Impact of hot temperatures on death in London: a time series approach

The 2018 Heat Wave's Impact on the Mortality of Older People in Seoul, South Korea

Few studies on social welfare in South Korea have examined the effects of climate change, especially heat waves on vulnerable populations. The present study aims to investigate how heat waves affect vulnerable populations. This study utilized a cross-sectional study design, using the daily heat index and heat-related mortality data for Seoul, South Korea, in summer 2018. The research used micro-raw data of deaths caused by hypertensive, ischemic heart, and cerebrovascular diseases, as well as heat index data. An effect was observed for the heat index on mortality for individuals over 65 years of age, men, people with spouses, and those ages 75-79 years.

High average daily temperature in summer and the incidence of thrombolytic treatment for acute ischemic stroke

INTRODUCTION

Meteorological factors can increase stroke risk; however, their impact is not precisely understood. Heat waves during summer increase total mortality. Therefore, we hypothesized that the average daily temperature in summer may correlate with the incidence of thrombolytic treatment for acute ischemic stroke in Budapest and Pest County, Hungary.

METHODS

We analyzed the relationship between the average daily temperature in summer months and the daily number of thrombolytic treatments (TT) performed with the indication of acute ischemic stroke between 1st June and 31st August each year from 2007 to 2016. The analysis was also performed after the omission of the data of the last day of the months due to possible psychosocial impact reported in our previous study. Spearman's correlation was used for statistical analysis.

RESULTS

No significant correlation was found between the average summer daily temperature and the number of TT in the entire sample of the 10-year period. When omitting the data of the last day of each month, positive correlations were suspected in 2014 (r=0.225, P=0.034) and 2015 (r=0.276, P=0.009).

CONCLUSION

Our findings did not confirm an association between the average daily temperature in summer and the daily number of TT throughout the examined 10-year period. However, importantly, in 2014 and 2015, the years with the highest average daily temperatures in this period, a positive correlation was found. The level of correlation is modest, indicating that risk factors, both meteorological and non-meteorological, other than the average temperature, play equally important roles in determining the incidence of thrombolytic treatment for acute ischemic stroke on the population level.

Effects of heatwave features on machine-learning-based heat-related ambulance calls prediction models in Japan

Researchers agree that there is substantial evidence of an increasing trend in both the frequency and duration of extreme temperature events. Increasing extreme temperature events will place more pressure on public health and emergency medical resources, and societies will need to find effective and reliable solutions to adapt to hotter summers. This study developed an effective method to predict the number of daily heat-related ambulance calls. Both national- and regional-level models were developed to evaluate the performance of machine-learning-based methods on heat-related ambulance call prediction. The national model showed a high prediction accuracy and can be applied over most regions, while the regional model showed extremely high prediction accuracy in each corresponding region and reliable accuracy in special cases. We found that the introduction of heatwave features, including accumulated heat stress, heat acclimatization, and optimal temperature, significantly improved prediction accuracy. The adjusted coefficient of determination (adjusted R²) of the national model improved from 0.9061 to 0.9659 by including these features, and the adjusted R² of the regional model also improved from 0.9102 to 0.9860. Furthermore, we used five bias-corrected global climate models (GCMs) to forecast the total number of summer heat-related ambulance calls under three different future climate scenarios nationally and regionally. Our analysis demonstrated that, at the end of the 21st century, the total number of heat-related ambulance calls in Japan will reach approximately 250,000 per year (nearly four times the current amount) under SSP-5.85. Our results suggest that disaster management agencies can use this highly accurate model to forecast potential high emergency medical resource burden caused by extreme heat events, allowing them to raise and improve public awareness and prepare countermeasures in advance. The method proposed in Japan in this paper can be applied to other countries that have relevant data and weather information systems.

Historic evolution of population exposure to heatwaves in Xinjiang Uygur Autonomous Region, China

Heatwaves have pronounced impacts on human health and the environment on a global scale. Although the characteristics of heatwaves has been well documented, there still remains a lack of dynamic studies of population exposure to heatwaves (PEH), particularly in the arid regions. In this study, we analyzed the spatio-temporal evolution characteristics of heatwaves and PEH in Xinjiang using the daily maximum temperature (T_max), relative humidity (RH), and high-resolution gridded population datasets. The results revealed that the heatwaves in Xinjiang occur more continually and intensely from 1961 to 2020. Furthermore, there is substantial spatial heterogeneity of heatwaves with eastern part of the Tarim Basin, Turpan, and Hami been the most prone areas. The PEH in Xinjiang showed an increasing trend with high areas mainly in Kashgar, Aksu, Turpan, and Hotan. The increase in PEH is mainly contributed from population growth, climate change and their interaction. From 2001 to 2020, the climate effect contribution decreased by 8.5%, the contribution rate of population and interaction effects increased by 3.3% and 5.2%, respectively. This work provides a scientific basis for the development of policies to improve the resilience against hazards in arid regions.

The contribution of demographic changes to future heat-related health burdens under climate change scenarios

Anthropogenic climate change will have a detrimental impact on global health, including the direct impact of higher ambient temperatures. Existing projections of heat-related health outcomes in a changing climate often consider increasing ambient temperatures alone. Population growth and structure has been identified as a key source of uncertainty in future projections. Age acts as a modifier of heat risk, with heat-risk generally increasing in older age-groups. In many countries the population is ageing as lower birth rates and increasing life expectancy alter the population structure. Preparing for an older population, in particular in the context of a warmer climate should therefore be a priority in public health research and policy. We assess the level of inclusion of population growth and demographic changes in research projecting exposure to heat and heat-related health outcomes. To assess the level of inclusion of population changes in the literature, keyword searches of two databases were implemented, followed by reference and citation scans to identify any missed papers. Relevant papers, those including a projection of the heat health burden under climate change, were then checked for inclusion of population scenarios. Where sensitivity to population change was studied the impact of this on projections was extracted. Our analysis suggests that projecting the heat health burden is a growing area of research, however, some areas remain understudied including Africa and the Middle East and morbidity is rarely explored with most studies focusing on mortality. Of the studies pairing projections of population and climate, specifically SSPs and RCPs, many used pairing considered to be unfeasible. We find that not including any projected changes in population or demographics leads to underestimation of health burdens of on average 64 %. Inclusion of population changes increased the heat health burden across all but two studies.

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.

Environmental variable importance for under-five mortality in Malaysia: A random forest approach

BACKGROUND

Environmental factors have been associated with adverse health effects in epidemiological studies. The main exposure variable is usually determined via prior knowledge or statistical methods. It may be challenging when evidence is scarce to support prior knowledge, or to address collinearity issues using statistical methods. This study aimed to investigate the importance level of environmental variables for the under-five mortality in Malaysia via random forest approach.

METHOD

We applied a conditional permutation importance via a random forest (CPI-RF) approach to evaluate the relative importance of the weather- and air pollution-related environmental factors on daily under-five mortality in Malaysia. This study spanned from January 1, 2014 to December 31, 2016. In data preparation, deviation mortality counts were derived through a generalized additive model, adjusting for long-term trend and seasonality. Analyses were conducted considering mortality causes (all-cause, natural-cause, or external-cause) and data structures (continuous, categorical, or all types [i.e., include all variables of continuous type and all variables of categorical type]). The main analysis comprised of two stages. In Stage 1, Boruta selection was applied for preliminary screening to remove highly unimportant variables. In Stage 2, the retained variables from Boruta were used in the CPI-RF analysis. The final importance value was obtained as an average value from a 10-fold cross-validation.

RESULT

Some heat-related variables (maximum temperature, heat wave), temperature variability, and haze-related variables (PM10, PM10-derived haze index, PM10- and fire-derived haze index, fire hotspot) were among the prominent variables associated with under-five mortality in Malaysia. The important variables were consistent for all- and natural-cause mortality and sensitivity analyses. However, different most important variables were observed between natural- and external-cause under-five mortality.

CONCLUSION

Heat-related variables, temperature variability, and haze-related variables were consistently prominent for all- and natural-cause under-five mortalities, but not for external-cause.

Association between heat exposure and hospitalization for diabetic ketoacidosis, hyperosmolar hyperglycemic state, and hypoglycemia in Japan

BACKGROUND

An increase in extreme heat events has been reported along with global warming. Heat exposure in ambient temperature is associated with all-cause diabetes mortality and all-cause hospitalization in diabetic patients. However, the association between heat exposure and hospitalization for hyperglycemic emergencies, such as diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), and hypoglycemia is unclear. The objective of our study is to clarify the impact of heat exposure on the hospitalization for DKA, HHS, and hypoglycemia.

METHODS

Data of daily hospitalizations for hyperglycemic emergencies (i.e., DKA or HHS) and hypoglycemia was extracted from a nationwide administrative database in Japan and linked with temperature in each prefecture in Japan during 2012-2019. We applied distributed lag non-linear model to evaluate the non-linear and lagged effects of heat exposure on hospitalization for hyperglycemic emergencies.

RESULTS

The pooled relative risk for hyperglycemic emergencies of heat effect (the 90th percentile of temperature with reference to the 75th percentile of temperature) and extreme heat effect (the 99th percentile of temperature with reference to the 75th percentile of temperature) over 0-3 lag days was 1.27 (95 %CI: 1.16-1.39) and 1.64 (95 %CI: 1.38-1.93), respectively. The pooled relative risk for heat effect on hospitalization for hypoglycemia and extreme heat effect over 0-3 lag days was 1.33 (95 %CI: 1.17-1.52) and 1.65 (95 %CI: 1.29-2.10), respectively. These associations were consistent by type of hyperglycemic emergencies and type of diabetes and were generally consistent by regions.

DISCUSSION

Heat exposure was associated with hospitalizations for DKA, HHS and hypoglycemia. These results may be useful to guide preventive actions for the risk of fatal hyperglycemic emergencies and hypoglycemia.

Assessment of Social Housing Energy and Thermal Performance in Relation to Occupants’ Behaviour and COVID-19 Influence—A Case Study in the Basque Country, Spain

Evidence shows that people have a major impact on building performance. Occupants’ impact is especially important in social housing, where their occupants may present greater vulnerabilities, and their needs are not always considered. This study aims to analyse the socio-demographic influence in social rental housing concerning hygrothermal comfort and energy consumption in a case study located in Vitoria, Spain during the first 4-month period of 2020 and 2021 (during and after COVID-19 lockdown). An innovative data management system is included, where the users and administration can see in real-time the temperature and consumption in the dwellings. A 2-phase method has been applied; phase 1 is associated with outdoor climate conditions, building properties and social profile. Phase 2 determined the results in energy consumption, indoor hygrothermal comfort and occupant energy-use pattern. The results show that the comfort levels and energy consumption vary according to the analysed social profiles, as well as the heating activation periods and domestic hot water system usage. In conclusion, socio-demographic characteristics of social housing households influence the hygrothermal comfort of their dwellings, occupants’ behaviour and heating and domestic hot water energy consumption.

Heat-Related Mortality in Two Regions of Poland: Focus on Urban and Rural Areas during the Most Severe and Long-Lasting Heatwaves

The vast majority of studies on heat-related mortality are focused on large cities. The aim of this study is to fill this research gap and to estimate the impact of high temperatures on the risk of death in smaller towns and villages. The results show that increased mortality is not only a problem in large cities. The risk of death, although usually slightly lower than in highly populated areas, may be higher for the age-related risk group. At temperatures above 35 °C, it may exceed 1.3 in smaller towns and even 1.6 in villages. The increase in mortality during five selected heat waves of high intensity and long duration was also studied for two regions of Poland: Małopolska and Wielkopolska. Towns with a population of less than 10,000 in Małopolska region, during the 2006 heatwave, experienced an increase in the number of deaths by as much as 18%. At the same time in the largest city of Małopolska-Kraków, the death toll rose by 4%. This paper also presents some differences between regions in terms of the impact of heat waves: in the lowland region of Wielkopolska, the mortality rate is generally higher than in the upland region of Małopolska.

The association between diurnal temperature range and clinic visits for upper respiratory tract infection among college students in Wuhan, China

The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.

A heat-health watch and warning system with extended season and evolving thresholds

BACKGROUND

Many countries have developed heat-health watch and warning systems (HHWWS) or early-warning systems to mitigate the health consequences of extreme heat events. HHWWS usually focuses on the four hottest months of the year and imposes the same threshold over these months. However, according to climate projections, the warm season is expected to extend and/or shift. Some studies demonstrated that health impacts of heat waves are more severe when the human body is not acclimatized to the heat. In order to adapt those systems to potential heat waves occurring outside the hottest months of the season, this study proposes specific health-based monthly heat indicators and thresholds over an extended season from April to October in the northern hemisphere.

METHODS

The proposed approach, an adoption and extension of the HHWWS methodology currently implemented in Quebec (Canada). The latter is developed and applied to the Greater Montreal area (current population 4.3 million) based on historical health and meteorological data over the years. This approach consists of determining excess mortality episodes and then choosing monthly indicators and thresholds that may involve excess mortality.

RESULTS

We obtain thresholds for the maximum and minimum temperature couple (in °C) that range from (respectively, 23 and 12) in April, to (32 and 21) in July and back to (25 and 13) in October. The resulting HHWWS is flexible, with health-related thresholds taking into account the seasonality and the monthly variability of temperatures over an extended summer season.

CONCLUSIONS

This adaptive and more realistic system has the potential to prevent, by data-driven health alerts, heat-related mortality outside the typical July-August months of heat waves. The proposed methodology is general and can be applied to other regions and situations based on their characteristics.

The air quality changes and related mortality benefits during the coronavirus disease 2019 pandemic in China: Results from a nationwide forecasting study

Air quality changes during the coronavirus disease 2019 (COVID-19) pandemic in China has attracted increasing attention. However, more details in the changes, future air quality trends, and related death benefits on a national scale are still unclear. In this study, a total of 352 Chinese cities were included. We collected air pollutants (including fine particulate matter [PM_2.5], inhalable particulate matter [PM₁₀], nitrogen dioxide [NO₂], and ozone [O₃]) data for each city from January 2015 to July 2020. Convolutional neural network-quantile regression (CNN-QR) forecasting model was used to predict pollutants concentrations from February 2020 to January 2021 and the changes in air pollutants were compared. The relationships between the socioeconomic factors and the changes and the avoided mortality due to the changes were further estimated. We found sharp declines in all air pollutants from February 2020 to January 2021. Specifically, PM_2.5, PM₁₀, NO₂, and O₃ would drop by 3.86 μg/m³ (10.81%), 4.84 μg/m³ (7.65%), 0.55 μg/m³ (2.18%), and 3.14 μg/m³ (3.36%), respectively. The air quality changes were significantly related to many of the socioeconomic factors, including the size of built-up area, gross regional product, population density, gross regional product per capita, and secondary industry share. And the improved air quality would avoid a total of 7237 p.m._2.5-related deaths (95% confidence intervals [CI]: 4935, 9209), 9484 p.m.₁₀-related deaths (95%CI: 5362, 13604), 4249 NO₂-related deaths (95%CI: 3305, 5193), and 6424 O₃-related deaths (95%CI: 3480, 9367), respectively. Our study shows that the interventions to control COVID-19 would improve air quality, which had significant relationships with some socioeconomic factors. Additionally, improved air quality would reduce the number of non-accidental deaths.

Analysis on Effectiveness of Impact Based Heatwave Warning Considering Severity and Likelihood of Health Impacts in Seoul, Korea

Many countries are operating a heatwave warning system (HWWS) to mitigate the impact of heatwaves on human health. The level of heatwave warning is normally determined by using the threshold temperature of heat-related morbidity or mortality. However, morbidity and mortality threshold temperatures have not been used together to account for the severity of health impacts. In this study, we developed a heatwave warning system with two different warning levels: Level-1 and Level-2, by analyzing the severity and likelihood of heat-related morbidity and mortality using the generalized additive model. The study particularly focuses on the cases in Seoul, South Korea, between 2011 and 2018. The study found that the threshold temperature for heat-related morbidity and mortality are 30 °C and 33 °C, respectively. Approximately 73.1% of heat-related patients visited hospitals when temperature was between 30 °C and 33 °C. We validated the developed HWWS by using both the threshold temperatures of morbidity and mortality. The area under curves (AUCs) of the proposed model were 0.74 and 0.86 at Level-1 and Level-2, respectively. On the other hand, the AUCs of the model using only the mortality threshold were 0.60 and 0.86 at Level-1 and Level-2, respectively. The AUCs of the model using only the morbidity threshold were 0.73 and 0.78 at Level-1 and Level-2, respectively. The results suggest that the updated HWWS can help to reduce the impact of heatwaves, particularly on vulnerable groups, by providing the customized information. This also indicates that the HWWS could effectively mitigate the risk of morbidity and mortality.

A System Dynamics Model to Facilitate the Development of Policy for Urban Heat Island Mitigation

This article presents a customized system dynamics model to facilitate the informed development of policy for urban heat island mitigation within the context of future climate change, and with special emphasis on the reduction of heat-related mortality. The model incorporates a variety of components (incl.: the urban heat island effect; population dynamics; climate change impacts on temperature; and heat-related mortality) and is intended to provide urban planning and related professionals with: a facilitated means of understanding the risk of heat-related mortality within the urban heat island; and location-specific information to support the development of reasoned and targeted urban heat island mitigation policy.

Extreme temperatures and cardiovascular mortality: assessing effect modification by subgroups in Ganzhou, China

Background

Many people die from cardiovascular diseases each year, and extreme temperatures are regarded as a risk factor for cardiovascular deaths. However, the relationship between temperature and cardiovascular deaths varies in different regions because of population density, demographic inequality, and economic situation, and the evidence in Ganzhou, China is limited and inconclusive.

Objective

This study aimed to assess extreme temperature-related cardiovascular mortality and identify the potential vulnerable people.

Methods

After controlling other meteorological measures, air pollution, seasonality, relative humidity, day of the week, and public holidays, we examined temperature-related cardiovascular mortality along 21 lag days by Poisson in Ganzhou, China.

Results

A J-shaped relationship was observed between mean temperature and cardiovascular mortality. Extremely low temperatures substantially increased the relative risks (RR) of cardiovascular mortality. The effect of cold temperature was delayed by 2–6 days and persisted for 4–10 days. However, the risk of cardiovascular mortality related to extremely high temperatures was not significant (p > 0.05). Subgroup analysis indicated that extremely low temperatures had a stronger association with cardiovascular mortality in people with cerebrovascular diseases (RR: 1.282, 95% confidence interval [CI]: 1.020–1.611), males (RR: 1.492, 95% CI: 1.175–1.896), married people (RR: 1.590, 95% CI: 1.224–2.064), and people above the age of 65 years (RR: 1.641, 95% CI: 1.106–2.434) than in people with ischemic heart disease, females, unmarried people, and the elderly (≥65 years old), respectively.

Conclusions

The type of cardiovascular disease, sex, age, and marital status modified the effects of extremely low temperatures on the risk of cardiovascular mortality. These findings may help local governments to establish warning systems and precautionary measures to reduce temperature-related cardiovascular mortality.

Hot and cold weather based on the spatial synoptic classification and cause-specific mortality in Sweden: a time-stratified case-crossover study

The spatial synoptic classification (SSC) is a holistic categorical assessment of the daily weather conditions at specific locations; it is a useful tool for assessing weather effects on health. In this study, we assessed (a) the effect of hot weather types and the duration of heat events on cardiovascular and respiratory mortality in summer and (b) the effect of cold weather types and the duration of cold events on cardiovascular and respiratory mortality in winter. A time-stratified case-crossover design combined with a distributed lag nonlinear model was carried out to investigate the association of weather types with cause-specific mortality in two southern (Skåne and Stockholm) and two northern (Jämtland and Västerbotten) locations in Sweden. During summer, in the southern locations, the Moist Tropical (MT) and Dry Tropical (DT) weather types increased cardiovascular and respiratory mortality at shorter lags; both hot weather types substantially increased respiratory mortality mainly in Skåne. The impact of heat events on mortality by cardiovascular and respiratory diseases was more important in the southern than in the northern locations at lag 0. The cumulative effect of MT, DT and heat events lagged over 14 days was particularly high for respiratory mortality in all locations except in Jämtland, though these did not show a clear effect on cardiovascular mortality. During winter, the dry polar and moist polar weather types and cold events showed a negligible effect on cardiovascular and respiratory mortality. This study provides valuable information about the relationship between hot oppressive weather types with cause-specific mortality; however, the cold weather types may not capture sufficiently effects on cause-specific mortality in this sub-Arctic region.

Comparison of Respiratory and Ischemic Heart Mortalities and their Relationship to the Thermal Environment

Chronic respiratory and ischemic heart diseases are globally important parts of total mortality. This study focuses on the occurrence of mortality due to these disease groups in Germany and possible effects of the thermal environment. A retrospective analysis on the mortality rates of chronic lower respiratory diseases (CLRD) and ischemic heart diseases (IHD) at the regional level in Germany for the period 2001–2015 was done in combination with meteorological observations from the network of the German Meteorological Service. In order to control the mortality data for long-term and seasonal trends, a 365-day Gaussian low-pass filter with a filter response function was applied. The thermal environment was analysed using 2 m air temperature (Ta) and the human biometeorological index Perceived Temperature (PT). The relationship of the Relative Risk (RR) of mortality to the thermal environment is displayed as an exposure–response curve, with threshold values at which RR increases significantly towards higher and lower temperature values. CLRD mortality increases above 17.6 °C, at approximately 4.4%/°C (CI: ± 0.3). The increase of IHD mortality above the threshold of 18.8 °C is less steep, at 3.5%/°C (CI: ± 0.2). During hot periods, CLRD mortality increases by 19.9%, which is twice as much as IHD mortality, with an increase of 9.8%. However, cold days and cold periods affect IHD slightly more than CLRD. The results highlight the concerns of CLRD patients during hot days as well as heat waves. This could lead to better precautions being taken for respiratory patients, which are already established for cardiac patients in Germany.

Heat load increases the risk of clinical mastitis in dairy cattle

The study was aimed at assessing heat load-related risk of clinical mastitis (CM) in dairy cows. Records of CM for the years 2014 and 2015 were obtained from a large conventional dairy farm milking about 1,200 Holstein cows in central Italy. A case of CM was defined by the presence of clinical signs and veterinary confirmation. Quarter milk samples were collected and bacteriological investigated for each CM. Etiological agents were identified and classified as environmental or contagious pathogens. Hourly weather data from the nearest weather station were used to calculate heat load index (HLI). Upper and lower thresholds of HLI, at which the animal accumulates or dissipates heat, were settled and used to measure heat load balance through the accumulated heat load (AHL) model. Zero and positive values of AHL indicate periods of thermo-neutral and heat accumulation, respectively. Each case of CM was associated with HLI-AHL values recorded 5 d before the event. The risk of CM was evaluated using a case-crossover design. A conditional logistic regression model was used to calculate the odds ratio and 95% confidence intervals of CM recorded in thermo-neutral (AHL = 0) or heat load (AHL > 0) days, pooled or stratified for pathogen type (environmental or contagious). Classes of AHL as low (<6.5), medium (6.6-34.9), and high (>35) were included in the model. Other variables included in the model were milk yield as liters (<20, 20-30, and >30), days in milk (<60, 60-150, and >150), and parity (1, 2-3, and >3). A total of 1,086 CM cases were identified from 677 cows. Escherichia coli, Streptococcus spp., and Streptococcus uberis were the environmental pathogens isolated with the highest frequency; Staphylococcus aureus prevailed within contagious species. The analysis of pooled data indicated a significant effect of heat load on the occurrence of CM in the contagious pathogen stratum. Higher milk yield, middle and late stage of lactation, and older parity increased the risk of CM under heat load conditions. However, the association between pathogen type and these factors was not clear because the model provided significant odds ratios within all pathogen categories. The present study provided the first evidence of an association between HLI and CM in dairy cattle and suggested the ability of the AHL model to assess the risk of mastitis associated with heat load.

The Effects of Temperature on Accident and Emergency Department Attendances in London: A Time-Series Regression Analysis

The epidemiological research relating mortality and hospital admissions to ambient temperature is well established. However, less is known about the effect temperature has on Accident and Emergency (A&E) department attendances. Time-series regression analyses were conducted to investigate the effect of temperature for a range of cause- and age-specific attendances in Greater London (LD) between 2007 to 2012. A seasonally adjusted Poisson regression model was used to estimate the percent change in daily attendances per 1 °C increase in temperature. The risk of overall attendance increased by 1.0% (95% CI 0.8, 1.4) for all ages and 1.4% (1.2, 1.5) among 0- to 15-year-olds. A smaller but significant increase in risk was found for cardiac, respiratory, cerebrovascular and psychiatric presentations. Importantly, for fracture-related attendances, the risk rose by 1.1% (0.7, 1.5) per 1 °C increase in temperature above the identified temperature threshold of 16 °C, with the highest increase of 2.1% (1.5, 3.0) seen among 0- to 15-year-olds. There is a positive association between increasing temperatures and A&E department attendance, with the risk appearing highest in children and the most deprived areas. A&E departments are vulnerable to increased demand during hot weather and therefore need to be adequately prepared to address associated health risks posed by climate change.

Excess Mortality in Istanbul during Extreme Heat Waves between 2013 and 2017

Heat waves are one of the most common direct impacts of anthropogenic climate change and excess mortality their most apparent impact. While Turkey has experienced an increase in heat wave episodes between 1971 and 2016, no epidemiological studies have examined their potential impacts on public health so far. In this study excess mortality in Istanbul attributable to extreme heat wave episodes between 2013 and 2017 is presented. Total excess deaths were calculated using mortality rates across different categories, including age, sex, and cause of death. The analysis shows that three extreme heat waves in the summer months of 2015, 2016, and 2017, which covered 14 days in total, significantly increased the mortality rate and caused 419 excess deaths in 23 days of exposure. As climate simulations show that Turkey is one of the most vulnerable countries in the Europe region to the increased intensity of heat waves until the end of the 21st century, further studies about increased mortality and morbidity risks due to heat waves in Istanbul and other cities, as well as intervention studies, are necessary.

New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California

Rapid 21st century urbanization combined with anthropogenic climate warming are significantly increasing heat-related health threats in cities worldwide. In Los Angeles (LA), increasing trends in extreme heat are expected to intensify and exacerbate the urban heat island effect, leading to greater health risks for vulnerable populations. Partnerships between city policymakers and scientists are becoming more important as the need to provide data-driven recommendations for sustainability and mitigation efforts becomes critical. Here we present a model to produce heat vulnerability index (HVI) maps driven by surface temperature data from National Aeronautics and Space Administration’s (NASA) new Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal infrared sensor. ECOSTRESS was launched in June 2018 with the capability to image fine-scale urban temperatures at a 70 m resolution throughout different times of the day and night. The HVI model further includes information on socio-demographic data, green vegetation abundance, and historical heatwave temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua spacecraft since 2002. During a period of high heat in July 2018, we identified the five most vulnerable communities at a sub-city block scale in the LA region. The persistence of high HVI throughout the day and night in these areas indicates a clear and urgent need for implementing cooling technologies and green infrastructure to curb future warming.

Evaluation of wearable sensors for physiologic monitoring of individually experienced temperatures in outdoor workers in southeastern U.S

Climate-related increases in global mean temperature and the intensification of heat waves present a significant threat to outdoor workers. Limited research has been completed to assess the potential differences in heat exposures that exist between individuals within similar microenvironments. Yet, there is a paucity of individual data characterizing patterns of individually experienced temperatures in workers and the associated physiologic heat strain response. The objective of this study was to apply a wearable sensor-based approach to examine the occupational, environmental, and behavioral factors that contribute to individual-level variations in heat strain in grounds maintenance workers. Outdoor workers from three diverse climatic locations in the southeastern United States - high temperature, high temperature + high humidity, and moderate temperature environments - participated in personal heat exposure monitoring during a 5-day work period in the summer. We performed Cox proportional hazards modeling to estimate associations between multiple heat strain events per worker and changes in individually experienced temperatures. Heat strain risk was higher among workers with a place to cool-off, higher education, and who worked in hotter temperatures. A mismatch was observed between workers' perceptions of heat strain and actual heat strain prevalence across exposure groups. We also used a quasi-Poisson regression with distributed lag non-linear function to estimate the non-linear and lag effects of individually experienced temperatures on risk of heat strain. The association between increasing temperature and heat strain was nonlinear and exhibited an U-shaped relationship. Heat strain was less common during issued heat warnings demonstrating behavioral adaptive actions taken by workers. This study is one of the first temperature monitoring studies to quantify the individual-level exposure-response function in this vulnerable population and highlights the elevated risk of heat strain both immediately and several days after worker exposure to high temperatures.

Mining Social Media to Identify Heat Waves

Heat waves are one of the deadliest of natural hazards and their frequency and intensity will likely increase as the climate continues to warm. A challenge in studying these phenomena is the lack of a universally accepted quantitative definition that captures both temperature anomalies and associated mortality. We test the hypothesis that social media mining can be used to identify heat wave mortality. Applying the approach to India, we find that the number of heat-related tweets correlates with heat-related mortality much better than traditional climate-based indicators, especially at larger scales, which identify many heat wave days that do not lead to excess mortality. We conclude that social media based heat wave identification can complement climatic data and can be used to: (1) study heat wave impacts at large scales or in developing countries, where mortality data are difficult to obtain and uncertain, and (2) to track dangerous heat wave events in real time.

Assessment of Intraseasonal Variation in Hospitalization Associated With Heat Exposure in Brazil

IMPORTANCE

The onset of the hot season is known to be adversely associated with a range of health outcomes. However, little is known about whether the association is constant over the course of the hot season.

OBJECTIVE

To quantify the change in the association between heat exposure and hospitalization from the early to late hot season in the Brazilian population.

DESIGN, SETTING, AND PARTICIPANTS

This time-stratified case-crossover study used daily data on hospitalization and weather conditions during the 2000 to 2015 hot seasons in 1814 Brazilian cities. There were 49 145 997 admissions during the study period. Data analysis was conducted between May 12, 2018, and July 2, 2018.

EXPOSURES

Increase in daily mean temperature.

MAIN OUTCOMES AND MEASURES

Daily hospitalizations were recorded. Conditional quasi-Poisson regression with time-varying constrained distributed lag model was used to examine the city-specific association between heat and hospitalization in the early or late hot season. City-specific estimates were then pooled at the national level using random-effect meta-analysis. Stratified analyses were conducted by 5 regions, sex, 10 age groups, and 7 cause-specific categories.

RESULTS

Of the 49 145 997 admissions (59% women), the median (interquartile range) age was 33.3 (19.8-55.7) years. At the national level, the risk of hospitalization increased by 4.6% (95% CI, 4.3%-4.9%) and 2.3% (95% CI, 1.9%-2.6%) for every 5°C increase in daily mean temperature in the early and late hot season, respectively. Exposure to early heat was associated with greater risk of hospitalization for residents in the northeast (6.4%; 95% CI, 5.5%-7.3%) and central west (7.1%; 95% CI, 6.1%-8.2%) compared with other regions. Children aged 0 to 9 years and elderly individuals (aged ≥80 years) were most susceptible. Admissions due to endocrine, nutritional, and metabolic diseases were most strongly associated with heat exposure. There was an attenuation in the heat-associated risk of hospitalization from the early to late hot season for all subgroups except young children and patients with hospitalization caused by respiratory illness.

CONCLUSIONS AND RELEVANCE

In this study, the association between heat exposure and hospitalization attenuated temporally for most of the Brazilian population. Preventive strategies to mitigate the association of high temperature with population health should focus in particular on the first few days of heat exposure.

Impact of Atmospheric Circulation on the Occurrence of Hot Nights in Central Europe

The main goal of the study is to determine the pressure conditions that cause waves of hot nights in Central Europe. The goal was implemented on the basis of data from 1966 to 2015, made available by the Institute of Meteorology and Water Management—National Research Institute, Deutscher Wetterdienst and the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). A hot night was defined as a day with the minimum air temperature above 18 °C. In the analysed years, an increase in the number of hot nights was found, which was predominantly statistically significant within the studied area. The study shows that the occurrence of waves of hot nights in Central Europe was associated on average with the ridge of high pressure, within which a local high-pressure area developed. During the waves of hot nights, there were positive anomalies of heights of isobaric surfaces over the study area with a maximum in the upper troposphere.

Performance of Excess Heat Factor Severity as a Global Heatwave Health Impact Index

The establishment of an effective policy response to rising heatwave impacts is most effective when the history of heatwaves, their current impacts and future risks, are mapped by a common metric. In response meteorological agencies aim to develop seamless climate, forecast, and warning heat impact services, spanning all temporal and spatial scales. The ability to diagnose heatwave severity using the Excess Heat Factor (EHF) has allowed the Australian Bureau of Meteorology (the Bureau) to publicly release 7-day heatwave severity maps since 2014. National meteorological agencies in the UK and the United States are evaluating global 7-day and multi-week EHF heatwave severity probability forecasts, whilst the Bureau contributes to a Copernicus project to supply the health sector with global EHF severity heatwave projection scenarios. In an evaluation of impact skill within global forecast systems, EHF intensity and severity is reviewed as a predictor of human health impact, and extended using climate observations and human health data for sites around the globe. Heatwave intensity, determined by short and long-term temperature anomalies at each locality, is normalized to permit spatial analysis and inter-site comparison. Dimensionless heatwave event moments of peak severity and accumulated severity are shown to correlate with noteworthy events around the globe, offering new insights into current and future heatwave variability and vulnerability. The EHF severity metric permits the comparison of international heatwave events and their impacts, and is readily implemented within international heatwave early warning systems.

A new look at weather-related health impacts through functional regression

A major challenge of climate change adaptation is to assess the effect of changing weather on human health. In spite of an increasing literature on the weather-related health subject, many aspect of the relationship are not known, limiting the predictive power of epidemiologic models. The present paper proposes new models to improve the performances of the currently used ones. The proposed models are based on functional data analysis (FDA), a statistical framework dealing with continuous curves instead of scalar time series. The models are applied to the temperature-related cardiovascular mortality issue in Montreal. By making use of the whole information available, the proposed models improve the prediction of cardiovascular mortality according to temperature. In addition, results shed new lights on the relationship by quantifying physiological adaptation effects. These results, not found with classical model, illustrate the potential of FDA approaches.

The impact of home energy efficiency interventions and winter fuel payments on winter- and cold-related mortality and morbidity in England: a natural equipment mixed-methods study

Background

England, and the UK more generally, has a large burden of winter- and cold-related mortality/morbidity in comparison with nearby countries in continental Europe. Improving the energy efficiency of the housing stock may help to reduce this, as well as being important for climate change and energy security objectives.

Objectives

To evaluate the impact of home energy efficiency (HEE) interventions on winter- and cold-related mortality/morbidity, including assessing the impact of winter fuel payments (WFPs) and fuel costs.

Design

A mixed-methods study – an epidemiological time-series analysis, an analysis of data on HEE interventions, the development and application of modelling methods including a multicriteria decision analysis and an in-depth interview study of householders.

Setting

England, UK.

Participants

The population of England. In-depth interviews were conducted with 12 households (2–4 participants each) and 41 individuals in three geographical regions.

Interventions

HEE interventions.

Main outcome measures

Mortality, morbidity and intervention-related changes to the home indoor environment.

Data sources

The Homes Energy Efficiency Database, mortality and hospital admissions data and weather (temperature) data.

Results

There has been a progressive decline in cold-related deaths since the mid-1970s. Since the introduction of WFPs, the gradient of association between winter cold and mortality [2.00%, 95% confidence interval (CI) 1.74% to 2.28%] per degree Celsius fall in temperature is somewhat weaker (i.e. that the population is less vulnerable to cold) than in earlier years (2.37%, 95% CI 0.22% to 2.53%). There is also evidence that years with above-average fuel costs were associated with higher vulnerability to outdoor cold. HEE measures installed in England in 2002–10 have had a relatively modest impact in improving the indoor environment. The gains in winter temperatures (around +0.09 °C on a day with maximum outdoor temperature of 5 °C) are associated with an estimated annual reduction of ≈280 cold-related deaths in England (an eventual maximum annual impact of 4000 life-years gained), but these impacts may be appreciably smaller than those of changes in indoor air quality. Modelling studies indicate the potential importance of the medium- and longer-term impacts that HEE measures have on health, which are not observable in short-term studies. They also suggest that HEE improvements of similar annualised cost to current WFPs would achieve greater improvements in health while reducing (rather than increasing) carbon dioxide emissions. In-depth interviews suggest four distinct householder framings of HEE measures (as home improvement, home maintenance, subsidised public goods and contributions to sustainability), which do not dovetail with current ‘consumerist’ national policy and may have implications for the uptake of HEE measures.

Limitations

The quantification of intervention impacts in this national study is reliant on various indirect/model-based assessments.

Conclusions

Larger-scale changes are required to the housing stock in England if the full potential benefits for improving health and for reaching increasingly important climate change mitigation targets are to be realised.

Future work

Studies based on data linkage at individual dwelling level to examine health impacts. There is a need for empirical assessment of HEE interventions on indoor air quality.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 6, No. 11. See the NIHR Journals Library website for further project information.

Climate Change and Heat-Related Excess Mortality in the Eastern USA

Climate change will increase extreme heat-related health risks. To quantify the health impacts of mid-century climate change, we assess heat-related excess mortality across the eastern USA. Health risks are estimated using the US Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program (BenMAP). Mid-century temperature estimates, downscaled using the Weather Research and Forecasting model, are compared to 2007 temperatures at 36 km and 12 km resolutions. Models indicate the average apparent and actual summer temperatures rise by 4.5° and 3.3° C, respectively. Warmer average apparent temperatures could cause 11,562 additional annual deaths (95% confidence interval, CI: 2641-20,095) due to cardiovascular stress in the population aged 65 years and above, while higher minimum temperatures could cause 8767 (95% CI: 5030-12,475) additional deaths each year. Modeled future climate data available at both coarse (36 km) and fine (12 km) resolutions predict significant human health impacts from warmer climates. The findings suggest that currently available information on future climates is sufficient to guide regional planning for the protection of public health. Higher resolution climate and demographic data are still needed to inform more targeted interventions.

The Impact of Heat Waves on Emergency Department Admissions in Charlottesville, Virginia, U.S.A

Heat waves have been linked to increases in emergency-related morbidity, but more research is needed on the demographic and disease-specific aspects of these morbidities. Using a case-crossover approach, over 700,000 daily emergency department hospital admissions in Charlottesville, Virginia, U.S.A. from 2005–2016 are compared between warm season heat wave and non-heat wave periods. Heat waves are defined based on the exceedance, for at least three consecutive days, of two apparent temperature thresholds (35 °C and 37 °C) that account for 3 and 6% of the period of record. Total admissions and admissions for whites, blacks, males, females, and 20–49 years old are significantly elevated during heat waves, as are admissions related to a variety of diagnostic categories, including diabetes, pregnancy complications, and injuries and poisoning. Evidence that heat waves raise emergency department admissions across numerous demographic and disease categories suggests that heat exerts comorbidity influences that extend beyond the more well-studied direct relationships such as heat strokes and cardiac arrest.

The relationship between diurnal temperature range and COPD hospital admissions in Changchun, China

Diurnal temperature range (DTR) has been suggested to be an adverse health factor especially related to respiratory and cardiovascular diseases. In the current study, we investigated the association between DTR and chronic obstructive pulmonary disease (COPD) hospital admissions during 2009 to 2012 in northeast city of Changchun, China. Based on generalized additive model (GAM), the effects were expressed as relative risk (RR) values of COPD with 95% confidence intervals (CIs) with each 1 °C increase in DTR. And they were significantly increased with an increment of 1 °C in DTR, modified by season, age, and sex. The elderly were more vulnerable, with relative risk values of 1.048 (1.029, 1.066) in cold season and 1.037 (1.021, 1.053) in warm season. Regarding the gender, the DTR effect on females was greater during cold season and the RR value was 1.051 (1.033, 1.069) on the current day (lag 0). The greater estimates for males appeared at lag 7 days, with RR of 1.019 (0.998, 1.040). A season-specific effect was detected that the relative risk values with per 1 °C increase in DTR were greater in cold season than in warm season. These findings support the hypothesis of significant relationship between DTR and COPD in Changchun, one northeast city of China.

Longer-Term Outdoor Temperatures and Health Effects: A Review

PURPOSE OF REVIEW

Our goal was to assess current literature and knowledge on associations between characteristics (mean, variability, extremes) of ambient temperatures and human health. We were motivated by concerns that climate change, which operates on a time frame of decades or longer, may influence not only shorter-term associations between weather and health (daily/weekly) but also have enduring implications for population health. We reviewed papers published between 2010 and 2017 on the health effects of longer-term (3 weeks to years) exposures to ambient temperature. We sought to answer: 'What health outcomes have been associated with longer-term exposures?' We included studies on a diverse range of health outcomes, with the exception of vector borne diseases such as malaria. Longer-term exposures were considered to be exposures to annual and seasonal temperatures and temperature variability.

RECENT FINDINGS

We found 26 papers meeting inclusion criteria, which addressed mortality, morbidity, respiratory disease, obesity, suicide, infectious diseases and allergies among various age groups. In general, most studies found associations between longer-term temperature metrics and health outcomes. Effects varied by population subgroup. For example, associations with suicide differed by sex and underlying chronic illness modified effects of heat on mortality among the elderly.

SUMMARY

We found that regional and local temperatures, and changing conditions in weather due to climate change, were associated with a diversity of health outcomes through multiple mechanisms. Future research should focus on evidence for particular mechanistic pathways in order to inform adaptation responses to climate change.

Towards establishing evidence-based guidelines on maximum indoor temperatures during hot weather in temperate continental climates

Rising environmental temperatures represent a major threat to human health. The activation of heat advisories using evidence-based thresholds for high-risk outdoor ambient temperatures have been shown to be an effective strategy to save lives during hot weather. However, although the relationship between weather and human health has been widely defined by outdoor temperature, corresponding increases in indoor temperature during heat events can also be harmful to health especially in vulnerable populations. In this review, we discuss our current understanding of the relationship between outdoor temperature and human health and examine how human health can also be adversely influenced by high indoor temperatures during heat events. Our assessment of the existing literature revealed a high degree of variability in what can be considered an acceptable indoor temperature because there are differences in how different groups of people may respond physiologically and behaviorally to the same living environment. Finally, we demonstrate that both non-physiological (e.g., geographical location, urban density, building design) and physiological (e.g., sex, age, fitness, state of health) factors must be considered when defining an indoor temperature threshold for preserving human health in a warming global climate.

A public health needs assessment for domestic indoor overheating

OBJECTIVES

Indoor overheating is a potentially fatal health hazard that was identified as an issue requiring urgent action in the 2017 UK Climate Change Risk Assessment. We aimed to make research on this issue more accessible to local public health teams to encourage its inclusion in local strategic needs assessments.

STUDY DESIGN

Epidemiological health needs assessment.

METHODS

We adapted established health needs assessment methods, focussing on the epidemiological component, drawing evidence from a non-systematic literature review that was complemented by discussion with experts.

RESULTS

Indoor overheating arises from an interaction between occupants' susceptibility to heat, their behaviour and the building's location and its characteristics. Many of these factors are interrelated and, at a national level, are expected to vary over time with demographic and climate change. Understanding these factors, ways to mitigate them and a long-term view are all essential for managing overheating risk.

CONCLUSIONS

There is a need for services to be provided at the local level that consider the home environment and its impact on health in all seasons. A population-level approach to risk management across a local area is also useful to inform collaborative efforts to reduce future incidence of overheating and better understand how it varies with socio-economic deprivation.

Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model

This study investigates the relationship between all-cause mortality and extreme temperature events (ETEs) from 1975 to 2004. For 50 U.S. locations, these heat and cold events were defined based on location-specific thresholds of daily mean apparent temperature. Heat days were defined by a 3-day mean apparent temperature greater than the 95th percentile while extreme heat days were greater than the 97.5th percentile. Similarly, calculations for cold and extreme cold days relied upon the 5th and 2.5th percentiles. A distributed lag non-linear model assessed the relationship between mortality and ETEs for a cumulative 14-day period following exposure. Subsets for season and duration effect denote the differences between early- and late-season as well as short and long ETEs. While longer-lasting heat days resulted in elevated mortality, early season events also impacted mortality outcomes. Over the course of the summer season, heat-related risk decreased, though prolonged heat days still had a greater influence on mortality. Unlike heat, cold-related risk was greatest in more southerly locations. Risk was highest for early season cold events and decreased over the course of the winter season. Statistically, short episodes of cold showed the highest relative risk, suggesting unsettled weather conditions may have some relationship to cold-related mortality. For both heat and cold, results indicate higher risk to the more extreme thresholds. Risk values provide further insight into the role of adaptation, geographical variability, and acclimatization with respect to ETEs.

Ambient temperature and added heat wave effects on hospitalizations in California from 1999 to 2009

Investigators have examined how heat waves or incremental changes in temperature affect health outcomes, but few have examined both simultaneously. We utilized distributed lag nonlinear models (DLNM) to explore temperature associations and evaluate possible added heat wave effects on hospitalizations in 16 climate zones throughout California from May through October 1999-2009. We define heat waves as a period when daily mean temperatures were above the zone- and month-specific 95th percentile for at least two consecutive days. DLNMs were used to estimate climate zone-specific non-linear temperature and heat wave effects, which were then combined using random effects meta-analysis to produce an overall estimate for each. With higher temperatures, admissions for acute renal failure, appendicitis, dehydration, ischemic stroke, mental health, non-infectious enteritis, and primary diabetes were significantly increased, with added effects from heat waves observed for acute renal failure and dehydration. Higher temperatures also predicted statistically significant decreases in hypertension admissions, respiratory admissions, and respiratory diseases with secondary diagnoses of diabetes, though heat waves independently predicted an added increase in risk for both respiratory types. Our findings provide evidence that both heat wave and temperature exposures can exert effects independently.

Effect of night-time temperatures on cause and age-specific mortality in London

Supplemental Digital Content is available in the text.

Background:

High ambient temperatures are associated with an acute increase in mortality risk. Although heat exposure during the night is anecdotally cited as being important, this has not been rigorously demonstrated in the epidemiological literature.

Methods:

We quantified the contribution of nighttime temperatures using time-series quasi-Poisson regression on cause and age-specific daily mortality in London between 1993 and 2015. Daytime and nighttime exposures were characterized by average temperatures between 9 am and 9 pm and between 4 am and 8 am, respectively, lagged by 7 days. We also examined the differential impacts of hot and cool nights preceded by very hot days. All models were adjusted for air quality, season, and day of the week. Nighttime models were additionally adjusted for daytime exposure.

Results:

Effects from nighttime exposure persisted after adjusting for daytime exposure. This was highest for stroke, RR (relative risk) = 1.65 (95% confidence interval (CI) = 1.27 to 2.14) estimated by comparing mortality risk at the 80th and 99th temperature percentiles. Compared to daytime exposure, nighttime exposure had a higher mortality risk on chronic ischemic and stroke and in the younger age groups. Respiratory mortality was most sensitive to daytime temperatures. Hot days followed by hot nights had a greater mortality risk than hot days followed by cool nights.

Conclusions:

Nighttime exposures make an additional important contribution to heat-related mortality. This impact was highest on warm nights that were preceded by a hot day, which justifies the alert criteria in heat–health warning system that is based on hot days followed by hot nights. The highest mortality risk was from stroke; targeted interventions would benefit patients most susceptible to stroke.

The health effects of hotter summers and heat waves in the population of the United Kingdom: a review of the evidence

It is widely acknowledged that the climate is warming globally and within the UK. In this paper, studies which assess the direct impact of current increased temperatures and heat-waves on health and those which project future health impacts of heat under different climate change scenarios in the UK are reviewed.This review finds that all UK studies demonstrate an increase in heat-related mortality occurring at temperatures above threshold values, with respiratory deaths being more sensitive to heat than deaths from cardiovascular disease (although the burden from cardiovascular deaths is greater in absolute terms). The relationship between heat and other health outcomes such as hospital admissions, myocardial infarctions and birth outcomes is less consistent. We highlight the main populations who are vulnerable to heat. Within the UK, these are older populations, those with certain co-morbidities and those living in Greater London, the South East and Eastern regions.In all assessments of heat-related impacts using different climate change scenarios, deaths are expected to increase due to hotter temperatures, with some studies demonstrating that an increase in the elderly population will also amplify burdens. However, key gaps in knowledge are found in relation to how urbanisation and population adaptation to heat will affect health impacts, and in relation to current and future strategies for effective, sustainable and equitable adaptation to heat. These and other key gaps in knowledge, both in terms of research needs and knowledge required to make sound public- health policy, are discussed.

The Summers 2003 and 2015 in South-West Germany: Heat Waves and Heat-Related Mortality in the Context of Climate Change

After 2003, another hot summer took place in Western and Central Europe in 2015. In this study, we compare the characteristics of the two major heat waves of these two summers and their effect on the heat related mortality. The analysis is performed with focus on South-West Germany (Baden–Württemberg). With an additional mean summer mortality of +7.9% (2003) and +5.8% (2015) both years mark the top-two records of the summer mortality in the period 1968–2015. In each summer, one major heat wave contributed strongly to the excess summer mortality: In August 2003, daily mortality reached anomalies of +70% and in July 2015 maximum deviations of +56% were observed. The August 2003 heat wave was very long-lasting and characterized by exceptional high maximum and minimum temperatures. In July 2015, temperatures were slightly lower than in 2003, however, the high air humidity during the day and night, lead to comparable heat loads. Furthermore, the heat wave occurred earlier during the summer, when the population was less acclimated to heat stress. Using regional climate models we project an increasing probability for future 2003- and 2015-like heat waves already in the near future (2021–2050), with a 2015-like event occurring about every second summer. In the far future (2070–2099) pronounced increases with more than two 2015-like heat waves per summer are possible.

Effect modification of individual- and regional-scale characteristics on heat wave-related mortality rates between 2009 and 2012 in Seoul, South Korea

Many studies have investigated the associations between heat waves, ambient temperature, cold spells, and mortality or morbidity. Some studies have utilized effect modification to reveal the factors that increase an individual's susceptibility to temperature extremes, which can then be used to reshape public policy. In this study, we used a time-stratified case-crossover technique to examine how individual- and regional-scale characteristics modified heat wave-related impacts on mortality rates in Seoul, South Korea, between 2009 and 2012. We defined a heat wave as having at least two consecutive days with a daily mean temperature greater than or equal to the 95th percentile recorded in each of Seoul's twenty-five districts. At the individual scale, citizens classified as belonging to a lower education group had a higher vulnerability to heat wave-related morbidity or mortality [odds ratio (OR) 1.261; 95% confidence interval (CI): 1.034-1.538]. At a regional scale, death during heat waves was more likely to occur in districts with a high deprivation index (OR=1.194; 95% CI: 1.028-1.388). And a low proportion of green space around buildings (OR=1.178; 95% CI: 1.016-1.366), a low proportion of rooftop green space (OR=1.207; 95% CI: 1.042-1.399), or those that had fewer hospitals (OR=1.186; 95% CI: 1.019-1.379). Our data show that mortality during heat waves is more likely where these individual and regional-scale vulnerabilities overlap. Our findings support evidence of mortality impacts from heat waves and provide a basis for selection to policy makers choose on the target groups to reduce the public health burden of heat waves.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

BACKGROUND AND OBJECTIVES

Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research.

METHODS

The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis.

RESULTS

A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised.

CONCLUSIONS

Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality.

Decompose the association between heatwave and mortality: Which type of heatwave is more detrimental?

BACKGROUND

Heatwaves is the most hazardous natural disaster in Australia and its health impacts need to be well unveiled, but how to properly define a heatwave is still debatable. This study aimed to identify which type of heatwave is more detrimental to health and to elucidate which temperature indicator is more suitable for heatwave definition and early warning.

METHODS

We categorized temperature into extremely-hot and not-extremely-hot, and extremely-hot temperature refers to temperature at least ≥96th percentile of the monthly temperature distribution, and accordingly, heatwaves were categorized into four types: 1) Type I: extremely-hot days followed by extremely-hot nights (HW_both); 2) Type II: extremely-hot days followed by not-extremely-hot nights (HW_day); 3) Type III: not-extremely-hot days followed by extremely-hot nights (HW_night); and 4) Type IV: not-extremely-hot days followed by not-extremely-hot nights (HW_warm). A Poisson regression allowing for over-dispersion was used to examine the relationship between different types of heatwaves and mortality in Sydney, Melbourne and Brisbane using the data from 1988 to 2011.

RESULTS

Mortality in Brisbane increased significantly during HW_both and HW_warm, and mortality in Melbourne increased significantly during HW_both and HW_day. For Sydney, HW_both, HW_warm, and HW_day were all associated with mortality increase, although no appreciable difference in the magnitudes of mortality increase among these three heatwave types was observed. HW_night was not associated with any significant mortality increase in these cities. Mean temperature is the best temperature indicator for heatwaves in Brisbane and maximum temperature is the best temperature indicator for heatwaves in Melbourne.

CONCLUSIONS

Extremely-hot days rather than extremely-hot nights played a critical role in heatwave-related mortality. City-specific heatwave early warning may be optimal for Australia.

Nonlinear relationship between extreme temperature and mortality in different temperature zones: A systematic study of 122 communities across the mainland of China

BACKGROUND

Numerous previous studies have reported that human health risk is extremely sensitive to temperature. Very few studies, however, have characterized the relationship between temperature and mortality in different temperature zones due to the previous conclusions deduced from a regional or administrative division. A research covers different temperature zones was indispensable to have a comprehensive understanding of regional ambient temperature effect on public health.

METHODS

Based on the mortality dataset and meteorological variables of 122 communities in China from 2007 to 2012, a distributed lag nonlinear model (DLNM) was utilized to estimate the temperature effect on non-accidental mortality at the community level. Then, a meta-regression analysis was applied to pool the estimates of community-specific effects in various latitude-effected temperature zones.

RESULTS

At the community level, the mean value of relative extreme cold risk (1.63) of all 122 communities was higher than that of extreme high temperature (1.15). At regional level, we found temperature-mortality relationship (e.g., U- or J-shaped) varied in different temperature zones. Meanwhile, the minimum-mortality temperature of each zone was near the 75th percentile of local mean temperature except the north subtropics (50th percentiles). Lag effect was also obvious, especially for cold effect. An interesting M-shaped curve for the relationship between cold risk and temperature was detected, while an inverted "U" shaped with a right tail for the heat effect. Such different responses might be attributed to the difference in social-economic status of temperature zones.

CONCLUSION

The temperature-mortality relationship showed a distinct spatial heterogeneity along temperature zones across the Chinese mainland. Different characteristics of mortality responding to cold and heat stress highlighted the fact that, apart from the circumstance of temperature, the social-economic condition was also linked with health risk. Our findings suggest decision-makers should take more adaptive and effective measures to reduce health risks in China.

Vulnerability to extreme-heat-associated hospitalization in three counties in Michigan, USA, 2000-2009

With climate change, extreme heat (EH) events are increasing, so it is important to understand who is vulnerable to heat-associated morbidity. We determined the association between EH and hospitalizations for all natural causes; cardiovascular, respiratory, and renal diseases; diabetes mellitus; and acute myocardial infarction in Michigan, USA, at different intensities and durations. We assessed confounding by ozone and how individual characteristics and health insurance payer (a proxy for income) modified these associations. We obtained Michigan Inpatient Database, National Climatic Data Center, and US Environmental Protection Agency ozone data for May-September, 2000-2009 for three Michigan counties. We employed a case-crossover design and modeled EH as an indicator for temperature above the 95th, 97th, or 99th percentile thresholds for 1, 2, 3, or 4 days. We examined effect modification by patient age, race, sex, and health insurance payer and pooled the county results. Among non-whites, the pooled odds ratio for hospitalization on EH (97th percentile threshold) vs. non-EH days for renal diseases was 1.37 (95 % CI = 1.13-1.66), which increased with increasing EH intensity, but was null among whites (OR = 1.00, 95 % CI = 0.81, 1.25). We observed a null association between EH and cardiovascular hospitalization. EH (99th percentile threshold) was associated with myocardial infarction hospitalizations. Confounding by ozone was minimal. EH was associated with hospitalizations for renal disease among non-whites. This information on vulnerability to heat-associated morbidity helps characterize the public health burden of EH and target interventions including patient education.

An Inter-comparison of Three Heat Wave Types in China during 1961-2010: Observed Basic Features and Linear Trends

Using observed daily temperatures in China, three independent types of heat waves (HWs), including daytime HWs, nighttime HWs, and compound HWs (with both extreme daily maxima and minima), were defined. Different types of HWs showed distinctive preferences in occurrence locations and timing. However, spatial patterns of accompanying relative humidity were generally independent of categorization, except for closer association of nighttime events with high humidity level. Compound HWs and nighttime HWs experienced significant increases in frequency, participating days, mean duration, intensity and areal extent. Conversely, significant decreasing trends of above indicators prevailed in daytime HWs, especially in central-eastern China. Tendency of relative humidity changes didn’t vary with HW types. Instead it caused an interesting phenomenon that dry HWs in the west became more humid and humid events in the east got dryer, as manifested most obviously in compound type. Thorough comparisons highlight the evolutionary dominance of HW types. Specifically, previously-dominating independent daytime HWs have been increasingly replaced by independent nighttime events in central-eastern China, and by compound HWs in southern China. That’s the very reason for negative trends of independent daytime HWs in eastern China, even in a warming climate.

Climatic conditions and human mortality: spatial and regional variation in the United States

Previous research on climatic conditions and human mortality in the United States has three gaps: largely ignoring social conditions, lack of nationwide focus, and overlooking potential spatial variations. Our goal is to understand whether climatic conditions contribute to mortality after considering social conditions and to investigate whether spatial non-stationarity exists in these factors. Applying geographically weighted regression to a unique nationwide county-level dataset, we found that (1) net of other factors, average July temperatures are positively (detrimentally) associated with mortality while January temperatures mainly have a curvilinear relationship, (2) the mortality-climatic condition associations are spatially non-stationary, (3) the relationships between social conditions (e.g., social capital) and mortality are stable geographically, and (4) without a spatial approach to understanding the environment-mortality relationship, important spatial variations are overlooked. Our findings suggest that a universal approach to coping with the relationships between rapid climate changes and health may not be appropriate and effective.