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It is often suggested that housing assistance helps adults overcome mental health challenges, yet researchers have long struggled to unravel the complex psychological pathways that explain whether and how housing assistance affects mental health. We advance the literature by testing for a direct association between housing assistance and two mental health outcomes: depression and anxiety. We also tested for indirect associations, focusing on whether housing assistance affected mental health by affecting psychological stress, sense of control over life circumstances (i.e., mastery), and exposure to discrimination. We found that housing assistance was directly associated with reduced anxiety, but no direct association was found for depression. We also found that housing assistance was associated with variables believed to indirectly influence mental health, including mastery and psychological stress. However, neither of these variables was associated with depression or anxiety. Although our findings show some positive relationships, receipt of housing assistance alone was only modestly associated with anxiety, and there was no association for depression. Our findings therefore suggest that mental health services should be made available to program participants because housing assistance alone may not promote better mental health. Supportive housing programs provide a promising model for delivering mental health services to program participants. However, housing planners and policymakers will need to develop new areas of expertise and new strategic priorities to ensure the effective expansion, implementation, and administration of such programs. [ABSTRACT FROM AUTHOR]

This paper describes how the Modified Lilien Index (MLI) can be used to measure the rate of neighborhood racial and ethnic change. The MLI is useful because it measures the rate of change across multiple racial and ethnic groups. It also weights the rate of change for each neighborhood based on changes in the racial and ethnic composition of the entire population, which helps contrast neighborhoods undergoing high and low rates of change compared to the nation as a whole. Using harmonized census data, we demonstrate the utility of the MLI by analyzing neighborhood change across four groups—White, Black, Latino, and Asian—from 1970 to 2010. We find that the rate of racial and ethnic change decreased substantially during this time period, but also that there is significant variation in this trend at the regional and metropolitan level. Based on these results, we suggest that the MLI can be used to identify emergent geographies of neighborhood racial and ethnic change within a broader territory and to quantify how change impacts community structure and the outcomes of individuals. [ABSTRACT FROM AUTHOR]

Critics of U.S. public housing often argue that the program discourages nonemployed residents from looking for work, yet little research has actually explored how public housing residents make decisions about whether to look for work. Thus, this article explores what factors distinguish nonemployed residents who are in the labor force (actively looking for work) from those who are out of the labor force (not actively looking for work). Relying on a sample of nonelderly, nondisabled public housing residents from Charlotte, North Carolina, we find that nonemployed residents who were older and showed signs of depression were more likely to be out of the labor force. In contrast, residents who were younger, had previously completed jobs training, or had some college education were more likely to be in the labor force. These findings suggest that health, education, and life-course stage may play an important role in determining nonemployed residents' decision to look for work. Our conclusion discusses how these factors may influence labor-force participation and the relevance of our findings to housing policymakers and scholars. [ABSTRACT FROM AUTHOR]

As hazards become more prevalent in the era of climate change, there have been a number of initiatives to develop'big data' indices to define areas most at risk. Across a number of these indices, place-based vulnerability is attributed, in part, to the racial and ethnic composition of a given neighborhood, city, or region. Within these vulnerability frameworks, areas with high concentrations of black, indigenous, and people of color (BIPOC) are often labeled as most vulnerable. We argue that this practice is problematic because it implies but does not make explicit an important link between BIPOC, vulnerability, and a long history of racialized development, while failing to illuminate and address theunderlying causes. [ABSTRACT FROM AUTHOR]