Mental health and air temperature: Attributable risk analysis for schizophrenia hospital admissions in arid urban climates.

Health researchers have examined the physiological impacts of extreme air temperature on the human body. Yet, the mental health impacts of temperature have been understudied. Research has shown that the environment can create circumstances that exacerbate mental health issues. This may be particularly challenging for some of the fastest growing cities, located in hot, dry climates. Given the theoretical relationship between air temperature and mental health, we seek to measure the association between temperature and schizophrenia hospital admissions in an arid urban climate and quantify the associated public health burden. We collected 86,672 hospitalization records for schizophrenia from 2006 to 2014 in Maricopa County, Arizona, USA. Using a distributed lag non-linear model (DLNM), we tested for a statistical association between temperature and schizophrenia hospital admissions after controlling for year, season, weekends, and holidays. We calculated the cumulative attributable risk of nighttime temperature on schizophrenia for the entire dataset as well as among demographic subgroups. The relative risk of schizophrenia hospital admissions increased with both high and low temperatures. Statistical models using daily minimum temperature were more strongly associated with hospitalization than those using mean or maximum. Schizophrenia hospital admissions increased on days with minimum temperatures above 30 °C and below 3 °C, with some subgroups experiencing higher rates of hospitalization. The total fraction of schizophrenia hospital admissions attributable to non-optimal minimum temperature is 3.45 % (CI: -4.91-10.80 %) and high minimum temperature is 0.28 % (CI: -1.18-1.78 %). We found that non-whites and males appear to be at a slightly increased risk than the general population, although there did not appear to be a statistically significant difference. A conservative estimate of healthcare costs annually from non-optimal temperature attributed schizophrenia hospitalization is $1.95 million USD. Therefore, nighttime cooling strategies and efforts could increase the accessibility of shelters to reduce overnight exposure to extreme air temperature.

Impact of environmental factors on heat-associated mortalities in an urban desert region.

The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM2.5, and daily average PM10. This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.

Extreme Heat Exposure: Access and Barriers to Cooling Centers - Maricopa and Yuma Counties, Arizona, 2010-2020.

Extreme heat exposure increases the risk for heat-related illnesses (HRIs) and deaths, and comprehensive strategies to prevent HRIs are increasingly important in a warming climate (1). An estimated 702 HRI-associated deaths and 67,512 HRI-associated emergency department visits occur in the United States each year (2,3). In 2020, Phoenix and Yuma, Arizona, experienced a record 145 and 148 days, respectively, of temperatures >100°F (37.8°C), and a record 522 heat-related deaths occurred in the state. HRIs are preventable through individual and community-based strategies*,†; cooling centers,§ typically air-conditioned or cooled buildings designated as sites to provide respite and safety during extreme heat, have been established in Maricopa and Yuma counties to reduce HRIs among at-risk populations, such as older adults. This analysis examined trends in HRIs by age during 2010-2020 for Maricopa and Yuma counties and data from a survey of older adults related to cooling center availability and use in Yuma County during 2018-2019. Data from CDC's Social Vulnerability Index (SVI) were also used to overlay cooling center locations with SVI scores. During 2010-2020, heat days, defined as days with an excessive heat warning issued by the National Weather Service Phoenix Office,¶ for any part of Maricopa and Yuma counties (4), increased in both Maricopa County (1.18 days per year) and Yuma County (1.71 days per year) on average. Adults aged ≥65 years had higher rates of HRI hospitalization compared with those aged <65 years. In a survey of 39 adults aged ≥65 years in Yuma County, 44% reported recent HRI symptoms, and 18% reported electricity cost always or sometimes constrained their use of air conditioning. Barriers to cooling center access among older adults include awareness of location and transportation. Collaboration among diverse community sectors and health profession education programs is important to better prepare for rising heat exposure and HRIs. States and communities can implement adaptation and evaluation strategies to mitigate and assess heat risk, such as the use of cooling centers to protect communities disproportionately affected by HRI during periods of high temperatures.

Evaporative misters for urban cooling and comfort: effectiveness and motivations for use.

Thermal comfort is an important determinant of quality of life and economic vitality in cities. Strategies to improve thermal comfort may become a more critical part of urban sustainability efforts with projections of continued urban growth and climate change. A case study was performed in the hot, dry summertime climate of Tempe, Arizona to quantify the influence of evaporative misters on the thermal environment in outdoor restaurants and to understand business managers' motivations to use misters. Microclimate measurements (air temperature (Ta), wind speed, relative humidity, globe temperature) were taken at five restaurants midday within four exposures: misted sun, misted shade, sun only, and shade only. We assessed Ta, mean radiant temperature (MRT), universal thermal climate index (UTCI), and physiological equivalent temperature (PET) between these four conditions within each location. Misters improved thermal comfort across all days, sites, and exposure conditions. MRT was on average 7.6 °C lower in misted locations, which significantly lowered average PET (- 6.5 °C) and UTCI (- 4.4 °C) (p < 0.05). Thermal comfort was most improved using mist in combination with shade. Under such conditions, PET and UTCI were reduced by 15.5 °C and 9.7 °C (p < 0.05), respectively. Business managers identified customer comfort and increased seating capacity as the principal factors for mister use. Esthetics of misters further encouraged use, while cost and environmental concerns were perceived to be less important. While this case study demonstrates value in outdoor misting in a hot, dry climate, additional work is needed to more fully evaluate tradeoffs between cost, water use, and comfort with continuing urban growth.

Public transit infrastructure and heat perceptions in hot and dry climates.

Many cities aim to progress toward their sustainability and public health goals by increasing use of their public transit systems. However, without adequate protective infrastructure that provides thermally comfortable conditions for public transit riders, it can be challenging to reach these goals in hot climates. We took micrometeorological measurements and surveyed riders about their perceptions of heat and heat-coping behaviors at bus stops with a variety of design attributes in Phoenix, AZ, USA, during the summer of 2018. We identified the design attributes and coping behaviors that made riders feel cooler. We observed that current infrastructure standards and material choices for bus stops in Phoenix are insufficient to provide thermal comfort, and can even expose riders to health risks. Almost half of the study participants felt hot or very hot at the time they were surveyed, and more than half reported feeling thermally uncomfortable. On average, shade reduced the physiological equivalent temperature (PET) by 19 °C. Moreover, we found significant diurnal differences in PET reductions from the shade provided by various design attributes. For instance, all design attributes were effective in reducing PET in the morning; however, a vegetated awning did not provide statistically significant shade reductions in the afternoon. Temperatures of sun-exposed surfaces of man-made materials exceeded skin burn thresholds in the afternoon, but shade was effective in bringing the same surfaces to safe levels. Aesthetically pleasing stops were rated as cooler than stops rated as less beautiful. We conclude that cities striving to increase public transit use should prioritize thermal comfort when designing public transit stops in hot climates.

Menopausal Symptoms in Underserved and Homeless Women Living in Extreme Temperatures in the Southwest.

Background: Little is known about menopausal symptoms in underserved women. Aim: To better understand self-reported menopausal symptoms in underserved and homeless women living in extreme heat during different seasons. Methods: A cross-sectional study, including the Greene Climacteric Scale (GCS), climate-related questions, and demographics was administered June to August of 2017 and December to February 2018 to women 40-65 years of age. Results: In 104 predominantly Hispanic (56%), uninsured (53%), menopausal (56%), and mid-aged (50 ± 9.5) women, 57% reported any bother, while 20% of these women reported "quite a bit" or "extreme" bother from hot flushes. The total GCS score was a mean of 41 ± 15.0; out of 63 indicating significant symptoms, the psychological and somatic clusters were highest. Women did not think temperature outside influenced their menopausal symptoms at either time point (69% in winter vs. 57% in summer, p = 0.23). In multivariable analyses after adjusting for race, body mass index, and living situation neither season nor temperature was associated with self-reported hot flush bother. While one-third of women reported becoming ill from the heat, 90% of women reported not seeking care from a doctor for their illness. Conclusion: Menopausal, underserved, homeless women living in Arizona reported few vasomotor symptoms regardless of season, and endorsed psychological and somatic complaints. Socioeconomic factors may influence types of bothersome menopausal symptoms in this population of women.

Novel metrics for relating personal heat exposure to social risk factors and outdoor ambient temperature.

A more precise understanding of individual-level heat exposure may be helpful to advance knowledge about heat-health impacts and effective intervention strategies, especially in light of projected increases in the severity and frequency of extreme heat events. We developed and interrogated different metrics for quantifying personal heat exposure and explored their association with social risk factors. To do so, we collected simultaneous personal heat exposure data from 64 residents of metropolitan Phoenix, Arizona. From these data, we derived five exposure metrics: Mean Individually Experienced Temperature (IET), Maximum IET, Longest Exposure Period (LEP), Percentage Minutes Above Threshold (PMAT), and Degree Minutes Above Threshold (DMAT), and calculated each for Day Hours, Night Hours, and All Hours of the study period. We then calculated effect sizes for the associations between those metrics and four social risk factors: neighborhood vulnerability, income, home cooling type, and time spent outside. We also investigated exposure misclassification by constructing linear regression models of observations from a regional weather station and hourly IET for each participant. Our analysis revealed that metric choice and timeframe added depth and nuance to our understanding of differences in exposure within and between populations. We found that time spent outside and income were the two risk factors most strongly associated with personal heat exposure. We also found evidence that Mean IET is a good, but perhaps not optimal, measure for assessing group differences in exposure. Most participants' IETs were poorly correlated with regional weather station observations and the slope and correlation coefficient for linear regression models between regional weather station data and IETs varied widely among participants. We recommend continued efforts to investigate personal heat exposure, especially in combination with physiological indicators, to improve our understanding of links between ambient temperatures, social risk factors, and health outcomes.

Extreme Weather and Climate Change: Population Health and Health System Implications.

Extreme weather and climate events, such as heat waves, cyclones, and floods, are an expression of climate variability. These events and events influenced by climate change, such as wildfires, continue to cause significant human morbidity and mortality and adversely affect mental health and well-being. Although adverse health impacts from extreme events declined over the past few decades, climate change and more people moving into harm's way could alter this trend. Long-term changes to Earth's energy balance are increasing the frequency and intensity of many extreme events and the probability of compound events, with trends projected to accelerate under certain greenhouse gas emissions scenarios. While most of these events cannot be completely avoided, many of the health risks could be prevented through building climate-resilient health systems with improved risk reduction, preparation, response, and recovery. Conducting vulnerability and adaptation assessments and developing health system adaptation plans can identify priority actions to effectively reduce risks, such as disaster risk management and more resilient infrastructure. The risks are urgent, so action is needed now.

Hiking Time Trial Performance in the Heat with Real-Time Observation of Heat Strain, Hydration Status and Fluid Intake Behavior.

This study investigated the real-time progression of heat strain in mountain hikers during time trials (TT). Participants (n = 12; 7M/5F; age 21.6 ± 2.47) attempted to climb Tempe Butte (~1.1 mi) four times in HOT and MOD trials (wet bulb globe temperature 31.6 °C vs. 19.0 °C). Performance, physiological outcomes, and fluid intake behavior were measured in real-time. Hot conditions significantly impaired hiking TT performance by 11%, reduced aerobic capacity by 7%, increased peak rate of perceived exertion (RPE) by 19%, and elevated core temperature (Tc) by 0.7 °C compared to MOD (all p < 0.03). Less-aerobically-fit participants were most negatively-affected by heat stress. Based on sweat lost, participants in HOT required 2.26 ± 0.91 L of fluids, brought 1.52 ± 0.83 L, and consumed 1.54 ± 0.49 L, losing an average of 1.1% ± 1.0%BM. Participants in MOD required 1.28 ± 0.39 L of fluids, brought 1.57 ± 1.09 L, and consumed 0.79 ± 0.57 L, losing an average of 1.0% ± 0.8%BM. Morning-after urine specific gravity (USG) values revealed 75% of hikers were hypohydrated (USG ≥ 1.020) after HOT; 67% after MOD. Heat stress impairs hiking TT performance while increasing RPE and Tc. Fitter participants showed less performance and physiological impairment from heat stress. Although hikers in both conditions lost similar body weight, hikers were limited in HOT by fluid availability, whereas in MOD, fluid was available and dehydration was voluntary.

Physical Activity in the Summer Heat: How Hot Weather Moderates the Relationship Between Built Environment Features and Outdoor Physical Activity of Adults.

BACKGROUND: Research has not yet examined how hot weather moderates the relationship between the built environment and outdoor physical activity levels. The authors posited that hot days will increase the magnitude of the expected directional effect of built environment features on physical activity. METHODS: This longitudinal study included 134 US adults from the Three city Heat and Electrical failure AdapTation study. Adults self-reported physical activity for multiple summer days (nstudy-days = 742) in 2016. Hot days were defined as ≥90th percentile of daily maximum heat index. Built environment features included density, safety, trees, hilliness, connectivity, access to parks, and access to shops + services. Separate growth curve models with interaction terms (ie, hot day × built environment feature) were run for daily minutes of outdoor physical activity (ie, any activity and recommended activity). RESULTS: Neither hot days nor built environment features impacted outdoor physical activity significantly, and hot days did not moderate the relationship between built environment features and physical activity (P > .05). CONCLUSIONS: With adults failing to modify behavior on hot days, cities may be placing adults at increased risk of exertional heat illness. The authors recommend incorporating the risk of exertional heat illness in health impact assessments and deploying heat management strategies.

Examining the diurnal temperature range enigma: why is human health related to the daily change in temperature?

An increasing number of epidemiological studies are finding statistical evidence that diurnal temperature range (DTR) is positively correlated to human morbidity and mortality despite the lack of clear clinical understanding. We examine a 14-year daily time series of emergency department (ED) admissions to the University of Virginia Medical Center in Charlottesville, Virginia, relative to long-term climate records from the Charlottesville/Albemarle County Airport weather station and the Spatial Synoptic Classification. DTR has a consistent strong positive correlation (r ~ 0.5) with maximum temperature in all months but only a weak, negative correlation (r ~- 0.1) with minimum temperature except in late summer (r ~- 0.4). Warm season DTR is highest on dry air mass days with low dew point temperatures. Cool season DTR is unrelated to morning temperature. Using a distributed lag non-linear model with an emphasis on DTR and its seasonal variation, after stratifying the models by season, we find that ED visits are linked to extreme cold events (cold days and nights) and high DTR in the cold season. In the warm season, ED visits are also linked to high DTR, but these are cool, dry, and pleasant days. The existing confusion regarding interpretation of DTR impacts on health might be rectified through a more careful analysis of the underlying physical factors that drive variations in DTR over the course of a year.

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

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

In the light of change: a mixed methods investigation of climate perceptions and the instrumental record in northern Sweden.

Significant climate change in the Arctic has been observed by indigenous peoples and reported in scientific literature, but there has been little research comparing these two knowledge bases. In this study, Sami reindeer herder interviews and observational weather data were combined to provide a comprehensive description of climate changes in Northern Sweden. The interviewees described warmer winters, shorter snow seasons and cold periods, and increased temperature variability. Weather data supported three of these four observed changes; the only change not evident in the weather data was increased temperature variability. Winter temperatures increased, the number of days in cold periods was significantly reduced, and some stations displayed a 2 month-shorter snow cover season. Interviewees reported that these changes to the wintertime climate are significant, impact their identity, and threaten their livelihood. If consistency between human observations of changing weather patterns and the instrumental meteorological record is observed elsewhere, mixed methods research like this study can produce a clearer, more societally relevant understanding of how the climate is changing and the impacts of those changes on human well-being.

Heat exposure during outdoor activities in the US varies significantly by city, demography, and activity.

Environmental heat is a growing public health concern in cities. Urbanization and global climate change threaten to exacerbate heat as an already significant environmental cause of human morbidity and mortality. Despite increasing risk, very little is known regarding determinants of outdoor urban heat exposure. To provide additional evidence for building community and national-scale resilience to extreme heat, we assess how US outdoor urban heat exposure varies by city, demography, and activity. We estimate outdoor urban heat exposure by pairing individual-level data from the American Time Use Survey (2004-2015) with corresponding meteorological data for 50 of the largest metropolitan statistical areas in the US. We also assess the intersection of activity intensity and heat exposure by pairing metabolic intensities with individual-level time-use data. We model an empirical relationship between demographic indicators and daily heat exposure with controls for spatiotemporal factors. We find higher outdoor heat exposure among the elderly and low-income individuals, and lower outdoor heat exposure in females, young adults, and those identifying as Black race. Traveling, lawn and garden care, and recreation are the most common outdoor activities to contribute to heat exposure. We also find individuals in cities with the most extreme temperatures do not necessarily have the highest outdoor heat exposure. The findings reveal large contrasts in outdoor heat exposure between different cities, demographic groups, and activities. Resolving the interplay between exposure, sensitivity, adaptive capacity, and behavior as determinants of heat-health risk will require advances in observational and modeling tools, especially at the individual scale.

Estimated Effect of Temperature on Years of Life Lost: A Retrospective Time-Series Study of Low-, Middle-, and High-Income Regions.

BACKGROUND: Numerous studies have reported a strong association between temperature and mortality. Additional insights can be gained from investigating the effects of temperature on years of life lost (YLL), considering the life expectancy at the time of death. OBJECTIVES: The goal of this work was to assess the association between temperature and YLL at seven low-, middle-, and high-income sites. METHODS: We obtained meteorological and population data for at least nine years from four Health and Demographic Surveillance Sites in Kenya (western Kenya, Nairobi), Burkina Faso (Nouna), and India (Vadu), as well as data from cities in the United States (Philadelphia, Phoenix) and Sweden (Stockholm). A distributed lag nonlinear model was used to estimate the association of daily maximum temperature and daily YLL, lagged 0-14 d. The reference value was set for each site at the temperature with the lowest YLL. RESULTS: Generally, YLL increased with higher temperature, starting day 0. In Nouna, the hottest location, with a minimum YLL temperature at the first percentile, YLL increased consistently with higher temperatures. In Vadu, YLL increased in association with heat, whereas in Nairobi, YLL increased in association with both low and high temperatures. Associations with cold and heat were evident for Phoenix (stronger for heat), Stockholm, and Philadelphia (both stronger for cold). Patterns of associations with mortality were generally similar to those with YLL. CONCLUSIONS: Both high and low temperatures are associated with YLL in high-, middle-, and low-income countries. Policy guidance and health adaptation measures might be improved with more comprehensive indicators of the health burden of high and low temperatures such as YLL. https://doi.org/10.1289/EHP1745.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

BACKGROUND: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. OBJECTIVES: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. METHODS: We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. RESULTS: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. CONCLUSIONS: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.