Objectives: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000–2008).
Methods: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods.
Results: Neighborhood scores on three factors—socioeconomic vulnerability, elderly/isolation, and unvegetated area—varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor.
Conclusions: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.
In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (ATmax) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥65 during the months May–October for years 2000–2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (ATmax = 90–97 °F; 32.2‒36.1 °C) were below local median seasonal temperatures in the study period (ATmax = 99.5 °F; 37.5 °C). Heat threshold was defined as ATmax at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (ATmax = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (ATmax = 109 °F; 42.8 °C) and for all-cause mortality in females (ATmax = 107 °F; 41.7 °C) and males <65 years (ATmax = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.
The forthcoming century will see cities exposed to temperature rises from urbanisation as well as greenhouse gas induced radiative forcing. Increasing levels of urban heat will have a direct impact upon the people living in cities in terms of health, but will also have an indirect effect by impacting upon the critical infrastructure networks of the city itself (e.g., ICT, transport and energy). Some infrastructures are more resistant than others, but there is a growing reliance on the energy network to provide the power for all of our future critical infrastructure networks. Unfortunately, the energy network is far from resilient from the effects of urban heat and is set to face a perfect storm of increasing temperatures and loadings as demand increases for air conditioning, refrigeration, an electrified transport network and a high-speed ICT network. The result is that any failure on the energy network could quickly cascade across much of our critical infrastructure. System vulnerabilities will become increasingly apparent as the impacts of climate change begin to manifest and this paper calls for interdisciplinary action outlining the need for high resolution monitoring and modelling of the impact of urban heat on infrastructure.
Summer extreme heat events in the arid Phoenix, Arizona (USA) metropolitan region for the period 2041-2070 are projected based on the ensemble of ten climate models from the North American Regional Climate Change Assessment Program for the SRES A2 greenhouse gas emissions scenario by the Intergovernmental Panel on Climate Change. Extreme heat events are identified by measures related to two thresholds of the maximum daily air temperature distribution for the historical reference period 1971-2000. Comparing this reference period to the model ensemble-mean, the frequency of extreme heat events is projected to increase by a factor of six to 1.9 events per summer and the average number of event days per year is projected to increase by a factor of 14. The inter-model range for the average number of EHE days per summer is larger for the projected climate, 10.6 to 42.2 days, than for simulations of the past climate simulations (1.5 to 2.4 days).
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.