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ABSTRACT
Research has demonstrated that natural disasters, like flooding that are increasing with climate change, can have profound mental health effects. Moreover, these outcomes are not experienced evenly across the population with disadvantaged populations like racial/ethnic minorities and lower socio-economic status individuals being more likely to report psychological diagnoses and symptoms related to floods. However, the mechanisms that could account for the link between social vulnerability and worry about the threat of flooding remain poorly understood. In this analysis, we use a 2022 survey of Houston-area residents to examine how perceived flood risk and subjective flood preparedness relate to racial/ethnic differences in worry about the threat of flooding. We find that both individual-level and area-level race/ethnicity are significantly related to greater worry about the threat of flooding. Further, this is partially mediated by perceived flood risk, but not subjective flood preparedness. This suggests that policies and infrastructure priorities that reduce risk rather than prepare households for flooding would accomplish more in closing the gap in social disparities in mental health outcomes from flooding.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. We acknowledge that this method of single imputation for income is limited compared to multiple imputation, which allows for less certainty in the precision of the estimated values by computing several permutations of the same dataset (Rubin Citation2004). However, for imputation of a single control variable for which we have several related socio-economic variables, single imputation is the most parsimonious approach.
2. As a check on this choice of measure, we ran all of the same models using racial/ethnic composition scores, with percent Black, percent Latino, and percent Asian in the ZIP code. These results are fairly similar to the ones presented here, with only minor differences in the coefficient size, with slightly smaller effect sizes for percent Black in particular (results available upon request). Using these scores presented a problem with multicollinearity, though, with a higher variance inflation factor between percent Black and percent in poverty. Thus, for both the conceptual and empirical reasons laid out here, we decided to present the results with the clustering scores as described.
3. As a check on this limitation, we also ran a version of these analyses using weighted least squares to adjust the models to the proportions of some of these variables that are skewed as compared to Harris County statistics, including race, sex, and education levels (Dickens Citation1990). These results were not substantively different in their major findings with only minor differences in the coefficients and standard errors, indeed with standard errors that were slightly smaller in most cases as compared to the analysis presented here. Thus, in order to present a simpler version of the analysis, and to allow for the correction on the standard errors for geographic clustering, we present the models with ordered logistic regression models with cluster robust standard errors in lieu of using a weighted approach.
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Notes on contributors
Kathryn Freeman Anderson
Kathryn Freeman Anderson is an Associate Professor in the Department of Sociology at the University of Houston. Her research focuses on understanding the social sources of health disparities in the United States. In particular, she examines the role of race/ethnicity and urban neighborhood dynamics to analyze how these factors may affect individual well-being. Her recent work has been published in the Journal of Health and Social Behavior, City & Community, and Race and Social Problems.
Nicole Hart
Nicole Hart is currently a Ph.D. student in Department of Sociology at the University of Chicago. Her interests mainly involve anti-Black racism and how that affects Black well-being in several contexts. She focuses on urban sociology, particularly Houston, Texas, and has previously completed projects related to Black-White education disparities, racial differences in mental health coping strategies, as well as racial differences in flood consequences. Her work incorporates geospatial, quantitative, and qualitative methods to explore how anti-Black racism shapes Black mental and physical health, as well as their social position in American society.
Hanadi S. Rifai
Hanadi S. Rifai is Moores Professor of Civil and Environmental Engineering at the University of Houston and Director of the Hurricane Resilience Research Institute (HuRRI). She researches natural hazards and their cascading impacts on environment, communities, and health of people and ecosystems in addition to assessing risks, mitigation and adaptation to climate stressors.