On the estimation of heat-intensity and heat-duration effects in time series models of temperature-related mortality in Stockholm, Sweden

The effects of heatwaves on hospital admissions in the Edirne province of Turkey: A cohort study

Studies show that heat waves (HWs) are among the most important atmospheric phenomena that negatively affect human health. This study aims to determine the effects of HWs on hospital admissions (HA) in the Edirne province of Turkey. Polyclinic admission and atmospheric data, including daily maximum temperatures, were used. HW is defined as temperature at the % 90 threshold of daily maximum temperatures that persists for at least 3 consecutive days or more. With this definition, a 6-day HW was detected, and a lag of 3 days was added to this HW. Logarithmic Z test was used for the analysis. As a result of the study, The Risk Ratio (RR) showing the relationship between 9-day HW and HAs was calculated as 1.19 (95% confident interval [CI]: 1.17-1.21, P < .05), and it was determined that there were 2557 extra HAs in total. When HAs were analyzed according to sex, it was observed that female admissions were higher than male admissions. To analyze admissions by age, the data were divided into 3 groups: children (<15 years), adult (15-64 years), and elderly (≥65 years). As a result of the analysis, the highest increase was observed in patients < 15 years of age, and the RR was 1.33 (95% CI: 1.24-1.42 P < .05). When the patient density in polyclinics was analyzed, the Cardiology polyclinic had the highest number of patient admissions with an RR, 1.36 (95% CI: 1.30-1.43 P < .05). The results of this study will guide measures to be taken against HWs.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

Short-term exposure to temperature and mental health in North Carolina: a distributed lag nonlinear analysis

Adverse mental health outcomes have been associated with high temperatures in studies worldwide. Few studies explore a broad range of mental health outcomes, and to our knowledge, none are specific to NC, USA. This ecological study explored the relationship between ambient temperature and mental health outcomes (suicide, self-harm and suicide ideation, anxiety and stress, mood disorders, and depression) in six urban counties across the state of NC, USA. We applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM) to examine the short-term effects of daily ambient temperature on emergency admissions for mental health conditions (2016 to 2018) and violent deaths (2004 to 2018). The results were predominately insignificant, with some key exceptions. The county with the greatest temperature range (Wake) displays higher levels of significance, while counties with the lowest temperature ranges (New Hanover and Pitt) are almost entirely insignificant. Self-harm and suicidal ideation peak in the warm months (July) and generally exhibit a protective effect at lower temperatures and shorter lag intervals. Whereas anxiety, depression, and major depressive disorders peak in the cooler months (May and September). Suicide is the only outcome that favored a 20-day lag period in the sensitivity analysis, although the association with temperature was insignificant. Our findings suggest additional research is needed across a suite of mental health outcomes to fully understand the effects of temperatures on mental health.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Health Risks to the Russian Population from Temperature Extremes at the Beginning of the XXI Century

Climate change and climate-sensitive disasters caused by climatic hazards have a significant and increasing direct and indirect impact on human health. Due to its vast area, complex geographical environment and various climatic conditions, Russia is one of the countries that suffers significantly from frequent climate hazards. This paper provides information about temperature extremes in Russia in the beginning of the 21st century, and their impact on human health. A literature search was conducted using the electronic databases Web of Science, Science Direct, Scopus, and e-Library, focusing on peer-reviewed journal articles published in English and in Russian from 2000 to 2021. The results are summarized in 16 studies, which are divided into location-based groups, including Moscow, Saint Petersburg and other large cities located in various climatic zones: in the Arctic, in Siberia and in the southern regions, in ultra-continental and monsoon climate. Heat waves in cities with a temperate continental climate lead to a significant increase in all-cause mortality than cold waves, compared with cities in other climatic zones. At the same time, in northern cities, in contrast to the southern regions and central Siberia, the influence of cold waves is more pronounced on mortality than heat waves. To adequately protect the population from the effects of temperature waves and to carry out preventive measures, it is necessary to know specific threshold values of air temperature in each city.

Equids engineer desert water availability

Megafauna play important roles in the biosphere, yet little is known about how they shape dryland ecosystems. We report on an overlooked form of ecosystem engineering by donkeys and horses. In the deserts of North America, digging of ≤2-meter wells to groundwater by feral equids increased the density of water features, reduced distances between waters, and, at times, provided the only water present. Vertebrate richness and activity were higher at equid wells than at adjacent dry sites, and, by mimicking flood disturbance, equid wells became nurseries for riparian trees. Our results suggest that equids, even those that are introduced or feral, are able to buffer water availability, which may increase resilience to ongoing human-caused aridification.

Heat wave-related mortality in Sweden: A case-crossover study investigating effect modification by neighbourhood deprivation

Aims: The present study aimed to investigate if set thresholds in the Swedish heat-wave warning system are valid for all parts of Sweden and if the heat-wave warning system captures a potential increase in all-cause mortality and coronary heart disease (CHD) mortality. An additional aim was to investigate whether neighbourhood deprivation modifies the relationship between heat waves and mortality. Methods: From 1990 until 2014, in 14 municipalities in Sweden, we collected data on daily maximum temperatures and mortality for the five warmest months. Heat waves were defined according to the categories used in the current Swedish heat-wave warning system. Using a case-crossover approach, we investigated the association between heat waves and mortality in Sweden, as well as a modifying effect of neighbourhood deprivation. Results: On a national as well as a regional level, heat waves significantly increased both all-cause mortality and CHD mortality by approximately 10% and 15%, respectively. While neighbourhood deprivation did not seem to modify heat wave-related all-cause mortality, CHD mortality did seem to modify the risk. Conclusions: It may not be appropriate to assume that heat waves in Sweden will have the same impact in a northern setting as in a southern, or that the impact of heat waves will be the same in affluent and deprived neighbourhoods. When designing and implementing heat-wave warning systems, neighbourhood, regional and national information should be incorporated.

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.

Future Heat Waves in Different European Capitals Based on Climate Change Indicators

Changes in the frequency and intensity of heat waves have shown substantial negative impacts on public health. At the same time, climate change towards increasing air temperatures throughout Europe will foster such extreme events, leading to the population being more exposed to them and societies becoming more vulnerable. Based on two climate change scenarios (Representative Concentration Pathway 4.5 and 8.5) we analysed the frequency and intensity of heat waves for three capital cities in Europe representing a North-South transect (London, Luxembourg, Rome). We used indices proposed by the Expert Team on Sector-Specific Climate Indices of the World Meteorological Organization to analyze the number of heat waves, the number of days that contribute to heat waves, the length of the longest heat waves, as well as the mean temperature during heat waves. The threshold for the definition of heat waves is calculated based on a reference period of 30 years for each of the three cities, allowing for a direct comparison of the projected changes between the cities. Changes in the projected air temperature between a reference period (1971-2000) and three future periods (2001-2030 near future, 2031-2060 middle future, and 2061-2090 far future) are statistically significant for all three cities and both emission scenarios. Considerable similarities could be identified for the different heat wave indices. This directly affects the risk of the exposed population and might also negatively influence food security and water supply.

Crisis support-seeking behavior and temperature in the United States: Is there an association in young adults and adolescents?

BACKGROUND

Mounting evidence demonstrates the relationship between high temperatures and adverse mental health outcomes. Yet, no study has examined the influence of temperature on crisis support-seeking behavior among youth in large urban areas.

METHODS

Crisis Text Line (CTL) is a text messaging service that provides crisis interventions for support-seeking individuals for a range of mental-health outcomes in the United States. We applied a distributed lag non-linear modeling technique to assess the short-term impacts of daily maximum and minimum temperature on crisis-related events in four metropolitan locations in the USA.

RESULTS

There were multiple positive associations in three of the four study locations that demonstrate crisis help-seeking behavior increased during anomalously warm conditions.

CONCLUSIONS

This study suggests that there is a significant association between high minimum or maximum temperatures and crisis help-seeking behaviors in young adults and adolescents in urban areas in the United States.

Implications for workability and survivability in populations exposed to extreme heat under climate change: a modelling study

BACKGROUND

Changes in temperature and humidity due to climate change affect living and working conditions. An understanding of the effects of different global temperature changes on population health is needed to inform the continued implementation of the Paris Climate Agreement and to increase global ambitions for greater cuts in emissions. By use of historical and projected climate conditions, we aimed to investigate the effects of climate change on workability (ie, the ability to work) and survivability (the ability to survive).

METHODS

In this modelling study, we estimated the changes in populations exposed to excessive heat stress between the recent past (ie, 1986-2005) and 2100. We used climate data from four models to calculate the wet-bulb globe temperature, an established heat exposure index that can be used to assess the effects of temperature, humidity, and other environmental factors on humans. We defined and applied thresholds for risks to workability (where the monthly mean of daily maximum wet-bulb globe temperature exceeds 34°C) and survivability (where the maximum daily wet-bulb globe temperature exceeds 40°C for 3 consecutive days), and we used population projections to quantify changes in risk associated with different changes to the global temperature.

FINDINGS

The risks to workability increase substantially with global mean surface temperature in all four climate models, with approximately 1 billion people affected globally after an increase in the global temperature of about 2·5°C above pre-industrial levels. There is greater variability between climate models for exposures above the threshold for risks to survivability than for risks to workability. The number of people who are likely to be exposed to heat stress exceeding the survivability threshold increases with global temperature change, to reach around 20 million people globally after an increase of about 2·5°C, estimated from the median of the models, but with a large model uncertainty. More people are likely to be exposed to heat stress in urban than in rural areas. Population exposure can fluctuate over time and change substantially within one decade.

INTERPRETATION

Exposure to excessive heat stress is projected to be widespread in tropical or subtropical low-income and middle-income countries, highlighting the need to build on the Paris Agreement regarding global temperature targets, to protect populations who have contributed little to greenhouse gas emissions. The non-linear dependency of heat exposure risk on temperature highlights the importance of understanding thresholds in coupled human-climate systems.

FUNDING

Wellcome Trust.

A new approach to modeling temperature-related mortality: Non-linear autoregressive models with exogenous input

Temperature-mortality relationships are nonlinear, time-lagged, and can vary depending on the time of year and geographic location, all of which limits the applicability of simple regression models in describing these associations. This research demonstrates the utility of an alternative method for modeling such complex relationships that has gained recent traction in other environmental fields: nonlinear autoregressive models with exogenous input (NARX models). All-cause mortality data and multiple temperature-based data sets were gathered from 41 different US cities, for the period 1975-2010, and subjected to ensemble NARX modeling. Models generally performed better in larger cities and during the winter season. Across the US, median absolute percentage errors were 10% (ranging from 4% to 15% in various cities), the average improvement in the r-squared over that of a simple persistence model was 17% (6-24%), and the hit rate for modeling spike days in mortality (>80th percentile) was 54% (34-71%). Mortality responded acutely to hot summer days, peaking at 0-2 days of lag before dropping precipitously, and there was an extended mortality response to cold winter days, peaking at 2-4 days of lag and dropping slowly and continuing for multiple weeks. Spring and autumn showed both of the aforementioned temperature-mortality relationships, but generally to a lesser magnitude than what was seen in summer or winter. When compared to distributed lag nonlinear models, NARX model output was nearly identical. These results highlight the applicability of NARX models for use in modeling complex and time-dependent relationships for various applications in epidemiology and environmental sciences.

Where are weather-suicide associations valid? An examination of nine US counties with varying seasonality

There has been much research on the associations between weather variables and suicide rates. However, the state of understanding has remained rather stagnant due to many contradictory findings. The purpose of this project is to examine a larger database of suicides that includes a longer and more recent period of record (1975-2010) across numerous locations in the USA. In all, we examine nine total counties (and the primary city associated with them) with a special effort made to compare locations with varying degrees of temperature seasonality: Cook (Chicago), Fulton (Atlanta), King (Seattle), Los Angeles (Los Angeles), Maricopa (Phoenix), Miami-Dade (Miami), Philadelphia (Philadelphia), Salt Lake (Salt Lake City), and St. Louis (St. Louis). We first examine the unique seasonal cycle in suicides evident in each locale and then use distributed lag nonlinear modeling (DLNM) to relate the suicide data to daily surface temperatures. Results suggest that a late spring/summer peak generally exists in suicide rates, and above average temperatures are associated with increased suicide risk in almost all study counties. Further, it appears that these associations can be found in both mid-latitude and sub-tropical climate types.

Heat Wave and Mortality: A Multicountry, Multicommunity Study

BACKGROUND

Few studies have examined variation in the associations between heat waves and mortality in an international context.

OBJECTIVES

We aimed to systematically examine the impacts of heat waves on mortality with lag effects internationally.

METHODS

We collected daily data of temperature and mortality from 400 communities in 18 countries/regions and defined 12 types of heat waves by combining community-specific daily mean temperature ≥90th, 92.5th, 95th, and 97.5th percentiles of temperature with duration ≥2, 3, and 4 d. We used time-series analyses to estimate the community-specific heat wave-mortality relation over lags of 0-10 d. Then, we applied meta-analysis to pool heat wave effects at the country level for cumulative and lag effects for each type of heat wave definition.

RESULTS

Heat waves of all definitions had significant cumulative associations with mortality in all countries, but varied by community. The higher the temperature threshold used to define heat waves, the higher heat wave associations on mortality. However, heat wave duration did not modify the impacts. The association between heat waves and mortality appeared acutely and lasted for 3 and 4 d. Heat waves had higher associations with mortality in moderate cold and moderate hot areas than cold and hot areas. There were no added effects of heat waves on mortality in all countries/regions, except for Brazil, Moldova, and Taiwan. Heat waves defined by daily mean and maximum temperatures produced similar heat wave-mortality associations, but not daily minimum temperature.

CONCLUSIONS

Results indicate that high temperatures create a substantial health burden, and effects of high temperatures over consecutive days are similar to what would be experienced if high temperature days occurred independently. People living in moderate cold and moderate hot areas are more sensitive to heat waves than those living in cold and hot areas. Daily mean and maximum temperatures had similar ability to define heat waves rather than minimum temperature. https://doi.org/10.1289/EHP1026.

The association between consecutive days' heat wave and cardiovascular disease mortality in Beijing, China

BACKGROUND

Although many studies have examined the effects of heat waves on the excess mortality risk (ER) posed by cardiovascular disease (CVD), scant attention has been paid to the effects of various combinations of differing heat wave temperatures and durations. We investigated such effects in Beijing, a city of over 20 million residents.

METHODS

A generalized additive model (GAM) was used to analyze the ER of consecutive days' exposure to extreme high temperatures.

RESULTS

A key finding was that when extremely high temperatures occur continuously, at varying temperature thresholds and durations, the adverse effects on CVD mortality vary significantly. The longer the heat wave lasts, the greater the mortality risk is. When the daily maximum temperature exceeded 35 °C from the fourth day onward, the ER attributed to consecutive days' high temperature exposure saw an increase to about 10% (p < 0.05), and at the fifth day, the ER even reached 51%. For the thresholds of 32 °C, 33 °C, and 34 °C, from the fifth day onward, the ER also rose sharply (16, 29, and 31%, respectively; p < 0.05). In addition, extreme high temperatures appeared to contribute to a higher proportion of CVD deaths among elderly persons, females and outdoor workers. When the daily maximum temperature was higher than 33 °C from the tenth consecutive day onward, the ER of CVD death among these groups was 94, 104 and 149%, respectively (p < 0.05), which is considerably higher than the ER for the overall population (87%; p < 0.05).

CONCLUSIONS

The results of this study may assist governments in setting standards for heat waves, creating more accurate heat alerts, and taking measures to prevent or reduce temperature-related deaths, especially against the backdrop of global warming.

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.

Heatwaves and Hospital Admissions for Mental Disorders in Northern Vietnam

Studies in high-income countries have shown an association between heatwaves and hospital admissions for mental disorders. It is unknown whether such associations exist in subtropical nations like Vietnam. The study aim was to investigate whether hospital admissions for mental disorders may be triggered, or exacerbated, by heat exposure and heatwaves, in a low- and middle-income country, Vietnam. For this, we used data from the Hanoi Mental Hospital over five years (2008–2012) to estimate the effect of heatwaves on admissions for mental disorders. A zero-inflated negative binomial regression model accounting for seasonality, time trend, days of week, and mean humidity was used to analyse the relationship. Heatwave events were mainly studied as periods of three or seven consecutive days above the threshold of 35°C daily maximum temperature (90^th percentile). The study result showed heatwaves increased the risk for admission in the whole group of mental disorders (F00-79) for more persistent heatwaves of at least 3 days when compared with non-heatwave periods. The relative risks were estimated at 1.04 (0.95–1.13), 1.15 (1.005–1.31), and 1.36 (1–1.90) for a one-, three- and seven-day heatwave, respectively. Admissions for mental disorders increased among men, residents in rural communities, and the elderly population during heatwaves. The groups of organic mental disorders, including symptomatic illnesses (F0-9) and mental retardation (F70-79), had increased admissions during heatwaves. The findings are novel in their focus on heatwave impact on mental diseases in a population habituating in a subtropical low- and middle-income country characterized by rapid epidemiological transitions and environmental changes.

Modifying Effect of Heat Waves on the Relationship between Temperature and Mortality

Studies conducted to evaluate temporal trends of heat-related mortality have not considered the effects of heat waves; although it is known they can affect mortality and act as a modifying factor. After adjusting for long-term trends and seasonality, the effects of temperature on non-accidental deaths in Seoul and Busan (inland and coastal cities, respectively) were analyzed using a generalized additive model of Poisson distribution. We evaluated temporal trends of heat-related mortalities in four periods (1991-1995, 1996-2000, 2001-2005, and 2006-2012). The effects of temperature on mortality were evaluated according to the occurrence of a heat wave and results were compared in the two cities. The effect of temperature on mortality was the greatest in 1991-1995 in Seoul; no significant change was observed in Busan. When we stratified the study period by heat wave status, the risk increase in mortality was 15.9% per 1℃ during years with a heat wave in Seoul, which was much higher than 0.31% increase observed during years without a heat wave. On the other hand, Busan showed a linear relationship between temperature and mortality and no significant difference between years with or without a heat wave. Variations in the relationship between temperature and mortality could be misunderstood if heat waves are not considered. Furthermore, heterogeneity was found in the modifying effect of heat waves on heat-related mortality in inland and coastal cities. The findings of this study help understand relations between temperature and mortality.

Added effect of heat wave on mortality in Seoul, Korea

A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0-30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5-22.6, 95 % confidence interval (CI)), 18.1 % (10.8-26.0, 95 % CI), 18.1 % (10.7-25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7-5.8 % and 8.6-11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies.

Mortality during a Large-Scale Heat Wave by Place, Demographic Group, Internal and External Causes of Death, and Building Climate Zone

Mortality increases during periods of elevated heat. Identification of vulnerable subgroups by demographics, causes of death, and geographic regions, including deaths occurring at home, is needed to inform public health prevention efforts. We calculated mortality relative risks (RRs) and excess deaths associated with a large-scale California heat wave in 2006, comparing deaths during the heat wave with reference days. For total (all-place) and at-home mortality, we examined risks by demographic factors, internal and external causes of death, and building climate zones. During the heat wave, 582 excess deaths occurred, a 5% increase over expected (RR = 1.05, 95% confidence interval (CI) 1.03-1.08). Sixty-six percent of excess deaths were at home (RR = 1.12, CI 1.07-1.16). Total mortality risk was higher among those aged 35-44 years than ≥ 65, and among Hispanics than whites. Deaths from external causes increased more sharply (RR = 1.18, CI 1.10-1.27) than from internal causes (RR = 1.04, CI 1.02-1.07). Geographically, risk varied by building climate zone; the highest risks of at-home death occurred in the northernmost coastal zone (RR = 1.58, CI 1.01-2.48) and the southernmost zone of California's Central Valley (RR = 1.43, CI 1.21-1.68). Heat wave mortality risk varied across subpopulations, and some patterns of vulnerability differed from those previously identified. Public health efforts should also address at-home mortality, non-elderly adults, external causes, and at-risk geographic regions.

A spatial analysis of heat stress related emergency room visits in rural Southern Ontario during heat waves

BACKGROUND

In Southern Ontario, climate change may have given rise to an increasing occurrence of heat waves since the year 2000, which can cause heat stress to the general public, and potentially have detrimental health consequences. Heat waves are defined as three consecutive days with temperatures of 32 °C and above. Heat stress is the level of discomfort. A variety of heat stress indices have been proposed to measure heat stress (e.g., the heat stress index (HSI)), and has been shown to predict increases in morbidity and/or mortality rates in humans and other species. Maps visualizing the distribution of heat stress can provide information about related health risks and insight for control strategies. Information to inform heat wave preparedness models in Ontario was previously only available for major metropolitan areas.

METHODS

Hospitals in communities of fewer than 100,000 individuals were recruited for a pilot study by telephone. The number of people visiting the emergency room or 24-hour urgent care service was collected for a total of 27 days, covering three heat waves and six 3-day control periods from 2010-2012. The heat stress index was spatially predicted using data from 37 weather stations across Southern Ontario by geostatistical kriging. Poisson regression modeling was applied to determine the rate of increased number of emergency room visits in rural hospitals with respect to the HSI.

RESULTS

During a heat wave, the average rate of emergency room visits was 1.11 times higher than during a control period (IRR = 1.11, CI95% (IRR) = (1.07,1.15), p ≤ 0.001). In a univariable model, HSI was not a significant predictor of emergency room visits, but when accounting for the confounding effect of a spatial trend polynomial in the hospital location coordinates, a one unit increase in HSI predicted an increase in daily emergency rooms visits by 0.4% (IRR = 1.004, CI95%(IRR) = (1.0005,1.007), p = 0.024) across the region. One high-risk cluster and no low risk clusters were identified in the southwestern portion of the study area by the spatial scan statistic during heat waves. The high-risk cluster is located in a region with high levels of heat stress during heat waves.

CONCLUSIONS

This finding will aid hospitals and rural public health units in preventing and preparing for emergencies of foreseeable heat waves. Future research is needed to assess the relation between heat stress and individual characteristics and demographics of rural communities in Ontario.

Temperature variation and heat wave and cold spell impacts on years of life lost among the urban poor population of Nairobi, Kenya

Weather extremes are associated with adverse health outcomes, including mortality. Studies have investigated the mortality risk of temperature in terms of excess mortality, however, this risk estimate may not be appealing to policy makers assessing the benefits expected for any interventions to be adopted. To provide further evidence of the burden of extreme temperatures, we analyzed the effect of temperature on years of life lost (YLL) due to all-cause mortality among the population in two urban informal settlements. YLL was generated based on the life expectancy of the population during the study period by applying a survival analysis approach. Association between daily maximum temperature and YLL was assessed using a distributed lag nonlinear model. In addition, cold spell and heat wave effects, as defined according to different percentiles, were investigated. The exposure-response curve between temperature and YLL was J-shaped, with the minimum mortality temperature (MMT) of 26 °C. An average temperature of 21 °C compared to the MMT was associated with an increase of 27.4 YLL per day (95% CI, 2.7-52.0 years). However, there was no additional effect for extended periods of cold spells, nor did we find significant associations between YLL to heat or heat waves. Overall, increased YLL from all-causes were associated with cold spells indicating the need for initiating measure for reducing health burdens.

Assessing variability in the impacts of heat on health outcomes in New York City over time, season, and heat-wave duration

While the impacts of heat upon mortality and morbidity have been frequently studied, few studies have examined the relationship between heat, morbidity, and mortality across the same events. This research assesses the relationship between heat events and morbidity and mortality in New York City for the period 1991-2004. Heat events are defined based on oppressive weather types as determined by the Spatial Synoptic Classification. Morbidity data include hospitalizations for heat-related, respiratory, and cardiovascular causes; mortality data include these subsets as well as all-cause totals. Distributed-lag models assess the relationship between heat and health outcome for a cumulative 15-day period following exposure. To further refine analysis, subset analyses assess the differences between early- and late-season events, shorter and longer events, and earlier and later years. The strongest heat-health relationships occur with all-cause mortality, cardiovascular mortality, and heat-related hospital admissions. The impacts of heat are greater during longer heat events and during the middle of summer, when increased mortality is still statistically significant after accounting for mortality displacement. Early-season heat waves have increases in mortality that appear to be largely short-term displacement. The impacts of heat on mortality have decreased over time. Heat-related hospital admissions have increased during this time, especially during the earlier days of heat events. Given the trends observed, it suggests that a greater awareness of heat hazards may have led to increased short-term hospitalizations with a commensurate decrease in mortality.

Association of weekly suicide rates with temperature anomalies in two different climate types

Annual suicide deaths outnumber the total deaths from homicide and war combined. Suicide is a complex behavioral endpoint, and a simple cause-and-effect model seems highly unlikely, but relationships with weather could yield important insight into the biopsychosocial mechanisms involved in suicide deaths. This study has been designed to test for a relationship between air temperature and suicide frequency that is consistent enough to offer some predictive abilities. Weekly suicide death totals and anomalies from Toronto, Ontario, Canada (1986-2009) and Jackson, Mississippi, USA (1980-2006) are analyzed for relationships by using temperature anomaly data and a distributed lag nonlinear model. For both analysis methods, anomalously cool weeks show low probabilities of experiencing high-end suicide totals while warmer weeks are more likely to experience high-end suicide totals. This result is consistent for Toronto and Jackson. Weekly suicide totals demonstrate a sufficient association with temperature anomalies to allow some prediction of weeks with or without increased suicide frequency. While this finding alone is unlikely to have immediate clinical implications, these results are an important step toward clarifying the biopsychosocial mechanisms of suicidal behavior through a more nuanced understanding of the relationship between temperature and suicide.

Heat, heat waves, and hospital admissions among the elderly in the United States, 1992-2006

BACKGROUND

Heat-wave frequency, intensity, and duration are increasing with global climate change. The association between heat and mortality in the elderly is well documented, but less is known regarding associations with hospital admissions.

OBJECTIVES

Our goal was to determine associations between moderate and extreme heat, heat waves, and hospital admissions for nonaccidental causes among Medicare beneficiaries ≥ 65 years of age in 114 cities across five U.S. climate zones.

METHODS

We used Medicare inpatient billing records and city-specific data on temperature, humidity, and ozone from 1992 through 2006 in a time-stratified case-crossover design to estimate the association between hospitalization and moderate [90th percentile of apparent temperature (AT)] and extreme (99th percentile of AT) heat and heat waves (AT above the 95th percentile over 2-8 days). In sensitivity analyses, we additionally considered confounding by ozone and holidays, different temperature metrics, and alternate models of the exposure-response relationship.

RESULTS

Associations between moderate heat and hospital admissions were minimal, but extreme heat was associated with a 3% (95% CI: 2%, 4%) increase in all-cause hospital admissions over the subsequent 8 days. In cause-specific analyses, extreme heat was associated with increased hospitalizations for renal (15%; 95% CI: 9%, 21%) and respiratory (4%; 95% CI: 2%, 7%) diseases, but not for cardiovascular diseases. An added heat-wave effect was observed for renal and respiratory admissions.

CONCLUSION

Extreme heat is associated with increased hospital admissions, particularly for renal causes, among the elderly in the United States.

The effect of heat waves on mortality and effect modifiers in four communities of Guangdong Province, China

BACKGROUND

Heat waves have been reported to be associated with increased mortality; however, fewer studies have examined the effect modification by heat wave characteristics, individual characteristics and community characteristics.

METHODS

This study investigated the effect of extreme heat on mortality in 2 urban and 2 rural communities in Guangdong Province, China during 2006-2010. The effect of extreme heat was divided into two parts: main effect due to high temperature and added effect due to prolonged heat for several consecutive days. A distributed lag non-linear model was used to calculate the relative risk with consideration of lag days and potential confounding factors. Separate models were further fit by individual characteristics (cause of death, age and gender) and heat wave characteristics (intensity, duration and timing), and potential effect modification of community characteristics was examined using a meta-regression, such as educational levels, percentage of the elderly, Gross Regional Domestic Product (GDP).

RESULTS

The overall main effects (ER=8.2%, 95% CI: 3.4%, 13.2%) were greater than the added effects (ER=0.0%, 95% CI: -3.8%, 4.0%) on the current day. The main effect peaked at lag0-2, and was higher for the two rural areas compared to the two cities, for respiratory compared to cardiovascular mortality, for those ≥75 years old and for females. The modifying effects of heat wave characteristics and community characteristics on mortality were not statistically significant.

CONCLUSION

This study suggests the effects of extreme heat were mainly driven by high temperature, which can be modified by some individual characteristics.

Association of weather and air pollution interactions on daily mortality in 12 Canadian cities

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981-2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 μm). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality (p < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM.

Mortality related to air pollution with the moscow heat wave and wildfire of 2010

BACKGROUND

Prolonged high temperatures and air pollution from wildfires often occur together, and the two may interact in their effects on mortality. However, there are few data on such possible interactions.

METHODS

We analyzed day-to-day variations in the number of deaths in Moscow, Russia, in relation to air pollution levels and temperature during the disastrous heat wave and wildfire of 2010. Corresponding data for the period 2006-2009 were used for comparison. Daily average levels of PM10 and ozone were obtained from several continuous measurement stations. The daily number of nonaccidental deaths from specific causes was extracted from official records. Analyses of interactions considered the main effect of temperature as well as the added effect of prolonged high temperatures and the interaction with PM10.

RESULTS

The major heat wave lasted for 44 days, with 24-hour average temperatures ranging from 24°C to 31°C and PM10 levels exceeding 300 μg/m on several days. There were close to 11,000 excess deaths from nonaccidental causes during this period, mainly among those older than 65 years. Increased risks also occurred in younger age groups. The most pronounced effects were for deaths from cardiovascular, respiratory, genitourinary, and nervous system diseases. Continuously increasing risks following prolonged high temperatures were apparent during the first 2 weeks of the heat wave. Interactions between high temperatures and air pollution from wildfires in excess of an additive effect contributed to more than 2000 deaths.

CONCLUSIONS

Interactions between high temperatures and wildfire air pollution should be considered in risk assessments regarding health consequences of climate change.

Susceptibility to mortality related to temperature and heat and cold wave duration in the population of Stockholm County, Sweden

Background

Ambient temperatures can cause an increase in mortality. A better understanding is needed of how health status and other factors modify the risk associated with high and low temperatures, to improve the basis of preventive measures. Differences in susceptibility to temperature and to heat and cold wave duration are relatively unexplored.

Objectives

We studied the associations between mortality and temperature and heat and cold wave duration, stratified by age and individual and medical factors.

Methods

Deaths among all residents of Stockholm County between 1990 and 2002 were linked to discharge diagnosis data from hospital admissions, and associations were examined using the time stratified case-crossover design. Analyses were stratified by gender, age, pre-existing disease, country of origin, and municipality level wealth, and adjusted for potential confounding factors.

Results

The effect on mortality by heat wave duration was higher for lower ages, in areas with lower wealth, for hospitalized patients younger than age 65. Odds were elevated among females younger than age 65, in groups with a previous hospital admission for mental disorders, and in persons with previous cardiovascular disease. Gradual increases in summer temperatures were associated with mortality in people older than 80 years, and with mortality in groups with a previous myocardial infarction and with chronic obstructive pulmonary disease (COPD) in the population younger than 65 years. During winter, mortality was associated with a decrease in temperature particularly in men and with the duration of cold spells for the population older than 80. A history of hospitalization for myocardial infarction increased the odds associated with cold temperatures among the population older than 65. Previous mental disease or substance abuse increased the odds of death among the population younger than 65.

Conclusion

To increase effectiveness, we suggest preventive efforts should not assume susceptible groups are the same for warm and cold days and heat and cold waves, respectively.

A time series approach for evaluating intra-city heat-related mortality

Extreme heat is a leading cause of weather-related mortality. Most research has considered the aggregate response of the populations of large metropolitan areas, but the focus of heat-related mortality and morbidity investigations is shifting towards a more fine-scale approach in which impacts are measured in smaller units such as postal codes. However, most existing statistical techniques to model the relationship between temperature and mortality cannot be directly applied to the intra-city scale because small sample sizes inhibit proper modelling of seasonality and long-term trends. Here we propose a time series technique based on local-scale mortality observations that can provide more reliable information about vulnerability within metropolitan areas. The method combines a generalised additive model with direct standardisation to account for changing death rates in intra-city zones. We apply the method to a 26-year time series of postal code-referenced mortality data from Philadelphia County, USA, where we find that heat-related mortality is unevenly spatially distributed. Fifteen of 46 postal codes are associated with significantly increased mortality on extreme heat days, most of which are located in the central and western portions of the county. In some cases the local death rate is more than double the county average. Identification of high-risk areas can enable targeted public health intervention and mitigation strategies.

Short-term effects of summer temperatures on mortality in Portugal: a time-series analysis

Heat stress is a current public health concern during the warm months in many urban areas. Climate change and increasing urbanization are expected to worsen this concern, with some locations being more vulnerable than others. The aim of this study was to determine the short-term effect of heat on mortality in the two most populated cities in Portugal: Lisbon and Oporto. Each city was assessed for specific heat stress threshold above which heat-related mortality becomes significant. A Poisson generalized estimating equations (GEE) model was used to estimate the impact of maximum apparent temperature (ATmax) and maximum temperature (Tmax) on daily mortality, in the summer season. Data show ATmax thresholds of 30.4°C for Lisbon and 26.3°C for Oporto, and Tmax thresholds of 29.3°C and 25.0°C, respectively. For every 1°C elevation in ATmax above the city-specific threshold, all-cause mortality rate rose by 7.13% (95% CI: 5.9; 8.4) in Lisbon and 4.31% (95% CI: 3.2; 5.4) in Oporto. The Tmax threshold increases were 5.6% (95% CI: 4.6; 6.6) in Lisbon and 3% (95% CI: 2.0, 3.9) in Oporto. In both cities, stronger associations were found for respiratory diseases and the elderly group was the most vulnerable. This study confirmed that elevated temperatures have a considerable impact on daily mortality frequency in the two most urbanized areas in Portugal. Our results also provide useful data for policymakers to better prepare local actions to mitigate and reduce the health risks associated with high temperatures.