Sheltered from the heat? How tents and shade covers may unintentionally increase air temperature exposures to unsheltered communities

Objective

Heat vulnerability and homelessness are central public health concerns in cities globally, and public health implementation should address these two challenges in tandem to minimize preventable heat-related morbidity and mortality. Populations facing unsheltered homelessness use tents (or similar shelters) with shading features to minimize sun and heat exposure. This study evaluates the efficacy of different tent cover (shading) materials and how they moderate the in-tent air temperature (Tair) exposures of tent users during extreme summer conditions.

Study design

Within-tent Tair monitoring using Kestrel Drop devices occurred across three full typical summer days in Phoenix, Arizona in July 2022.

Methods

In-tent Tair were statistically compared between six small side-by-side identical tents with different cover materials (control (no cover), mylar, white bedsheet, tarp, sunbrella fabric, aluminum foil), as well as with ambient Tair.

Results

Using any tent resulted in higher daytime in-tent Tair than ambient Tair. Further, compared to a control tent, the Tair within tents shaded with sunbrella, tarp, and white bedsheet had significantly higher Tair at all times (2.36 °C, 2.46 °C, and 1.11 °C higher Tair, respectively), controlling for Tair and day/night.

Conclusion

Adding cover materials over tents may increase heat risk to an already vulnerable population at certain times of the day. Higher in-tent Tair is attributable to the reduced ability for heat and vapor to escape, largely due to reduced ventilation (mixing). Local authorities and welfare associations should reconsider using unventilated tents for shading and promote more widespread, ventilated tents and shade to ensure that prevention efforts do not further marginalize the most vulnerable. Future work should incorporate more comprehensive measurements of solar radiation to quantify overall heat stress for exposure reduction techniques.

Mapping the gaps between cooling benefits of urban greenspace and population heat vulnerability

We provide a novel method to assess the heat mitigation impacts of greenspace though studying the mechanisms of ecosystems responsible for benefits and connecting them to heat exposure metrics. We demonstrate how the ecosystem services framework can be integrated into current practices of environmental health research using supply/demand state-of-the-art methods of ecological modeling of urban greenspace. We compared the supply of cooling ecosystem services in Boston measured through an indicator of high resolution evapotranspiration modeling, with the demand for benefits from cooling measured as a heat exposure risk score based on exposure, hazard and population characteristics. The resulting evapotranspiration indicator follows a pattern similar to conventional greenspace indicators based on vegetation abundance, except in warmer areas such as those with higher levels of impervious surface. We identified demand-supply mismatch areas across the city of Boston, some coinciding with affordable housing complexes and long term care facilities. This novel ES-framework provides cross-disciplinary methods to prioritize urban areas where greenspace interventions can have the most impact based on heat-related demand.

Heat illness data strengthens vulnerability maps

Background

Previous extreme heat and human health studies have investigated associations either over time (e.g. case-crossover or time series analysis) or across geographic areas (e.g. spatial models), which may limit the study scope and regional variation. Our study combines a case-crossover design and spatial analysis to identify: 1) the most vulnerable counties to extreme heat; and 2) demographic and socioeconomic variables that are most strongly and consistently related to heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, acute renal disease, and respiratory disease) across 67 counties in the state of Florida, U. S over 2008–2012.

Methods

We first used a case-crossover design to examine the effects of air temperature on daily counts of health outcomes. We employed a time-stratified design with a 28-day comparison window. Referent periods were extracted from ±7, ±14, or ± 21 days to address seasonality. The results are expressed as odds ratios, or the change in the likelihood of each health outcome for a unit change in heat exposure. We then spatially examined the case-crossover extreme heat and health odds ratios and county level demographic and socioeconomic variables with multiple linear regression or spatial lag models.

Results

Results indicated that southwest Florida has the highest risks of cardiovascular disease, dehydration, acute renal disease, and respiratory disease. Results also suggested demographic and socioeconomic variables were significantly associated with the magnitude of heat-related health risk. The counties with larger populations working in farming, fishing, mining, forestry, construction, and extraction tended to have higher risks of dehydration and acute renal disease, whereas counties with larger populations working in installation, maintenance, and repair workers tended to have lower risks of cardiovascular, dehydration, acute renal disease, and respiratory disease. Finally, our results showed that high income counties consistently have lower health risks of dehydration, heat-related illness, acute renal disease, and respiratory disease.

Conclusions

Our study identified different relationships with demographic/socioeconomic variables for each heat-sensitive health outcome. Results should be incorporated into vulnerability or risk indices for each health outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12097-6.

The relationship between population heat vulnerability and urbanization levels: A county-level modeling study across China

The purpose of this work was to assess population vulnerability to heat-related health risks and its relationship with urbanization levels to provide essential information for the future development and policy-making for climate change adaptation. We constructed a heat vulnerability index (HVI), quantified the population heat vulnerability in each county across China by a principal component analysis (PCA) of multiple factors, and assessed urbanization levels in each county using multisource data. Then, the HVI was validated using the heat-attributable fraction (heat-AF) of nonaccidental mortality based on death monitoring data and meteorological data from 95 counties across China. The results showed that our HVI was significantly positively associated with the heat AF of nonaccidental mortality. A negative correlation was observed between the urbanization level and the HVI. The HVI was generally higher in less urbanized western China and lower in the more urbanized eastern regions. The baseline mortality occupies the top position in the importance ranking of the heat-vulnerability indicators at all three urbanization levels, but the other indicators, including the aging rate, agricultural population rate, education, ethnic structure, economic status, air conditioner ownership rate, and number of hospitals, ranked differently among different urbanization levels. This finding indicates that to reduce population heat vulnerability, the most important approach is to improve the health status of the whole population and reduce baseline mortality; additionally, regional-specific measures and emphasis should be adjusted reasonably along with the process of urbanization according to the characteristics and key factors of local heat vulnerability.

Development of a heat vulnerability index for New York State

OBJECTIVES

The frequency and intensity of extreme heat events are increasing in New York State (NYS) and have been linked with increased heat-related morbidity and mortality. But these effects are not uniform across the state and can vary across large regions due to regional sociodemographic and environmental factors which impact an individual's response or adaptive capacity to heat and in turn contribute to vulnerability among certain populations. We developed a heat vulnerability index (HVI) to identify heat-vulnerable populations and regions in NYS.

STUDY DESIGN

Census tract level environmental and sociodemographic heat-vulnerability variables were used to develop the HVI to identify heat-vulnerable populations and areas.

METHODS

Variables were identified from a comprehensive literature review and climate-health research in NYS. We obtained data from 2010 US Census Bureau and 2011 National Land Cover Database. We used principal component analysis to reduce correlated variables to fewer uncorrelated components, and then calculated the cumulative HVI for each census tract by summing up the scores across the components. The HVI was then mapped across NYS (excluding New York City) to display spatial vulnerability. The prevalence rates of heat stress were compared across HVI score categories.

RESULTS

Thirteen variables were reduced to four meaningful components representing 1) social/language vulnerability; 2) socioeconomic vulnerability; 3) environmental/urban vulnerability; and 4) elderly/ social isolation. Vulnerability to heat varied spatially in NYS with the HVI showing that metropolitan areas were most vulnerable, with language barriers and socioeconomic disadvantage contributing to the most vulnerability. Reliability of the HVI was supported by preliminary results where higher rates of heat stress were collocated in the regions with the highest HVI.

CONCLUSIONS

The NYS HVI showed spatial variability in heat vulnerability across the state. Mapping the HVI allows quick identification of regions in NYS that could benefit from targeted interventions. The HVI will be used as a planning tool to help allocate appropriate adaptation measures like cooling centers and issue heat alerts to mitigate effects of heat in vulnerable areas.