What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

Random forest analysis of the relative importance of meteorological indicators for heatstroke cases in Japan based on the degree of severity and place of occurrence

Heatstroke is a serious health concern in Japan. To reduce heatstroke risk, the government of Japan implemented the "Heatstroke Alert" nationwide in 2021, employing the wet bulb globe temperature (WBGT) as a criterion. Although the WBGT is a useful meteorological indicator for assessing the risk of heatstroke, other important meteorological indicators must also be investigated. Therefore, using a random forest approach, this study analyzed the relative importance of several meteorological indicators, including those representing heat acclimatization, for each of the 47 Japanese prefectures. Using the generalized linear model, important meteorological indicators were employed as explanatory variables in the heatstroke prediction model to determine the predictive meteorological indicator. Heatstroke cases were evaluated separately by the degree of severity and the place of occurrence. The results showed that the relative temperature (RelTemp), which represents heat acclimatization and was calculated considering past temperature history, was the most predictive (i.e., provided the best goodness of fit) concerning the degree of severity, place of occurrence, and prefectures. RelTemp can be a complementary indicator of WBGT in countries and regions such as Japan, where seasonal differences in heat acclimatization must be considered. In addition, the findings of this study contribute to the development of a more accurate assessment of heatstroke risk.

Regional variation in the role of humidity on city-level heat-related mortality

The rising humid heat is regarded as a severe threat to human survivability, but the proper integration of humid heat into heat-health alerts is still being explored. Using state-of-the-art epidemiological and climatological datasets, we examined the association between multiple heat stress indicators (HSIs) and daily human mortality in 739 cities worldwide. Notable differences were observed in the long-term trends and timing of heat events detected by HSIs. Air temperature (Tair) predicts heat-related mortality well in cities with a robust negative Tair-relative humidity correlation (CT-RH). However, in cities with near-zero or weak positive CT-RH, HSIs considering humidity provide enhanced predictive power compared to Tair. Furthermore, the magnitude and timing of heat-related mortality measured by HSIs could differ largely from those associated with Tair in many cities. Our findings provide important insights into specific regions where humans are vulnerable to humid heat and can facilitate the further enhancement of heat-health alert systems.

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HE2AT Center study protocol

INTRODUCTION

African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the complexities of heat-related health impacts in these cities. The objectives are: (1) mapping intraurban heat risk and exposure using health, socioeconomic, climate and satellite imagery data; (2) creating a stratified heat-health forecast model to predict adverse health outcomes; and (3) establishing an early warning system for timely heatwave alerts. The ultimate goal is to foster climate-resilient African cities, protecting disproportionately affected populations from heat hazards.

METHODS AND ANALYSIS

The research will acquire health-related datasets from eligible adult clinical trials or cohort studies conducted in Johannesburg and Abidjan between 2000 and 2022. Additional data will be collected, including socioeconomic, climate datasets and satellite imagery. These resources will aid in mapping heat hazards and quantifying heat-health exposure, the extent of elevated risk and morbidity. Outcomes will be determined using advanced data analysis methods, including statistical evaluation, machine learning and deep learning techniques.

ETHICS AND DISSEMINATION

The study has been approved by the Wits Human Research Ethics Committee (reference no: 220606). Data management will follow approved procedures. The results will be disseminated through workshops, community forums, conferences and publications. Data deposition and curation plans will be established in line with ethical and safety considerations.

Revisiting the importance of temperature, weather and air pollution variables in heat-mortality relationships with machine learning

Extreme heat events have significant health impacts that need to be adequately quantified in the context of climate change. Traditionally, heat-health association methods have relied on statistical models using a single air temperature index, without considering other heat-related variables that may influence the relationship and their potentially complex interactions. This study aims to introduce and compare different machine learning (ML) models, which naturally consider interactions between predictors and non-linearities, to re-examine the importance of temperature, weather and air pollution predictors in modeling the heat-mortality relationship. ML approaches based on tree ensembles and neural networks, as well as non-linear statistical models, were used to model the heat-mortality relationship in the two most populated metropolitan areas of the province of Quebec, Canada. The models were calibrated using a comprehensive database of heat-related predictors including various lagged temperature indices, temperature variations, meteorological and air pollution variables. Performance was evaluated based on out-of-sample summer mortality predictions. For the two studied regions, models relying only on lagged temperature indices performed better, or equally well, than models considering more heat-related predictors such as temperature variations, weather and air pollution variables. The temperature index with the best performance differed by region, but both mean temperature and humidex were among the best indices. In terms of modeling approaches, non-linear statistical models were as competent as more advanced ML models for predicting out-of-sample summer mortality. This research validated the current use of non-linear statistical models with the appropriate lagged temperature index to model the heat-mortality relationship. Although ML models have not improved the performance of all-cause mortality modeling, these approaches should continue to be explored, particularly for other health effects that may be more directly linked to heat exposure and, in the future, when more data become available.

Ozone, Heat Wave, and Cardiovascular Disease Mortality: A Population-Based Case-Crossover Study

A case-crossover study among 511,767 cardiovascular disease (CVD) deaths in Jiangsu province, China, during 2015-2021 was conducted to assess the association of exposure to ambient ozone (O3) and heat wave with CVD mortality and explore their possible interactions. Heat wave was defined as extreme high temperature for at least two consecutive days. Grid-level heat waves were defined by multiple combinations of apparent temperature thresholds and durations. Residential O3 and heat wave exposures were assessed using grid data sets (spatial resolution: 1 km × 1 km for O3; 0.0625° × 0.0625° for heat wave). Conditional logistic regression models were applied for exposure-response analyses and evaluation of additive interactions. Under different heat wave definitions, the odds ratios (ORs) of CVD mortality associated with medium-level and high-level O3 exposures ranged from 1.029 to 1.107 compared with low-level O3, while the ORs for heat wave exposure ranged from 1.14 to 1.65. Significant synergistic effects on CVD mortality were observed for the O3 and heat wave exposures, which were generally greater with higher levels of the O3 exposure, higher temperature thresholds, and longer durations of heat wave exposure. Up to 5.8% of the CVD deaths were attributable to O3 and heat wave. Women and older adults were more vulnerable to the exposure to O3 and heat wave exposure. Exposure to both O3 and heat wave was significantly associated with an increased odds of CVD mortality, and O3 and heat wave can interact synergistically to trigger CVD deaths.

Effects of apparent temperature on daily outpatient and inpatient visits for cause-specific respiratory diseases in Ganzhou, China: a time series study

BACKGROUND

Non-optimum temperatures are associated with increased risk of respiratory diseases, but the effects of apparent temperature (AT) on respiratory diseases remain to be investigated.

METHODS

Using daily data from 2016 to 2020 in Ganzhou, a large city in southern China, we analyzed the impact of AT on outpatient and inpatient visits for respiratory diseases. We considered total respiratory diseases and five subtypes (influenza and pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma and chronic obstructive pulmonary disease [COPD]). Our analysis employed a distributed lag nonlinear model (DLNM) combined with a generalized additive model (GAM).

RESULTS

We recorded 94,952 outpatients and 72,410 inpatients for respiratory diseases. We found AT significantly non-linearly associated with daily outpatient and inpatient visits for total respiratory diseases, influenza and pneumonia, and URTI, primarily during comfortable AT levels, while it was exclusively related with daily inpatient visits for LRTI and COPD. Moderate heat (32.1 °C, the 75.0th centile) was observed with a significant effect on both daily outpatient and inpatient visits for total respiratory diseases at a relative risk of 1.561 (1.161, 2.098) and 1.276 (1.027, 1.585), respectively (both P < 0.05), while the results of inpatients became insignificant with the adjustment for CO and O3. The attributable fractions in outpatients and inpatients were as follows: total respiratory diseases (24.43% and 18.69%), influenza and pneumonia (31.54% and 17.33%), URTI (23.03% and 32.91%), LRTI (37.49% and 30.00%), asthma (9.83% and 3.39%), and COPD (30.67% and 10.65%). Stratified analyses showed that children ≤5 years old were more susceptible to moderate heat than older participants.

CONCLUSIONS

In conclusion, our results indicated moderate heat increase the risk of daily outpatient and inpatient visits for respiratory diseases, especially among children under the age of 5.

Nationwide Geospatial Analysis to Identify Variations in Primary Cardiovascular Risk in Ethiopia

BACKGROUND

Cardiovascular disease (CVD) varies across regions due to socioeconomic, cultural, lifestyle, healthcare access, and environmental factors.

OBJECTIVE

To find geographical variations in 10-year primary CVD risk and assess the impact of contextual factors on CVD risk.

METHOD

Data from 2658 Ethiopians aged 40 to 69 years with no previous CVD who participated in a nationally representative World Health Organization (WHO) STEPS survey in 2015 were included in the analysis. The mean 10-year CVD risk for 450 enumeration areas (EA) was used to identify spatial autocorrelation (using Global Moran's I) and CVD hot spots (using getas-Ord Gi*). Geographically Weighted Regression (GWR) analysis quantified the relationship between mean 10-year CVD risk and climate-related factors across areas.

RESULT

The spatial autocorrelation analysis identified significant spatial variation in the 10-year CVD risk at the EA level, with a global Moran's I value of 0.016. Statistically significant hot spot areas with 10-year CVD risk were identified in Addis Ababa (the capital), Benishangul Gumuz, SNNPR (Southern Nations, Nationalities, and Peoples' Region), Amhara, Afar, Oromia, and Hareri regions. In a multivariable GWR analysis, average water vapor pressure was a statistically significant explanatory variable for the geographical variations in 10-year CVD risk.

CONCLUSION

Hot spot areas for 10-year CVD risk were identified across numerous country regions rather than concentrated in a specific region. Alongside these hot spot areas, regions with a higher annual water vapor pressure (humidity) were identified as geographical targets for CVD prevention.

Temperature modifies the association between air pollution and respiratory disease mortality in Cape Town, South Africa

The aim of this 10-year study was to investigate whether and how temperature modifies the association between daily ambient PM10, NO2, SO2 air pollution and daily respiratory disease mortality in Cape Town. A time-stratified case-crossover epidemiological design was applied. Susceptibility by sex and age groups (15-64 years and ≥65 years) was also investigated. On days with medium Tapp levels, NO2 displayed a stronger association with respiratory mortality than PM10 or SO2. Females appeared to be more susceptible to NO2 at medium Tapp levels to males. The 15-64-year-old age group seemed to be more vulnerable to NO2 and PM10 at medium Tapp levels compared to the elderly (≥65 years). At high Tapp levels, females were more susceptible to PM10. The 15-64-year-old group were more vulnerable to NO2 and SO2. The results can be used in present-day early warning systems and in risk assessments to estimate the impact of increased air pollution and temperature.

Long-term exposure to summer specific humidity and cardiovascular disease hospitalizations in the US Medicare population

INTRODUCTION

Most climate-health studies focus on temperature; however, less is known about health effects of exposure to atmospheric moisture. Humid air limits sweat evaporation from the body and can in turn exert strain on the cardiovascular system. We evaluated associations of long-term exposure to summer specific humidity with cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization.

METHODS

We built an open cohort consisting of ∼63 million fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US (2000-2016). We assessed zip code level summer average specific humidity and specific humidity variability, based on daily estimates from the Gridded Surface Meteorological dataset (∼4km spatial resolution). To estimate associations of summer specific humidity with first CVD, CHD, and CBV hospitalization, we used Cox-equivalent Poisson models adjusted for individual and area-level socioeconomic status indicators, temperature, and winter specific humidity.

RESULTS

Higher summer average specific humidity was associated with an increased risk of CVD, CHD, and CBV hospitalization. We found hazard ratios (HRs) of 1.07 (95%CI: 1.07, 1.08) for CVD hospitalization, 1.08 (95%CI: 1.08, 1.09) for CHD hospitalization, and 1.07 (95%CI: 1.07, 1.08) for CBV hospitalization per IQR increase (4.0 g of water vapor/kg of dry air) in summer average specific humidity. Associations of summer average specific humidity were strongest for beneficiaries eligible for Medicaid and for beneficiaries with an unknown or other race. Higher summer specific humidity variability was also associated with increased risk of CVD, CHD, and CBV hospitalization. Associations were not affected by adjustment for temperature and regions of the US, as well as exclusion of potentially prevalent cases.

CONCLUSION

Long-term exposure to higher summer average specific humidity and specific humidity variability were positively associated with CVD hospitalization. As global warming could increase humidity levels, our findings are important to assess potential health impacts of climate change.

Short-term excess mortality following tropical cyclones in the United States

Knowledge of excess deaths after tropical cyclones is critical to understanding their impacts, directly relevant to policies on preparedness and mitigation. We applied an ensemble of 16 Bayesian models to 40.7 million U.S. deaths and a comprehensive record of 179 tropical cyclones over 32 years (1988-2019) to estimate short-term all-cause excess deaths. The deadliest tropical cyclone was Hurricane Katrina in 2005, with 1491 [95% credible interval (CrI): 563, 3206] excess deaths (>99% posterior probability of excess deaths), including 719 [95% CrI: 685, 752] in Orleans Parish, LA (>99% probability). Where posterior probabilities of excess deaths were >95%, there were 3112 [95% CrI: 2451, 3699] total post-hurricane force excess deaths and 15,590 [95% CrI: 12,084, 18,835] post-gale to violent storm force deaths; 83.1% of post-hurricane force and 70.0% of post-gale to violent storm force excess deaths occurred more recently (2004-2019); and 6.2% were in least socially vulnerable counties.

Extreme Temperature Events, Fine Particulate Matter, and Myocardial Infarction Mortality

BACKGROUND

Extreme temperature events (ETEs), including heat wave and cold spell, have been linked to myocardial infarction (MI) morbidity; however, their effects on MI mortality are less clear. Although ambient fine particulate matter (PM2.5) is suggested to act synergistically with extreme temperatures on cardiovascular mortality, it remains unknown if and how ETEs and PM2.5 interact to trigger MI deaths.

METHODS

A time-stratified case-crossover study of 202 678 MI deaths in Jiangsu province, China, from 2015 to 2020, was conducted to investigate the association of exposure to ETEs and PM2.5 with MI mortality and evaluate their interactive effects. On the basis of ambient apparent temperature, multiple temperature thresholds and durations were used to build 12 ETE definitions. Daily ETEs and PM2.5 exposures were assessed by extracting values from validated grid datasets at each subject's geocoded residential address. Conditional logistic regression models were applied to perform exposure-response analyses and estimate relative excess odds due to interaction, proportion attributable to interaction, and synergy index.

RESULTS

Under different ETE definitions, the odds ratio of MI mortality associated with heat wave and cold spell ranged from 1.18 (95% CI, 1.14-1.21) to 1.74 (1.66-1.83), and 1.04 (1.02-1.06) to 1.12 (1.07-1.18), respectively. Lag 01-day exposure to PM2.5 was significantly associated with an increased odds of MI mortality, which attenuated at higher exposures. We observed a significant synergistic interaction of heat wave and PM2.5 on MI mortality (relative excess odds due to interaction >0, proportion attributable to interaction >0, and synergy index >1), which was higher, in general, for heat wave with greater intensities and longer durations. We estimated that up to 2.8% of the MI deaths were attributable to exposure to ETEs and PM2.5 at levels exceeding the interim target 3 value (37.5 μg/m3) of World Health Organization air quality guidelines. Women and older adults were more vulnerable to ETEs and PM2.5. The interactive effects of ETEs or PM2.5 on MI mortality did not vary across sex, age, or socioeconomic status.

CONCLUSIONS

This study provides consistent evidence that exposure to both ETEs and PM2.5 is significantly associated with an increased odds of MI mortality, especially for women and older adults, and that heat wave interacts synergistically with PM2.5 to trigger MI deaths but cold spell does not. Our findings suggest that mitigating both ETE and PM2.5 exposures may bring health cobenefits in preventing premature deaths from MI.

The Combined Effects of Short-Term Exposure to Multiple Meteorological Factors on Unintentional Drowning Mortality: Large Case-Crossover Study

BACKGROUND

Drowning is a serious public health problem worldwide. Previous epidemiological studies on the association between meteorological factors and drowning mainly focused on individual weather factors, and the combined effect of mixed exposure to multiple meteorological factors on drowning is unclear.

OBJECTIVE

We aimed to investigate the combined effects of multiple meteorological factors on unintentional drowning mortality in China and to identify the important meteorological factors contributing to drowning mortality.

METHODS

Unintentional drowning death data (based on International Classification of Diseases, 10th Edition, codes W65-74) from January 1, 2013, to December 31, 2018, were collected from the Disease Surveillance Points System for Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces, China. Daily meteorological data, including daily mean temperature, relative humidity, sunlight duration, and rainfall in the same period were obtained from the Chinese Academy of Meteorological Science Data Center. We constructed a time-stratified case-crossover design and applied a generalized additive model to examine the effect of individual weather factors on drowning mortality, and then used quantile g-computation to estimate the joint effect of the mixed exposure to meteorological factors.

RESULTS

A total of 46,179 drowning deaths were reported in the 5 provinces in China from 2013 to 2018. In an effect analysis of individual exposure, we observed a positive effect for sunlight duration, a negative effect for relative humidity, and U-shaped associations for temperature and rainfall with drowning mortality. In a joint effect analysis of the above 4 meteorological factors, a 2.99% (95% CI 0.26%-5.80%) increase in drowning mortality was observed per quartile rise in exposure mixture. For the total population, sunlight duration was the most important weather factor for drowning mortality, with a 93.1% positive contribution to the overall effects, while rainfall was mainly a negative factor for drowning deaths (90.5%) and temperature and relative humidity contributed 6.9% and -9.5% to the overall effects, respectively.

CONCLUSIONS

This study found that mixed exposure to temperature, relative humidity, sunlight duration, and rainfall was positively associated with drowning mortality and that sunlight duration, rather than temperature, may be the most important meteorological factor for drowning mortality. These findings imply that it is necessary to incorporate sunshine hours and temperature into early warning systems for drowning prevention in the future.

Increased emergency cases for out-of-hospital cardiac arrest due to cold spells in Shenzhen, China

Cold spells have been associated with specific diseases. However, there is insufficient scientific evidence on the effects of cold spells on out-of-hospital cardiac arrest (OHCA). Data on OHCA cases and on meteorological factors and air pollutants were collected between 2013 and 2020. We adopted a quasi-Poisson generalized additive model with a distributed lag nonlinear model (DLNM) to estimate the effect of cold spells on daily OHCA incidence. Backward attributable risk within the DLNM framework was calculated to quantify the disease burden. We compared the effects and OHCA burden of cold spells using nine definitions. The risks of different cold spells on OHCA increased at higher intensities and longer durations. Based on Akaike's information criterion for the quasi-Poisson regression model and the attributable risk, the optimal cold spell was defined as a period in the cold month when the daily mean temperature was below the 10th percentile of the temperature distribution in the study period for at least 2 days. The single-day effect of the optimal cold spell on OHCA occurred immediately and lasted for approximately 1 week. The maximum single-day effect was 1.052 (95% CI: 1.018-1.087) at lag0, while the maximum cumulative effect was 1.433 (95% CI:1.148-1.788) after a 14-day lag. Men were more susceptible to cold spells. Young and middle-aged people were affected by cold spells similar to the elderly. Cold spells can increase the risk of OHCA with an approximately 1-week lag effect. Health regulators should take more targeted measures to protect susceptible populations during cold weather.

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.

Web-Based Data to Quantify Meteorological and Geographical Effects on Heat Stroke: Case Study in China

Heat stroke is a serious heat-related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large-scale relationship between heat stroke and meteorological factors is still unclear. This work aims to clarify the potential relationship between meteorological variables and heat stroke, and quantify the meteorological threshold that affected the severity of heat stroke. We collected daily heat stroke search index (HSSI) and meteorological data for the period 2013-2020 in 333 Chinese cities to analyze the relationship between meteorological variables and HSSI using correlation analysis and Random forest (RF) model. Temperature and relative humidity (RH) accounted for 62% and 9% of the changes of HSSI, respectively. In China, cases of heat stroke may start to occur when temperature exceeds 36°C and RH exceeds 58%. This threshold was 34.5°C and 79% in the north of China, and 36°C and 48% in the south of China. Compared to RH, the threshold of temperature showed a more evident difference affected by altitude and distance from the ocean, which was 35.5°C in inland cities and 36.5°C in coastal cities; 35.5°C in high-altitude cities and 36°C in low-altitude cities. Our findings provide a possible way to analyze the interaction effect of meteorological variables on heat-related illnesses, and emphasizes the effects of geographical environment. The meteorological threshold quantified in this research can also support policymaker to establish a better meteorological warning system for public health.

Short-Term Effects of Apparent Temperature on Cause-Specific Mortality in the Urban Area of Thessaloniki, Greece

Although there is a growing interest in the association between ambient temperatures and mortality, little evidence is available for Thessaloniki, the second largest city of Greece. In this study, we present an assessment of the effects of temperature on daily mortality from 2006 to 2016 in the urban area of Thessaloniki, by describing the exposure-lag-response association between temperature and cause-specific mortality with the use of a distributed lag non-linear model (DLNM). A J-shaped relationship was found between temperature and mortality. The highest values of risk were evident for respiratory (RR > 10) and cardiovascular causes (RR > 3), probably due to the fact that health status of individuals with chronic respiratory and cardiovascular diseases rapidly deteriorates during hot periods. Cold effects had longer lags of up to 15 days, whereas heat effects were short-lived, up to 4 days. Percentage change in all- and cause-specific mortality per 1 °C change above and below Minimum Mortality Temperature showed a larger increase for all-cause mortality in heat (1.95%, 95% CI: 1.07–2.84), in contrast to a smaller increase in cold (0.54%, 95% CI: 0, 1.09). Overall, 3.51% of all-cause deaths were attributable to temperature, whereas deaths attributed to heat (2.34%) were more than deaths attributed to cold (1.34%). The findings of this study present important evidence for planning public-health interventions, to reduce the health impact of extreme temperatures.

Correlating indoor and outdoor temperature and humidity in a sample of buildings in tropical climates

The incidence of several respiratory viral infections has been shown to be related to climate. Because humans spend most of their time indoors, measures of indoor climate, rather than outdoor climate, may be better predictors of disease incidence and transmission. Therefore, understanding the relationship between indoor and outdoor climate will help illuminate their influence on the seasonality of diseases caused by respiratory viruses. Indoor-outdoor relationships between temperature and humidity have been documented in temperate regions, but little information is available for tropical regions, where seasonal patterns of respiratory viral diseases differ. We have examined indoor-outdoor correlations of temperature, relative humidity (RH), and absolute humidity (AH) over a 1-year period in each of seven tropical cities. Across all cities, the average monthly indoor temperature was 25 ± 3°C (mean ± standard deviation) with a range of 20-30°C. The average monthly indoor RH was 66 ± 9% with a range of 50-78%, and the average monthly indoor AH was 15 ± 3 g/m³ with a range of 10-23 g/m³ . Indoor AH and RH were linearly correlated with outdoor AH when the air conditioning (AC) was off, suggesting that outdoor AH may be a good proxy of indoor humidity in the absence of AC. All indoor measurements were more strongly correlated with outdoor measurements as distance from the equator increased. Such correlations were weaker during the wet season, especially when AC was in operation. These correlations will provide insight for assessing the seasonality of respiratory viral infections using outdoor climate data, which is more widely available than indoor data, even though transmission of these diseases mainly occurs indoors.

Associations of apparent temperature with acute cardiac events and subtypes of acute coronary syndromes in Beijing, China

Limited evidence is available on apparent temperature (AT) and hospital admissions for acute cardiac events. We examined the associations of AT with admissions for acute cardiac events and acute coronary syndrome (ACS), and explored the effect difference between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction ACS (NSTE-ACS). Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-admission associations. Stratified analyses were performed by gender and age-groups for acute cardiac events. A total of 11,657 acute cardiac events admissions were collected from hospital-based chest pain centers in Beijing, during 2017-2019. The single day effect of low AT (- 11 °C, 2.5th percentile) appeared on the 2nd day and persisted until the 11th day, with estimated relative risk (RR) ranging from 1.44 (95% CI: 1.159, 1.790) to 1.084 (95% CI: 1.022, 1.150) for acute cardiac events and from 1.034 (95% CI: 1.010, 1.059) to 1.006 (95% CI: 1.000, 1.011) for ACS. The single day effect of high AT (34 °C, 97.5th percentile) was only observed on the current day. The cold effect on acute cardiac events was more pronounced among female and older patients. The cumulative effect of high AT on STEMI admissions and low AT on NSTE-ACS reached a peak RR peak of 2.545 (95% CI: 1.016, 6.375) and 3.71 (95% CI: 1.315, 10.469) on lag 0-6 days, respectively. Both high and low ATs were associated with increased risk of acute cardiac events and ACS admissions. STEMI admissions may be more sensitive to high AT while NSTE-ACS to low AT.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Knowledge, Attitudes, and Practices of Military Personnel Regarding Heat-Related Illness Risk Factors: Results of a Chinese Cross-Sectional Study

Background: Military personnel are widely exposed to risk factors for heat-related illnesses. Knowledge, attitudes, and practices (KAP) are three of the most important means by which to prevent such illnesses, but there has been a lack of investigations into and correlation analyses of KAP. This study aimed to explore the heat-related KAP of military personnel in China. Methods: We conducted a cross-sectional study (June 1-25, 2019). A total of 646 military personnel were recruited from two Chinese Navy troops in the tropical zone and one troop in the temperate zone. We collected data on demographic characteristics and KAP scores using questionnaires. Univariate analysis and Scheffe's method were used for data analyses. Results: The mean KAP scores were 10.37 (range = 3-13, standard deviation = 1.63) for knowledge (K-score), 7.76 (range = 0-16, SD = 2.65) for attitudes (A-score), and 3.80 (range = 1-6, SD = 1.12) for practices (P-score). There were noticeable differences in mean K-score according to age, military rank, and educational level (P < 0.05). Participants from the tropical zone had higher A-scores (P < 0.05) and higher P-scores (P < 0.001) than those from the temperate zone. Additionally, participants with relevant experience also had higher A-scores (P < 0.05) than those without such experience. Conclusions: Military personnel's awareness of preventive and first-aid measures against heat-related illnesses need to be strengthened. It will be very important to develop educational programmes and enrich systematic educational resources to raise this awareness.

The Mortality Effect of Apparent Temperature: A Multi-City Study in Asia

(1) Background: The health effect of temperature has become a rising public health topic. The objective of this study is to assess the association between apparent temperature and non-accidental deaths, and the mortality burden attributed to cold and heat temperature; (2) Methods: The daily data on temperature and deaths were collected from 10 cities in Thailand, Korea and China. We fitted a time-series regression with a distributed lag nonlinear model (DLNM) to derive the health risk of temperature for each city and then pooled them to get the overall cumulative risk by multivariate meta-analysis. Additionally, we calculated the attributable fraction of deaths for heat and cold, which was defined as temperatures above and below minimum-mortality temperature (MMT); (3) Results: There are regional heterogeneities in the minimum mortality percentiles (MMP) and attributable fractions for different countries. The MMP varied from about the 5-10th percentile in Thailand to 63-93rd percentile in China and Korea. The attributable fractions of the total deaths due to short-term exposure to temperature in Asia is 7.62%, of which the cold effect (6.44%) is much higher than the heat effect (1.18%); (4) Conclusions: Our study suggested that apparent temperature was associated with an increase in non-accidental mortality. Most of the temperature-related mortality burden was attributable to cold, except for Thailand.

Effect of extreme hot and cold weather on cause-specific hospitalizations in Sweden: A time series analysis

Considering that several meteorological variables can contribute to weather vulnerability, the estimation of their synergetic effects on health is particularly useful. The spatial synoptic classification (SSC) has been used in biometeorological applications to estimate the effect of the entire suite of weather conditions on human morbidity and mortality. In this study, we assessed the relationships between extremely hot and dry (dry tropical plus, DT+) and hot and moist (moist tropical plus, MT+) weather types in summer and extremely cold and dry (dry polar plus, DP+) and cold and moist (moist polar, MP+) weather types in winter and cardiovascular and respiratory hospitalizations by age and sex. Time-series quasi-Poisson regression with distributed lags was used to assess the relationship between oppressive weather types and daily hospitalizations over 14 subsequent days in the extended summer (May to August) and 28 subsequent days during the extended winter (November to March) over 24 years in 4 Swedish locations from 1991 to 2014. In summer, exposure to hot weather types appeared to reduce cardiovascular hospitalizations while increased the risk of hospitalizations for respiratory diseases, mainly related to MT+. In winter, the effect of cold weather on both cause-specific hospitalizations was small; however, MP+ was related to a delayed increase in cardiovascular hospitalizations, whilst MP+ and DP + increased the risk of hospitalizations due to respiratory diseases. This study provides useful information for the staff of hospitals and elderly care centers who can help to implement protective measures for patients and residents. Also, our results could be helpful for vulnerable people who can adopt protective measures to reduce health risks.

Higher Temperatures, Higher Solar Radiation, and Less Humidity Is Associated With Poor Clinical and Laboratory Outcomes in COVID-19 Patients

Background: The COVID-19 pandemic varies between countries, with suggestions that weather might contribute to the transmission mode, disease presentation, severity, and clinical outcomes. Yet the exact link between climate and COVID-19 is still not well-explored. Objectives: This study aimed to evaluate the effect of hot geographical region weather [like United Arab Emirates (UAE)] on COVID-19 clinical profile and outcomes. Temperature, wind speed, cloud cover, precipitation, and other weather-related variables were studied concerning COVID-19 patients outcomes and laboratory results. Methodology: A total of 434 COVID-19 positive patients admitted between January and June 2020, were recruited from Al Kuwait Hospital, Dubai, UAE. Temperature, wind speed, cloud cover, and precipitation rate were retrieved from history+ for the day when COVID-19 patients presented to the hospital. These weather parameters were correlated with COVID-19 clinical and laboratory parameters. Results: Our results showed that patients needed admission in days with higher temperatures, higher solar radiation, and less humidity were associated with higher deaths. This association can be linked to the association of these weather parameters with age at diagnosis; higher C-reactive protein (CRP), neutrophil count, white cell count (WCC), aspartate aminotransferase (AST), and alkaline phosphatase (ALP); and lower lymphocyte count, estimated glomerular filtration rate (eGFR), hemoglobin (Hb), Na, and albumin, all of which are considered poor prognostic factors for COVID-19. Conclusion: Our study highlighted the importance of weather-related variables on the dynamics of mortality and clinical outcomes of COVID-19. The hot weather might makes some people, especially those with comorbidities or older ages, develop aggressive inflammation that ends up with complications and mortality.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID-19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below 0 °C, 12 cities had average AH below 4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition, we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission.

Temperature as a modifier of the effects of air pollution on cardiovascular disease hospital admissions in Cape Town, South Africa

Climate change and air pollution are two independent risk factors to cardiovascular diseases (CVD). Few studies investigated their interaction and potential effect modification of one another in developing countries. Individual level CVD hospital admission (ICD10: I00-I99) data for 1 January 2011 to 31 October 2016 were obtained from seven private hospitals in Cape Town. NO₂, SO₂, PM₁₀, temperature and relative humidity data were obtained from the South African Weather Services and the City of Cape Town. A case-crossover epidemiological study design and conditional logistic regression model were applied. Various cut-off values were applied to classify cold and warm days. In total, 54,818 CVD hospital admissions were included in the study. In general, on warm and cold days the 15-64 years old group was more at risk for CVD hospitalization with increasing air pollution levels compared to all ages combined or the ≥ 65 years old group. Females appeared to be more at risk than males with increasing PM₁₀ levels. In contrast, males were more vulnerable to the effects of NO₂ and SO₂ than females. The study showed the modification effect of temperature on air pollution associated with CVD hospital admissions. The consideration of such interaction will help in policy making and public health interventions dealing with climate change-related health risks.

Heat wave intensity and daily mortality in four of the largest cities of Spain

In the current context of climate change, heat waves have become a significant problem for human health. This study assesses the effects of heat wave intensity on mortality (natural, respiratory and cardiovascular causes) in four of the largest cities of Spain (Barcelona, Bilbao, Madrid and Seville) during the period between 1990 and 2014. To model the heat wave severity the Excess Heat Factor (EHF) was used. The EHF is a two-component index. The first is the comparison of the three-day average daily mean temperature with the 95th percentile. The second component is a measure of the temperatures reached during the three-day period compared with the recent past (the previous 30 days). The city-specific exposure-response curves showed a non-linear J-shaped relationship between mortality and the EHF. Overall city-specific mortality risk estimates in natural causes for 1st vs. 99th percentile increases range from the highest mortality risk with 2.73 (95% CI: 2.34-3.18) in Seville to a risk of 1.78 (95% CI: 1.62-1.97) and 1.78 (95% CI: 1.45-2.19) in Barcelona and Bilbao, respectively. When we compare our results with risk estimates for the analyzed Spanish cities in other studies, the heat wave related mortality risks seem to be clearly higher. Furthermore, it has been demonstrated that different heat wave days of the same event do not present the same degree of severity/intensity. Thus, the intensity of a heat wave is an important mortality risk indicator during heat wave days. Due to the low number of studies on the EHF as a heat wave intensity indicator and heat-related mortality and morbidity, further research is required to validate its application in other geographic areas and focus populations.

Effective analysis of a community-based intervention during heat waves to improve knowledge, attitude and practice in a population in Licheng District, Jinan City, China

Background

Intervention strategies that focus on coping with continuous heat wave threats have been implemented in many countries. Despite these efforts, we still lack evidence concerning intervention efficacy. A Heat Wave Intervention Program (HWIP) that impacts knowledge, attitude and practice (KAP) was designed, and its effectiveness during heat waves was evaluated.

Methods

A stratified two-stage probability proportion to size sampling method was employed to analyze an intervention group and a control group. Two cross-sectional surveys, which included questions about heat waves in 2014 and 2015, were analyzed using difference-in-difference (DID) analysis.

Results

Mean KAP scores among participants with different demographic characteristics in the intervention group were higher in 2015 than those in 2014. Further analysis by DID found that implementing interventions was positively associated with knowledge (ß = 0.387, P < 0.001) and attitude (ß = 0.166, P < 0.01).

Conclusion

Intervention measures can significantly promote levels of knowledge and attitude. However, as the practice level, most of the sub-groups showed no significant differences for net values between in the intervention group and control group. A cost-benefit analysis was suggested as future work to check the effectiveness of the program. Therefore, further improvement measures should be targeted towards the populations to enable them to effectively cope with the heat waves.

Estimation of heat-related morbidity from weather data: A computational study in three prefectures of Japan over 2013-2018

In recent years, the rates of heat-related morbidity and mortality have begun to increase with the increase in global warming; in this context, it is noteworthy that the number of patients transported by ambulance in heat-related cases in Japan reached 95,137 in 2018. The estimation of heat-related morbidity forms a key factor in proposing and implementing suitable intervention strategies and ambulance availability and arrangements. Heat-related morbidity is known to be fairly correlated to metrics related to ambient conditions, thus necessitating the exploration of new metrics to more accurately estimate morbidity. In this study, we use an integrated computational technique relating to thermodynamics and thermoregulation to estimate daily peak core temperature elevation and daily water loss, which are linked to heat-related illnesses, from weather data of three different prefectures in Japan (Tokyo, Osaka, and Aichi). The correlations of the computed core temperature elevation and water loss as well as conventional ambient conditions are investigated in terms of number of patients suffering from heat-related illnesses transported by ambulance from 2013 to 2018. The estimated water loss per the proposed computation yields better correlation with the number of patients transported by ambulance. In particular, the weight-sum daily water loss for two to three successive days is found to be an important metric for predicting the number of patients transported by ambulance. For the same ambient conditions, morbidity is found to decrease to 0.4 owing to heat adaption at the end of summer (60 days) as compared with that at the end of the rainy season. Thus, the weighted sum of water loss and daily average ambient temperature for successive days can be used as better metrics than conventional weather data for the application of intervention strategies and planning of ambulance arrangements for heat-related morbidity.

The Role of Humidity in Associations of High Temperature with Mortality: A Multicountry, Multicity Study

BACKGROUND

There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature.

OBJECTIVES

We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset.

METHODS

In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques.

RESULTS

Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1-3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly.

DISCUSSION

The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.

Use of earth observations for temperature exposure assessment in epidemiological studies

PURPOSE OF REVIEW

Low, high, extreme, and variable temperatures have been linked to multiple adverse health outcomes, particularly among the elderly and children. Recent models incorporating satellite remote sensing data have mitigated several limitations of previous studies, improving exposure assessment. This review focuses on these new temperature exposure models and their application in epidemiological studies.

RECENT FINDINGS

Satellite observations of land surface temperature have been used to model air temperature across large spatial areas at high spatiotemporal resolutions. These models enable exposure assessment of entire populations and have been shown to reduce error in exposure estimates, thus mitigating downward bias in health effect estimates.

SUMMARY

Satellite-based models improve our understanding of spatiotemporal variation in temperature and the associated health effects. Further research should focus on improving the resolution of these models, especially in urban areas, and increasing their use in epidemiological studies of direct temperature exposure and vector-borne diseases.

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

Despite the active applications of thermal comfort indices for heat wave definitions, there is lack of evaluation for the impact of extended days of high temperature on health outcomes using many of the indices. This study compared the impact of heat waves on health outcomes among different heat wave definitions based on thermal comfort and air temperature. We compared heat waves in South Korea (cities and provinces) for the warm season for 2011-2014, using air temperature, heat index (HI), and web-bulb globe temperature (WBGT). Heat waves were defined as days with daily maximum values of each index at a specified threshold (literature-based, the 90th and 95th percentiles) or above. Distributed lag non-linear models and meta-analysis were used to estimate risk of mortality and hospitalization for all-causes, cardiovascular causes, respiratory causes and heat disorders during heat wave days compared to non-heat wave days. WBGT identified 1.15 times longer maximum heat wave duration for the study periods than air temperature when the thresholds were based on 90th and 95th percentiles. Over the study period, for heat waves defined by WBGT and HI, the Southwestern region showed the highest total number of heat wave days, whereas for air temperature the longest heat wave days were identified in the southeastern region. The highest and most significant impact of heat waves were found by WBGT for hospitalization from heat disorders (Relative risk = 2.959, 95% CI: 1.566-5.594). In sensitivity analyses using different structure of lags and temperature metrics (e.g., daily mean and minimum), the impacts of heat waves on most health outcomes substantially increased by using WBGT for heat wave definitions. As a result, WBGT and its thresholds can be used to relate heat waves and heat-related diseases to improve the prevention effectiveness of heat wave warnings and give informative health guidelines according to the range of WBGT thresholds.

Increasing Probability of Heat-Related Mortality in a Mediterranean City Due to Urban Warming

Extreme temperatures impose thermal stress on human health, resulting in increased hospitalizations and mortality rate. We investigated the circulatory and respiratory causes of death for the years 2007 to 2014 inclusive for the urban and rural areas of Nicosia, Cyprus under urban heatwave and non-heatwave conditions. Heatwaves were defined as four or more consecutive days with mean urban daily temperature over the 90th percentile threshold temperature of the eight investigated years. Lag period of adverse health effects was found to be up to three days following the occurrence of high temperatures. The relative risk (RR) for mortality rate under heatwave and non-heatwave conditions was found taking in consideration the lag period. The results showed the increase of mortality risk particularly for men of ages 65⁻69 (RR = 2.38) and women of ages 65⁻74 (around RR = 2.54) in the urban area, showing that women were more vulnerable to heat extremities. High temperatures were also associated with high ozone concentrations, but they did not impose an excess risk factor, as they did not reach extreme values. This analysis highlights the importance of preparing for potential heat related health impacts even in Cyprus, which is an island with frequent heatwaves.

Seasonal Influenza Infections and Cardiovascular Disease Mortality

IMPORTANCE

Cardiovascular deaths and influenza epidemics peak during winter in temperate regions.

OBJECTIVES

To quantify the temporal association between population increases in seasonal influenza infections and mortality due to cardiovascular causes and to test if influenza incidence indicators are predictive of cardiovascular mortality during the influenza season.

DESIGN, SETTING, AND PARTICIPANTS

Time-series analysis of vital statistics records and emergency department visits in New York City, among cardiovascular deaths that occurred during influenza seasons between January 1, 2006, and December 31, 2012. The 2009 novel influenza A(H1N1) pandemic period was excluded from temporal analyses.

EXPOSURES

Emergency department visits for influenza-like illness, grouped by age (≥0 years and ≥65 years) and scaled by laboratory surveillance data for viral types and subtypes, in the previous 28 days.

MAIN OUTCOMES AND MEASURES

Mortality due to cardiovascular disease, ischemic heart disease, and myocardial infarction.

RESULTS

Among adults 65 years and older, who accounted for 83.0% (73 363 deaths) of nonpandemic cardiovascular mortality during influenza seasons, seasonal average influenza incidence was correlated year to year with excess cardiovascular mortality (Pearson correlation coefficients ≥0.75, P ≤ .05 for 4 different influenza indicators). In daily time-series analyses using 4 different influenza metrics, interquartile range increases in influenza incidence during the previous 21 days were associated with an increase between 2.3% (95% CI, 0.7%-3.9%) and 6.3% (95% CI, 3.7%-8.9%) for cardiovascular disease mortality and between 2.4% (95% CI, 1.1%-3.6%) and 6.9% (95% CI, 4.0%-9.9%) for ischemic heart disease mortality among adults 65 years and older. The associations were most acute and strongest for myocardial infarction mortality, with each interquartile range increase in influenza incidence during the previous 14 days associated with mortality increases between 5.8% (95% CI, 2.5%-9.1%) and 13.1% (95% CI, 5.3%-20.9%). Out-of-sample prediction of cardiovascular mortality among adults 65 years and older during the 2009-2010 influenza season yielded average estimates with 94.0% accuracy using 4 different influenza metrics.

CONCLUSIONS AND RELEVANCE

Emergency department visits for influenza-like illness were associated with and predictive of cardiovascular disease mortality. Retrospective estimation of influenza-attributable cardiovascular mortality burden combined with accurate and reliable influenza forecasts could predict the timing and burden of seasonal increases in cardiovascular mortality.

Assessing Heat Stress and Health among Construction Workers in a Changing Climate: A Review

Construction workers are at an elevated risk of heat stress, due to the strenuous nature of the work, high temperature work condition, and a changing climate. An increasing number of workers are at risk, as the industry’s growth has been fueled by high demand and vast numbers of immigrant workers entering into the U.S., the Middle East and Asia to meet the demand. The risk of heat-related illnesses is increased by the fact that little to no regulations are present and/or enforced to protect these workers. This review recognizes the issues by summarizing epidemiological studies both in the U.S. and internationally. These studies have assessed the severity with which construction workers are affected by heat stress, risk factors and co-morbidities associated with heat-related illnesses in the construction industry, vulnerable populations, and efforts in implementing preventive measures.

The effects of hot nights on mortality in Barcelona, Spain

Heat-related effects on mortality have been widely analyzed using maximum and minimum temperatures as exposure variables. Nevertheless, the main focus is usually on the former with the minimum temperature being limited in use as far as human health effects are concerned. Therefore, new thermal indices were used in this research to describe the duration of night hours with air temperatures higher than the 95% percentile of the minimum temperature (hot night hours) and intensity as the summation of these air temperatures in degrees (hot night degrees). An exposure-response relationship between mortality due to natural, respiratory, and cardiovascular causes and summer night temperatures was assessed using data from the Barcelona region between 2003 and 2013. The non-linear relationship between the exposure and response variables was modeled using a distributed lag non-linear model. The estimated associations for both exposure variables and mortality shows a relationship with high and medium values that persist significantly up to a lag of 1-2 days. In mortality due to natural causes, an increase of 1.1% per 10% (CI95% 0.6-1.5) for hot night hours and 5.8% per each 10° (CI95% 3.5-8.2%) for hot night degrees is observed. The effects of hot night hours reach their maximum with 100% and lead to an increase by 9.2% (CI95% 5.3-13.1%). The hourly description of night heat effects reduced to a single indicator in duration and intensity is a new approach and shows a different perspective and significant heat-related effects on human health.

Exploring the association between heat and mortality in Switzerland between 1995 and 2013

Designing effective public health strategies to prevent adverse health effect of hot weather is crucial in the context of global warming. In Switzerland, the 2003 heat have caused an estimated 7% increase in all-cause mortality. As a consequence, the Swiss Federal Office of Public Health developed an information campaign to raise public awareness on heat threats. For a better understanding on how hot weather affects daily mortality in Switzerland, we assessed the effect of heat on daily mortality in eight Swiss cities and population subgroups from 1995 to 2013 using different temperature metrics (daily mean (Tmean), maximum (Tmax), minimum (Tmin) and maximum apparent temperature (Tappmax)), and aimed to evaluate variations of the heat effect after 2003 (1995-2002 versus 2004-2013). We applied conditional quasi-Poisson regression models with non-linear distributed lag functions to estimate temperature-mortality associations over all cities (1995-2013) and separately for two time periods (1995-2002, 2004-2013). Relative risks (RR) of daily mortality were estimated for increases in temperature from the median to the 98th percentile of the warm season temperature distribution. Over the whole time period, significant temperature-mortality relationships were found for all temperature indicators (RR (95% confidence interval): Tappmax: 1.12 (1.05; 1.18); Tmax: 1.15 (1.08-1.22); Tmean: 1.16 (1.09-1.23); Tmin 1.23 (1.15-1.32)). Mortality risks were higher at the beginning of the summer, especially for Tmin. In the more recent time period, we observed a non-significant reduction in the effect of high temperatures on mortality, with the age group > 74 years remaining the population at highest risk. High temperatures continue to be a considerable risk factor for human health in Switzerland after 2003. More effective public health measures targeting the elderly should be promoted with increased attention to the first heat events in summer and considering both high day-time and night-time temperatures.

Impacts of cold weather on all-cause and cause-specific mortality in Texas, 1990-2011

Cold weather was estimated to account for more than half of weather-related deaths in the U.S. during 2006-2010. Studies have shown that cold-related excessive mortality is especially relevant with decreasing latitude or in regions with mild winter. However, only limited studies have been conducted in the southern U.S. The purpose of our study is to examine impacts of cold weather on mortality in 12 major Texas Metropolitan Areas (MSAs) for the 22-year period, 1990-2011. Our study used a two-stage approach to examine the cold-mortality association. We first applied distributed lag non-linear models (DLNM) to 12 major MSAs to estimate cold effects for each area. A random effects meta-analysis was then used to estimate pooled effects. Age-stratified and cause-specific mortalities were modeled separately for each MSA. Most of the MSAs were associated with an increased risk in mortality ranging from 0.1% to 5.0% with a 1 °C decrease in temperature below the cold thresholds. Higher increased mortality risks were generally observed in MSAs with higher average daily mean temperatures and lower latitudes. Pooled effect estimate was 1.58% (95% Confidence Interval (CI) [0.81, 2.37]) increase in all-cause mortality risk with a 1 °C decrease in temperature. Cold wave effects in Texas were also examined, and several MSAs along the Texas Gulf Coast showed statistically significant cold wave-mortality associations. Effects of cold on all-cause mortality were highest among people over 75 years old (1.86%, 95% CI [1.09, 2.63]). Pooled estimates for cause-specific mortality were strongest in myocardial infarction (4.30%, 95% CI [1.18, 7.51]), followed by respiratory diseases (3.17%, 95% CI [0.26, 6.17]) and ischemic heart diseases (2.54%, 95% CI [1.08, 4.02]). In conclusion, cold weather generally increases mortality risk significantly in Texas, and the cold effects vary with MSAs, age groups, and cause-specific deaths.

Heat effects of ambient apparent temperature on all-cause mortality in Cape Town, Durban and Johannesburg, South Africa: 2006-2010

Due to climate change, an increase of 3-4°C in ambient temperature is projected along the South African coast and 6-7°C inland during the next 80years. The objective of this study was to investigate the association between daily ambient apparent temperature (Tapp) and daily all-cause non-accidental mortality (hereafter mortality) in Cape Town, Durban and Johannesburg during a 5-year study period (2006-2010). Susceptibility by sex and age groups (<15years, 15-64years and ≥65years) was also investigated. The associations were investigated with the time-stratified case-crossover epidemiological design. Models were controlled for PM₁₀, public holidays and influenza epidemics. City-specific Tapp thresholds were determined using quasi-Poisson generalised additive models. The pooled estimates by sex and age groups were determined in meta-analyses. The city-specific Tapp thresholds were 18.6°C, 24.8°C and 18.7°C, respectively for Cape Town, Durban and Johannesburg. A 3.3%, 2.6% and 2.8% increase in mortality per IQR increase in Tapp (lag0-1) was observed in Cape Town, Durban and Johannesburg, respectively above the city-specific thresholds. The elderly were more at risk in Cape Town and Johannesburg. No difference in risk was observed for males and females in the three cities. In the meta-analysis an overall significant increase of 0.9% in mortality per 1°C increase in Tapp (lag0-1) was observed for all age groups combined in the three cities. For the ≥65year group a significant increase of 2.1% in mortality was observed. In conclusion, the risks for all age groups combined and the elderly are similar to those reported in studies from developed and developing countries. The results can be used in present-day early warning systems and in risk assessments to estimate the impact of increased Tapp in the country due to climate change. Future research should investigate the association between Tapp and cause-specific mortality and also morbidity.

Delineation of Spatial Variability in the Temperature-Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

BACKGROUND

Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision.

OBJECTIVES

We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada.

METHODS

Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables.

RESULTS

The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas.

CONCLUSIONS

Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75; http://dx.doi.org/10.1289/EHP224.

Iterative management of heat early warning systems in a changing climate

Extreme heat is a leading weather-related cause of morbidity and mortality, with heat exposure becoming more widespread, frequent, and intense as climates change. The use of heat early warning and response systems (HEWSs) that integrate weather forecasts with risk assessment, communication, and reduction activities is increasingly widespread. HEWSs are frequently touted as an adaptation to climate change, but little attention has been paid to the question of how best to ensure effectiveness of HEWSs as climates change further. In this paper, we discuss findings showing that HEWSs satisfy the tenets of an intervention that facilitates adaptation, but climate change poses challenges infrequently addressed in heat action plans, particularly changes in the onset, duration, and intensity of dangerously warm temperatures, and changes over time in the relationships between temperature and health outcomes. Iterative management should be central to a HEWS, and iteration cycles should be of 5 years or less. Climate change adaptation and implementation science research frameworks can be used to identify HEWS modifications to improve their effectiveness as temperature continues to rise, incorporating scientific insights and new understanding of effective interventions. We conclude that, at a minimum, iterative management activities should involve planned reassessment at least every 5 years of hazard distribution, population-level vulnerability, and HEWS effectiveness.

Susceptibility to Heat-Related Fluid and Electrolyte Imbalance Emergency Department Visits in Atlanta, Georgia, USA

Identification of populations susceptible to heat effects is critical for targeted prevention and more accurate risk assessment. Fluid and electrolyte imbalance (FEI) may provide an objective indicator of heat morbidity. Data on daily ambient temperature and FEI emergency department (ED) visits were collected in Atlanta, Georgia, USA during 1993-2012. Associations of warm-season same-day temperatures and FEI ED visits were estimated using Poisson generalized linear models. Analyses explored associations between FEI ED visits and various temperature metrics (maximum, minimum, average, and diurnal change in ambient temperature, apparent temperature, and heat index) modeled using linear, quadratic, and cubic terms to allow for non-linear associations. Effect modification by potential determinants of heat susceptibility (sex; race; comorbid congestive heart failure, kidney disease, and diabetes; and neighborhood poverty and education levels) was assessed via stratification. Higher warm-season ambient temperature was significantly associated with FEI ED visits, regardless of temperature metric used. Stratified analyses suggested heat-related risks for all populations, but particularly for males. This work highlights the utility of FEI as an indicator of heat morbidity, the health threat posed by warm-season temperatures, and the importance of considering susceptible populations in heat-health research.

Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities

BACKGROUND

Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat-mortality relationships.

OBJECTIVES

We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.

METHODS

Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.

RESULTS

In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature-mortality relationships were associated with maximum temperature, although mean temperature results were comparable.

CONCLUSIONS

There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature-mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.

CITATION

Davis RE, Hondula DM, Patel AP. 2016. Temperature observation time and type influence estimates of heat-related mortality in seven U.S. cities. Environ Health Perspect 124:795-804; http://dx.doi.org/10.1289/ehp.1509946.

A comparison of urban heat islands mapped using skin temperature, air temperature, and apparent temperature (Humidex), for the greater Vancouver area

Apparent temperature is more closely related to mortality during extreme heat events than other temperature variables, yet spatial epidemiology studies typically use skin temperature (also known as land surface temperature) to quantify heat exposure because it is relatively easy to map from satellite data. An empirical approach to map apparent temperature at the neighborhood scale, which relies on publicly available weather station observations and spatial data layers combined in a random forest regression model, was demonstrated for greater Vancouver, Canada. Model errors were acceptable (cross-validated RMSE=2.04 °C) and the resulting map of apparent temperature, calibrated for a typical hot summer day, corresponded well with past temperature research in the area. A comparison with field measurements as well as similar maps of skin temperature and air temperature revealed that skin temperature was poorly correlated with both air temperature (R(2)=0.38) and apparent temperature (R(2)=0.39). While the latter two were more similar (R(2)=0.87), apparent temperature was predicted to exceed air temperature by more than 5 °C in several urban areas as well as around the confluence of the Pitt and Fraser rivers. We conclude that skin temperature is not a suitable proxy for human heat exposure, and that spatial epidemiology studies could benefit from mapping apparent temperature, using an approach similar to the one reported here, to better quantify differences in heat exposure that exist across an urban landscape.

Heat effects among migrant and seasonal farmworkers: a case study in Colorado

BACKGROUND

Although migrant and seasonal farmworkers are highly vulnerable to ambient heat because of their working conditions, heat effects in this population have been rarely studied.

OBJECTIVES

We estimated effects of heat on mean daily counts of clinic visits among migrant and seasonal farmworkers by taking advantage of a unique longitudinal medical records database in the USA.

METHODS

We compiled a daily weather and clinic visit data set based on data from a health centre in Colorado for the summer of 2013. A total of 14 481 patients were included in our analysis, including 150 migrant farmworkers and 231 seasonal farmworkers with an average of 3 and 4 visits per day. We used Poisson regression to estimate the associations between heat and daily all-cause or cardiovascular-specific clinic visits among migrant or seasonal farmworkers or other stratified patients. We defined heat effects as the percentage difference in average daily counts of clinic visits, comparing 90-50th centiles of daily mean apparent temperature, a composite index accounting for both temperature and humidity. We conducted a sensitivity analysis to evaluate the impact of adjustment for ozone levels and different heat definitions.

RESULTS

Estimates of heat effects on average daily clinic visits among migrant farmworkers were positive (88.0%, 95% CI: 26.2% to 180.0%). We did not observe statistically significant associations between heat and clinic visits among other stratified groups.

CONCLUSIONS

Our study appears to be the first to link heat effects with clinic data among migrant and seasonal farmworkers. This research suggests possible significant impact of heat on migrant farmworkers and provides justifications for further studies.

Drier air, lower temperatures, and triggering of paroxysmal atrial fibrillation

BACKGROUND

The few previous studies on the onset of paroxysmal atrial fibrillation and meteorologic conditions have focused on outdoor temperature and hospital admissions, but hospital admissions are a crude indicator of atrial fibrillation incidence, and studies have found other weather measures in addition to temperature to be associated with cardiovascular outcomes.

METHODS

Two hundred patients with dual chamber implantable cardioverter-defibrillators were enrolled and followed prospectively from 2006 to 2010 for new onset episodes of atrial fibrillation. The date and time of arrhythmia episodes documented by the implanted cardioverter-defibrillators were linked to meteorologic data and examined using a case-crossover analysis. We evaluated associations with outdoor temperature, apparent temperature, air pressure, and three measures of humidity (relative humidity, dew point, and absolute humidity).

RESULTS

Of the 200 enrolled patients, 49 patients experienced 328 atrial fibrillation episodes lasting ≥30 seconds. Lower temperatures in the prior 48 hours were positively associated with atrial fibrillation. Lower absolute humidity (ie, drier air) had the strongest and most consistent association: each 0.5 g/m decrease in the prior 24 hours increased the odds of atrial fibrillation by 4% (95% confidence interval [CI]: 0%, 7%) and by 5% (95% CI: 2%, 8%) for exposure in the prior 2 hours. Results were similar for dew point but slightly weaker.

CONCLUSIONS

Recent exposure to drier air and lower temperatures were associated with the onset of atrial fibrillation among patients with known cardiac disease, supporting the hypothesis that meteorologic conditions trigger acute cardiovascular episodes.

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.