Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia

The spatial distribution of heat related hospitalizations and classification of the most dangerous heat events in California at a small-scale level

Many studies have explored the impact of extreme heat on health, but few have investigated localized heat-health outcomes across a wide area. We examined fine-scale variability in vulnerable areas, considering population distribution, local weather, and landscape characteristics. Using 36 different heat event definitions, we identified the most dangerous types of heat events based on minimum, maximum, and diurnal temperatures with varying thresholds and durations. Focusing on California's diverse climate, elevation, and population distribution, we analyzed hospital admissions for various causes of admission (2004-2013). Our matching approach identified vulnerable zip codes, even with small populations, on absolute and relative scales. Bayesian Hierarchical models leveraged spatial correlation. We ranked the 36 heat event types by attributable hospital admissions per zip code and provided code, simulated data, and an interactive web app for reproducibility. Our findings showed high variation in heat-related hospitalizations in coastal cities and substantial heat burdens in the Central Valley. Diurnal heat events had the greatest impact in the Central Valley, while nighttime extreme heat events drove burdens in the southeastern desert. This spatially informed approach guides local policies, prioritizing dangerous heat events to reduce the heat-health burden. The methodology is applicable to other regions, informing early warning systems and characterizing extreme heat impacts.

Spatio-temporal interpolation and delineation of extreme heat events in California between 2017 and 2021

Robust spatio-temporal delineation of extreme climate events and accurate identification of areas that are impacted by an event is a prerequisite for identifying population-level and health-related risks. In prior research, attributes such as temperature and humidity have often been linearly assigned to the population of the study unit from the closest weather station. This could result in inaccurate event delineation and biased assessment of extreme heat exposure. We have developed a spatio-temporal model to dynamically delineate boundaries for Extreme Heat Events (EHE) across space and over time, using a relative measure of Apparent Temperature (AT). Our surface interpolation approach offers a higher spatio-temporal resolution compared to the standard nearest-station (NS) assignment method. We show that the proposed approach can provide at least 80.8 percent improvement in identification of areas and populations impacted by EHEs. This improvement in average adjusts the misclassification of about one million Californians per day of an extreme event, who would be either unidentified or misidentified under EHEs between 2017 and 2021.

Space-time clusters of cardiovascular mortality and the role of heatwaves and cold spells in the city of São Paulo, Brazil

The effects extreme air temperature events are related with an increase in cardiovascular mortality among vulnerable groups worldwide. Therefore, we identify spatiotemporal mortality clusters associated with diseases of the cardiovascular system among people ≥ 65 years in São Paulo, from 2006 to 2015, and investigate whether high-risk mortality clusters occurred during or following extreme air temperature events. To detect the clusters, we used daily mortality data and a retrospective space-time scan analysis with a discrete Poisson model. Extreme air temperature events were defined by daily mean temperatures, below the 10th percentile for cold spells and above the 90th percentile for heatwaves, with two or more consecutive days. We found statistically significant high-risk mortality clusters located in the peripheral areas. The spatiotemporal clusters of risk areas for cardiovascular and ischemic heart disease occurred during or following cold spell events, whereas those for stroke and ischemic stroke events were related to heatwaves.

Effects of ambient temperature on mortality among elderly residents of Chengdu city in Southwest China, 2016-2020: a distributed-lag non-linear time series analysis

BACKGROUND

With complex changes in the global climate, it is critical to understand how ambient temperature affects health, especially in China. We aimed to assess the effects of temperature on daily mortality, including total non-accidental, cardiovascular disease (CVD), respiratory disease, cerebrovascular disease, and ischemic heart disease (IHD) mortality between 2016 and 2020 in Chengdu, China.

METHODS

We obtained daily temperature and mortality data for the period 2016-2020. A Poisson regression model combined with a distributed-lag nonlinear model was used to examine the association between temperature and daily mortality. We investigated the effects of individual characteristics by sex, age, education level, and marital status.

RESULTS

We found significant non-linear effects of temperature on total non-accidental, CVD, respiratory, cerebrovascular, and IHD mortality. Heat effects were immediate and lasted for 0-3 days, whereas cold effects persisted for 7-10 days. The relative risks associated with extreme high temperatures (99th percentile of temperature, 28 °C) over lags of 0-3 days were 1.22 (95% confidence interval [CI]: 1.17, 1.28) for total non-accidental mortality, 1.40 (95% CI: 1.30, 1.50) for CVD morality, 1.34 (95% CI: 1.24, 1.46) for respiratory morality, 1.33 (95% CI: 1.20, 1.47) for cerebrovascular mortality, and 1.38 (95% CI: 1.20, 1.58) for IHD mortality. The relative risks associated with extreme cold temperature (1st percentile of temperature, 3.0 °C) over lags of 0-14 days were 1.32 (95% CI: 1.19, 1.46) for total mortality, 1.45 (95% CI: 1.24, 1.68) for CVD morality, 1.28 (95% CI: 1.09, 1.50) for respiratory morality, 1.36 (95% CI: 1.09, 1.70) for cerebrovascular mortality, and 1.26 (95% CI: 0.95, 1.68) for IHD morality. We found that hot and cold affects were greater in those over 85 years of age, and that women, individuals with low education levels, and those who were widowed, divorced, or never married, were more vulnerable.

CONCLUSIONS

This study showed that exposure to hot and cold temperatures in Chengdu was associated with increased mortality, with people over 85 years old, women, those with low education levels, and unmarried individuals being more affected by hot and cold temperatures.

A spatiotemporal analysis of COVID-19 transmission in Jakarta, Indonesia for pandemic decision support

With 25% confirmed cases of the country's total number of coronavirus disease 2019 (COVID-19) on 31 January 2021, Jakarta has the highest confirmed cases of in Indonesia. The city holds a significant role as the centre of government and national economic activity for which pandemic have had a huge impact. Spatiotemporal analysis was employed to identify the current condition of disease transmission and to provide comprehensive information on the COVID-19 outbreak in Jakarta. We applied space-time analysis to visualise the pattern of COVID-19 hotspots in each time series. We also mapped area capacity of the referral hospitals covering the entire area of Jakarta to understand the hospital service range. This research was conducted in 4 stages: i) disease mapping; ii) spatial autocorrelation analysis; iii) space-time pattern analysis; and iv) areal capacity mapping. The analysis resulted in 144 sub-districts categorised as high vulnerability. Autocorrelation studies by Moran's I identified cluster patterns and the emerging hotspot results indicated successful interventions as the number of hotspots fell in the first period of social restrictions. The results presented should be beneficial for policy makers.

Human health outcomes at the neighbourhood scale implications: Elderly's heat-related cardiorespiratory mortality and its influencing factors

The excessively warm weather, especially in cities, can lead to several adverse impacts, including heat-related mortality, becoming an increasingly important public health issue. Previous studies on heat-related mortality have assessed risk factors at the municipal scale, missing the intra-urban variability in heat risk and vulnerability. The knowledge of the spatial intra-variability can help to design spatially targeted measures to better protect citizens' health. Through hot spot analysis, we identified the neighbourhood-scale spatial pattern of heat-related cardiorespiratory mortality in the elderly, during the yearly warmest five months of a three years period. Potential associations between spatial variability in heat-related mortality and several independent factors in each neighbourhood were investigated and their predictions. Two approaches were adopted: one is eminently statistical, using Generalized Linear Models (GLM) and another using Geographically Weighted Regression (GWR). This new recent regression technique is increasing in international attention on spatial modelling. The spatial model explains about 60% of the spatial variations in elderly's heat-related cardiorespiratory mortality. The two-analyses produced an overlapping set of predictor variables, with emphasis on the elderly, vegetation cover and employment. The results also show that the areas where heat-related mortality is high, are also the areas where the number of deaths is higher than expected. These neighbourhoods should be considered as the most vulnerable to heat-related mortality. We concluded that studying human health outcomes at neighbourhood-scale is relevant for public health heat-related plans. Essential suggestions are provided to decision-making support and city planners designing strategies to reduce heat-related mortality.

Analyzing the local and climatic conditions affecting the urban overheating magnitude during the Heatwaves (HWs) in a coastal city: A case study of the greater Sydney region

Urban overheating coincides with Heatwaves (HWs) and the thermal stress might get amplified in cities. To predict the interactions between urban overheating and HWs, the surface energy balance response to HWs is crucial. HW is a regional phenomenon and the climatic conditions may influence the local conditions to alter the energy budget contrast between a city and its adjacent peripheral areas. The interactions between the urban overheating and HWs are explored in a coastal city (Sydney Australia), also in the proximity of dry landmass, while considering the site characteristics, distance from the coast, and the population density. A positive response between urban overheating and HWs is reported. Advective heat flux in the form of a dualistic circulation system is found responsible for exacerbating the urban overheating magnitude (ΔT) during the HWs and altering the available energy balance. Land-coastal distance is also found as an important contributor in magnifying the urban-suburban temperature contrast. Considering the future urbanization in western Sydney, surfaces capable of retaining higher moisture content are prescribed to reduce the occurrence of extreme HW events. Activation of the ventilation corridor for the coastal wind penetration in western Sydney is another recommendation of this study.

Geospatial context of social and environmental factors associated with health risk during temperature extremes: Review and discussion

This study reviews forty-six publications between 2008 and 2017 dealing with socio-environmental impacts on adverse health effects of temperature extremes, in a geospatial context. The review showed that most studies focus on extremely hot weather but lack analysis of how spatial heterogeneity across a region can influence cold mortality/morbidity. There are limitations regarding the use of temperature datasets for spatial analyses. Only a few studies have applied air temperature datasets with high spatial resolution to health studies, but none of these studies have used anthropogenic heat as a factor for analysis of health risk. In addition, the elderly is generally recognized as a vulnerable group in most studies, but the interaction between old age and temperature risk varies by location. Other socio-demographic factors such as low income, low education and accessibility to community shelters may also need to be considered in the future. There are only a few studies which investigate the interaction between temperature and air pollution in a geospatial context, despite the fact that this is a known interaction that can influence health risk under extreme weather. In conclusions, although investigation of temperature effects on health risk is already at the "mature stage", studies of socio-environmental influences on human health under extreme weather in a geospatial context is still being investigated. A comprehensive assessment is required to analyse how the spatial aspects of the geophysical and social environments can influence human health under extreme weather, in order to develop a better community plan and health protocols for disaster preparedness.

Exploring the Synergies between Urban Overheating and Heatwaves (HWs) in Western Sydney

There is no consensus regarding the change of magnitude of urban overheating during HW periods, and possible interactions between the two phenomena are still an open question, despite the increasing frequency and impacts of Heatwaves (HW). The purpose of this study is to explore the interactions between urban overheating and HWs in Sydney, which is under the influence of two synoptic circulation systems. For this purpose, a detailed analysis has been performed for the city of Sydney, while considering an urban (Observatory Hill), in the Central Business District (CBD), and a non-urban station in Western Sydney (Penrith Lakes). Summer 2017 was considered as a study period, and HW and Non-Heatwave (NHW) periods were identified to explore the interactions between urban overheating and HWs. A strong link was observed between urban overheating and HWs, and the difference between the peak average urban overheating magnitude during HWs and NHWs was around 8 °C. Additionally, the daytime urban overheating effect was more pronounced during the HWs when compared to nighttime. The advective flux was found as the most important interaction between urban overheating and HWs, in addition to the sensible and latent heat fluxes.

Spatial Variability in the Effect of High Ambient Temperature on Mortality: An Analysis at Municipality Level within the Greater Athens Area

Spatial variability in temperature exists within metropolitan areas but very few studies have investigated intra-urban differentiation in the temperature-mortality effects. We investigated whether local characteristics of 42 Municipalities within the Greater Athens Area lead to modified temperature effects on mortality and if effect modifiers can be identified. Generalized Estimating Equations models were used to assess the effect of high ambient temperature on the total and cause-specific daily number of deaths and meta-regression to investigate effect modification. We found significant effects of daily temperature increases on all-cause, cardiovascular, and respiratory mortality (e.g., for all ages 4.16% (95% CI: 3.73,4.60%) per 1 °C increase in daily temperature (lags 0–3). Heterogeneity in the effect estimates between Municipalities was observed in several outcomes and environmental and socio-economic effect modifying variables were identified, such as % area coverage of buildings, length of roads/km², population density, % unemployed, % born outside the EU countries and mean daily temperature. To further examine the role of temperature, we alternatively used modelled temperature per Municipality and calculated the effects. We found that heterogeneity was reduced but not eliminated. It appears that there are socioeconomic status and environmental determinants of the magnitude of heat-related effects on mortality, which are detected with some consistency and should be further investigated.

Spatial variation of heat-related morbidity: A hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region

This study examined spatial variability of heat-related morbidity in multiple districts of the Mekong Delta Region (MDR), Vietnam. It was conducted in 132 district/cities of the MDR. We used a series of hierarchical Bayesian models to examine the region-wide and district-specific association between temperatures and hospitalizations during the period of 2010-2013. The potential effects of seasonality, long-term trends, day of the week and holidays were controlled in the models. We also examined influences of socio-demographic factors on the temperature-hospitalization relationship. The results indicate that an increase of 5 °C in average temperature was associated with a 6.1% increase (95%CI: 5.9, 6.2) in region-wide hospital admissions. However, the district-level risks ranged from a 55.2% decrease {95%CI: (-54), (-56)} to a 24.4% increase (24.3-24.6) in admissions per 5 °C increase in average temperature. This reflects the heterogeneous magnitudes of temperature-hospitalization risk across districts. The results also indicate that temperature-hospitalization risk increased by 1.3% (95%CI: 1.2-1.4), for each increase of 1000 persons/km² in population density, 2.1% (95%CI: 2.04-2.11) for each 1% increase in percent of females, and 2.7% (95%CI: 2.6-2.8) for each 1% increase in percent of pre-school students. In contrast, the temperature-related hospitalization risk decreased up to 6.8% {(95%CI: (-6.6)-(-6.9)} for each 1% increase in rural population. Public health intervention measures for both short-term and long-term effects of heat-related health risk should be developed with consideration of the use of city/district scale for the factors rather than the province scale. The province scale of factors does not accurately represent the variability of health risk due to exposure to high temperatures.

Assessment of heat- and cold-related emergency department visits in cities of China and Australia: Population vulnerability and attributable burden

BACKGROUND

Non-optimal ambient temperature has detrimental impacts on mortality worldwide, but little is known about the difference in population vulnerability to non-optimal temperature and temperature-related morbidity burden between developing and developed countries.

OBJECTIVES

We estimated and compared the associations of emergency department visits (EDV) with non-optimal temperature in terms of risk trigger temperature, the average slope of exposure-risk function and attributable risk in 12 cities from China and Australia.

METHODS

We modelled the associations of EDV with heat during warm season and with cold during cold season, separately, using generalized additive model. Population vulnerability within a given region was quantified with multiple risk trigger points including minimum risk temperature, increasing risk temperature and excessive risk temperature, and average coefficient of exposure-risk function. Fraction of EDV attributable to heat and cold was also calculated.

RESULTS

We found large between- and within-country contrasts in the identified multiple risk trigger temperatures, with higher heat and cold trigger points, except excessive risk temperature, observed in Australia than in China. Heat was associated with a relative risk (RR) of 1.009 [95% confidence interval (CI):1.007, 1.011] in China, which accounted for 5.9% of EDV. Higher RR of heat was observed in Australia (1.014, 95% CI: 1.010, 1.018), responsible for 4.0% of EDV. For cold effects, the RR was similar between two countries, but the attributable fraction was higher in China (9.6%) than in Australia (1.5%).

CONCLUSIONS

Exposure to heat and cold had adverse but divergent impacts on EDV in China and Australia. Further mitigation policy efforts incorporating region-specific population vulnerability to temperature impacts are necessary in both countries.

The impact of prevention and control of infectious disease law on diarrhoea control: a 5-year evaluation in multiple provinces in Vietnam

To address to burden of infectious diseases such as diarrhoea, the Vietnamese government has enacted the Law on Prevention and Control of Infectious Diseases (LPCIDs) since July 2008. However, no evaluation of the impact of the LPCID has been conducted. This study aims to evaluate the impact of the LPCID on diarrhoeal control for the 5 years following the implementation of LPCID in Vietnam. We used an interrupted time series design using a segmented regression analysis to estimate the 'province-level' impact of LPCID and then used random-effect meta-analysis to estimate the pooled effect sizes of the 'country-level' impact of LPCID on diarrhoeal control throughout Vietnam. The results show that the impacts varied by provinces. They were classified in four groups: 'positive impact, positive impact without sustainability, possibly positive impact, no or negative impact' of the LPCID. The meta-analysis indicated that the country-level impact of the LPCID became significant at 11 months after the LPCID took effect, with a decrease in level of diarrhoea of 9.7% (coefficient, -0.097; 95% CI: -19.1 to - 0.002) and a permanent downward trend of diarrhoea at a rate of 1.1% per month (coefficient, -0.011; 95% CI: -0.02 to - 0.003); whereas the trend in diarrhoea before the LPCID took effect was unchanging (coefficient, 0.002; 95% CI, 0-0.004). At 12, 24, 36, 48 and 60 months following the LPCID implementation date the levels of diarrhoea decreased by 10.9% (coefficient, -0.109; 95% CI: -0.203 to - 0.015), P < 0.01), 21.8% (coefficient, -0.218; 95% CI: -0.338 to - 0.098), P < 0.01), 31% (coefficient, -0.31; 95% CI: -0.474 to - 0.145), P < 0.01), 46.8% (coefficient, -0.468; 95% CI: -0.667 to - 0.27), P < 0.01), 48.2% (coefficient, -0.482; 95% CI: -0.708 to - 0.256), P < 0.01) respectively. The findings of this study reveal the effectiveness of the LPCID in reducing diarrhoea incidence in Vietnam. However, further studies should be conducted to better understanding the cost-effectiveness, acceptability, and sustainability of each component of the LPCID.

Heat, Disparities, and Health Outcomes in San Diego County's Diverse Climate Zones

Climate variability and change are issues of growing public health importance. Numerous studies have documented risks of extreme heat on human health in different locations around the world. Strategies to prevent heat-related morbidity and reduce disparities are possible but require improved knowledge of health outcomes during hot days at a small-scale level as important within-city variability in local weather conditions, socio-demographic composition, and access to air conditioning (AC) may exist. We analyzed hospitalization data for three unique climate regions of San Diego County alongside temperature data spanning 14 years to quantify the health impact of ambient air temperature at varying exceedance threshold levels. Within San Diego, coastal residents were more sensitive to heat than inland residents. At the coast, we detected a health impact at lower temperatures compared to inland locations for multiple disease categories including heat illness, dehydration, acute renal failure, and respiratory disease. Within the milder coastal region where access to AC is not prevalent, heat-related morbidity was higher in the subset of zip codes where AC saturation is lowest. We detected a 14.6% increase (95% confidence interval [4.5%, 24.6%]) in hospitalizations during hot weather in comparison to colder days in coastal locations where AC is less common, while no significant impact was observed in areas with higher AC saturation. Disparities in AC ownership were associated with income, race/ethnicity, and homeownership. Given that heat waves are expected to increase with climate change, understanding health impacts of heat and the role of acclimation is critical for improving outcomes in the future.

Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada

Excess mortality can be caused by extreme hot weather events, which are increasing in severity and frequency in Canada due to climate change. Individual and social vulnerability factors influence the mortality risk associated with a given heat exposure. We constructed heat vulnerability indices using census data from 2006 and 2011 in Canada, developed a novel design to compare spatiotemporal changes of heat vulnerability, and identified locations that may be increasingly vulnerable to heat. The results suggest that 1) urban areas in Canada are particularly vulnerable to heat, 2) suburban areas and satellite cities around major metropolitan areas show the greatest increases in vulnerability, and 3) heat vulnerability changes are driven primarily by changes in the density of older ages and infants. Our approach is applicable to heat vulnerability analyses in other countries.

Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model

This study investigates the relationship between all-cause mortality and extreme temperature events (ETEs) from 1975 to 2004. For 50 U.S. locations, these heat and cold events were defined based on location-specific thresholds of daily mean apparent temperature. Heat days were defined by a 3-day mean apparent temperature greater than the 95th percentile while extreme heat days were greater than the 97.5th percentile. Similarly, calculations for cold and extreme cold days relied upon the 5th and 2.5th percentiles. A distributed lag non-linear model assessed the relationship between mortality and ETEs for a cumulative 14-day period following exposure. Subsets for season and duration effect denote the differences between early- and late-season as well as short and long ETEs. While longer-lasting heat days resulted in elevated mortality, early season events also impacted mortality outcomes. Over the course of the summer season, heat-related risk decreased, though prolonged heat days still had a greater influence on mortality. Unlike heat, cold-related risk was greatest in more southerly locations. Risk was highest for early season cold events and decreased over the course of the winter season. Statistically, short episodes of cold showed the highest relative risk, suggesting unsettled weather conditions may have some relationship to cold-related mortality. For both heat and cold, results indicate higher risk to the more extreme thresholds. Risk values provide further insight into the role of adaptation, geographical variability, and acclimatization with respect to ETEs.

Effect modification of individual- and regional-scale characteristics on heat wave-related mortality rates between 2009 and 2012 in Seoul, South Korea

Many studies have investigated the associations between heat waves, ambient temperature, cold spells, and mortality or morbidity. Some studies have utilized effect modification to reveal the factors that increase an individual's susceptibility to temperature extremes, which can then be used to reshape public policy. In this study, we used a time-stratified case-crossover technique to examine how individual- and regional-scale characteristics modified heat wave-related impacts on mortality rates in Seoul, South Korea, between 2009 and 2012. We defined a heat wave as having at least two consecutive days with a daily mean temperature greater than or equal to the 95th percentile recorded in each of Seoul's twenty-five districts. At the individual scale, citizens classified as belonging to a lower education group had a higher vulnerability to heat wave-related morbidity or mortality [odds ratio (OR) 1.261; 95% confidence interval (CI): 1.034-1.538]. At a regional scale, death during heat waves was more likely to occur in districts with a high deprivation index (OR=1.194; 95% CI: 1.028-1.388). And a low proportion of green space around buildings (OR=1.178; 95% CI: 1.016-1.366), a low proportion of rooftop green space (OR=1.207; 95% CI: 1.042-1.399), or those that had fewer hospitals (OR=1.186; 95% CI: 1.019-1.379). Our data show that mortality during heat waves is more likely where these individual and regional-scale vulnerabilities overlap. Our findings support evidence of mortality impacts from heat waves and provide a basis for selection to policy makers choose on the target groups to reduce the public health burden of heat waves.

Small-area spatiotemporal analysis of heatwave impacts on elderly mortality in Paris: A cluster analysis approach

BACKGROUND

Heat-waves have a substantial public health burden. Understanding spatial heterogeneity at a fine spatial scale in relation to heat and related mortality is central to target interventions towards vulnerable communities.

OBJECTIVES

To determine the spatial variability of heat-wave-related mortality risk among elderly in Paris, France at the census block level. We also aimed to assess area-level social and environmental determinants of high mortality risk within Paris.

METHODS

We used daily mortality data from 2004 to 2009 among people aged >65 at the French census block level within Paris. We used two heat wave days' definitions that were compared to non-heat wave days. A Bernoulli cluster analysis method was applied to identify high risk clusters of mortality during heat waves. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the mortality risk.

RESULTS

The spatial approach revealed a spatial aggregation of death cases during heat wave days. We found that small scale chronic PM₁₀ exposure was associated with a 0.02 (95% CI: 0.001; 0.045) increase of the risk of dying during a heat wave episode. We also found a positive association with the percentage of foreigners and the percentage of labor force, while the proportion of elderly people living in the neighborhood was negatively associated. We also found that green space density had a protective effect and inversely that the density of constructed feature increased the risk of dying during a heat wave episode.

CONCLUSION

We showed that a spatial variation in terms of heat-related vulnerability exists within Paris and that it can be explained by some contextual factors. This study can be useful for designing interventions targeting more vulnerable areas and reduce the burden of heat waves.

Urban vegetation and heat-related mortality in Seoul, Korea

Urban areas are particularly vulnerable to heat-related health outcomes. Simultaneous trends of climate change and urbanization may increase the urban heat-related health burden. We investigated the effects of urban vegetation on heat-related mortality, and evaluated whether different levels of vegetation and individuals' characteristics affect the temperature-mortality associations within Seoul, Korea 2000-2009. We used Normalized Difference Vegetation Index (NDVI) to assess the urban vegetation within Seoul. We applied an overdispersed Poisson generalized linear model with interaction term between temperature and indicator of NDVI group (categorized in 3 levels) to assess the effect modification of the temperature-mortality association by urban vegetation. We conducted stratified analysis to explore whether associations are affected by individual characteristics of sex and age. The association between total mortality and a 1°C increase in temperature above the 90th percentile (25.1°C) (the "heat effect") was the highest for gus with low NDVI. The heat effect was a 4.1% (95% confidence interval (CI) 2.3, 5.9%), 3.0% (95% CI 0.2, 5.9%), and 2.2% (95% CI -0.5, 5.0%) increase in mortality risk for low, medium, and high NDVI group, respectively. Estimated risks showed similar effects by sex and age. Our findings suggest a higher mortality effect of high temperature in areas with lower vegetation in Seoul, Korea.

Spatiotemporal analysis of heat and heat wave effects on elderly mortality in Texas, 2006-2011

BACKGROUND

Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits.

OBJECTIVES

This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65years) in Texas.

METHODS

We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2days of county-specific daily maximum HI>95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week.

DISCUSSION

On average, the lag effect of heat on elderly mortality risk lasted up to 10days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95% Confidence Interval=4.33, 5.10).

CONCLUSIONS

Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.

Hot of Not: Physiological versus Meteorological Heatwaves-Support for a Mean Temperature Threshold

The aim of this study was to determine whether a revised heat warning threshold provides an enhanced predictive tool for increases in Emergency Department heat-related presentations in Canberra, Australia. All Emergency Department triage records containing the word “heat”, as well as those diagnosing a heat related illness for the summer periods 2013/2014, 2014/2015, and 2015/2016 were searched. Then a medical record review was conducted to confirm that the patient’s presentation was related to environmental heat, which was defined by the final clinical diagnosis, presentation complaint and details of the patient’s treatment. Researchers then compared this presentation data, to a mean threshold formula. The mean threshold formula included the past three consecutive daily mean temperatures and the last measured temperature upon presentation. This formula was designed to take into account the variance of night-time lows, with concurrent daily ambient temperatures, and was used to determine whether there was a correlation between heat-related presentations and increasing mean temperatures. Heat-related presentations appeared to occur when the mean threshold temperature reached 25 °C (77 °F), with significant increases when the mean threshold reached 30 °C (86 °F). These results confirm that a mean temperature of 30 °C corresponds to a relevant local public health heat-related threat.

Spatial and temporal variation in emergency transport during periods of extreme heat in Japan: A nationwide study

BACKGROUND

Several studies have reported the burden of climate change on extreme heat-related mortality or morbidity. However, few studies have investigated the spatial and temporal variation in emergency transport during periods of extreme heat on a national scale.

METHODS

Daily emergency ambulance dispatch data from 2007 to 2010 were acquired from all 47 prefectures of Japan. The temporal variability in the relationship between heat and morbidity in each prefecture was estimated using Poisson regression combined with a distributed lag non-linear model and adjusted for time trends. The spatial variability in the heat-morbidity relationships between prefectures was estimated using a multivariate meta-analysis.

RESULTS

A total of 5,289,660 emergency transports were reported during the summer months (June through September) within the study period. The overall cumulative relative risk (RR) at the 99th percentile vs. the minimum morbidity percentile was 1.292 (95% CI: 1.251-1.333) for all causes, 1.039 (95% CI: 0.989-1.091) for cardiovascular diseases, and 1.287 (95% CI: 1.210-1.368) for respiratory diseases. Temporal variation in the estimated effects indicated a non-linear relationship, and there were differences in the temporal variations between heat and all-cause and cause-specific morbidity. Spatial variation between prefectures was observed for all causes (Cochran Q test, p<0.001; I(2)=45.8%); however, there was no significant spatial heterogeneity for cardiovascular (Cochran Q test, p=0.054; I(2)=15.1%) and respiratory (Cochran Q test, p=0.681; I(2)=1.0%) diseases.

CONCLUSIONS

Our nationwide study demonstrated differences in the spatial and temporal variations in the relative risk for all-cause and cause-specific emergency transport during periods of extreme heat in Japan between 2007 and 2010. Our results suggest that public health strategies aimed at controlling heat-related morbidity should be tailored according to region-specific weather conditions.

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare data sets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Spatial analysis of the effect of the 2010 heat wave on stroke mortality in Nanjing, China

To examine the spatial variation of stroke mortality risk during heat wave, we collected 418 stroke mortality cases with permanent addresses for a severe heat wave (July 28–August 15, 2010) and 624 cases for the reference period (July 29–August 16, 2009 and July 27–August 14, 2011) in Nanjing, China. Generalized additive models were used to explore the association between location and stroke mortality risk during the heat wave while controlling individual-level risk factors. Heat wave vulnerability was then applied to explain the possible spatial variations of heat-wave-related mortality risk. The overall risk ratio (95% confidence intervals) of stroke mortality due to the heat wave in Nanjing was 1.34 (1.21 to 1.47). Geolocation was found to be significantly associated with the heat-wave-related stroke mortality risk. Using alternative reference periods generated similar results. A district-level risk assessment revealed similar spatial patterns. The highest stroke mortality risk observed in Luhe district was due to the combination of high heat exposure and high vulnerability. Our findings provide evidence that stroke mortality risk is higher in rural areas during heat waves and that these areas require future interventions to reduce vulnerability.

Geographic dimensions of heat-related mortality in seven U.S. cities

Spatially targeted interventions may help protect the public when extreme heat occurs. Health outcome data are increasingly being used to map intra-urban variability in heat-health risks, but there has been little effort to compare patterns and risk factors between cities. We sought to identify places within large metropolitan areas where the mortality rate is highest on hot summer days and determine if characteristics of high-risk areas are consistent from one city to another. A Poisson regression model was adapted to quantify temperature-mortality relationships at the postal code scale based on 2.1 million records of daily all-cause mortality counts from seven U.S. cities. Multivariate spatial regression models were then used to determine the demographic and environmental variables most closely associated with intra-city variability in risk. Significant mortality increases on extreme heat days were confined to 12-44% of postal codes comprising each city. Places with greater risk had more developed land, young, elderly, and minority residents, and lower income and educational attainment, but the key explanatory variables varied from one city to another. Regression models accounted for 14-34% of the spatial variability in heat-related mortality. The results emphasize the need for public health plans for heat to be locally tailored and not assume that pre-identified vulnerability indicators are universally applicable. As known risk factors accounted for no more than one third of the spatial variability in heat-health outcomes, consideration of health outcome data is important in efforts to identify and protect residents of the places where the heat-related health risks are the highest.

Heat-related morbidity in brisbane, australia: spatial variation and area-level predictors

BACKGROUND

Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities.

OBJECTIVES

We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane.

METHODS

We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007-2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects.

RESULTS

On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city's 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density.

CONCLUSIONS

Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

The impact of heatwaves on mortality in Australia: a multicity study

OBJECTIVES

To assess the heterogeneity of heatwave-related impacts on mortality across different cities.

DESIGN

A multicity time series study.

SETTING

3 largest Australian cities: Brisbane, Melbourne and Sydney.

PARTICIPANTS

All residents living in these cities.

MAIN OUTCOME MEASURES

Non-external causes mortality data by gender and two age groups (ie, 0-75 and 75+) for these cities during the period 1988-2009 were obtained from relevant government agencies.

RESULTS

Total mortality increased mostly within the same day (lag 0) or a lag of 1 day (lag 1) during almost all heatwaves in three cities. Using the heatwave definition (HWD) as the 95th centile of mean temperature for two or more consecutive days in the summer season, the relative risk for total mortality at lag 1 in Brisbane, Melbourne and Sydney was 1.13 (95% CI 1.08 to 1.19), 1.10 (95% CI 1.06 to 1.14) and 1.06 (95% CI 1.01 to 1.10), respectively. Using the more stringent HWD-the 99th centile of mean temperature for two or more consecutive days, the relative risk of total mortality at the lags of 0-2 days in Brisbane and Melbourne was 1.40 (95% CI 1.29 to 1.51) and 1.47 (95% CI 1.36 to 1.59), respectively. Elderly, particularly females, were more vulnerable to the impact of heatwaves.

CONCLUSIONS

A consistent and significant increase in mortality was observed during heatwaves in the three largest Australian cities, but the impacts of heatwave appeared to vary with age, gender, the HWD and geographical area.

The impact of heat on mortality and morbidity in the Greater Metropolitan Sydney Region: a case crossover analysis

BACKGROUND

This study examined the association between unusually high temperature and daily mortality (1997-2007) and hospital admissions (1997-2010) in the Sydney Greater Metropolitan Region (GMR) to assist in the development of targeted health programs designed to minimise the public health impact of extreme heat.

METHODS

Sydney GMR was categorized into five climate zones. Heat-events were defined as severe or extreme. Using a time-stratified case-crossover design with a conditional logistic regression model we adjusted for influenza epidemics, public holidays, and climate zone. Odds ratios (OR) and 95% confidence intervals were estimated for associations between daily mortality and hospital admissions with heat-event days compared to non-heat event days for single and three day heat-events.

RESULTS

All-cause mortality overall had similar magnitude associations with single day and three day extreme and severe events as did all cardiovascular mortality. Respiratory mortality was associated with single day and three day severe events (95th percentile, lag0: OR = 1.14; 95%CI: 1.04 to 1.24). Diabetes mortality had similar magnitude associations with single day and three day severe events (95th percentile, lag0: OR = 1.22; 95%CI: 1.03 to 1.46) but was not associated with extreme events. Hospital admissions for heat related injuries, dehydration, and other fluid disorders were associated with single day and three day extreme and severe events. Contrary to our findings for mortality, we found inconsistent and sometimes inverse associations for extreme and severe events with cardiovascular disease and respiratory disease hospital admissions. Controlling for air pollutants did not influence the mortality associations but reduced the magnitude of the associations with hospital admissions particularly for ozone and respiratory disease.

CONCLUSIONS

Single and three day events of unusually high temperatures in Sydney are associated with similar magnitude increases in mortality and hospital admissions. The trend towards an inverse association between cardio-vascular admissions and heat-events and the strong positive association between cardio-vascular mortality and heat-events suggests these events may lead to a rapid deterioration in persons with existing cardio-vascular disease resulting in death. To reduce the adverse effects of high temperatures over multiple days, and less extreme but more frequent temperatures over single days, targeted public health messages are critical.

Have the short-term mortality effects of particulate matter air pollution changed in Australia over the period 1993-2007?

The author investigates whether the mortality effect of particulate matter air pollution (PM10) has changed in Australia over the period 1993-2007. This period corresponds to an era of increasing Government intervention aimed at improving air quality and, as a result, a potential decrease in the toxicity of PM10. Evidence is found that the mortality effect of PM10 has declined in both Brisbane and Sydney. For Sydney we estimate that the effects of PM10 on total and cardiovascular mortality are, respectively, decreasing at the rate of 10% and 13% annually. We speculate that one possible reason for this decline could be a reduction in the toxicity of PM10. A difference between this study and a similar United States study is that PM10 concentrations have not been declining in Australia. This means that the observed decline in the mortality effect of PM10 is not an artefact of a declining PM10 concentration.

Extreme heat and health: perspectives from health service providers in rural and remote communities in South Australia

Among the challenges for rural communities and health services in Australia, climate change and increasing extreme heat are emerging as additional stressors. Effective public health responses to extreme heat require an understanding of the impact on health and well-being, and the risk or protective factors within communities. This study draws on lived experiences to explore these issues in eleven rural and remote communities across South Australia, framing these within a socio-ecological model. Semi-structured interviews with health service providers (n = 13), and a thematic analysis of these data, has identified particular challenges for rural communities and their health services during extreme heat. The findings draw attention to the social impacts of extreme heat in rural communities, the protective factors (independence, social support, education, community safety), and challenges for adaptation (vulnerabilities, infrastructure, community demographics, housing and local industries). With temperatures increasing across South Australia, there is a need for local planning and low-cost strategies to address heat-exacerbating factors in rural communities, to minimise the impact of extreme heat in the future.

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

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

Staying cool in a changing climate: Reaching vulnerable populations during heat events

The frequency and intensity of hot weather events are expected to increase globally, threatening human health, especially among the elderly, poor, and chronically ill. Current literature indicates that emergency preparedness plans, heat health warning systems, and related interventions may not be reaching or supporting behavior change among those most vulnerable in heat events. Using a qualitative multiple case study design, we comprehensively examined practices of these populations to stay cool during hot weather ("cooling behaviors") in four U.S. cities with documented racial/ethnic and socio-economic disparities and diverse heat preparedness strategies: Phoenix, Arizona; Detroit, Michigan; New York City, New York; and Philadelphia, Pennsylvania. Based on semi-structured in-depth interviews we conducted with 173 community members and organizational leaders during 2009-2010, we assessed why vulnerable populations do or do not participate in health-promoting behaviors at home or in their community during heat events, inquiring about perceptions of heat-related threats and vulnerability and the role of social support. While vulnerable populations often recognize heat's potential health threats, many overlook or disassociate from risk factors or rely on experiences living in or visiting warmer climates as a protective factor. Many adopt basic cooling behaviors, but unknowingly harmful behaviors such as improper use of fans and heating and cooling systems are also adopted. Decision-making related to commonly promoted behaviors such as air conditioner use and cooling center attendance is complex, and these resources are often inaccessible financially, physically, or culturally. Interviewees expressed how interpersonal, intergenerational relationships are generally but not always protective, where peer relationships are a valuable mechanism for facilitating cooling behaviors among the elderly during heat events. To prevent disparities in heat morbidity and mortality in an increasingly changing climate, we note the implications of local context, and we broadly inform heat preparedness plans, interventions, and messages by sharing the perspectives and words of community members representing vulnerable populations and leaders who work most closely with them.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Projecting future heat-related mortality under climate change scenarios: a systematic review

BACKGROUND

Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality.

OBJECTIVES

We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios.

DATA SOURCES AND EXTRACTION

A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010.

DATA SYNTHESIS

Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature-mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement.

CONCLUSIONS

Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality.

The impact of temperature on mortality in Tianjin, China: a case-crossover design with a distributed lag nonlinear model

BACKGROUND

Although interest in assessing the impacts of temperature on mortality has increased, few studies have used a case-crossover design to examine nonlinear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China or on what temperature measure is the best predictor of mortality.

OBJECTIVES

Our objectives were to use a distributed lag nonlinear model (DLNM) as a part of case-crossover design to examine the nonlinear and distributed lag effects of temperature on mortality in Tianjin, China and to explore which temperature measure is the best predictor of mortality.

METHODS

We applied the DLNM to a case-crossover design to assess the nonlinear and delayed effects of temperatures (maximum, mean, and minimum) on deaths (nonaccidental, cardiopulmonary, cardiovascular, and respiratory).

RESULTS

A U-shaped relationship was found consistently between temperature and mortality. Cold effects (i.e., significantly increased mortality associated with low temperatures) were delayed by 3 days and persisted for 10 days. Hot effects (i.e., significantly increased mortality associated with high temperatures) were acute and lasted for 3 days and were followed by mortality displacement for nonaccidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature.

CONCLUSIONS

In Tianjin, extreme cold and hot temperatures increased the risk of mortality. The effects of cold last longer than the effects of heat. Combining the DLNM and the case-crossover design allows the case-crossover design to flexibly estimate the nonlinear and delayed effects of temperature (or air pollution) while controlling for season.

Including the urban heat island in spatial heat health risk assessment strategies: a case study for Birmingham, UK

BACKGROUND

Heatwaves present a significant health risk and the hazard is likely to escalate with the increased future temperatures presently predicted by climate change models. The impact of heatwaves is often felt strongest in towns and cities where populations are concentrated and where the climate is often unintentionally modified to produce an urban heat island effect; where urban areas can be significantly warmer than surrounding rural areas. The purpose of this interdisciplinary study is to integrate remotely sensed urban heat island data alongside commercial social segmentation data via a spatial risk assessment methodology in order to highlight potential heat health risk areas and build the foundations for a climate change risk assessment. This paper uses the city of Birmingham, UK as a case study area.

RESULTS

When looking at vulnerable sections of the population, the analysis identifies a concentration of "very high" risk areas within the city centre, and a number of pockets of "high risk" areas scattered throughout the conurbation. Further analysis looks at household level data which yields a complicated picture with a considerable range of vulnerabilities at a neighbourhood scale.

CONCLUSIONS

The results illustrate that a concentration of "very high" risk people live within the urban heat island, and this should be taken into account by urban planners and city centre environmental managers when considering climate change adaptation strategies or heatwave alert schemes. The methodology has been designed to be transparent and to make use of powerful and readily available datasets so that it can be easily replicated in other urban areas.

Constraints and barriers to public health adaptation to climate change: a review of the literature

Public health adaptation to climate change is an important issue and inevitably is needed to address the adverse health impacts of climate change over the next few decades. This paper provides an overview of the constraints and barriers to public health adaptation and explores future research directions in this emerging field. An extensive literature review was conducted in 2010 and published literature from 2000 to 2010 was retrieved. This review shows that public health adaptation essentially can operate at two levels, namely, adaptive-capacity building and implementation of adaptation actions. However, there are constraints and barriers to public health adaptation arising from uncertainties of future climate and socioeconomic conditions, as well as financial, technologic, institutional, social capital, and individual cognitive limits. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome these constraints and barriers. It is proposed here that high research priority should be given to multidisciplinary research on the assessment of potential health impacts of climate change, projections of health impacts under different climate and socioeconomic scenarios, identification of health co-benefits of mitigation strategies, and evaluation of cost-effective public health adaptation options.

The effects of summer temperature, age and socioeconomic circumstance on acute myocardial infarction admissions in Melbourne, Australia

Background

Published literature detailing the effects of heatwaves on human health is readily available. However literature describing the effects of heat on morbidity is less plentiful, as is research describing events in the southern hemisphere and Australia in particular. To identify susceptible populations and direct public health responses research must move beyond description of the temperature morbidity relationship to include social and spatial risk factors. This paper presents a spatial and socio-demographic picture of the effects of hot weather on persons admitted to hospital with acute myocardial infarction (AMI) in Melbourne.

Results

In this study, the use of a spatial and socio-economic perspective has identified two groups within the population that have an increased 'risk' of AMI admissions to hospital during hot weather. AMI increases during hot weather were only identified in the most disadvantaged and the least disadvantaged areas. Districts with higher AMI admissions rates during hot weather also had larger proportions of older residents. Age provided some explanation for the spatial distribution of AMI admissions on single hot days whereas socio-economic circumstance did not. During short periods (3-days) of hot weather, age explained the spatial distribution of AMI admissions slightly better than socioeconomic circumstance.

Conclusions

This study has demonstrated that both age and socioeconomic inequality contribute to AMI admissions to hospital in Melbourne during hot weather. By using socioeconomic circumstance to define quintiles, differences in AMI admissions were quantified and demographic differences in AMI admissions were described. Including disease specificity into climate-health research methods is necessary to identify climate-sensitive diseases and highlight the burden of climate-sensitive disease in the community. Cardiac disease is a major cause of death and disability and identifying cardiac-specific climate thresholds and the spatio-demographic characteristics of vulnerable groups within populations is an important step towards preventative health care by informing public health officials and providing a guide for an early heat-health warning system. This information is especially important under current climatic conditions and for assessing the future impact of climate change.