Municipal Policy Heat Framework and Social Vulnerability: A City-Level Analysis

Background and Purpose: Heat-related illness and death disproportionately affect marginalized communities, with social vulnerability playing a bigger role than air temperature according to recent research. Cities must consider the inequitable effects of heat on their residents, as over 80% of heat deaths occur in urban areas. Municipal heat plans typically use the frameworks of urban heat island (UHI) and extreme heat event (EHE) to implement "hard" and "soft" interventions which modify the built environment and prepare for heat, respectively. This study examines how UHI and EHE framework statements relate to city-level interventions, controlling for selected vulnerability characteristics known to have a pronounced impact on heat vulnerability.

Methods: This study combines data from a previous study on heat-specific clauses in 50 U.S. cities and the American Community Survey (2015-2019), where heat data was coded based on the number of heat-related keywords presented in the municipal heat-response statements, and social vulnerability was measured based on city level. Hierarchical regression models were conducted to examine which variables of hard or soft interventions best predicted heat-problem framing, controlling for social vulnerability factors. Correlation analysis was further used to investigate the relationship between the framework of heat-problem and 21 specific interventions.

Results: Cities frame UHI and EHE in different ways, and the type of response hinges on how heat is viewed. The results of hierarchical regression indicated that UHI and EHE were individually positively associated with the number of hard and soft interventions. When hard and soft interventions were concurrently considered in the same model, hard intervention (p<.001) and the percentage of impoverished people in the city (p=.045) were significant in UHI, while soft interventions (p<.001) was significant and the percentage of people living in mobile homes was of marginal significance (p=0.056) in EHE. The correlation analysis results showed that UHI is highly correlated with mentions of trees (r = 0.82) and comprehensive approaches (r = 0.58) in hard interventions and mentions of policies (r = 0.59) and partnership (r = 0.57) in soft interventions. EHE is only highly correlated with comprehensive approaches (r = 0.58) in hard interventions but many in soft interventions, such as planning efforts (r = 0.81), program (r = 0.71), and funding (r = 0.66).

Conclusions and Implications: This study emphasizes the importance of city heat framing to guide intervention. Social work can help municipalities develop equitable action plans informed by physical science data. Hard interventions appear to be associated with active heat mitigation as they are aimed at decreasing UHI which is almost entirely man made as opposed to preparing for a heat wave that can occur regardless of human intervention that may be more associated with EHE. Therefore, we propose that cities prioritize UHI framing and hard interventions to encourage action. Limitations due to a small sample size and the variable of framework rather than implemented interventions call for future studies to investigate the experiences of marginalized populations in urban heat. Policy change is necessary as cities aim to eliminate heat related illness and death.