatory mechanisms. In our second topic, we explore cold tolerance and intolerance. By the 1930s, hypothermia was known to reduce cutaneous circulation, particularly at the extremities, conserving body heat. Cold-induced vasodilatation hindered heat conservation, but it was protective. Increased metabolic heat production followed, driven by shivering and non-shivering thermogenesis, even during exercise and work. Physical endurance and shivering could both be compromised by hypoglycaemia. Later, treatments for hypothermia and cold injuries were refined, and the thermal after-drop was explained. In our final topic, we critique the numerous indices developed in attempts to numerically rate hot and cold stresses. The criteria for an effective thermal stress index were established by the 1930s. However, few indices satisfied those requirements, either then or now, and the surviving indices, including the unvalidated Wet-Bulb Globe-Thermometer index, do not fully predict thermal strain.

Comparing Approximated Heat Stress Measures Across the United States

Climate change is escalating the threat of heat stress to global public health, with the majority of humans today facing increasingly severe and prolonged heat waves. Accurate weather data reflecting the complexity of measuring heat stress is crucial for reducing the impact of extreme heat on health worldwide. Previous studies have employed Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) metrics to understand extreme heat exposure, forming the basis for heat stress guidelines. However, systematic comparisons of meteorological and climate data sets used for these metrics and the related parameters, like air temperature, humidity, wind speed, and solar radiation crucial for human thermoregulation, are lacking. We compared three heat measures (HImax, WBGTBernard, and WBGTLiljegren) approximated from gridded weather data sets (ERA5-Land, PRISM, Daymet) with ground-based data, revealing strong agreement from HI and WBGTBernard (R 2 0.76-0.95, RMSE 1.69-6.64°C). Discrepancies varied by Köppen-Geiger climates (e.g., Adjusted R 2 HImax 0.88-0.95, WBGTBernard 0.79-0.97, and WBGTLiljegren 0.80-0.96), and metrological input variables (Adjusted R 2 T max 0.86-0.94, T min 0.91-0.94, Wind 0.33, Solarmax 0.38, Solaravg 0.38, relative humidity 0.51-0.74). Gridded data sets can offer reliable heat exposure assessment, but further research and local networks are vital to reduce measurement errors to fully enhance our understanding of how heat stress measures link to health outcomes.

Heat impacts on human health in the Western Pacific Region: an umbrella review

Background

High temperatures and heatwaves are occurring more frequently and lasting longer because of climate change. A synthesis of existing evidence of heat-related health impacts in the Western Pacific Region (WPR) is lacking. This review addresses this gap.

Methods

The Scopus and PubMed databases were searched for reviews about heat impacts on mortality, cardiovascular morbidity, respiratory morbidity, dehydration and heat stroke, adverse birth outcomes, and sleep disturbance. The last search was conducted in February 2023 and only publications written in English were included. Primary studies and reviews that did not include specific WPR data were excluded. Data were extracted from 29 reviews.

Findings

There is strong evidence of heat-related mortality in the WPR, with the evidence concentrating on high-income countries and China. Associations between heat and cardiovascular or respiratory morbidity are not robust. There is evidence of heat-related dehydration and stroke, and preterm and still births in high-income countries in the WPR. Some evidence of sleep disturbance from heat is found for Australia, Japan and China.

Interpretation

Mortality is by far the most studied and robust health outcome of heat. Future research should focus on morbidity, and lower income countries in continental Asia and Pacific Island States, where there is little review-level evidence.

Funding

Funded by the World Health Organization WPR Office.

Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model

BACKGROUND

The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is essential.

OBJECTIVE

This paper is the first of its kind to propose land-use based spatial machine learning (LBSM) models for predicting highly spatial-temporal variations of wet-bulb globe temperature (WBGT), which is a heat stress indicator used to assess thermal comfort in indoor and outdoor environments, specifically for the main island of Taiwan.

METHODS

To develop spatiotemporal prediction models for both the working period and noon period, we calculated the WBGT of each weather station from 2001 to 2019 using temperature, humidity, and solar radiation data. These WBGT estimations were then used as the dependent variable for developing the spatiotemporal prediction models. To enhance model performance, we used innovative approaches that combined SHapley Additive exPlanations (SHAP) values for the selection of non-linear variables, along with machine learning algorithms for model development.

RESULTS

When incorporating temperature along with other land-use/land cover predictor variables, the performance of LBSM models was excellent, with an R2 value of up to 0.99. The LBSM models explained 98% and 99% of the spatial-temporal variations in WBGT for the working and noon periods, respectively, within the complete models. In the temperature-excluded models, the explained variances were 94% and 96% for the working and noon periods, respectively.

IMPACT

WBGT is a common method used by many organizations to access the impact of heat stress on human beings. However, limited studies have mentioned the association between WBGT and health impacts due to the absence of spatiotemporal databases. This study develops a new approach using land-use-based spatial machine learning (LBSM) models to better predict the fine spatial-temporal WBGT levels, with a 50-m × 50-m grid resolution for both working time and noontime. Our proposed methodology could be used in future studies aimed at evaluating the potential long-term loss of work productivity due to the effects of global warming or urban heat island.

Analysis of heatwaves based on the universal thermal climate index and apparent temperature over mainland Southeast Asia

Heatwaves have caused significant damage to human health, infrastructure, and economies in recent decades, and the occurrences of heatwaves are becoming more frequent and severe across the globe under climate change. The previous studies on heatwaves have primarily focused on air temperature, neglecting other variables like wind speed, relative humidity, and radiation, which could lead to a serious underestimation of the adverse effects of heatwaves. To address this issue, this study proposed to the use of more sophisticated thermal indices, such as universal thermal climate index (UTCI) and apparent temperature (AT), to define heatwaves and carry out a comprehensive heatwave assessment over mainland southeast Asia (MSEA) from 1961 to 2020. The traditional temperature-based method was also compared. The results of the study demonstrate that the annual maximum temperature in heatwave days (HWA) and the annual average temperature in heatwave days (HWM) are significantly underestimated if only air temperature is considered. However, UTCI and AT tend to predict a lower frequency of yearly heatwave occurrences and shorter durations. Trend analysis indicates a general increase in heatwave occurrences across MSEA under all thermal indices in the past six decades, particularly in the last 30 years. This study's approach and findings provide a holistic view of heatwave characteristics based on thermal indices and highlight the risk of intensified heat stress during heatwaves in MSEA.

Assessing the Effect of Extreme Weather on Population Health Using Consumer-Grade Wearables in Rural Burkina Faso: Observational Panel Study

BACKGROUND

Extreme weather, including heat and extreme rainfall, is projected to increase owing to climate change, which can have adverse impacts on human health. In particular, rural populations in sub-Saharan Africa are at risk because of a high burden of climate-sensitive diseases and low adaptive capacities. However, there is a lack of data on the regions that are anticipated to be most exposed to climate change. Improved public health surveillance is essential for better decision-making and health prioritization and to identify risk groups and suitable adaptation measures. Digital technologies such as consumer-grade wearable devices (wearables) may generate objective measurements to guide data-driven decision-making.

OBJECTIVE

The main objective of this observational study was to examine the impact of weather exposure on population health in rural Burkina Faso using wearables. Specifically, this study aimed to assess the relationship between individual daily activity (steps), sleep duration, and heart rate (HR), as estimated by wearables, and exposure to heat and heavy rainfall.

METHODS

Overall, 143 participants from the Nouna health and demographic surveillance system in Burkina Faso wore the Withings Pulse HR wearable 24/7 for 11 months. We collected continuous weather data using 5 weather stations throughout the study region. The heat index and wet-bulb globe temperature (WBGT) were calculated as measures of heat. We used linear mixed-effects models to quantify the relationship between exposure to heat and rainfall and the wearable parameters. Participants kept activity journals and completed a questionnaire on their perception of and adaptation to heat and other weather exposure.

RESULTS

Sleep duration decreased significantly (P<.001) with higher heat exposure, with approximately 15 minutes shorter sleep duration during heat stress nights with a heat index value of ≥25 °C. Many participants (55/137, 40.1%) reported that heat affected them the most at night. During the day, most participants (133/137, 97.1%) engaged in outdoor physical work such as farming, housework, or fetching water. During the rainy season, when WBGT was highest, daily activity was highest and increased when the daily maximum WBGT surpassed 30 °C during the rainiest month. In the hottest month, daily activity decreased per degree increase in WBGT for values >30 °C. Nighttime HR showed no significant correlation with heat exposure. Daytime HR data were insufficient for analysis. We found no negative health impact associated with heavy rainfall. With increasing rainfall, sleep duration increased, average nightly HR decreased, and activity decreased.

CONCLUSIONS

During the study period, participants were frequently exposed to heat and heavy rainfall. Heat was particularly associated with impaired sleep and daily activity. Essential tasks such as harvesting, fetching water, and caring for livestock expose this population to weather that likely has an adverse impact on their health. Further research is essential to guide interventions safeguarding vulnerable communities.

Urban Versus Lake Impacts on Heat Stress and Its Disparities in a Shoreline City

Shoreline cities are influenced by both urban-scale processes and land-water interactions, with consequences on heat exposure and its disparities. Heat exposure studies over these cities have focused on air and skin temperature, even though moisture advection from water bodies can also modulate heat stress. Here, using an ensemble of model simulations covering Chicago, we find that Lake Michigan strongly reduces heat exposure (2.75°C reduction in maximum average air temperature in Chicago) and heat stress (maximum average wet bulb globe temperature reduced by 0.86°C) during the day, while urbanization enhances them at night (2.75 and 1.57°C increases in minimum average air and wet bulb globe temperature, respectively). We also demonstrate that urban and lake impacts on temperature (particularly skin temperature), including their extremes, and lake-to-land gradients, are stronger than the corresponding impacts on heat stress, partly due to humidity-related feedback. Likewise, environmental disparities across community areas in Chicago seen for skin temperature are much higher (1.29°C increase for maximum average values per $10,000 higher median income per capita) than disparities in air temperature (0.50°C increase) and wet bulb globe temperature (0.23°C increase). The results call for consistent use of physiologically relevant heat exposure metrics to accurately capture the public health implications of urbanization.

A multiscale analysis of heatwaves and urban heat islands in the western U.S. during the summer of 2021

Extreme heat events are occurring more frequently and with greater intensity due to climate change. They result in increased heat stress to populations causing human health impacts and heat-related deaths. The urban environment can also exacerbate heat stress because of man-made materials and increased population density. Here we investigate the extreme heatwaves in the western U.S. during the summer of 2021. We show the atmospheric scale interactions and spatiotemporal dynamics that contribute to increased temperatures across the region for both urban and rural environments. In 2021, daytime maximum temperatures during heat events in eight major cities were 10-20 °C higher than the 10-year average maximum temperature. We discuss the temperature impacts associated with processes across scales: climate or long-term change, the El Niño-Southern Oscillation, synoptic high-pressure systems, mesoscale ocean/lake breezes, and urban climate (i.e., urban heat islands). Our findings demonstrate the importance of scale interactions impacting extreme heat and the need for holistic approaches in heat mitigation strategies.

Wet Bulb Globe Temperature: Indicating Extreme Heat Risk on a Global Grid

The Wet Bulb Globe Temperature (WBGT) is an international standard heat index used by the health, industrial, sports, and climate sectors to assess thermal comfort during heat extremes. Observations of its components, the globe and the wet bulb temperature (WBT), are however sparse. Therefore WBGT is difficult to derive, making it common to rely on approximations, such as the ones developed by Liljegren et al. (2008, https://doi.org/10.1080/15459620802310770, W B G T L i l j e g r e n ) and by the American College of Sports Medicine ( W B G T A C S M 87 ). In this study, a global data set is created by implementing an updated WBGT method using ECMWF ERA5 gridded meteorological variables and is evaluated against existing WBGT methods. The new method, W B G T B r i m i c o m b e , uses globe temperature calculated using mean radiant temperature and is found to be accurate in comparison to W B G T L i l j e g r e n across three heatwave case studies. In addition, it is found that W B G T A C S M 87 is not an adequate approximation of WBGT. Our new method is a candidate for a global forecasting early warning system.

Urban heat in Johannesburg and Ekurhuleni, South Africa: A meter-scale assessment and vulnerability analysis

Heat stress is an important threat for human health and urban areas are affected at higher rates compared to rural environments. Additionally, climate change will increase the vulnerability towards urban heat stress in the future. Current high-resolution urban heat stress assessments are limited in time and space due to the high computational costs. In this paper, the UrbClim numerical model is used to simulate urban heat accurately at a fast rate and high spatial resolution for the cities of Johannesburg and Ekurhuleni, South Africa. Using detailed terrain information, (future) urban heat stress assessments are provided at 30 m resolution for both city agglomerations, while meter-scale simulations are executed for a selection of neighborhoods. These model simulations are evaluated using an extensive monitoring campaign in which the local community was heavily engaged. Distinct spatial differences in the urban heat island effect are observed, with greatest heat stress in areas with high building densities and low vegetation numbers. These areas are often characterized by lower socio-economic living conditions. The meter-scale analysis further shows the importance of shade provided by vegetation to lower heat stress in both present and future climate. These assessments offer assistance in the design of climate-resilient urban planning strategies.

Associations Between Ambient Extreme Heat Exposure and Emergency Department Visits Related to Kidney Disease

RATIONALE & OBJECTIVE

Extreme heat exposure is associated with multiple diseases. However, our current understanding of the specific impact of extreme heat exposure on kidney disease is limited.

STUDY DESIGN

Case-crossover study.

SETTING & PARTICIPANTS

1,114,322 emergency department (ED) visits with a principal diagnosis of kidney disease were identified in New York state, 2005-2013.

EXPOSURE

Extreme heat exposure was defined as when the daily temperature exceeded the 90th percentile temperature of that month during the study period in the county.

OUTCOME

ED visits with a principal diagnosis of kidney disease and its subtypes (ICD-9 [International Classification of Diseases, Ninth Revision] codes 580-599, 788).

ANALYTICAL APPROACH

Extreme heat exposure on the ED visit days was compared with extreme heat exposure on control days using a conditional logistic regression model, controlling for humidity, air pollutants, and holidays. The excess risk of kidney disease was calculated for a week (lag days 0-6) after extreme heat exposure during the warm season (May through September). We also stratified our estimates by sociodemographic characteristics.

RESULTS

Extreme heat exposure was associated with a 1.7% (lag day 0) to 3.1% (lag day 2) higher risk of ED visits related to kidney disease; this association was stronger with a greater number of extreme heat exposure days in the previous week. The association with extreme heat exposure lasted for an entire week and was stronger in the transitional months (ie, May and September; excess rates ranged from 1.8% to 5.1%) rather than the summer months (June through August; excess rates ranged from 1.5% to 2.7%). The strength of association was greater among those with ED visits related to acute kidney injury, kidney stones, and urinary tract infections. Age and sex may modify the association between extreme heat exposure and ED visits.

LIMITATIONS

Individual exposure to heat-how long people were outside or whether they had access to air conditioning-was unknown.

CONCLUSIONS

Extreme heat exposure was significantly associated with a dose-dependent greater risk of ED visits for kidney disease.

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.

Internet searches and heat-related emergency department visits in the United States

Emerging research suggests that internet search patterns may provide timely, actionable insights into adverse health impacts from, and behavioral responses to, days of extreme heat, but few studies have evaluated this hypothesis, and none have done so across the United States. We used two-stage distributed lag nonlinear models to quantify the interrelationships between daily maximum ambient temperature, internet search activity as measured by Google Trends, and heat-related emergency department (ED) visits among adults with commercial health insurance in 30 US metropolitan areas during the warm seasons (May to September) from 2016 to 2019. Maximum daily temperature was positively associated with internet searches relevant to heat, and searches were in turn positively associated with heat-related ED visits. Moreover, models combining internet search activity and temperature had better predictive ability for heat-related ED visits compared to models with temperature alone. These results suggest that internet search patterns may be useful as a leading indicator of heat-related illness or stress.

Knowledge Gaps and Research Priorities on the Health Effects of Heatwaves: A Systematic Review of Reviews

Although extreme weather events have played a constant role in human history, heatwaves (HWs) have become more frequent and intense in the past decades, causing concern especially in light of the increasing evidence on climate change. Despite the increasing number of reviews suggesting a relationship between heat and health, these reviews focus primarily on mortality, neglecting other important aspects. This systematic review of reviews gathered the available evidence from research syntheses conducted on HWs and health. Following the PRISMA guidelines, 2232 records were retrieved, and 283 reviews were ultimately included. Information was extracted from the papers and categorized by topics. Quantitative data were extracted from meta-analyses and, when not available, evidence was collected from systematic reviews. Overall, 187 reviews were non-systematic, while 96 were systematic, of which 27 performed a meta-analysis. The majority evaluated mortality, morbidity, or vulnerability, while the other topics were scarcely addressed. The following main knowledge gaps were identified: lack of a universally accepted definition of HW; scarce evidence on the HW-mental health relationship; no meta-analyses assessing the risk perception of HWs; scarcity of studies evaluating the efficacy of adaptation strategies and interventions. Future efforts should meet these priorities to provide high-quality evidence to stakeholders.

Impact of low-intensity heat events on mortality and morbidity in regions with hot, humid summers: a scoping literature review

The objective of this study is to determine the impacts of low-intensity heat on human health in regions with hot, humid summers. Current literature has highlighted an increase in mortality and morbidity rates during significant heat events. While the impacts on high-intensity events are established, the impacts on low-intensity events, particularly in regions with hot, humid summers, are less clear. A scoping review was conducted searching three databases (PubMed, EMBASE, Web of Science) using key terms based on the inclusion criteria. We included papers that investigated the direct human health impacts of low-intensity heat events (single day or heatwaves) in regions with hot, humid summers in middle- and high-income countries. We excluded papers written in languages other than English. Of the 600 publications identified, 33 met the inclusion criteria. Findings suggest that low-intensity heatwaves can increase all-cause non-accidental, cardiovascular-, respiratory- and diabetes-related mortality, in regions experiencing hot, humid summers. Impacts of low-intensity heatwaves on morbidity are less clear, with research predominantly focusing on hospitalisation rates with a range of outcomes. Few studies investigating the impact of low-intensity heat events on emergency department presentations and ambulance dispatches were found. However, the data from a limited number of studies suggest that both of these outcome measures increase during low-intensity heat events. Low-intensity heat events may increase mortality. There is insufficient evidence of a causal effect of low-intensity heat events on increasing morbidity for a firm conclusion. Further research on the impact of low-intensity heat on morbidity and mortality using consistent parameters is warranted.

Investigating city bike rental usage and wet-bulb globe temperature

Extreme heat exacerbates human illness and constrains the intensity and/or duration of outdoor activities. Temperature is an incomplete metric of outdoor heat exposures. By contrast, Wet Bulb Globe Temperature (WBGT) is a heat exposure metric that considers air temperature, moisture, solar radiation, and wind speed. In the USA, bicycle activity increased by 60% from 2000 to 2010. Several studies examined weather conditions and bicycling activities. However, few studies examined how the public should conduct their daily physical activities per weather conditions.This study investigated the relationship between WBGT and shared city bicycle activity in New York City (NYC) and San Francisco (SF), USA. Generalized Additive Models examined nonlinear relationships between WBGT and bicycle activity while controlling for rider demographics and temporal trends. Next, bootstrapping estimated the "peak point", when the relationship between the bike rentals and WBGT notably changed.The analysis also examined whether the heat warning messages affected cycling activities. We found that the number of rented bikes declined at different peak points in each city. The peak point was in NYC at 34.3°C (95% CI 33°C-35°C) and 10.8°C (95% CI 10-12°C) in SF. Somewhat paradoxically, bike rentals increased when heat warnings were issued in both cities.

Mapping Heat-Health Vulnerability Based on Remote Sensing: A Case Study in Karachi

As a result of global climate change, the frequency and intensity of heat waves have increased significantly. According to the World Meteorological Organization (WMO), extreme temperatures in southwestern Pakistan have exceeded 54 °C in successive years. The identification and assessment of heat-health vulnerability (HHV) are important for controlling heat-related diseases and mortality. At present, heat waves have many definitions. To better describe the heat wave mortality risk, we redefine the heat wave by regarding the most frequent temperature (MFT) as the minimum temperature threshold for HHV for the first time. In addition, different indicators that serve as relevant evaluation factors of exposure, sensitivity and adaptability are selected to conduct a kilometre-level HHV assessment. The hesitant analytic hierarchy process (H-AHP) method is used to evaluate each index weight. Finally, we incorporate the weights into the data layers to establish the final HHV assessment model. The vulnerability in the study area is divided into five levels, high, middle-high, medium, middle-low and low, with proportions of 3.06%, 46.55%, 41.85%, 8.53% and 0%, respectively. Health facilities and urbanization were found to provide advantages for vulnerability reduction. Our study improved the resolution to describe the spatial heterogeneity of HHV, which provided a reference for more detailed model construction. It can help local government formulate more targeted control measures to reduce morbidity and mortality during heat waves.

Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries

The low-cost and easy-to-use nature of rapidly developed PM_2.5 sensors provide an opportunity to bring breakthroughs in PM_2.5 research to resource-limited countries in Southeast Asia (SEA). This review provides an evaluation of the currently available literature and identifies research priorities in applying low-cost sensors (LCS) in PM_2.5 environmental and health research in SEA. The research priority is an outcome of a series of participatory workshops under the umbrella of the International Global Atmospheric Chemistry Project–Monsoon Asia and Oceania Networking Group (IGAC–MANGO). A literature review and research prioritization are conducted with a transdisciplinary perspective of providing useful scientific evidence in assisting authorities in formulating targeted strategies to reduce severe PM_2.5 pollution and health risks in this region. The PM_2.5 research gaps that could be filled by LCS application are identified in five categories: source evaluation, especially for the distinctive sources in the SEA countries; hot spot investigation; peak exposure assessment; exposure–health evaluation on acute health impacts; and short-term standards. The affordability of LCS, methodology transferability, international collaboration, and stakeholder engagement are keys to success in such transdisciplinary PM_2.5 research. Unique contributions to the international science community and challenges with LCS application in PM_2.5 research in SEA are also discussed.

Outdoor thermal stress changes in South Korea: Increasing inter-annual variability induced by different trends of heat and cold stresses

Changes of thermal environment can lead to unfavorable impacts such as a decrease of thermal stratification, increase of energy consumption, and increase of thermal health risk. Investigating changes in outdoor thermal environments can provide meaningful information for addressing economic and social issues and related challenges. In this study, thermal environment changes in South Korea were investigated using a nonstationary two-component Gaussian mixture model (NSGMM) for air temperature and two thermal comfort indices. For this, the perceived temperature (PT) and universal thermal climate index (UTCI) were employed as the thermal comfort index. Thermal comfort indices were computed using observed meteorological data at 26 weather stations for 37 years in South Korea. Meanwhile, trends of thermal comforts in the warm and cool seasons were simultaneously modeled by the NSGMM. The results indicate significant increasing trends in thermal comfort indices for South Korea. The increasing trends in thermal comfort indices both the warm and cool seasons were detected while the magnitudes of the trends are significantly different. This difference between the magnitude of trends led to an increase in mean and inter-annual variability of thermal comfort indices based on PT, while an increase of mean and decrease of inter-annual variability were observed based on the UTCI. Moreover, the annual proportion of the category referring to days in comfort based on the results of PT has decreased due to the different trends of thermal comfort indices in the warm and cool seasons. This decrease may lead to an increase of thermal health risk that is larger than what would be expected from the results considering the increasing trend of the annual mean temperature in South Korea. From this result, it can be inferred that the thermal health risk in South Korea may be more adverse than what we originally expected from the current temperature trend.

Approaches for identifying heat-vulnerable populations and locations: A systematic review

Heat related morbidity and mortality, especially during extreme heat events, are increasing due to climate change. More Americans die from heat than from all other natural disasters combined. Identifying the populations and locations that are under high risk of heat vulnerability is important for urban planning and design policy making as well as health interventions. An increasing number of heat vulnerability/risk models and indices (HV/R) have been developed based on indicators related to population heat susceptibility such as sociodemographic and environmental factors. The objectives of this study are to summarize and analyze current HV/R's construction, calculation, and validation, evaluate the limitation of these methods, and provide directions for future HV/R and related studies. This systematic review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework and used 5 datasets for the literature search. Journal articles that developed indices or models to assess population level heat-related vulnerability or risks in the past 50 years were included. A total of 52 papers were included for analysis on model construction, data sources, weighting schemes and model validation. By synthesizing the findings, we suggested: (1) include relevant and accurately measured indicators; (2) select rational weighting methods and; (3) conduct model validation. We also concluded that it is important for future heat vulnerability models and indices studies to: (1) be conducted in more tropical areas; (2) include a comprehensive understanding of energy exchanges between landscape elements and humans; and (3) be applied in urban planning and policy making practice.

Feasibility, acceptability and validation of wearable devices for climate change and health research in the low-resource contexts of Burkina Faso and Kenya: Study protocol

As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population's burden of disease. The burden of disease of climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vulnerable populations, such as heat stress on human cardiovascular response. The overall goal of this study is to investigate whether consumer-grade wearable devices are an acceptable, feasible and valid means to generate data on the individual level in low-resource contexts. Three hundred individuals are recruited from the two study locations in the Nouna health and demographic surveillance system (HDSS), Burkina Faso, and the Siaya HDSS, Kenya. Participants complete a structured questionnaire that comprises question items on acceptability and feasibility under the supervision of trained data collectors. Validity will be evaluated by comparing consumer-grade wearable devices to research-grade devices. Furthermore, we will collect demographic data as well as the data generated by wearable devices. This study will provide insights into the usage of consumer-grade wearable devices to measure individual vital signs in low-resource contexts, such as Burkina Faso and Kenya. Vital signs comprising activity (steps), sleep (duration, quality) and heart rate (hr) are important measures to gain insights on individual behavior and activity patterns in low-resource contexts. These vital signs may be associated with weather variables-as we gather them from weather stations that we have setup as part of this study to cover the whole Nouna and Siaya HDSSs-in order to explore changes in behavior and other variables, such as activity, sleep, hr, during extreme weather events like heat stress exposure. Furthermore, wearable data could be linked to health outcomes and weather events. As a result, consumer-grade wearables may serve as a supporting technology for generating reliable measurements in low-resource contexts and investigating key links between weather occurrences and health outcomes. Thus, wearable devices may provide insights to better inform mitigation and adaptation interventions in these low-resource settings that are direly faced by climate change-induced changes, such as extreme weather events.

Does Ethnic Diversity Impact on Risk Perceptions, Preparedness, and Management of Heat Waves?

Detrimental health impacts of heatwaves, including excess mortality, are increasing worldwide. To assess risk perceptions, protective knowledge and behaviors concerning heatwaves in Israel, a study was initiated, comparing attitudes of majority (Jewish) and minority (Arab) populations. A quantitative survey was disseminated through an internet panel, to a representative sample of 556 individuals (79% Jews; 21% Arabs). Overall, 74% consider heatwaves a problem, 93% believe that heatwaves' frequencies will increase, 27% are very concerned about the effects of heatwaves. Higher levels of awareness to heatwaves were found among Jewish compared to Arab respondents; 90 vs. 77% (respectively) could name heatwaves' symptoms (p < 0.001); 81 vs. 56% (respectively) reported knowing how to protect themselves (p < 0.001); 74 vs. 47% (respectively) reported knowing what to do when someone suffers from heat stroke (p < 0.001). Arab compared to Jewish respondents presented higher levels of concern about heatwaves' effects (3.22 vs. 3.09 respectively; t −2.25, p = 0.03), while knowledge of protective measures was higher among Jews compared to Arabs (3.67 vs. 3.56 t = 2.13 p = 0.04). A crucial component of enhancing preparedness to heatwaves is empowerment of minority as well as majority groups, to strengthen their capacity to implement protective behavior and elevate their self-belief in their individual ability and fortitude.

Ambient extreme heat exposure in summer and transitional months and emergency department visits and hospital admissions due to pregnancy complications

Although extreme heat exposure (EHE) was reported to be associated with increased risks of multiple diseases, little is known about the effects of EHE on pregnancy complications. We examined the EHE-pregnancy complications associations by lag days, subtypes, sociodemographic characteristics, and areas in New York State (NYS). We conducted a case-crossover analysis to assess the EHE-pregnancy complications associations in summer (June-August) and transitional months (May and September). All emergency department (ED) visits and hospital admissions due to pregnancy complications (ICD 9 codes: 630-649) from 2005 to 2013 in NYS were included. Daily mean temperature > 90th percentile of the monthly mean temperature in each county was defined as an EHE. We used conditional logistic regression while controlling for other weather factors, air pollutants and holidays to assess the EHE-pregnancy complications associations. EHE was significantly associated with increased ED visits for pregnancy complications in summer (ORs ranged: 1.01-1.04 from lag days 0-5). There was also a significant and stronger association in transitional months (ORs ranged: 1.02-1.06, Lag 0). Furthermore, we found EHE affected multiple subtypes of pregnancy complications, including threatened/spontaneous abortion, renal diseases, infectious diseases, diabetes, and hypertension (ORs range: 1.13-1.90) during transitional months. A significant concentration response effect between the number of consecutive days of EHE and ED visits in summer (P for trend <0.001), ED visits in September (P for trend =0.03), and hospital admission in May (P for trend<0.001) due to pregnancy complications was observed, respectively. African Americans and residents in lower socioeconomic position (SEP) counties were more susceptible to the effects of EHE. In conclusion, we found an immediate and prolonged effect of EHE on pregnancy complications in summer and a stronger, immediate effect in transitional months. These effects were stronger in African Americans and counties with lower SEP. Earlier warnings regarding extreme heat are recommended to decrease pregnancy complications.

Using logic regression to characterize extreme heat exposures and their health associations: a time-series study of emergency department visits in Atlanta

Background

Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations.

Methods

Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area.

Results

For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient.

Conclusion

Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01278-x.

Intensity-duration-frequency relationship of WBGT extremes using regional frequency analysis in South Korea

The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches—Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Heat related mortality in the two largest Belgian urban areas: A time series analysis

BACKGROUND

Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas.

OBJECTIVES

The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution.

METHODS

The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat.

RESULTS

Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone.

CONCLUSION

Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.

Event-Based Heat-Related Risk Assessment Model for South Korea Using Maximum Perceived Temperature, Wet-Bulb Globe Temperature, and Air Temperature Data

This study aimed to assess the heat-related risk (excess mortality rate) at six cities, namely, Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, in South Korea using the daily maximum perceived temperature (PTmax), which is a physiology-based thermal comfort index, the wet-bulb globe temperature, which is meteorology-based thermal comfort index, and air temperature. Particularly, the applicability of PTmax was evaluated using excess mortality rate modeling. An event-based heat-related risk assessment model was employed for modeling the excess mortality rate. The performances of excess mortality rate models using those variables were evaluated for two data sets that were used (training data, 2000-2016) and not used (test data, 2017-2018) for the construction of the assessment models. Additionally, the excess mortality rate was separately modeled depending on regions and ages. PTmax is a good temperature indicator that can be used to model the excess mortality rate in South Korea. The application of PTmax in modeling the total mortality rate yields the best performances for the test data set, particularly for young people. From a forecasting perspective, PTmax is the most appropriate temperature indicator for assessing the heat-related excess mortality rate in South Korea.

The Use of a Quasi-Experimental Study on the Mortality Effect of a Heat Wave Warning System in Korea

Many cities and countries have implemented heat wave warning systems to combat the health effects of extreme heat. Little is known about whether these systems actually reduce heat-related morbidity and mortality. We examined the effectiveness of heat wave alerts and health plans in reducing the mortality risk of heat waves in Korea by utilizing the discrepancy between the alerts and the monitored temperature. A difference-in-differences analysis combined with propensity score weighting was used. Mortality, weather monitoring, and heat wave alert announcement data were collected for 7 major cities during 2009–2014. Results showed evidence of risk reduction among people aged 19–64 without education (−0.144 deaths/1,000,000 people, 95% CI: −0.227, −0.061) and children aged 0–19 (−0.555 deaths/1,000,000 people, 95% CI: −0.993, −0.117). Decreased cardiovascular and respiratory mortality was found in several subgroups including single persons, widowed people, blue-collar workers, people with no education or the highest level of education (university or higher). No evidence was found for decreased all-cause mortality in the population (1.687 deaths/1,000,000 people per day; 95% CI: 1.118, 2.255). In conclusion, heat wave alerts may reduce mortality for several causes and subpopulations of age and socio-economic status. Further work needs to examine the pathways through which the alerts impact subpopulations differently.

Public Prevention Plans to Manage Climate Change and Respiratory Allergic Diseases. Innovative Models Used in Campania Region (Italy): The Twinning Aria Implementation and the Allergy Safe Tree Decalogue

In recent years, climate change has been influenced by air pollution, and this destructive combination has justifiably sounded an alarm for nations and many institutional bodies worldwide. Official reports state that the emission of greenhouse gases produced by human activity are growing, and consequently also the average temperature. The World Health Organization (WHO) believes that health effects expected in the future due to climate change will be dramatic, and has invited international groups to investigate potential remedies. A task force has been established by the Italian Society of Allergology, Asthma and Clinical Immunology (SIAAIC), with the aim to actively work on correlation between pollution and climate change. The Task Force provided prevention tools to suggest city leaders how to improve the health conditions of allergic people in public urban parks. The "Allergy Safe Tree Decalogue" suggests the preparation and maintenance of public low allergy-impact greenery. Through the Twinning ARIA project, the Division for the Promotion and Enhancement of Health Innovation Programs of Campania Region (Italy), sought to promote the implementation of the project in the regional Health System. The main objective will be to investigate the current use and usefulness of mobile phone Apps in the management of allergic respiratory disease, through Mobile Airways Sentinel networK (MASK), the Phase 3 of the ARIA initiative, based on the freely available MASK App (the Allergy Diary, Android and iOS platforms). The effects of these prevention activities will be registered and compared with monitoring efforts thanks to the Aerobiology Units, located throughout the Campania area. A joint effort between researchers and public administrations for the implementation of prevention plans coherently with the two models proposed in a specific area, i.e. the Decalogue for public administrations and the MASK Allergy Diary app for individual patients suffering from allergy, will be implemented as a pilot.