Summer temperature-related mortality: effect modification by previous winter mortality

Exploring the paradoxical nature of cold temperature mortality in Europe

While low winter temperatures are associated with increased mortality, this phenomenon has been suggested to be most severe in regions with seemingly mild winters. The study aimed to establish a temperature-based formula that could elucidate the previously ambiguous regional differences in vulnerability to low temperature. European weekly mortality data (2000-2019) were matched with meteorological data to determine for each region vulnerability to temperature decrease and the optimal temperature with lowest mortality. Regression models were developed to generalize and explain these findings considering regional temperature characteristics. Optimal temperature could be predicted based on local average summer temperature (R2 = 85.6%). Regional vulnerability to temperature decrease could be explained by combination of winter and summer temperatures (R2 = 86.1%). Regions with warm winters and cold summers showed the highest vulnerability to decrease of temperature during winter. Contrary to theories about economic disparities Eastern Europe exhibited resistance comparable to Scandinavia. The southern edges of Europe demonstrated serious low temperature vulnerability to decreased temperatures, even if temperature was relatively high around 20 °C. This suggests that the observed connection primarily reflects the modulation of the length of respiratory virus infection seasons by climate conditions, counterbalanced by varying levels of acquired immunity and the presence of heatwaves eliminating the most frail individuals. Thus, relatively low vulnerability and a flat mortality cycle in countries with harsh climates paradoxically imply the presence of threats throughout the whole year.

Seasonality of mortality under a changing climate: a time-series analysis of mortality in Japan between 1972 and 2015

BACKGROUND

Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate.

METHODS

Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics.

RESULTS

The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively.

CONCLUSION

Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.

Temporal dynamics in total excess mortality and COVID-19 deaths in Italian cities

BACKGROUND

Standardized mortality surveillance data, capable of detecting variations in total mortality at population level and not only among the infected, provide an unbiased insight into the impact of epidemics, like COVID-19 (Coronavirus disease). We analysed the temporal trend in total excess mortality and deaths among positive cases of SARS-CoV-2 by geographical area (north and centre-south), age and sex, taking into account the deficit in mortality in previous months.

METHODS

Data from the Italian rapid mortality surveillance system was used to quantify excess deaths during the epidemic, to estimate the mortality deficit during the previous months and to compare total excess mortality with deaths among positive cases of SARS-CoV-2. Data were stratified by geographical area (north vs centre and south), age and sex.

RESULTS

COVID-19 had a greater impact in northern Italian cities among subjects aged 75-84 and 85+ years. COVID-19 deaths accounted for half of total excess mortality in both areas, with differences by age: almost all excess deaths were from COVID-19 among adults, while among the elderly only one third of the excess was coded as COVID-19. When taking into account the mortality deficit in the pre-pandemic period, different trends were observed by area: all excess mortality during COVID-19 was explained by deficit mortality in the centre and south, while only a 16% overlap was estimated in northern cities, with quotas decreasing by age, from 67% in the 15-64 years old to 1% only among subjects 85+ years old.

CONCLUSIONS

An underestimation of COVID-19 deaths is particularly evident among the elderly. When quantifying the burden in mortality related to COVID-19, it is important to consider seasonal dynamics in mortality. Surveillance data provides an impartial indicator for monitoring the following phases of the epidemic, and may help in the evaluation of mitigation measures adopted.

Life Expectancy: Frequently Used, but Hardly Understood

Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Europe-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.

Impacts of exposure to ambient temperature on burden of disease: a systematic review of epidemiological evidence

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings.

The predictability of heat-related mortality in Prague, Czech Republic, during summer 2015-a comparison of selected thermal indices

We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices-Universal Thermal Climate Index and Excess Heat Factor (EHF)-were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May-September) during 1994-2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of "false alerts" compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.

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

Background

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

Objectives

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

Design

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

Setting

England, UK.

Participants

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

Interventions

HEE interventions.

Main outcome measures

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

Data sources

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

Results

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

Limitations

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

Conclusions

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

Future work

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

Funding

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

Investigating changes in mortality attributable to heat and cold in Stockholm, Sweden

Projections of temperature-related mortality rely upon exposure-response relationships using recent data. Analyzing long historical data and trends may extend knowledge of past and present impacts that may provide additional insight and improve future scenarios. We collected daily mean temperatures and daily all-cause mortality for the period 1901-2013 for Stockholm County, Sweden, and calculated the total attributable fraction of mortality due to non-optimal temperatures and quantified the contribution of cold and heat. Total mortality attributable to non-optimal temperatures varied between periods and cold consistently had a larger impact on mortality than heat. Cold-related attributable fraction (AF) remained stable over time whereas heat-related AF decreased. AF on cold days remained stable over time, which may indicate that mortality during colder months may not decline as temperatures increase in the future. More research is needed to enhance estimates of burdens related to cold and heat in the future.

The inter-annual variability of heat-related mortality in nine European cities (1990-2010)

BACKGROUND

The association between heat and daily mortality and its temporal variation are well known. However, few studies have analyzed the inter-annual variations in both the risk estimates and impacts of heat. The aim is to estimate inter-annual variations in the effect of heat for a fixed temperature range, on mortality in 9 European cities included in the PHASE (Public Health Adaptation Strategies to Extreme weather events) project for the period 1990-2010. The second aim is to evaluate overall summer effects and heat-attributable deaths for each year included in the study period, considering the entire air temperature range (both mild and extreme temperatures).

METHODS

A city-specific daily time-series analysis was performed, using a generalized additive Poisson regression model, restricted to the warm season (April-September). To study the temporal variation for a fixed air temperature range, a Bayesian Change Point analysis was applied to the relative risks of mortality for a 2 °C increase over the 90th percentile of the city-specific distribution. The number of heat attributable deaths in each summer were also calculated for mild (reference to 95th percentile) and extreme heat (95th percentile to maximum value).

RESULTS

A decline in the effects of heat over time was observed in Athens and Rome when considering a fixed interval, while an increase in effects was observed in Helsinki. The greatest impact of heat in terms of attributable deaths was observed in the Mediterranean cities (Athens, Barcelona and Rome) for extreme air temperatures. In the other cities the impact was mostly related to extreme years with 2003 as a record breaking year in Paris (+ 1900 deaths) and London (+ 1200 deaths).

CONCLUSIONS

Monitoring the impact of heat over time is important to identify changes in population vulnerability and evaluate adaptation measures.

Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement

BACKGROUND

In many places, daily mortality has been shown to increase after days with particularly high or low temperatures, but such daily time-series studies cannot identify whether such increases reflect substantial life shortening or short-term displacement of deaths (harvesting).

OBJECTIVES

To clarify this issue, we estimated the association between annual mortality and annual summaries of heat and cold in 278 locations from 12 countries.

METHODS

Indices of annual heat and cold were used as predictors in regressions of annual mortality in each location, allowing for trends over time and clustering of annual count anomalies by country and pooling estimates using meta-regression. We used two indices of annual heat and cold based on preliminary standard daily analyses: a) mean annual degrees above/below minimum mortality temperature (MMT), and b) estimated fractions of deaths attributed to heat and cold. The first index was simpler and matched previous related research; the second was added because it allowed the interpretation that coefficients equal to 0 and 1 are consistent with none (0) or all (1) of the deaths attributable in daily analyses being displaced by at least 1 y.

RESULTS

On average, regression coefficients of annual mortality on heat and cold mean degrees were 1.7% [95% confidence interval (CI): 0.3, 3.1] and 1.1% (95% CI: 0.6, 1.6) per degree, respectively, and daily attributable fractions were 0.8 (95% CI: 0.2, 1.3) and 1.1 (95% CI: 0.9, 1.4). The proximity of the latter coefficients to 1.0 provides evidence that most deaths found attributable to heat and cold in daily analyses were brought forward by at least 1 y. Estimates were broadly robust to alternative model assumptions.

CONCLUSIONS

These results provide strong evidence that most deaths associated in daily analyses with heat and cold are displaced by at least 1 y. https://doi.org/10.1289/EHP1756.

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Economic Evaluation of Vaccination Programmes in Older Adults and the Elderly: Important Issues and Challenges

High-income countries are undergoing demographic transitions towards populations with substantial larger proportions of older adults. Due to the increased susceptibility of older adults to infectious diseases and their consequences, vaccination programmes are an important health intervention to help maintain healthy ageing. While much of the existing literature suggests that current vaccination programmes targeted at older adults and the elderly are likely to be cost effective in high-income countries, we argue that it is important to more fully consider some important issues and challenges. Since the majority of vaccines have been developed for children, economic evaluations of vaccination programmes have consequentially tended to focus on this age group and on how to incorporate herd-immunity effects. While programmes targeted at older adults and the elderly may also induce some herd effects, there are other important challenges to consider in these economic evaluations. For example, age and time effects in relation to vaccine efficacy and duration of immunity, as well as heterogeneity between targeted individuals in terms of risk of infection, severity of disease and response to vaccination. For some pathogens, there is also the potential for interactions with childhood programmes in the form of herd-immunity effects.

Temperature deviation index and elderly mortality in Japan

Few studies have examined how the precedence of abnormal temperatures in previous neighboring years affects the population's health. In the present study, we attempted to quantify the health effects of abnormal weather patterns by creating a metric called the temperature deviation index (TDI) and estimated the effects of TDI on mortality in Japan. We used data from 47 prefectures in Japan to compute the TDI on days between May and September from 1966 to 2010. The TDI is a summed product of an indicator of absence of high temperatures in the neighboring years, and more weights were assigned to the years closest to the current year. To estimate the TDI effects on elderly mortality, we used generalized linear modeling with a Poisson distribution after adjusting for apparent temperature, barometric pressure, day of the week, and time trend. For each prefecture, we estimated the TDI effects and pooled the estimates to yield a national average for 1991-2010 in Japan. The estimated effects of TDI in middle- or high-latitude prefectures were greater than in low-latitude prefectures. The estimated national average of TDI effects was a 0.5 % (95 % confidence intervals [CI], 0.1, 1.0) increase in elderly mortality per 1-unit (around 1 standard deviation) increase in the TDI. The significant pooled estimation of TDI effects was mainly due to the TDI effects on summer days with moderate temperature (25th-49th percentile, mean temperature 22.9 °C): a 1.9 % (95 % CI, 1.1, 2.6) increase in elderly mortality per 1-unit increase in the TDI. However, TDI effects were insignificant in other temperature ranges. These findings suggest that elderly deaths increased on moderate temperature days in the summer that differed substantially from days during that time window in the neighboring years. Therefore, not only high temperature itself but also temperature deviation compared to previous years could be considered to be a risk factor for elderly mortality in the summer.

The burden of stroke mortality attributable to cold and hot ambient temperatures: Epidemiological evidence from China

BACKGROUND

Few data are available on the attributable burden, such as absolute excess or relative excess, of stroke death due to temperature.

METHODS

We collected data on daily temperature and stroke mortality from 16 large Chinese cities during 2007-2013. First, we applied a distributed lag non-linear model to estimate the city-/age-/gender-specific temperature-mortality association over lag 0-14days. Then, pooled estimates were calculated using a multivariate meta-analysis. Attributable deaths were calculated for cold and heat, defined as temperatures below and above the minimum-mortality temperature (MMT). Moderate and extreme temperatures were defined using cut-offs at the 2.5th and 97.5th percentiles of temperature.

RESULTS

The city-specific MMT increased from the north to the south, with a median of 24.9(o)C. Overall, 14.5% (95% empirical confidence interval: 11.5-17.0%) of stroke mortality (114, 662 deaths) was attributed to non-optimum temperatures, with the majority being attributable to cold (13.1%, 9.7-15.7%). The proportion of temperature-related death had a decreasing trend by latitude, ranging from 22.7% in Guangzhou to 6.3% in Shenyang. Moderate temperatures accounted for 12.6% (9.1-15.3%) of stroke mortality, whereas extreme temperatures accounted for only 2.0% (1.6-2.2%) of stroke mortality. Estimates of death burden due to both cold and heat were higher among males and the elderly, compared with females and the youth.

CONCLUSIONS

The burden of temperature-related stroke mortality increased from the north to the south. Most of this burden was caused by cold temperatures. The stroke burden was higher among males and the elderly. This information has important implications for preventing stroke due to adverse temperatures in vulnerable subpopulations in China.

Effect modification in the temperature extremes by mortality subgroups among the tropical cities of the Philippines

Background

Temperature–mortality relationships have been extensively probed with varying temperature range but with relatively similar patterns and in some instances are being modified by specific mortality groups such as causes of mortality, sex, and age.

Objective

This study aimed to determine the risk attributions in the extreme temperatures and also identified the risks associated with the various mortality subgroups.

Design

We used the 2006–2010 daily average meteorological and daily mortality variables from the Philippine Atmospheric Geophysical and Astronomical Services Administration and Philippine Statistics Authority–National Statistics Office, respectively. Mortality data were divided according to cause (cardiovascular and respiratory), sex, and age (0–14 years, 15–64 years, and >64 years). We performed a two-stage analysis to estimate the extreme temperature effects stratified by the different mortality subgroups to observe the effect modification.

Results

In the pooled analysis, greater risks were observed in the extreme high temperature (99th temperature percentile; RR (relative risk)=2.48 CI: 1.55–3.98) compared to the extreme low temperature (1st temperature percentile; RR=1.23 CI: 0.88–1.72). Furthermore, effect modification by mortality subgroups was evident, especially higher risks for extreme temperatures with respiratory-related diseases, women, and elderly.

Conclusions

Both sex and age were found to effect modify the risks in extreme temperatures of tropical cities; hence, health-related policies should take these risk variations into consideration to create strategies with respect to the risk population.

Changes in Susceptibility to Heat During the Summer: A Multicountry Analysis

Few studies have examined the variation in mortality risk associated with heat during the summer. Here, we apply flexible statistical models to investigate the issue by using a large multicountry data set. We collected daily time-series data of temperature and mortality from 305 locations in 9 countries, in the period 1985–2012. We first estimated the heat-mortality relationship in each location with time-varying distributed lag non-linear models, using a bivariate spline to model the exposure-lag-response over lag 0–10. Estimates were then pooled by country through multivariate meta-analysis. Results provide strong evidence of a reduction in risk over the season. Relative risks for the 99th percentile versus the minimum mortality temperature were in the range of 1.15–2.03 in early summer. In late summer, the excess was substantially reduced or abated, with relative risks in the range of 0.97–1.41 and indications of wider comfort ranges and higher minimum mortality temperatures. The attenuation is mainly due to shorter lag periods in late summer. In conclusion, this multicountry analysis suggests a reduction of heat-related mortality risk over the summer, which can be attributed to several factors, such as true acclimatization, adaptive behaviors, or harvesting effects. These findings may have implications on public health policies and climate change health impact projections.

Evolution of Minimum Mortality Temperature in Stockholm, Sweden, 1901-2009

BACKGROUND

The mortality impacts of hot and cold temperatures have been thoroughly documented, with most locations reporting a U-shaped relationship with a minimum mortality temperature (MMT) at which mortality is lowest. How MMT may have evolved over previous decades as the global mean surface temperature has increased has not been thoroughly explored.

OBJECTIVE

We used observations of daily mean temperatures to investigate whether MMT changed in Stockholm, Sweden, from the beginning of the 20th century until 2009.

METHODS

Daily mortality and temperature data for the period 1901-2009 in Stockholm, Sweden, were used to model the temperature-mortality relationship. We estimated MMT using distributed lag nonlinear Poisson regression models considering lags up to 21 days of daily mean temperature as the exposure variable. To avoid large influences on the MMT from intra- and interannual climatic variability, we estimated MMT based on 30-year periods. Furthermore, we investigated whether there were trends in the absolute value of the MMT and in the relative value of the MMT (the corresponding percentile of the same-day temperature distribution) over the study period.

RESULTS

Our findings suggest that both the absolute MMT and the relative MMT increased in Stockholm, Sweden, over the course of the 20th century.

CONCLUSIONS

The increase in the MMT over the course of the 20th century suggests autonomous adaptation within the context of the large epidemiological, demographical, and societal changes that occurred. Whether the rate of increase will be sustained with climate change is an open question.

CITATION

Oudin Åström D, Tornevi A, Ebi KL, Rocklöv J, Forsberg B. 2016. Evolution of minimum mortality temperature in Stockholm, Sweden, 1901-2009. Environ Health Perspect 124:740-744; http://dx.doi.org/10.1289/ehp.1509692.

Cardiovascular mortality risk attributable to ambient temperature in China

OBJECTIVE

To examine cardiovascular disease (CVD) mortality burden attributable to ambient temperature; to estimate effect modification of this burden by gender, age and education level.

METHODS

We obtained daily data on temperature and CVD mortality from 15 Chinese megacities during 2007-2013, including 1,936,116 CVD deaths. A quasi-Poisson regression combined with a distributed lag non-linear model was used to estimate the temperature-mortality association for each city. Then, a multivariate meta-analysis was used to derive the overall effect estimates of temperature at the national level. Attributable fraction of deaths were calculated for cold and heat (ie, temperature below and above minimum-mortality temperatures, MMTs), respectively. The MMT was defined as the specific temperature associated to the lowest mortality risk.

RESULTS

The MMT varied from the 70th percentile to the 99th percentile of temperature in 15 cities, centring at 78 at the national level. In total, 17.1% (95% empirical CI 14.4% to 19.1%) of CVD mortality (330,352 deaths) was attributable to ambient temperature, with substantial differences among cities, from 10.1% in Shanghai to 23.7% in Guangzhou. Most of the attributable deaths were due to cold, with a fraction of 15.8% (13.1% to 17.9%) corresponding to 305,902 deaths, compared with 1.3% (1.0% to 1.6%) and 24,450 deaths for heat.

CONCLUSIONS

This study emphasises how cold weather is responsible for most part of the temperature-related CVD death burden. Our results may have important implications for the development of policies to reduce CVD mortality from extreme temperatures.

Assessment of Short- and Long-Term Mortality Displacement in Heat-Related Deaths in Brisbane, Australia, 1996-2004

BACKGROUND

Mortality displacement (or "harvesting") has been identified as a key issue in the assessment of the temperature-mortality relationship. However, only a few studies have addressed the "harvesting" issue and findings have not been consistent.

OBJECTIVES

We examined the potential impact of both short- and long-term harvesting effects on heat-related deaths in Brisbane, Australia.

METHODS

We collected data on daily counts of deaths (nonaccidental, cardiovascular, and respiratory), weather, and air pollution in Brisbane from 1 January 1996 to 30 November 2004. We estimated heat-related deaths, identified potential short-term mortality displacement, and assessed how and to what extent the impact of summer temperature on mortality was modified by mortality in the previous winter using a Poisson time-series regression combined with distributed lag nonlinear model (DLNM).

RESULTS

There were significant associations between temperature and each mortality outcome in summer. We found evidence of short-term mortality displacement for respiratory mortality, and evidence of longer-term mortality displacement for nonaccidental and cardiovascular mortality when the preceding winter's mortality was low. The estimated heat effect on mortality was generally stronger when the preceding winter mortality level was low. For example, we estimated a 22% increase in nonaccidental mortality (95% CI: 14, 30) with a 1°C increase in mean temperature above a 28°C threshold in summers that followed a winter with low mortality, compared with 12% (95% CI: 7, 17) following a winter with high mortality. The short- and long-term mortality displacement appeared to jointly influence the assessment of heat-related deaths.

CONCLUSIONS

We found evidence of both short- and long-term harvesting effects on heat-related mortality in Brisbane, Australia. Our finding may clarify temperature-related health risks and inform effective public health interventions to manage the health impacts of climate change.

Clarifying life lost due to cold and heat: a new approach using annual time series

OBJECTIVE

To clarify whether deaths associated with hot and cold days are among the frail who would have died anyway in the next few weeks or months.

DESIGN

Time series regression analysis of annual deaths in relation to annual summaries of cold and heat.

SETTING

London, UK.

PARTICIPANTS

3 530 280 deaths from all natural causes among London residents between October 1949 and September 2006.

MAIN OUTCOME MEASURES

Change in annual risk of death (all natural cause, cardiovascular and respiratory) associated with each additional 1°C of average cold (or heat) below (above) the threshold (18°C) across each year.

RESULTS

Cold years were associated with increased deaths from all causes. For each additional 1° of cold across the year, all-cause mortality increased by 2.3% (95% CI 0.7% to 3.8%), after adjustment for influenza and secular trends. The estimated association between hot years and all-cause mortality was very imprecise and thus inconclusive (effect estimate 1.7%, -2.9% to 6.5%). These estimates were broadly robust to changes in the way temperature and trend were modelled. Estimated risk increments using weekly data but otherwise comparable were cold: 2.0% (2.0% to 2.1%) and heat: 3.9% (3.4% to 3.8%).

CONCLUSIONS

In this London annual series, we saw an association of cold with mortality which was broadly similar in magnitude to that found in published daily studies and our own weekly analysis, suggesting that most deaths due to cold were among individuals who would not have died in the next 6 months. The estimated association with heat was imprecise, with the CI including magnitudes found in daily studies but also including zero.

The association between temperature and mortality in tropical middle income Thailand from 1999 to 2008

We have investigated the association between tropical weather condition and age-sex adjusted death rates (ADR) in Thailand over a 10-year period from 1999 to 2008. Population, mortality, weather and air pollution data were obtained from four national databases. Alternating multivariable fractional polynomial (MFP) regression and stepwise multivariable linear regression analysis were used to sequentially build models of the associations between temperature variable and deaths, adjusted for the effects and interactions of age, sex, weather (6 variables), and air pollution (10 variables). The associations are explored and compared among three seasons (cold, hot and wet months) and four weather zones of Thailand (the North, Northeast, Central, and South regions). We found statistically significant associations between temperature and mortality in Thailand. The maximum temperature is the most important variable in predicting mortality. Overall, the association is nonlinear U-shape and 31 °C is the minimum-mortality temperature in Thailand. The death rates increase when maximum temperature increase with the highest rates in the North and Central during hot months. The final equation used in this study allowed estimation of the impact of a 4 °C increase in temperature as projected for Thailand by 2100; this analysis revealed that the heat-related deaths will increase more than the cold-related deaths avoided in the hot and wet months, and overall the net increase in expected mortality by region ranges from 5 to 13 % unless preventive measures were adopted. Overall, these results are useful for health impact assessment for the present situation and future public health implication of global climate change for tropical Thailand.

The characteristic of heat wave effects on coronary heart disease mortality in Beijing, China: a time series study

Background

There is limited evidence for the impacts of heat waves on coronary heart disease (CHD) mortality in Beijing, capital city of China.

Objectives

We aimed to find a best heat wave definition for CHD mortality; and explore the characteristic of heat wave effects on CHD in Beijing, China.

Methods

We obtained daily data on weather and CHD mortality in Beijing for years 2000–2011. A quasi-Poisson regression model was used to assess the short-term impact of heat waves on CHD mortality in hot season (May–September), while controlling for relative humidity, day of the week, long-term trend and season. We compared 18 heat wave definitions by combining heat wave thresholds (87.5^th, 90.0^th, 92.5^th, 95^th, 97.5^th, and 99^th percentile of daily mean temperature) with different duration days (≥ 2 to ≥ 4 days), using Akaike information criterion for quasi-Poisson. We examined whether heat wave effects on CHD mortality were modified by heat wave duration and timing.

Results

Heat wave definition using 97.5^th percentile of daily mean temperature (30.5 °C) and duration ≥ 2 days produced the best model fit. Based on this heat wave definition, we found that men and elderly were sensitive to the first heat waves of the season, while women and young were sensitive to the second heat waves. In general, the longer duration of heat waves increased the risks of CHD mortality more than shorter duration for elderly. The first two days of heat waves had the highest impact on CHD mortality. Women and elderly were at higher risks than men and young when exposed to heat waves, but the effect differences were not statistically significant.

Conclusions

Heat waves had significant impact on CHD mortality. This finding may have implications for policy making towards protecting human health from heat waves.

The impact of the February 2012 cold spell on health in Italy using surveillance data

In February 2012 Italy was hit by an exceptional cold spell with extremely low temperatures and heavy snowfall. The aim of this work is to estimate the impact of the cold spell on health in the Italian cities using data from the rapid surveillance systems. In Italy, a national mortality surveillance system has been operational since 2004 in 34 cities for the rapid monitoring of daily mortality. Data from this system were used to evaluate the impact of the February 2012 cold spell on mortality shortly after the occurrence of the event. Furthermore, a cause-specific analysis was conducted in Roma using the Regional Mortality Registry and the emergency visits (ER) surveillance system. Cold spell episodes were defined as days when mean temperatures were below the 10^th percentile of February distribution for more than three days. To estimate the impact of the cold spell, excess mortality was calculated as the difference between observed and daily expected values. An overall 1578 (+25%) excess deaths among the 75+ age group was recorded in the 14 cities that registered a cold spell in February 2012. A statistically significant excess in mortality was observed in several cities ranging from +22% in Bologna to +58% in Torino. Cause-specific analysis conducted in Roma showed a statistically significant excess in mortality among the 75+ age group for respiratory disease (+64%), COPD (+57%), cardiovascular disease +20% ischemic heart disease (14%) and other heart disease (+33%). Similar results were observed for ER visits. Surveillance systems need to become are a key component of prevention plans as they can help improve public health response and are a valid data source to rapidly quantify the impact on health. Cold-related mortality is still an important issue and should not be underestimated by public health Authorities.

Improving the estimation of influenza-related mortality over a seasonal baseline

BACKGROUND

Existing methods for estimation of mortality attributable to influenza are limited by methodological and data uncertainty. We have used proxies for disease incidence of the three influenza cocirculating subtypes (A/H3N2, A/H1N1, and B) that combine data on influenza-like illness consultations and respiratory specimen testing to estimate influenza-associated mortality in the United States between 1997 and 2007.

METHODS

Weekly mortality rate for several mortality causes potentially affected by influenza was regressed linearly against subtype-specific influenza incidence proxies, adjusting for temporal trend and seasonal baseline, modeled by periodic cubic splines.

RESULTS

Average annual influenza-associated mortality rates per 100,000 individuals were estimated for the following underlying causes of death: for pneumonia and influenza, 1.73 (95% confidence interval = 1.53-1.93); for chronic lower respiratory disease, 1.70 (1.48-1.93); for all respiratory causes, 3.58 (3.04-4.14); for myocardial infarctions, 1.02 (0.85-1.2); for ischemic heart disease, 2.7 (2.23-3.16); for heart disease, 3.82 (3.21-4.4); for cerebrovascular deaths, 0.65 (0.51-0.78); for all circulatory causes, 4.6 (3.79-5.39); for cancer, 0.87 (0.68-1.05); for diabetes, 0.33 (0.26-0.39); for renal disease, 0.19 (0.14-0.24); for Alzheimer disease, 0.41 (0.3-0.52); and for all causes, 11.92 (10.17-13.67). For several underlying causes of death, baseline mortality rates changed after the introduction of the pneumococcal conjugate vaccine.

CONCLUSIONS

The proposed methodology establishes a linear relation between influenza incidence proxies and excess mortality, rendering temporally consistent model fits, and allowing for the assessment of related epidemiologic phenomena such as changes in mortality baselines.

Temperature and cardiovascular and respiratory mortality in desert climate. A case study of Kerman, Iran

Many studies have suggested that cardiovascular and respiratory disease mortality may change with fluctuations in temperature. In this study the relation between temperature and mortality has been studied in a city with desert climate. Four years data on daily temperature, cardiovascular, respiratory mortality and air pollution was acquired for Kerman, Iran. Time series, regression and correlation analyses were performed. Results showed an inverse relationship between mortality and temperature in Kerman, in which decreases in temperature were associated with increases in mortality. This pattern is similar to some foreign studies which show acclimatization of people living in southern warmer climates and less negative effects of warm temperatures. Among the pollutants only dust (p=0.003) and SO2 (p<0.001) showed a positive correlation with respiratory mortality.

High temperatures-related elderly mortality varied greatly from year to year: important information for heat-warning systems

We examined the variation in association between high temperatures and elderly mortality (age ≥ 75 years) from year to year in 83 US cities between 1987 and 2000. We used a Poisson regression model and decomposed the mortality risk for high temperatures into: a "main effect" due to high temperatures using lagged non-linear function, and an "added effect" due to consecutive high temperature days. We pooled yearly effects across both regional and national levels. The high temperature effects (both main and added effects) on elderly mortality varied greatly from year to year. In every city there was at least one year where higher temperatures were associated with lower mortality. Years with relatively high heat-related mortality were often followed by years with relatively low mortality. These year to year changes have important consequences for heat-warning systems and for predictions of heat-related mortality due to climate change.

Daily average temperature and mortality among the elderly: a meta-analysis and systematic review of epidemiological evidence

The impact of climate change on the health of vulnerable groups such as the elderly has been of increasing concern. However, to date there has been no meta-analysis of current literature relating to the effects of temperature fluctuations upon mortality amongst the elderly. We synthesised risk estimates of the overall impact of daily mean temperature on elderly mortality across different continents. A comprehensive literature search was conducted using MEDLINE and PubMed to identify papers published up to December 2010. Selection criteria including suitable temperature indicators, endpoints, study-designs and identification of threshold were used. A two-stage Bayesian hierarchical model was performed to summarise the percent increase in mortality with a 1°C temperature increase (or decrease) with 95% confidence intervals in hot (or cold) days, with lagged effects also measured. Fifteen studies met the eligibility criteria and almost 13 million elderly deaths were included in this meta-analysis. In total, there was a 2-5% increase for a 1°C increment during hot temperature intervals, and a 1-2 % increase in all-cause mortality for a 1°C decrease during cold temperature intervals. Lags of up to 9 days in exposure to cold temperature intervals were substantially associated with all-cause mortality, but no substantial lagged effects were observed for hot intervals. Thus, both hot and cold temperatures substantially increased mortality among the elderly, but the magnitude of heat-related effects seemed to be larger than that of cold effects within a global context.

Climate change and future temperature-related mortality in 15 Canadian cities

The environmental changes caused by climate change represent a significant challenge to human societies. One part of this challenge will be greater heat-related mortality. Populations in the northern hemisphere will experience temperature increases exceeding the global average, but whether this will increase or decrease total temperature-related mortality burdens is debated. Here, we use distributed lag modeling to characterize temperature-mortality relationships in 15 Canadian cities. Further, we examine historical trends in temperature variation across Canada. We then develop city-specific general linear models to estimate change in high- and low-temperature-related mortality using dynamically downscaled climate projections for four future periods centred on 2040, 2060 and 2080. We find that the minimum mortality temperature is frequently located at approximately the 75th percentile of the city's temperature distribution, and that Canadians currently experience greater and longer lasting risk from cold-related than heat-related mortality. Additionally, we find no evidence that temperature variation is increasing in Canada. However, the projected increased temperatures are sufficient to change the relative levels of heat- and cold-related mortality in some cities. While most temperature-related mortality will continue to be cold-related, our models predict that higher temperatures will increase the burden of annual temperature-related mortality in Hamilton, London, Montreal and Regina, but result in slight to moderate decreases in the burden of mortality in the other 11 cities investigated.

The effect of various temperature indicators on different mortality categories in a subtropical city of Brisbane, Australia

BACKGROUND

The relationship between temperature and mortality has been explored for decades and many temperature indicators have been applied separately. However, few data are available to show how the effects of different temperature indicators on different mortality categories, particularly in a typical subtropical climate.

OBJECTIVE

To assess the associations between various temperature indicators and different mortality categories in Brisbane, Australia during 1996-2004.

METHODS

We applied two methods to assess the threshold and temperature indicator for each age and death groups: mean temperature and the threshold assessed from all cause mortality was used for all mortality categories; the specific temperature indicator and the threshold for each mortality category were identified separately according to the minimisation of AIC. We conducted polynomial distributed lag non-linear model to identify effect estimates in mortality with one degree of temperature increase (or decrease) above (or below) the threshold on current days and lagged effects using both methods.

RESULTS

Akaike's Information Criterion was minimized when mean temperature was used for all non-external deaths and deaths from 75 to 84 years; when minimum temperature was used for deaths from 0 to 64 years, 65-74 years, ≥ 85 years, and from the respiratory diseases; when maximum temperature was used for deaths from cardiovascular diseases. The effect estimates using certain temperature indicators were similar as mean temperature both for current day and lag effects.

CONCLUSION

Different age groups and death categories were sensitive to different temperature indicators. However, the effect estimates from certain temperature indicators did not significantly differ from those of mean temperature.

Effect of previous-winter mortality on the association between summer temperature and mortality in South Korea

BACKGROUND

It has recently been postulated that low mortality levels in the previous winter may increase the proportion of vulnerable individuals in the pool of people at risk of heat-related death during the summer months.

OBJECTIVES

We explored the sensitivity of heat-related mortality in summer (June-August) to mortality in the previous winter (December-February) in Seoul, Daegu, and Incheon in South Korea, from 1992 through 2007, excluding the summer of 1994.

METHODS

Poisson regression models adapted for time-series data were used to estimate associations between a 1 °C increase in average summer temperature (on the same day and the previous day) above thresholds specific for city, age, and cause of death, and daily mortality counts. Effects were estimated separately for summers preceded by winters with low and high mortality, with adjustment for secular trends.

RESULTS

Temperatures above city-specific thresholds were associated with increased mortality in all three cities. Associations were stronger in summers preceded by winters with low versus high mortality levels for all nonaccidental deaths and, to a lesser extent, among persons ≥ 65 years of age. Effect modification by previous-winter mortality was not evident when we restricted deaths to cardiovascular disease outcomes in Seoul.

CONCLUSIONS

Our results suggest that low winter all-cause mortality leads to higher mortality during the next summer. Evidence of a relation between increased summer heat-related mortality and previous wintertime deaths has the potential to inform public health efforts to mitigate effects of hot weather.

Health effects of hot weather: from awareness of risk factors to effective health protection

Because of the increasing concerns about climate change and deadly heatwaves in the past, the health effects of hot weather are fast becoming a global public health challenge for the 21st century. Some cities across the world have introduced public health protection measures, with the timely provision of appropriate home-based prevention advice to the general public being the most crucial point of intervention. In this Review, we report current epidemiological and physiological evidence about the range of health effects associated with hot weather, and draw attention to the interplay between climate factors, human susceptibility, and adaptation measures that contribute to heat burdens. We focus on the evidence base for the most commonly provided heat-protection advice, and make recommendations about the optimum clinical and public health practice that are expected to reduce health problems associated with current and future hot weather.