Housing cost, consistency, and context and their relationship to health

AbstractHousing insecurity is associated with myriad negative outcomes for individuals and communities. Less understood is the indirect and direct relationships between specific types of housing insecurity and health. Using Swope and Hernández’s (Citation2019) 4C’s of housing insecurity, data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), structural equation modelling, and binary logistic regression, we examine the relationship between different types of housing insecurity and mental and general health. We find housing cost independently decreases health outcomes while consistency insecurity indirectly affects health by increasing cost burdens. Most forms of housing cost, consistency, and context insecurity have independent and significant negative associations with short-term (12 month) and medium-term (seven to eight years) mental health. This suggests policymakers and advocates should place greater emphasis on housing assistance as an entitlement and cash assistance that vulnerable populations can use to address the cause of their specific type of housing insecurity.Keywords: Housing insecurityhealthhousing affordabilitycost burdenmental health AcknowledgementsWe thank the reviewers and editors for their helpful comments, which greatly improved this manuscript’s quality. An earlier version of this paper was presented at the 2021 American Society for Public Administration conference.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The most recent wave (wave V) was not fully released in time for this project.2 The final analytic sample used for this study is a subset of the original wave IV Add Health sample of 15,071 individuals. This sample consists of a total 11,303 respondents who possess non-missing data for all variables in the analysis (to avoid the need for data imputation).3 We do not include contextual variables in wave III in this model because of model stability issues. However, we get substantively similar results when including the context variables in wave III in our models.4 The SEM result without weights is largely similar to that of the analysis with weights, with three exceptions. As we expected, racial minority groups are statistically and significantly more likely to have housing insecurity for the unweighted SEM because Add Health oversampled racial minority parents with higher education (Chen & Chantala, Citation2014; Harris et al., Citation2009). Females are more likely to have a cost burden in wave IV (p < 0.001), and consistency in wave III and earlier has significant negative effects on general health (p < 0.001).Additional informationNotes on contributorsJinhee YunJinhee Yun is an Associate Research Fellow in the Department of Housing Culture Research at AURI (Architecture & Urban Research Institute). Her research focuses on poverty, the consequences of inequality, and the impacts of unequal access to opportunities, particularly on housing, neighborhoods, and community development.Megan E. HatchMegan E. Hatch is an associate professor in the Maxine Goodman Levin School of Urban Affairs at Cleveland State University. She studies the variation in policies within the US federalist system and the effects those disparities have on social equity, individuals, and institutions, with a particular focus on rental housing.