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.

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables.

Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983–2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (− 95%) to an increase of 339 deaths per year (+ 359%).

Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.

Preventing heat-associated morbidity and mortality is a public health priority in Maricopa County, Arizona (United States). The objective of this project was to evaluate Maricopa County cooling centers and gain insight into their capacity to provide relief for the public during extreme heat events. During the summer of 2014, 53 cooling centers were evaluated to assess facility and visitor characteristics. Maricopa County staff collected data by directly observing daily operations and by surveying managers and visitors. The cooling centers in Maricopa County were often housed within community, senior, or religious centers, which offered various services for at least 1500 individuals daily. Many visitors were unemployed and/or homeless. Many learned about a cooling center by word of mouth or by having seen the cooling center’s location. The cooling centers provide a valuable service and reach some of the region’s most vulnerable populations. This project is among the first to systematically evaluate cooling centers from a public health perspective and provides helpful insight to community leaders who are implementing or improving their own network of cooling centers.

This study aims to examine the relationship between urban densification and pedestrian thermal comfort at different times of the year, and to understand how this can impact patterns of activity in downtown areas. The focus of the research is on plazas in the urban core of downtown Tempe, given their importance to the pedestrian landscape. With that in mind, the research question for the study is: how does the microclimate of a densifying urban core affect thermal comfort in plazas at different times of the year? Based on the data, I argue that plazas in downtown Tempe are not maximally predisposed to pedestrian thermal comfort in the summer or the fall. Thus, the proposed intervention to improve thermal comfort in downtown Tempe’s plazas is the implementation of decision support tools focused on education, community engagement, and thoughtful building designs for heat safety.

Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month of measurable precipitation days per year (WRCC). With that, it is important to know the public’s understanding as well as their general trend of likeness towards the weather forecasts they receive. A questionnaire was distributed to 426 people in the state of Arizona to review what they understand from the forecasts and what they would like to see on social media and television.

Many people use public transportation in their daily lives, which is often praised at as a healthy and sustainable choice to make. However, in extreme temperatures this also puts people at a greater risk for negative consequences resulting from such exposure to heat. In Phoenix, public transportation riders are faced with extreme heat in the summer along with the increased internal heat production caused by the physical activity required to use public transportation. In this study, I estimated total exposure and average exposure per rider for six stops in Phoenix. To do this I used City of Phoenix ridership data, weather data, and survey responses from an ASU City of Phoenix Bus Stop Survey conducted in summer 2016. These data sets were combined by multiplying different metrics to produce various exposure values. During analysis two sets of calculations were made. One keeping weather constant and another keeping ridership constant. I found that there was a large range of exposure between the selected stops and that the thermal environment influences the amount of exposure depending on the time of day the exposure is occurring. During the morning a greener location leads to less exposure, while in the afternoon an urban location leads to less exposure. Know detailed information about exposure at these stops I was also able to evaluate survey participants' thermal comfort at each stop and how it may relate to exposure. These findings are useful in making educated transportation planning decisions and improving the quality of life for people living in places with extreme summer temperatures.

Regional and geographical differences may explain variability in menopausal symptom occurrence due to development of climate-specific thermoneutral zones leading to population-specific hot flash frequencies. Limited information available regarding menopausal symptoms in underserved women living in extreme heat.

Understanding the perception of menopausal symptoms in underserved women living in extreme heat regions to identify if heat impacts perception of menopausal symptoms was the objective of this study. Women in free, low-income, and homeless clinics in Phoenix were surveyed during summer and winter months using a self-administered, written questionnaire including demographic, climate and menopause related questions, including the Green Climacteric Scale (GCS).

A total of 139 predominantly Hispanic (56 %), uninsured (53 %), menopausal (56 %), mid-aged (mean 49.9, SD 10.3) women were surveyed— 36% were homeless or in shelters. Most women were not on menopausal hormone therapy (98 %). Twenty-two percent reported hot flashes and 26% night sweats. Twenty-five percent of women reported previously becoming ill from heat. More women thought season influenced menopausal symptoms during summer than winter (41 % vs. 14 %, p = 0.0009). However, majority of women did not think temperature outside influenced their menopausal symptoms and that did not differ by season (73 % in winter vs. 60% in summer, p=0.1094). No statistically significant differences seen for vasomotor symptoms between winter and summer months.

Regional and geographical differences may be key in understanding the variability in menopausal symptoms. Regardless of season, the menopausal, underserved and homeless women living in Arizona reported few vasomotor symptoms. In the summer, they were more likely to report that the season influenced their menopausal symptoms rather than temperature suggesting an influence of the season on symptom perception.