Characterization of heat index experienced by individuals residing in urban and rural settings

Overnight heat in sleep spaces of housed and unhoused residents: results and recommendations from a Knoxville, Tennessee, case study

Nighttime heat is an important factor in heat-health outcomes, though nighttime heat exposure and its impacts are poorly understood. We assessed overnight heat in indoor (n = 12) and outdoor (n = 3) living spaces in Knoxville, Tennessee, using iButton Hygrochrons in August 2021. Indoor sleep spaces, all of which were air conditioned, reported a variety of overnight conditions. Indoor sleep spaces were both warmer and cooler than outdoor temperatures overnight, and some participants noted having physical health effects of overnight heat in their homes. Downtown outdoor sleep spaces, including a park and encampment, exhibited an urban heat island signal, staying warmer than other outdoor areas. Future research should focus on the intensity and length of the overnight recovery period for individuals and how that affects heat-health outcomes, especially after being exposed to daytime heat. Specifically, do homes reach a cool enough temperature for recovery, and do outdoor sleeping spaces offer a long enough and cool enough period for recovery? We provide some recommendations for such future studies, including (1) focus on purposeful sampling, (2) use deliberate sensor placement for representative results, (3) prepare for participant drop-off due to non-compliance and technological problems, and (4) strategically gather demographic information.

Simulating patterns of life: More representative time-activity patterns that account for context

BACKGROUND

Complex contributions of environment to health are intimately connected to human behavior. Modeling of human behaviors and their influences helps inform important policy decisions related to critical environmental and public health challenges. A typical approach to human behavior modeling involves generating daily schedules based on time-activity patterns of individual humans, simulating 'agents' with these schedules, and interpreting patterns of life that emerge from the simulation to inform a research question. Current behavior modeling, however, rarely incorporates the context that surrounds individuals' truly broad scope of activities and influences on those activities.

OBJECTIVES

We describe in detail a range of elements involved in generating time-activity patterns and connect work in the social science field of behavior modeling with applications in exposure science and environmental health. We propose a framework for behavior modeling that takes a systems approach and considers the broad scope of activities and influences required to simulate more representative patterns of life and thus improve modeling that underlies understanding of environmental contributions to health and associated decisions to promote and protect public health.

METHODS

We describe an agent-based modeling approach reliant on generating a population's schedules, filtering the schedules, simulating behavior using the schedules, analyzing the emergent patterns, and interrogating results that leverages general empirical information in a systems context to inform fit-for-purpose action.

DISCUSSION

We propose a centralized and standardized program to codify behavior information and generate population schedules that researchers can select from to simulate human behavior and holistically characterize human-environment interactions for a variety of public health applications.

Individually experienced heat index in a coastal Southeastern US city among an occupationally exposed population

Recent studies have characterized individually experienced temperatures or individually experienced heat indices, including new exposure metrics that capture dimensions of exposure intensity, frequency, and duration. Yet, few studies have examined the personal thermal exposure in underrepresented groups, like outdoor workers, and even fewer have assessed corresponding changes in physiologic heat strain. The objective of this paper is to examine a cohort of occupationally exposed grounds and public safety workers (n = 25) to characterize their heat exposure and resulting heat strain. In addition, a secondary aim of this work is to compare individually heat index exposure (IHIE) across exposure metrics, fixed-site in situ weather stations, and raster-derived urban heat island (UHI) measurements in Charleston, SC, a humid coastal climate in the Southeastern USA. A Bland-Altman (BA) analysis was used to assess the level of agreement between the personal IHIE measurements and weather-station heat index (HI) and Urban Heat Island (UHI) measurements. Linear mixed-effect models were used to determine the association between individual risk factors and in situ weather station measurements significantly associated with IHIE measurements. Multivariable stepwise Cox proportional hazard modeling was used to identify the individual and workplace factors associated with time to heat strain in workers. We also examined the non-linear association between heat strain and exposure metrics using generalized additive models. We found significant heterogeneity in IHIE measurements across participants. We observed that time to heat strain was positively associated with a higher IHIE, older age, being male, and among Caucasian workers. Important nonlinear associations between heat strain occurrence and the intensity, frequency, and duration of personal heat metrics were observed. Lastly, our analysis found that IHIE measures were significantly similar for weather station HI, although differences were more pronounced for temperature and relative humidity measurements. Conversely, our IHIE findings were much lower than raster-derived UHI measurements. Real-time monitoring can offer important insights about unfolding temperature-health trends and emerging behaviors during thermal extreme events, which have significant potential to provide situational awareness.

Heat exposure misclassification: Do current methods of classifying diurnal range in individually experienced temperatures and heat indices accurately reflect personal exposure?

Wearable sensors have been used to collect information on individual exposure to excessive heat and humidity. To date, no consistent diurnal classification method has been established, potentially resulting in missed opportunities to understand personal diurnal patterns in heat exposure. Using individually experienced temperatures (IET) and heat indices (IEHI) collected in the southeastern United States, this work aims to determine whether current methods of classifying IETs and IEHIs accurately characterize "day," which is typically the warmest conditions, and "night," which is typically the coolest conditions. IET and IEHI data from four locations were compared with the closest hourly weather station. Different day/night classifications were compared to determine efficacy. Results indicate that diurnal IET and IEHI ranges are higher than fixed-site ranges. Maximum IETs and IEHIs are warmer and occur later in the day than ambient conditions. Minimum IETs are lower and occur earlier in the day than at weather stations, which conflicts with previous assumptions that minimum temperatures occur at night. When compared to commonly used classification methods, a method of classifying day and night based on sunrise and sunset times best captured the occurrence of maximum IETs and IEHIs. Maximum IETs and IEHIs are often identified later in the evening, while minimum IETs and IEHIs occur throughout the day. These findings support future research focusing on nighttime heat exposure, which can exacerbate heat-related health issues, and diurnal patterns of personal exposure throughout the entire day as individual patterns do not necessarily follow the diurnal pattern seen in ambient conditions.

Effect of the Near-Future Climate Change under RCP8.5 on the Heat Stress and Associated Work Performance in Thailand

Increased heat stress affects well-being, comfort, and economic activities across the world. It also causes a significant decrease in work performance, as well as heat-related mortality. This study aims to investigate the impacts of the projected climate change scenario under RCP8.5 on heat stress and associated work performance in Thailand during the years 2020–2029. The model evaluation shows exceptional performance in the present-day simulation (1990–1999) of temperature and relative humidity, with R2 values ranging from 0.79 to 0.87; however, the modeled temperature and relative humidity are all underestimated when compared to observation data by −0.9 °C and −27%, respectively. The model results show that the temperature change will tend to increase by 0.62 °C per decade in the future. This could lead to an increase in the heat index by 2.57 °C if the temperature increases by up to 1.5 °C in Thailand. The effect of climate change is predicted to increase heat stress by 0.1 °C to 4 °C and to reduce work performance in the range of 4% to >10% across Thailand during the years 2020 and 2029.

Environmental Heat Exposure Among Pet Dogs in Rural and Urban Settings in the Southern United States

With advancing global climate change, heat-related illnesses and injuries are anticipated to become more prevalent for humans and other species. Canine hyperthermia is already considered an important seasonal emergency. Studies have been performed on the risk factors for heat stroke in canine athletes and military working dogs; however there is limited knowledge on environmental risk factors for the average pet dog. This observational study explores variation in individually experienced environmental temperatures of pet dogs (N = 30) in rural and urban environments in central Alabama. Temperature data from dogs and their owners was collected using wearable personal thermometers. Demographic data on the dogs was collected using a brief survey instrument completed by their owners. Dogs included in the study varied in signalment, activity level, and home environment. Linear mixed effects regression models were used to analyze repeated measure temperature and heat index values from canine thermometers to explore the effect of environmental factors on the overall heat exposure risk of canine pets. Specifically, the heat exposures of dogs were modeled considering their owner's experienced temperatures, as well as neighborhood and local weather station measurements, to identify factors that contribute to the heat exposure of individual dogs, and therefore potentially contribute to heat stress in the average pet dog. Results show hourly averaged temperatures for dogs followed a diurnal pattern consistent with both owner and ambient temperature measurements, except for indoor dogs whose recordings remained stable throughout the day. Heat index calculations showed that owners, in general, had more hours categorized into the National Weather Station safe category compared to their dogs, and that indoor dogs had a greater proportion of hours categorized as safe compared to outdoor dogs. Our results suggest that the risk of the average pet dog to high environmental heat exposure may be greater than traditional measures indicate, emphasizing that more localized considerations of temperature are important when assessing a dog's environmental risk for heat-related injury or illness.

A community-engaged approach to understanding environmental health concerns and solutions in urban and rural communities

Background

Focus groups and workshops can be used to gain insights into the persistence of and potential solutions for environmental health priorities in underserved areas. The objective of this study was to characterize focus group and workshop outcomes of a community-academic partnership focused on addressing environmental health priorities in an urban and a rural location in Alabama between 2012 and 2019.

Methods

Six focus groups were conducted in 2016 with 60 participants from the City of Birmingham (urban) and 51 participants from Wilcox County (rural), Alabama to discuss solutions for identified environmental health priorities based on previous focus group results in 2012. Recorded focus groups were transcribed and analyzed using the grounded theory approach. Four follow-up workshops that included written survey instruments were conducted to further explore identified priorities and determine whether the priorities change over time in the same urban (68 participants) and rural (72 participants) locations in 2018 and 2019.

Results

Consistent with focus groups in 2012, all six focus groups in 2016 in Birmingham identified abandoned houses as the primary environmental priority. Four groups listed attending city council meetings, contacting government agencies and reporting issues as individual-level solutions. Identified city-level solutions included city-led confiscation, tearing down and transferring of abandoned property ownership. In Wilcox County, all six groups agreed the top priority was drinking water quality, consistent with results in 2012. While the priority was different in Birmingham versus Wilcox County, the top identified reason for problem persistence was similar, namely unresponsive authorities. Additionally, individual-level solutions identified by Wilcox County focus groups were similar to Birmingham, including contacting and pressuring agencies and developing petitions and protesting to raise awareness, while local policy-level solutions identified in Wilcox County included government-led provision of grants to improve septic systems, and transparency in allocation of funds. Workshops in 2018 and 2019 further emphasized water quality as the top priority in Wilcox County, while participants in Birmingham transitioned from abandoned houses as a top priority in 2018 to drinking water quality as a new priority in 2019.

Conclusions

Applying a community-engaged approach in both urban and rural locations provided better understanding of the unique opportunities and challenges for identifying potential interventions for environmental health priorities in both locations. Results can help inform future efforts to address locally defined environmental health issues and solutions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11799-1.