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Comparing last stable address parcel value versus neighborhood values for a random sample of homeless: An initial test of the “tenant of last resort” hypothesis
Wednesday, October 29, 2008
Brian McKean
,
School of Social Work, University of Alabama, Tuscaloosa, AL
Carol North, MD, MPE
,
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
Introduction: Research on homelessness has failed to develop causal models distinguishing homeless individuals from other high-risk poverty populations. Other research has found availability and affordability of rental units associated with neighborhood rates of homelessness. Building on this, we hypothesize that “future homeless” individuals may be identified through examining individual housing units, that these persons represent what we term the “tenant of last resort”. This presentation presents an initial, simplified test of this hypothesis. Methods: The sample of individuals was randomly recruited for a NIDA-funded homelessness study. As part of the interview, individuals identified their last stable address. Using public data from the City Assessor's Office, each address was geocoded and matched to parcel values assessed in the year 2000. This parcel was matched with “neighborhood” parcels (residential units within 200 feet of the address), and mean value calculated. To control for gentrification, parcel values greater than $150,000 were eliminated. Last housed address and neighborhood values were compared using paired-sample t-tests (n=168). Results: Last stable housing address values were less than half of the surrounding neighborhoods ($9,000 vs. $21,000); however, these differences were not statistically significant (p=.14). Discussion: While results failed to disprove the null hypothesis, they suggest the promise of the approach. More sophisticated modeling (e.g., change in values over time) represent a next step in testing the “tenant of last resort” hypothesis. If upheld, the ability to identify addresses from which individuals are likely to become homeless has potential to create a true primary prevention response to homelessness.
Learning Objectives: 1. To articulate the hypothesized relationship between housing parcel value and onset of homelessness.
2. To discuss how geocoding can be used to exam parcels within neighborhoods.
3. To describe differences between individual-level and environmental-level constructs of homelessness and housing.
Keywords: Geocoding, Homelessness
Presenting author's disclosure statement:Qualified on the content I am responsible for because: I am primary author of the presentation.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.
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