Association of mortality with high temperatures in a temperate climate: England and Wales

Methods to Estimate Acclimatization to Urban Heat Island Effects on Heat- and Cold-Related Mortality

BACKGROUND

Investigators have examined whether heat mortality risk is increased in neighborhoods subject to the urban heat island (UHI) effect but have not identified degrees of difference in susceptibility to heat and cold between cool and hot areas, which we call acclimatization to the UHI.

OBJECTIVES

We developed methods to examine and quantify the degree of acclimatization to heat- and cold-related mortality in relation to UHI anomalies and applied these methods to London, UK.

METHODS

Case-crossover analyses were undertaken on 1993-2006 mortality data from London UHI decile groups defined by anomalies from the London average of modeled air temperature at a 1-km grid resolution. We estimated how UHI anomalies modified excess mortality on cold and hot days for London overall and displaced a fixed-shape temperature-mortality function ("shifted spline" model). We also compared the observed associations with those expected under no or full acclimatization to the UHI.

RESULTS

The relative risk of death on hot versus normal days differed very little across UHI decile groups. A 1°C UHI anomaly multiplied the risk of heat death by 1.004 (95% CI: 0.950, 1.061) (interaction rate ratio) compared with the expected value of 1.070 (1.057, 1.082) if there were no acclimatization. The corresponding UHI interaction for cold was 1.020 (0.979, 1.063) versus 1.030 (1.026, 1.034) (actual versus expected under no acclimatization, respectively). Fitted splines for heat shifted little across UHI decile groups, again suggesting acclimatization. For cold, the splines shifted somewhat in the direction of no acclimatization, but did not exclude acclimatization.

CONCLUSIONS

We have proposed two analytical methods for estimating the degree of acclimatization to the heat- and cold-related mortality burdens associated with UHIs. The results for London suggest relatively complete acclimatization to the UHI effect on summer heat-related mortality, but less clear evidence for cold-related mortality.

CITATION

Milojevic A, Armstrong BG, Gasparrini A, Bohnenstengel SI, Barratt B, Wilkinson P. 2016. Methods to estimate acclimatization to urban heat island effects on heat- and cold-related mortality. Environ Health Perspect 124:1016-1022; http://dx.doi.org/10.1289/ehp.1510109.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CITATION

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

Mortality during the 2013 heatwave in England--How did it compare to previous heatwaves? A retrospective observational study

Heatwaves are predicted to increase in frequency and intensity as a result of climate change. The health impacts of these events can be significant, particularly for vulnerable populations when mortality can occur. England experienced a prolonged heatwave in summer 2013. Daily age-group and region-specific all-cause excess mortality during summer 2013 and previous heatwave periods back to 2003 was determined using the same linear regression model and heatwave definition to estimate impact and place observations from 2013 in context. Predicted excess mortality due to heat during this period was also independently estimated. Despite a sustained heatwave in England in 2013, the impact on mortality was considerably less than expected; a small cumulative excess of 195 deaths (95% confidence interval -87 to 477) in 65+ year olds and 106 deaths (95% CI -22 to 234) in <65 year olds was seen, nearly a fifth of excess deaths predicted based on observed temperatures. This impact was also less than seen in 2006 (2323 deaths) and 2003 (2234 deaths), despite a similarly prolonged period of high temperatures. The reasons for this are unclear and further work needs to be done to understand this and further clarify the predicted impact of increases in temperature.

Multiple Trigger Points for Quantifying Heat-Health Impacts: New Evidence from a Hot Climate

BACKGROUND

Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

OBJECTIVES

This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.

METHODS

Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature-health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different "trigger points" at which heat-health intervention measures might be activated.

RESULTS

We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22 °C) across multiple health events and diagnoses.

CONCLUSION

Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

How to estimate exposure when studying the temperature-mortality relationship? A case study of the Paris area

Time series studies assessing the effect of temperature on mortality generally use temperatures measured by a single weather station. In the Paris region, there is a substantial measurement network, and a variety of exposure indicators created from multiple stations can be tested. The aim of this study is to test the influence of exposure indicators on the temperature-mortality relationship in the Paris region. The relationship between temperature and non-accidental mortality was assessed based on a time series analysis using Poisson regression and a generalised additive model. Twenty-five stations in Paris and its three neighbouring departments were used to create four exposure indicators. These indicators were (1) the temperature recorded by one reference station, (2) a simple average of the temperatures of all stations, (3) an average weighted on the departmental population and (4) a classification of the stations based on land use and an average weighted on the population in each class. The relative risks and the Akaike criteria were similar for all the exposure indicators. The estimated temperature-mortality relationship therefore did not appear to be significantly affected by the indicator used, regardless of study zone (departments or region) or age group. The increase in temperatures from the 90(th) to the 99(th) percentile of the temperature distribution led to a significant increase in mortality over 75 years (RR = 1.10 [95% CI, 1.07; 1.14]). Conversely, the decrease in temperature between the 10(th) and 1(st) percentile had a significant effect on the mortality under 75 years (RR = 1.04 [95% CI, 1.01; 1.06]). In the Paris area, there is no added value in taking multiple climatic stations into account when estimating exposure in time series studies. Methods to better represent the subtle temperature variations in densely populated areas in epidemiological studies are needed.

Impact of climate change on the domestic indoor environment and associated health risks in the UK

There is growing evidence that projected climate change has the potential to significantly affect public health. In the UK, much of this impact is likely to arise by amplifying existing risks related to heat exposure, flooding, and chemical and biological contamination in buildings. Identifying the health effects of climate change on the indoor environment, and risks and opportunities related to climate change adaptation and mitigation, can help protect public health. We explored a range of health risks in the domestic indoor environment related to climate change, as well as the potential health benefits and unintended harmful effects of climate change mitigation and adaptation policies in the UK housing sector. We reviewed relevant scientific literature, focusing on housing-related health effects in the UK likely to arise through either direct or indirect mechanisms of climate change or mitigation and adaptation measures in the built environment. We considered the following categories of effect: (i) indoor temperatures, (ii) indoor air quality, (iii) indoor allergens and infections, and (iv) flood damage and water contamination. Climate change may exacerbate health risks and inequalities across these categories and in a variety of ways, if adequate adaptation measures are not taken. Certain changes to the indoor environment can affect indoor air quality or promote the growth and propagation of pathogenic organisms. Measures aimed at reducing greenhouse gas emissions have the potential for ancillary public health benefits including reductions in health burdens related heat and cold, indoor exposure to air pollution derived from outdoor sources, and mould growth. However, increasing airtightness of dwellings in pursuit of energy efficiency could also have negative effects by increasing concentrations of pollutants (such as PM2.5, CO and radon) derived from indoor or ground sources, and biological contamination. These effects can largely be ameliorated by mechanical ventilation with heat recovery (MVHR) and air filtration, where such solution is feasible and when the system is properly installed, operated and maintained. Groups at high risk of these adverse health effects include the elderly (especially those living on their own), individuals with pre-existing illnesses, people living in overcrowded accommodation, and the socioeconomically deprived. A better understanding of how current and emerging building infrastructure design, construction, and materials may affect health in the context of climate change and mitigation and adaptation measures is needed in the UK and other high income countries. Long-term, energy efficient building design interventions, ensuring adequate ventilation, need to be promoted.

The Impact of Heat on an Emergency Department in Italy: Attributable Visits among Children, Adults, and the Elderly during the Warm Season

Introduction

Recent studies suggest that heat is associated with an increase in the number of ambulance calls and emergency department visits. We investigated the association between heat and daily number of emergency department visits at the University Hospital of Verona during the warm seasons 2011–2012 and we assessed the magnitude of the impact in terms of attributable events, focusing on the role of age and triage codification.

Materials and methods

We used a Poisson model to analyse the association between daily number of visits and daily mean apparent temperature, accounting for air pollution level and seasonality. The analyses were stratified by age group and were performed both on the total number of emergency department visits and on the subsample of high-priority visits. Impact estimates were obtained only for this subsample, using a Monte Carlo approach to account for sampling variability. Number of attributable events and attributable community rate were calculated.

Results

We found a positive and immediate association between event occurrence and mean apparent temperatures exceeding a threshold located around 28–29°C. The estimated percent change in the total number of visits per 1°C increase of exposure above the threshold was equal to 3.75 (90% CI: 3.01; 4.49). Focusing only on high-priority visits, the estimated percent change was larger and the greatest effect was among children. We estimated that apparent temperatures above the threshold were responsible for 1177 high-priority visits during the study period. Due to the record high temperatures observed in 2012 in Italy and in Europe, the impact in 2012 was much larger than in 2011, and consisted in 34 high-priority visits every 10000 children, 30 every 10000 people aged 15–64, and 38 every 10000 people aged 65 and over.

Discussion

Our results indicate that heat affects not only the elderly, but also children and non-elderly adults, stressing the need for developing public health preparedness plans for the entire community.

Improving the Health Forecasting Alert System for Cold Weather and Heat-Waves In England: A Proof-of-Concept Using Temperature-Mortality Relationships

OBJECTIVES

In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office's (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings.

METHOD

The prototype health forecasting alert system introduces an "impact vs likelihood matrix" for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system.

CONCLUSIONS

The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.

Distinct atmospheric patterns and associations with acute heat-induced mortality in five regions of England

The main objective of this paper was to identify possible acute heat-induced summer mortality in five regions of England namely the Yorkshire and the Humber, West Midlands, North East, North West and South East regions and reveal associations with specific air flows. For this purpose, backward air mass trajectories corresponding to daily episodes of increased temperatures were produced and divided to clusters, in order to define atmospheric pathways associated with warm air mass intrusions. A statistically significant at 95 % confidence interval increase in daily total mortality (DTMORT) was observed during the selected episodes at all five regions and thus, heat-induced mortality was indicated. The calculated raise was more intense in the West Midlands, North West and South East regions, whereas the results in the North East and Yorkshire and the Humber regions were less evident. Large fractions of thermal episodes, elevated average temperature values and higher average DTMORT levels were primarily associated with the short-medium range South West (SW) and/or East-South East (E-SE) trajectory clusters, suggesting relations among heat-induced mortality and specific atmospheric circulations. Short-medium length of SW and E-SE airflows, calculated by an application of Haversine formula along the centroid trajectory of each cluster, implies the arrival of slow moving air masses. Atmospheric stagnation could enhance human thermal stress due to low wind speed.

Short-Term Effect of Ambient Temperature and the Risk of Stroke: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

The relationship between stroke and short-term temperature changes remains controversial. Therefore, we conducted a systematic review and meta-analysis to investigate the association between stroke and both high and low temperatures, and health assessment.

METHODS

We searched PubMed, Embase, Cochrane, China National Knowledge Infrastructure (CNKI) and Wanfang Data up to 14 September 2014. Study selection, quality assessment, and author-contractions were steps before data extraction. We converted all estimates effects into relative risk (RR) per 1 °C increase/decrease in temperature from 75th to 99th or 25th to 1st percentiles, then conducted meta-analyses to combine the ultimate RRs, and assessed health impact among the population.

RESULTS

20 articles were included in the final analysis. The overall analysis showed a positive relationship between 1 °C change and the occurrence of major adverse cerebrovascular events (MACBE), 1.1% (95% confidence intervals (CI), 0.6 to 1.7) and 1.2% (95% CI, 0.8 to 1.6) increase for hot and cold effects separately. The same trends can be found in both effects of mortality and the cold effect for morbidity. Hot temperature acted as a protective factor of hemorrhage stroke (HS), -1.9% (95% CI, -2.8 to -0.9), however, it acted as a risk factor for ischemic stroke (IS), 1.2% (95% CI, 0.7 to 1.8).

CONCLUSION

Short-term changes of both low and high temperature had statistically significant impacts on MACBE.

Global variation in the effects of ambient temperature on mortality: a systematic evaluation

BACKGROUND

Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously.

METHODS

We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country.

RESULTS

The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long.

CONCLUSIONS

People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context 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.

How much does latitude modify temperature-mortality relationship in 13 eastern US cities?

Although several studies have documented that latitude might be an effect modifier of the association between temperature and mortality, little is known about how much latitude modifies the temperature-mortality relationship. In this study, we examined this research question using a distributed lag non-linear model and meta-regression analysis based on data from 13 large cities of eastern US from the US National Morbidity, Mortality, and Air Pollution Study. We found that cold effects lasted about 1 month while hot effects were acute and short-term. Meta-regression analysis showed that latitude modified both the cold and hot effects with statistical significance. The cold effect decreased with the latitude increment, with -0.11 % change of mortality effect for 1° increment, while the hot effect increased with the latitude increment, with 0.18 % change of mortality effect for 1° increment. This finding indicates the importance of latitude on temperature-related mortality risk, which is helpful for city to develop localized effective adaptation strategy in the context of climate change.

Heat-attributable deaths between 1992 and 2009 in Seoul, South Korea

BACKGROUND

Climate change may significantly affect human health. The possible effects of high ambient temperature must be better understood, particularly in terms of certain diseases' sensitivity to heat (as reflected in relative risks [RR]) and the consequent disease burden (number or fraction of cases attributable to high temperatures), in order to manage the threat.

PURPOSE

This study investigated the number of deaths attributable to abnormally high ambient temperatures in Seoul, South Korea, for a wide range of diseases.

METHOD

The relationship between mortality and daily maximum temperature using a generalized linear model was analyzed. The threshold temperature was defined as the 90th percentile of maximum daily temperatures. Deaths were classified according to ICD-10 codes, and for each disease, the RR and attributable fractions were determined. Using these fractions, the total number of deaths attributable to daily maximum temperatures above the threshold value, from 1992 to 2009, was calculated. Data analyses were conducted in 2012-2013.

RESULTS

Heat-attributable deaths accounted for 3,177 of the 271,633 deaths from all causes. Neurological (RR 1.07; 95% CI, 1.04-1.11) and mental and behavioral disorders (RR 1.04; 95% CI, 1.01-1.07) had relatively high increases in the RR of mortality. The most heat-sensitive diseases (those with the highest RRs) were not the diseases that caused the largest number of deaths attributable to high temperatures.

CONCLUSION

This study estimated RRs and deaths attributable to high ambient temperature for a wide variety of diseases. Prevention-related policies must account for both particular vulnerabilities (heat-sensitive diseases with high RRs) and the major causes of the heat mortality burden (common conditions less sensitive to high temperatures).

The temperature-mortality relationship in China: An analysis from 66 Chinese communities

BACKGROUND

Previous studies examining temperature-mortality associations in China focused on a single city or a small number of cities. A multi-city study covering different climatic zones is necessary to better understand regional differences in temperature risk on mortality in China.

METHODS

Sixty-six communities from 7 regions across China were included in this study. We first used a Distributed Lag Non-linear Model (DLNM) to estimate community-specific effects of temperature on non-accidental mortality during 2006-2011. A multivariate meta-analysis was then applied to pool the estimates of community-specific effects.

RESULTS

A U-shaped curve was observed between temperature and mortality at the national level in China, indicating both low and high temperatures were associated with increased mortality risk. The overall threshold was at about the 75th percentile of the pooled temperature distribution. The relative risk was 1.61 (95% CI: 1.48-1.74) for extremely cold temperature (1st percentile of temperature), and 1.21 (95% CI: 1.10-1.34) for extreme hot temperature (99th percentile of temperature) at lag0-21 days. The temperature-mortality relationship is different for different regions. Compared with north China, south China had a higher minimum mortality temperature (MMT), and there was a larger cold effect in the more southern parts of China and a more pronounced hot effect in more northern parts.

CONCLUSIONS

Both cold and hot temperatures increase mortality risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.

Comparative assessment of the effects of climate change on heat- and cold-related mortality in the United Kingdom and Australia

BACKGROUND

High and low ambient temperatures are associated with increased mortality in temperate and subtropical climates. Temperature-related mortality patterns are expected to change throughout this century because of climate change.

OBJECTIVES

We compared mortality associated with heat and cold in UK regions and Australian cities for current and projected climates and populations.

METHODS

Time-series regression analyses were carried out on daily mortality in relation to ambient temperatures for UK regions and Australian cities to estimate relative risk functions for heat and cold and variations in risk parameters by age. Excess deaths due to heat and cold were estimated for future climates.

RESULTS

In UK regions, cold-related mortality currently accounts for more than one order of magnitude more deaths than heat-related mortality (around 61 and 3 deaths per 100,000 population per year, respectively). In Australian cities, approximately 33 and 2 deaths per 100,000 population are associated every year with cold and heat, respectively. Although cold-related mortality is projected to decrease due to climate change to approximately 42 and 19 deaths per 100,000 population per year in UK regions and Australian cities, heat-related mortality is projected to increase to around 9 and 8 deaths per 100,000 population per year, respectively, by the 2080s, assuming no changes in susceptibility and structure of the population.

CONCLUSIONS

Projected changes in climate are likely to lead to an increase in heat-related mortality in the United Kingdom and Australia over this century, but also to a decrease in cold-related deaths. Future temperature-related mortality will be amplified by aging populations. Health protection from hot weather will become increasingly necessary in both countries, while protection from cold weather will be still needed.

Effect of atmospheric mixing layer depth variations on urban air quality and daily mortality during Saharan dust outbreaks

Several epidemiological studies have shown that the outbreaks of Saharan dust over southern European countries can cause negative health effects. The reasons for the increased toxicity of airborne particles during dust storms remain to be understood although the presence of biogenic factors carried by dust particles and the interaction between dust and man-made air pollution have been hypothesized as possible causes. Intriguingly, recent findings have also demonstrated that during Saharan dust outbreaks the local man-made particulates can have stronger effects on health than during days without outbreaks. We show that the thinning of the mixing layer (ML) during Saharan dust outbreaks, systematically described here for the first time, can trigger the observed higher toxicity of ambient local air. The mixing layer height (MLH) progressively reduced with increasing intensity of dust outbreaks thus causing a progressive accumulation of anthropogenic pollutants and favouring the formation of new fine particles or specific relevant species likely from condensation of accumulated gaseous precursors on dust particles surface. Overall, statistically significant associations of MLH with all-cause daily mortality were observed. Moreover, as the MLH reduced, the risk of mortality associated with the same concentration of particulate matter increased due to the observed pollutant accumulation. The association of MLH with daily mortality and the effect of ML thinning on particle toxicity exacerbated when Saharan dust outbreaks occurred suggesting a synergic effect of atmospheric pollutants on health which was amplified during dust outbreaks. Moreover, the results may reflect higher toxicity of primary particles which predominate on low MLH days.

Characterizing the effect of summer temperature on heatstroke-related emergency ambulance dispatches in the Kanto area of Japan

Despite rising concern on the impact of heat on human health, the risk of high summer temperature on heatstroke-related emergency dispatches is not well understood in Japan. A time-series study was conducted to examine the association between apparent temperature and daily heatstroke-related ambulance dispatches (HSAD) within the Kanto area of Japan. A total of 12,907 HSAD occurring from 2000 to 2009 in five major cities-Saitama, Chiba, Tokyo, Kawasaki, and Yokohama-were analyzed. Generalized additive models and zero-inflated Poisson regressions were used to estimate the effects of daily maximum three-hour apparent temperature (AT) on dispatch frequency from May to September, with adjustment for seasonality, long-term trend, weekends, and public holidays. Linear and non-linear exposure effects were considered. Effects on days when AT first exceeded its summer median were also investigated. City-specific estimates were combined using random effects meta-analyses. Exposure-response relationship was found to be fairly linear. Significant risk increase began from 21 °C with a combined relative risk (RR) of 1.22 (95% confidence interval, 1.03-1.44), increasing to 1.49 (1.42-1.57) at peak AT. When linear exposure was assumed, combined RR was 1.43 (1.37-1.50) per degree Celsius increment. Overall association was significant the first few times when median AT was initially exceeded in a particular warm season. More than two-thirds of these initial hot days were in June, implying the harmful effect of initial warming as the season changed. Risk increase that began early at the fairly mild perceived temperature implies the need for early precaution.

Effects of high summer temperatures on mortality in 50 Spanish cities

BACKGROUND

Periods of high temperature have been widely found to be associated with excess mortality but with variable relationships in different cities. How these specifics depend on climatic and other characteristics of cities is not well understood. We assess summer temperature-mortality relationships using data from 50 provincial capitals in Spain, during the period 1990-2004.

METHODS

Poisson time series regression analyses were applied to daily temperature and mortality data, adjusting for potential confounding seasonal factors. Associations of heat with mortality were summarised for each city as the risk increments at the 99th compared to the 90th percentiles of the whole-year temperature distributions, as predicted from spline curves.

RESULTS

Risk increments averaged 14.6% between both centiles, or 3.3% per 1 Celsius degree. Although risk increments varied substantially between cities, the range of temperature from the 90th to 99th centile was the only characteristic independently significantly associated with them. The heat increment did not depend on other city climatic, socio-demographic and geographic determinants.

CONCLUSIONS

Cities in Spain are partially adapted to high mean summer temperatures but not to high variation in summer temperatures.

Health impacts of heat in a changing climate: how can emerging science inform urban adaptation planning?

Extreme heat is one of the most important global causes of weather-related mortality, and climate change is leading to more frequent and intense heat waves. Recent epidemiologic findings on heat-related health impacts have reinforced our understanding of mortality impacts of extreme heat and have shown a range of impacts on morbidity outcomes including cardiovascular, respiratory and mental health responses. Evidence is also emerging on temporal trends towards decreasing exposure-response, probably reflecting autonomous population adaptation. Many cities are actively engaged in the development of heat adaptation plans to reduce future health impacts. Epidemiologic research into the evolution of local heat-health responses over time can greatly aid adaptation planning for heat, prevention of adverse health outcomes among vulnerable populations, as well as evaluation of new interventions. Such research will be facilitated by the formation of research partnerships involving epidemiologists, climate scientists, and local stakeholders.

Climate change effects on human health: projections of temperature-related mortality for the UK during the 2020s, 2050s and 2080s

BACKGROUND

The most direct way in which climate change is expected to affect public health relates to changes in mortality rates associated with exposure to ambient temperature. Many countries worldwide experience annual heat-related and cold-related deaths associated with current weather patterns. Future changes in climate may alter such risks. Estimates of the likely future health impacts of such changes are needed to inform public health policy on climate change in the UK and elsewhere.

METHODS

Time-series regression analysis was used to characterise current temperature-mortality relationships by region and age group. These were then applied to the local climate and population projections to estimate temperature-related deaths for the UK by the 2020s, 2050s and 2080s. Greater variability in future temperatures as well as changes in mean levels was modelled.

RESULTS

A significantly raised risk of heat-related and cold-related mortality was observed in all regions. The elderly were most at risk. In the absence of any adaptation of the population, heat-related deaths would be expected to rise by around 257% by the 2050s from a current annual baseline of around 2000 deaths, and cold-related mortality would decline by 2% from a baseline of around 41 000 deaths. The cold burden remained higher than the heat burden in all periods. The increased number of future temperature-related deaths was partly driven by projected population growth and ageing.

CONCLUSIONS

Health protection from hot weather will become increasingly necessary, and measures to reduce cold impacts will also remain important in the UK. The demographic changes expected this century mean that the health protection of the elderly will be vital.

Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

Reducing and meta-analysing estimates from distributed lag non-linear models

Background

The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for investigating simultaneously non-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimates of multi-parameter associations. However, the application of both methods in two-stage analyses is prevented by the high-dimensional definition of DLNMs.

Methods

In this contribution we propose a method to synthesize DLNMs to simpler summaries, expressed by a reduced set of parameters of one-dimensional functions, which are compatible with current multivariate meta-analytical techniques. The methodology and modelling framework are implemented in R through the packages dlnm and mvmeta.

Results

As an illustrative application, the method is adopted for the two-stage time series analysis of temperature-mortality associations using data from 10 regions in England and Wales. R code and data are available as supplementary online material.

Discussion and Conclusions

The methodology proposed here extends the use of DLNMs in two-stage analyses, obtaining meta-analytical estimates of easily interpretable summaries from complex non-linear and delayed associations. The approach relaxes the assumptions and avoids simplifications required by simpler modelling approaches.

A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana, 1995-2010

Introduction

Climate and weather variability can have significant health consequences of increased morbidity and mortality. However, today the impact of climate and weather variability, and consequentially, of climate change on population health in sub-Saharan Africa is not well understood. In this study, we assessed the association of daily temperature and precipitation with daily mortality by age and sex groups in Northern Ghana.

Methods

We analysed daily mortality and weather data from 1995 to 2010. We adopted a time-series Poisson regression approach to examine the short-term association of daily mean temperature and daily mean precipitation with daily mortality. We included time factors and daily lagged weather predictors. The correlation between lagged weather predictors was also considered.

Results

For all populations, a statistically significant association of mean daily temperature with mortality at lag days 0–1 was observed below and above the 25th (27.48°C) and 75th (30.68°C) percentiles (0.19%; 95% confidence interval CI: 0.05%, 0.21%) and (1.14%; 95% CI: 0.12%, 1.54%), respectively. We also observed a statistically significant association of mean daily temperature above 75th percentile at lag days 2–6 and lag days 7–13 (0.32%; 95% CI: 0.16%, 0.25%) and (0.31% 95% CI: 0.14%, 0.26%), respectively. A 10 mm increase in precipitation was significantly associated with a 1.71% (95% CI: 0.10%, 3.34.9%) increase in mortality for all ages and sex groups at lag days 2–6. Similar results were also observed at lag days 2–6 and 14–27 for males, 2.92% (95% CI: 0.80%, 5.09%) and 2.35% (95% CI: 0.28%, 4.45%).

Conclusion

Short-term weather variability is strongly associated with mortality in Northern Ghana. The associations appear to differ among different age and sex groups. The elderly and young children were found to be more susceptible to short-term temperature-related mortality. The association of precipitation with mortality is more pronounced at the short-term for all age and sex groups and in the medium short-term among males. Reducing exposure to extreme temperature, particularly among the elderly and young children, should reduce the number of daily deaths attributable to weather-related mortality.

High-temperature indices associated with mortality and outpatient visits: characterizing the association with elevated temperature

This study aimed to identify optimal high-temperature indices to predict risks of all-cause mortality and outpatient visits for subtropical islanders in warm seasons (May to October). Eight high-temperature indices, including three single measurements (average, maximum and minimum temperature) and five composite indices (heat index, humidex, temperature humidity index, apparent temperature and wet-bulb globe temperature), and their standardized Z scores, were used in distributed lag non-linear models. Cumulative 8-day (lag zero to seven days) relative risks (RRs) and 95% confidence intervals were estimated, 1 and 2 standardized deviations above the medium (i.e., at 84.1th and 97.7th percentile, respectively), by comparing with Z scores for the lowest risks of mortality and outpatient visits as references. Analyses were performed for Taipei in north, Central Taiwan and Southern Taiwan. Results showed that standardized Z-values of high-temperature indices associated with the lowest health risk were approximately 0 in Taipei and Central Taiwan, and -1 in Southern Taiwan. As the apparent temperature was at Z=2, the cumulative 8-day mortality risk increased significantly, by 23% in Taipei and 28% in Southern Taiwan, but not in Central Taiwan. The maximum temperature displayed consistently a high correlation with all-cause outpatient visits at Z=1; with the cumulative 8-day RRs for outpatient visits increased by 7%, 3%, and 4% in the three corresponding areas. In conclusion, this study has demonstrated methods to compare multiple high-temperature indices associated with all-cause mortality and outpatient visits for population residing in a subtropical island. Apparent temperature is an optimal indicator for predicting all-cause mortality risk, and maximum temperature is recommended to associate with outpatient visits. The impact of heat varied with study areas, evaluated health outcomes, and high-temperature indices. The increased extreme heat is associated with stronger risk for all-cause mortality than for outpatient visits.

Mortality on extreme heat days using official thresholds in Spain: a multi-city time series analysis

Background

The 2003 heat wave had a high impact on mortality in Europe, which made necessary to develop heat health watch warning systems. In Spain this was carried-out by the Ministry of Health in 2004, being based on exceeding of city-specific simultaneous thresholds of minimum and maximum daily temperatures. The aim of this study is to assess effectiveness of the official thresholds established by the Ministry of Health for each provincial capital city, by quantifying and comparing the short-term effects of above-threshold days on total daily mortality.

Methods

Total daily mortality and minimum and maximum temperatures for the 52 capitals of province in Spain were collected during summer months (June to September) for the study period 1995-2004. Data was analysed using GEE for Poisson regression. Relative Risk (RR) of total daily mortality was quantified for the current day of official thresholds exceeded.

Results

The number of days in which the thresholds were exceeded show great inconsistency, with provinces with great number of exceeded days adjacent to provinces that did not exceed or rarely exceeded. The average overall excess risk of dying during an extreme heat day was about 25% (RR = 1.24; 95% confidence interval (CI) = [1.19-1.30]). Relative risks showed a significant heterogeneity between cities (I² = 54.9%). Western situation and low mean summer temperatures were associated with higher relative risks, suggesting thresholds may have been set too high in these areas.

Conclusions

This study confirmed that extreme heat days have a considerable impact on total daily mortality in Spain. Official thresholds gave consistent relative risk in the large capital cities. However, in some other cities thresholds

Excess mortality related to seasonal influenza and extreme temperatures in Denmark, 1994-2010

Background

In temperate zones, all-cause mortality exhibits a marked seasonality, and one of the main causes of winter excess mortality is influenza. There is a tradition of using statistical models based on mortality from respiratory illnesses (Pneumonia and Influenza: PI) or all-cause mortality for estimating the number of deaths related to influenza. Different authors have applied different estimation methodologies. We estimated mortality related to influenza and periods with extreme temperatures in Denmark over the seasons 1994/95 to 2009/10.

Methods

We applied a multivariable time-series model with all-cause mortality as outcome, activity of influenza-like illness (ILI) and excess temperatures as explanatory variables, controlling for trend, season, age, and gender. Two estimates of excess mortality related to influenza were obtained: (1) ILI-attributable mortality modelled directly on ILI-activity, and (2) influenza-associated mortality based on an influenza-index, designed to mimic the influenza transmission.

Results

The median ILI-attributable mortality per 100,000 population was 35 (range 6 to 100) per season which corresponds to findings from comparable countries. Overall, 88% of these deaths occurred among persons ≥ 65 years of age. The median influenza-associated mortality per 100,000 population was 26 (range 0 to 73), slightly higher than estimates based on pneumonia and influenza cause-specific mortality as estimated from other countries. Further, there was a tendency of declining mortality over the years. The influenza A(H3N2) seasons of 1995/96 and 1998/99 stood out with a high mortality, whereas the A(H3N2) 2005/6 season and the 2009 A(H1N1) influenza pandemic had none or only modest impact on mortality. Variations in mortality were also related to extreme temperatures: cold winters periods and hot summers periods were associated with excess mortality.

Conclusion

It is doable to model influenza-related mortality based on data on all-cause mortality and ILI, data that are easily obtainable in many countries and less subject to bias and subjective interpretation than cause-of-death data. Further work is needed to understand the variations in mortality observed across seasons and in particular the impact of vaccination against influenza.