Relationship between heat index and mortality of 6 major cities in Taiwan

Assessment of historical and projected changes in extreme temperatures of Balochistan, Pakistan using extreme value theory

The fundamental consequences of global warming include an upsurge in the intensity and frequency of temperature extremes. This study provides an insight into historical trends and projected changes in extreme temperatures on annual and seasonal scales across "Balochistan, Pakistan". Historical trends are analyzed through the Mann Kendal test, and extreme temperatures (Tmax and Tmin) are evaluated using generalized extreme value (GEV) distribution for historical period (1991-2020) from the observational data and the two projected periods as near-future (2041-2070) and far-future (2071-2100) using a six-member bias-corrected ensemble of regional climate models (RCMs) projections from the coordinate regional downscaling experiment (CORDEX) based on the worst emission scenario (RCP8.5). The evaluation of historical temperature trends suggests that Tmax generally increase on yearly scale and give mixed signals on seasonal scale (winter, spring, summer, and autumn); however, Tmin trends gave mixed signals at both yearly and seasonal scale. Compared to the historical period, the return levels are generally expected to be higher for Tmax and Tmin during the both projection periods in the order as far-future > near-future > historical on yearly and seasonal basis; however, the changes in Tmin are more evident. Station-averaged anomalies of + 1.9 °C and + 3.6 °C were estimated in 100-year return levels for yearly Tmax for near-future and far-future, respectively, while the anomalies in Tmin were found to be + 3.5 °C and + 4.8 °C which suggest the intensified heatwaves but milder colder extreme in future. The findings provide guidance on improved quantification of changing frequencies and severity in temperature extremes and the associated impacts.

Climate Change, Summer Temperature, and Heat-Related Mortality in Finland: Multicohort Study with Projections for a Sustainable vs. Fossil-Fueled Future to 2050

BACKGROUND

Climate change scenarios illustrate various pathways in terms of global warming ranging from "sustainable development" (Shared Socioeconomic Pathway SSP1-1.9), the best-case scenario, to 'fossil-fueled development' (SSP5-8.5), the worst-case scenario.

OBJECTIVES

We examined the extent to which increase in daily average urban summer temperature is associated with future cause-specific mortality and projected heat-related mortality burden for the current warming trend and these two scenarios.

METHODS

We did an observational cohort study of 363,754 participants living in six cities in Finland. Using residential addresses, participants were linked to daily temperature records and electronic death records from national registries during summers (1 May to 30 September) 2000 to 2018. For each day of observation, heat index (average daily air temperature weighted by humidity) for the preceding 7 d was calculated for participants' residential area using a geographic grid at a spatial resolution of 1 km × 1 km . We examined associations of the summer heat index with risk of death by cause for all participants adjusting for a wide range of individual-level covariates and in subsidiary analyses using case-crossover design, computed the related period population attributable fraction (PAF), and projected change in PAF from summers 2000-2018 compared with those in 2030-2050.

RESULTS

During a cohort total exposure period of 582,111,979 summer days (3,880,746 person-summers), we recorded 4,094 deaths, including 949 from cardiovascular disease. The multivariable-adjusted rate ratio (RR) for high (≥ 21 ° C ) vs. reference (14 - 15 ° C ) heat index was 1.70 (95% CI: 1.28, 2.27) for cardiovascular mortality, but it did not reach statistical significance for noncardiovascular deaths, RR = 1.14 (95% CI: 0.96, 1.36), a finding replicated in case-crossover analysis. According to projections for 2030-2050, PAF of summertime cardiovascular mortality attributable to high heat will be 4.4% (1.8%-7.3%) under the sustainable development scenario, but 7.6% (3.2%-12.3%) under the fossil-fueled development scenario. In the six cities, the estimated annual number of summertime heat-related cardiovascular deaths under the two scenarios will be 174 and 298 for a total population of 1,759,468 people.

DISCUSSION

The increase in average urban summer temperature will raise heat-related cardiovascular mortality burden. The estimated magnitude of this burden is > 1.5 times greater if future climate change is driven by fossil fuels rather than sustainable development. https://doi.org/10.1289/EHP12080.

Heat-mortality relationship in North Carolina: Comparison using different exposure methods

BACKGROUND

Many studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies' use of different exposure methods.

OBJECTIVE

This study evaluated different methods for estimating exposure to temperature using individual-level data and examined the impacts on the heat-mortality relationship.

METHODS

We calculated different temperature exposures for each individual death by using a modeled, gridded temperature dataset and a monitoring station dataset in North Carolina for 2000-2016. We considered individual-level vs. county-level averages and measured vs. modeled temperature data. A case-crossover analysis was conducted to examine the heat-mortality risk under different exposure methods.

RESULTS

The minimum mortality temperature (MMT) (i.e., the temperature with the lowest mortality rate) for the monitoring station dataset was 23.87 °C and 22.67 °C (individual monitor and county average, respectively), whereas for the modeled temperature dataset the MMT was 19.46 °C and 19.61 °C (individual and county, respectively). We found higher heat-mortality risk while using temperature exposure estimated from monitoring stations compared to risk based on exposure using the modeled temperature dataset. Individual-aggregated monitoring station temperature exposure resulted in higher heat mortality risk (odds ratio (95% CI): 2.24 (95% CI: 2.21, 2.27)) for a relative temperature change comparing the 99th and 90th temperature percentiles, while modeled temperature exposure resulted in lower odds ratio of 1.27 (95% CI: 1.25, 1.29).

SIGNIFICANCE

Our findings indicate that using different temperature exposure methods can result in different temperature-mortality risk. The impact of using various exposure methods should be considered in planning health policies related to high temperatures, including under climate change. IMPACT STATEMENT: (1) We estimated the heat-mortality association using different methods to estimate exposure to temperature. (2) The mean temperature value among different exposure methods were similar although lower for the modeled data, however, use of the monitoring station temperature dataset resulted in higher heat-mortality risk than the modeled temperature dataset. (3) Differences in mortality risk from heat by urbanicity varies depending on the method used to estimate temperature exposure.

The Scorching Truth: Investigating the Impact of Heatwaves on Selangor's Elderly Hospitalisations

Global climate change has contributed to the intensity, frequency, and duration of heatwave events. The association between heatwaves and elderly mortality is highly researched in developed countries. In contrast, heatwave impact on hospital admissions has been insufficiently studied worldwide due to data availability and sensitivity. In our opinion, the relationship between heatwaves and hospital admissions is worthwhile to explore as it could have a profound impact on healthcare systems. Therefore, we aimed to investigate the associations between heatwaves and hospitalisations for the elderly by age group in Selangor, Malaysia, from 2010 to 2020. We further explored the impact of heatwaves on the risks of cause-specific hospital admissions across age groups within the elderly. This study applied generalized additive models (GAMs) with the Poisson family and distributed lag models (DLMs) to estimate the effect of heatwaves on hospitalisations. According to the findings, there was no significant increase in hospitalisations for those aged 60 and older during heatwaves; however, a rise in mean apparent temperature (ATmean) by 1 °C significantly increased the risk of hospital admission by 12.9%. Heatwaves had no immediate effects on hospital admissions among elderly patients, but significant delay effects were identified for ATmean with a lag of 0-3 days. The hospital admission rates of the elderly groups started declining after a 5-day average following the heatwave event. Females were found to be relatively more vulnerable than males during heatwave periods. Consequently, these results can provide a reference to improve public health strategies to target elderly people who are at the greatest risk of hospitalisations due to heatwaves. Development of early heatwave and health warning systems for the elderly would assist with preventing and reducing health risks while also minimising the burden on the whole hospital system in Selangor, Malaysia.

Influences of temperature and humidity on cardiovascular disease among adults 65 years and older in China

Background

The burden of cardiovascular disease (CVD) on the current aging society in China is substantial. Climate change, including extreme temperatures and humidity, has a detrimental influence on health. However, epidemiological studies have been unable to fully identify the association between climate change and CVD among older adults. Therefore, we investigated the associations between temperature and relative humidity and CVD among older adults in China.

Methods

We used cohort data from the China Longitudinal Health and Longevity Survey (CLHLS) conducted in 2002, 2005, 2008, 2011, 2014, and 2018. A total of 39,278 Chinese adults 65 years and older participated in the analyses. The average annual temperatures and relative humidity during 2001 and 2017 (before the survey year) at the city level in China were used as the exposure measures. We selected patients with hypertension, heart disease, and stroke to create a sample of CVD patients. The associations between temperature and relative humidity and CVD were analyzed using the generalized estimation equation (GEE) model. Covariates included sociodemographic factors, health status, lifestyle, and cognitive function.

Results

The average annual temperature was negatively correlated with the prevalence of CVD. Every 1°C increase in the average annual temperature reduced the rates of hypertension by 3% [odds ratio (OR): 0.97; 95% confidence interval (CI): 0.96-0.97], heart disease by 6% (OR: 0.94; 95% CI: 0.92-0.95), and stroke by 5% (OR: 0.95; 95% CI: 0.94-0.97). The results of the analyses stratified by sex, urban/rural residence, and educational level were robust. The average annual relative humidity was inversely associated with the likelihood of CVD among older adults. Every 1% increase in the average annual relative humidity reduced the rates of hypertension by 0.4% (OR: 0.996; 95% CI: 0.99-1.00), heart disease by 0.6% (OR: 0.994; 95% CI: 0.99-1.00), and stroke by 0.08% (OR: 0.992; 95% CI: 0.98-1.00). However, the effects were more obvious with higher humidity levels (>70).

Conclusion

Our findings suggest that higher temperatures and relative humidity may reduce the risk of CVD among older adults.

Bayesian Approach to Disease Risk Evaluation Based on Air Pollution and Weather Conditions

BACKGROUND

Environmental factors such as meteorological conditions and air pollutants are recognized as important for human health, where mortality and morbidity of certain diseases may be related to abrupt climate change or air pollutant concentration. In the literature, environmental factors have been identified as risk factors for chronic diseases such as ischemic heart disease. However, the likelihood evaluation of the disease occurrence probability due to environmental factors is missing.

METHOD

We defined people aged 51-90 years who were free from ischemic heart disease (ICD9: 410-414) in 1996-2002 as the susceptible group. A Bayesian conditional logistic regression model based on a case-crossover design was utilized to construct a risk information system and applied to data from three databases in Taiwan: air quality variables from the Environmental Protection Administration (EPA), meteorological parameters from the Central Weather Bureau (CWB), and subject information from the National Health Insurance Research Database (NHIRD).

RESULTS

People living in different geographic regions in Taiwan were found to have different risk factors; thus, disease risk alert intervals varied in the three regions.

CONCLUSIONS

Disease risk alert intervals can be a reference for weather bureaus to issue health warnings. With early warnings, susceptible groups can take measures to avoid exacerbation of disease when meteorological conditions and air pollution become hazardous to their health.

Regional incidence risk of heat stroke in elderly individuals considering population, household structure, and local industrial sector

This study aims to clarify the regional characteristics of heat stroke incidence patterns inside and outside residences among the elderly from the perspective of working and living conditions. The study area comprised 41 municipalities belonging to Hyogo Prefecture in Japan. Based on information on heat stroke emergency medical evacuees in each municipality from 2011 to 2020, the regional differences in the incidence risk of heat stroke were analyzed. The results revealed that the number of cases and the proportion of males and females among them were related to the demographic structure of each municipality. A grouping analysis was conducted to classify the characteristics of each municipality based on the relationship between the incidence risk of heat stroke and the industrial structure. A factor analysis and binomial logistic regression analysis were also conducted to investigate the effect of demographic structure on the incidence risk of heat stroke. The results indicate that the incidence risk of heat stroke is correlated with industrial and demographic structures, and the risk is likely to vary regionally.

Experimental investigation of the effects of personal protective equipment on thermal comfort in hot environments

Since the outbreak of COVID-19, wearing personal protective equipment (PPE) has become increasingly common, especially for healthcare workers performing nucleic acid sample collection. A field experiment and questionnaire survey were conducted in a semi-open transition space of a university building in Guangzhou, southern China. Thirty-two subjects wore PPE to simulate nucleic acid sample collection, during which thermal parameters were recorded and subjective questionnaires were completed. The relationship between thermal sensation and thermal index was analyzed to determine the neutral temperature and comfort temperature zones. Subjects had higher requirements for thermal environment parameters when wearing PPE than when not wearing PPE, and were found to have statistically significant differences in thermal perception when wearing and not wearing PPE. Wearing PPE significantly raised the subjects' thermal and humidity sensations and restricted their airflow. Wearing PPE resulted in thermal discomfort for the subjects and a high unacceptability rate for environmental thermal parameters. The subjects wore PPE for an acceptable duration of approximately 1.5 h. The neutral operative temperatures were significantly lower when wearing PPE than when not wearing PPE, and the deviation from the neutral temperature was 9.7 °C. The neutral operative temperature was 19.5 °C and the comfort temperature zone was 17.4-21.5 °C when subjects wore PPE, demonstrating that subjects who wore PPE preferred lower temperatures. These results suggest that people who wear PPE for work, especially outdoors, should receive more attention to ensure thermal comfort and safety.

Fierce Heat and Players’ Health: Examining the View on Japan High School Baseball

A summer high school baseball tournament is held every mid-summer in Koshien Stadium. “Koshien Baseball” is very popular in Japan; however, it faces the problem of extremely high temperatures during games. Thus, high school players are threatened by harsh environmental conditions. For this reason, two Internet surveys were distributed to the same individuals. Then, their views regarding the Koshien tournament before and after the provision of information regarding environmental change in Japan were gathered. Using these data, this study examined how their views changed after being introduced to the information. Compared with their previous views, it was found that (1) respondents were more likely to agree that the management rules of the Koshien tournament should be altered to protect players’ health, and (2) the impact of providing information is greater for female respondents, young respondents, and highly educated respondents. This study provides evidence that the effect of information provision varies according to gender, age, and educational background. However, the mechanism causing this difference has not yet been analyzed. It would be valuable to consider this mechanism in future research.

Associations between ambient heat exposure early in pregnancy and risk of congenital heart defects: a large population-based study

Some epidemiological studies have confirmed the association between environmental factors and congenital heart defects (CHD). While the possibility that maternal ambient heat exposures are related to CHD has received little attention. Our study aims to investigate the association between maternal ambient extreme heat exposure early in pregnancy and the risk of CHD in offspring in China. We conducted a retrospective cohort study of 1,918,105 fetuses between 2 and 8 weeks after gestation from May to October in Guangdong, China, 2015-2019. The main heat exposure was defined as extreme heat events (EHE) by using the 90th (EHE90) or 95th (EHE95) percentile of the daily maximum temperature. For each EHE definition, we further defined four indicators: having EHE or not, frequency, duration, and cumulative days. We used the log-binomial regression models to calculate the prevalence ratios (PR) of CHD with 95% confidence intervals (CI) for the associations between CHD and EHE, adjusted for potentially confounding covariates. There are 1,918,105 infants included in the study, of which 9588 had CHD, with a prevalence rate of 499.9 per 100,000 (95% CI: 489.9, 509.8). We found that all EHE indicators were positively associated with the increased risks of overall CHD, some CHD classes (congenital malformations of cardiac septa, congenital malformations of great arteries, and congenital malformations of great arteries), and some CHD subtypes (atrial septal defect and patent ductus arteriosus). In addition, the PR yielded higher estimates when exposing to EHE95. For instance, the risk of suffering congenital malformations of great arteries was 1.548 (95% CI: 1.401, 1.712) for EHE90 exposure and 1.723 (95% CI: 1.565, 1.898) for EHE95 exposure, respectively. Our study demonstrated that EHE during 2-8 weeks postconception was associated with overall CHD in offspring, particularly atrial septal defects and patent ductus arteriosus. The associations strengthened with the extent and cumulative days of maternal exposure to EHE.

Retrospection of heatwave and heat index

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman's formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1-2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.

Selecting Thresholds of Heat-Warning Systems with Substantial Enhancement of Essential Population Health Outcomes for Facilitating Implementation

Most heat-health studies identified thresholds just outside human comfort zones, which are often too low to be used in heat-warning systems for reducing climate-related health risks. We refined a generalized additive model for selecting thresholds with substantial health risk enhancement, based on Taiwan population records of 2000–2017, considering lag effects and different spatial scales. Reference-adjusted risk ratio (RaRR) is proposed, defined as the ratio between the relative risk of an essential health outcome for a threshold candidate against that for a reference; the threshold with the highest RaRR is potentially the optimal one. It was found that the wet-bulb globe temperature (WBGT) is a more sensitive heat-health indicator than temperature. At lag 0, the highest RaRR (1.66) with WBGT occurred in emergency visits of children, while that in hospital visits occurred for the working-age group (1.19), presumably due to high exposure while engaging in outdoor activities. For most sex, age, and sub-region categories, the RaRRs of emergency visits were higher than those of hospital visits and all-cause mortality; thus, emergency visits should be employed (if available) to select heat-warning thresholds. This work demonstrates the applicability of this method to facilitate the establishment of heat-warning systems at city or country scales by authorities worldwide.

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.

Dwelling Characteristics Influence Indoor Temperature and May Pose Health Threats in LMICs

Background:

Shelter and safe housing is a basic human need that brings about a sense of ownership, self-sufficiency, and citizenship. Millions of people around the world live in inadequate dwellings in unhealthy areas, such as urban slums. These dwellings may experience indoor temperatures that impact inhabitants’ health. Indoor dwelling temperatures vary depending on many factors including geographic location, such as inland versus coastal. In an era of climate change, understanding how dwelling characteristics influence indoor temperature is important, especially in low- and middle-income countries, to protect health.

Objective:

To assess indoor temperature in low-cost dwellings located in a coastal setting in relation to dwelling characteristics.

Methods:

Indoor temperature and relative humidity loggers were installed from 1 June 2017 to 15 May 2018 in 50 dwellings in two settlements in a coastal town on the east coast of South Africa. Ambient outdoor temperature data were obtained from the national weather service, indoor temperature data were converted into apparent temperature, and heat index calculations were made to consider possible heat-health risks. A household questionnaire and dwelling observation assessment were administered. A mixed-effects linear regression model was constructed to consider the impact of dwelling characteristics on indoor apparent temperature.

Findings:

Among 17 dwellings with all data sets, indoor temperatures were consistently higher than, and well correlated (r = 0.92) with outdoor temperatures. Average differences in indoor and outdoor temperatures were about 4°C, with statistically significant differences in percentage difference of indoor/outdoor between seasons (p < 0.001). Heat indices for indoor temperatures were exceeded mostly in summer, thereby posing possible health risks. Dwellings with cement floors were statistically significantly cooler than any other floor type across all seasons.

Conclusions:

Low-cost dwellings experienced temperatures indoors higher than outdoor temperatures in part due to floor type. These results help inform interventions that consider housing and human health (n = 289).

Determining the correlation between outdoor heatstroke incidence and climate elements in Daegu metropolitan city

Background

Heatstroke is one of the most serious heat-related illnesses. However, establishing public policies to prevent heatstroke remains a challenge. This study aimed to investigate the most relevant climate elements and their warning criteria to prevent outdoor heatstroke (OHS).

Methods

We investigated heatstroke patients from five major hospitals in Daegu metropolitan city, Korea, from June 1 to August 31, 2011 to 2016. We also collected the corresponding regional climate data from Korea Meteorological Administration. We analyzed the relationship between the climate elements and OHS occurrence by logistic regression.

Results

Of 70 patients who had heatstroke, 45 (64.3%) experienced it while outdoors. Considering all climate elements, only mean heat index (MHI) was related with OHS occurrence (p=0.019). Therefore, the higher the MHI, the higher the risk for OHS (adjusted odds ratio, 1.824; 95% confidence interval, 1.102-3.017). The most suitable cutoff point for MHI by Youden's index was 30.0°C (sensitivity, 77.4%; specificity, 73.7%).

Conclusion

Among the climate elements, MHI was significantly associated with OHS occurrence. The optimal MHI cutoff point for OHS prevention was 30.0°C.

Short-term prediction of extremely hot days in summer due to climate change and ENSO and related attributable mortality

Summer days with extremely hot temperatures in Taiwan have been increasing for the past few decades, and this continuing trend is expected to worsen heat-related mortality. To mitigate the corresponding health impacts, in this study, we developed a statistical state-space model to predict the number of extremely hot days in June-September for the next year. Based on historical data from 1951 to 2017, we estimated the climate change trend after adjusting for the nonlinear lagged effect of the Niño 3.4 index. We then developed a predictive state-space model using these two primary factors and adjusting for residual autocorrelations. Validation results comparing the extremely hot days observed over 2015-2017 with predictions showed that 86% of the average prediction errors were within 4 days of the observations. To assess the health impacts, we applied the model to the projection of heat-attributable mortality (AM) in 2018 by adopting a comparative risk assessment (CRA) approach with the reference period of 2001-2010. The results showed that the Taipei metropolitan area in northern Taiwan is the most affected region with AM of 1501 deaths from all-causes, followed by Taichung in central Taiwan with 490 deaths. The prediction model and the CRA projection provide both a tool and guidance for public health administrators to address the imminent threat posed by climate change.

New approach to identifying proper thresholds for a heat warning system using health risk increments

BACKGROUND

A critical adaptation strategy for reducing heat-related health risk under climate change is to establish a heat warning system with a proper threshold that requires evaluation of heat-health relationships using empirical data.

OBJECTIVES

This work presents a new approach to selecting proper health-based thresholds for a heat warning system which are different from thresholds of heat-health relationship.

METHODS

The proposed approach examined heat-health relationships through analyzing 15 years of health records with a modified generalized additive model (GAM), compared risk ratio increments (RRIs) of threshold candidates against a reference, assessed frequency of days above these candidates, and presented results graphically for easy communication. The candidate with the maximum RRI and proper occurring frequency is potentially the best threshold. Three heat indicators, including wet-bulb globe temperature (WBGT), temperature (T), and apparent temperature (AT), as well as three health outcomes, including all-cause mortality, heat-related hospital admissions, and heat-related emergency visits were evaluated.

RESULTS

Risk ratios for all three health outcomes showed a consistent rising trend with increasing threshold candidates for all three heat indicators among different age and gender groups. WBGT had the most obvious increasing trend of RRIs with the three health outcomes. The maximum RRI was observed in heat-related emergency visits (242%), followed by heat-related hospital admissions (73%), and all-cause mortality (9%). The RRIs assessed for the three health outcomes pointed to the same thresholds, 33.0 °C, 34.0 °C, and 37.5 °C for WBGT, T, and AT, respectively. The number of days above these thresholds and for warning to be issued ranged between 0 and 7 days during 2000-2014.

DISCUSSION

This study demonstrated a new approach to determining heat-warning thresholds with different heat indicators and health outcomes. The proposed approach provides a straightforward, feasible, and flexible scientific tool that assists the authorities around the world in selecting a proper threshold for a heat warning system.

Differences of hemorrhagic and ischemic strokes in age spectra and responses to climatic thermal conditions

The risks of emergency room (ER) visits for cerebral infarction (CI) and intracerebral hemorrhage (ICH) is found to differ in different age groups under different climatic thermal environments. Based on CI and ICH related ER-visit records from three major hospitals in Beijing, China, from 2008 to 2012, the advanced Universal Thermal Climate Index (UTCI), was adopted in this study to assess the climatic thermal environment. Particularly, daily mean UTCI was used as a predictor for the risk of ER visits for CI and ICH. A generalized quasi-Poisson additive model combined with a distributed lag non-linear model was performed to quantify their association. The results indicated that (i) the highest growth rate of ER visits for ICH occurred in age 38 to 48, whereas an increasing ER admissions for CI maintained at age 38 to 78. (ii) The frequency distribution of UTCI in Beijing peaked at -8 and 30 °C, corresponding to moderate cold stress and moderate heat stress, respectively. (iii) Correlation analysis indicated that ICH morbidity was negatively correlated with UTCI, whereas occurrence of CI showed no significant association with UTCI. (iv) The estimated relative risk of ER visits corresponding to 1 °C change in UTCI, which was then stratified by age and gender, indicated that all sub-groups of ICH patients responded similarly to thermal stress. Namely, there is an immediate ICH risk (UTCI = -13 °C, RR = 1.35, 95% CIs: 1.11-1.63) from cold stress on the onset day, but non-significant impact from heat stress. As for CI occurrences, no effect from cold stress was identified, except for only those aged 45 to 65 were threatened by heat stress (UTCI = 38 °C, RR = 1.64, 95% CIs: 1.10-2.44) on lag 0-2 d.

Impact of Temperature in Summer on Emergency Transportation for Heat-Related Diseases in Japan

Background:

In Japan, the demand for emergency transportation for people with heat-related illness has recently increased. The purpose of this study was to investigate the relationship between incidents of heat-related illness and the daily maximum temperature.

Methods:

The daily maximum temperatures in Japan's 11 districts over the past 10 years were classified into four categories, with cutoff points at the 50^th, 75^th, 95^th, and higher than 95^th percentiles. We then conducted a logistic regression analysis of emergency transportation demand in each temperature category by age group, using the 50^th percentile as the reference category for each area.

Results:

There were 42,931 cases of emergency transportation due to heat-related diseases during the study period. Classified by age, 12.5%, 43.4%, and 44.1% of cases involved children, adults, and elderly people, respectively. The analysis showed that the number of cases of emergency transportation for people with heat-related diseases (per 100,000 people; corresponding to a 1.0°C increase in the daily maximum temperature) was 0.016–0.106 among children (24.9–169.9 children required emergency transportation for heat-related diseases), from 0.013 to 0.059 among adults (19.8–98.2 adults required emergency transportation), and from 0.045 to 0.159 among elderly persons (30.0–145.4 elderly people required emergency transportation). The risk was highest for elderly persons, followed by children and finally adults. Cases of emergency transportation due to heat-related illness increased by 2.4–8.9 times when the daily maximum temperature was approximately 1.5°C above the mean daily maximum temperature. In fact, the daily maximum temperature had a larger effect than the daily relative humidity level on emergency transportation for people with heat-related diseases.

Conclusion:

Public health organizations and health-care services should support elderly people and children, two high-risk groups for heat-related diseases.

Future heat stress arising from climate change on Iran's population health

Climate change-induced extreme heat events are becoming a major issue in different parts of the world, especially in developing countries. The assessment of regional and temporal past and future change in heat waves is a crucial task for public health strategies and managements. The historical and future heat index (HI) time series are investigated for temporal change across Iran to study the impact of global warming on public health. The heat index is calculated, and the nonparametric trend assessment is carried out for historical time series (1981-2010). The future change in heat index is also projected for 2020-2049 and 2070-2099 periods. A rise in the historical heat index and extreme caution conditions for summer and spring seasons for major parts of Iran are notable for historical (1981-2010) series in this study. Using different climate change scenarios shows that heat index will exceed the critical threshold for human adaptability in the future in the country. The impact of climate change on heat index risk in Iran is significant in the future. To cope with this crucial situation, developing early warning systems and health care strategies to deal with population growth and remarkable socio-economic features in future is essential.

Weighting Criteria and Prioritizing of Heat stress indices in surface mining using a Delphi Technique and Fuzzy AHP-TOPSIS Method

BACKGROUND

Heat stress as a physical harmful agent can increase the risk of health and safety problems in different workplaces such as mining. Although there are different indices to assess the heat stress imposed on workers, choosing the best index for a specific workplace is so important. Since various criteria affect an index applicability, extracting the most effective ones and determining their weights help to prioritize the existing indices and select the optimal index.

METHODS

In order to achieve this aim, present study compared some heat stress indices using effective methods. The viewpoints of occupational health experts and the qualitative Delphi methods were used to extract the most important criteria. Then, the weights of 11 selected criteria were determined by Fuzzy Analytic Hierarchy Process. Finally, fuzzy TOPSIS technique was applied for choosing the most suitable heat stress index.

RESULTS

According to result, simplicity, reliability, being low cost, and comprehensiveness were the most determinative criteria for a heat stress index. Based on these criteria and their weights, the existing indices were prioritized. Eventually, wet bulb glob temperature appropriated the first priority and it was proposed as an applicable index for evaluating the heat stress at outdoor hot environments such as surface mines.

CONCLUSIONS

The use of these strong methods allows introducing the most simple, precise, and applicable tool for evaluation the heat stress in hot environments. It seems that WBGT acts as an appropriate index for assessing the heat stress in mining activities at outdoors.

Humidity: A review and primer on atmospheric moisture and human health

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature.

Identifying Heat Waves in Florida: Considerations of Missing Weather Data

BACKGROUND

Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information.

OBJECTIVES

To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida.

METHODS

In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida.

RESULTS

Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September).

CONCLUSIONS

Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised.

When are we most vulnerable to temperature variations in a day?

Daily temperature measures are commonly used when examining the association between temperature and mortality. In fact, temperature measures are available 24 hours a day and more detailed records may provide a better prediction of mortality compared to daily statistics. In this article, monthly stratified analysis modeling for mortality is conducted for the total population as well as the stratified elderly and younger subgroups. We identified the most significant time during the day that is associated with daily mortality. Surprisingly, the estimates of relative risk and magnitude of associations derived from the hourly temperature measures are similar or even stronger compared to those modeled by the daily statistics. This phenomenon remains true for lagged hourly temperature measures and the changing patterns of associations from January through December are revealed. In summary, people are the most vulnerable to temperature variations in the early morning around 5 am and the night time around 8 pm.

Environmental temperature and thermal indices: what is the most effective predictor of heat-related mortality in different geographical contexts?

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (≥75 years) who died in inland and coastal cities from 2006 to 2008 (May–October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress.