Rent assistance and health: findings from Detroit

Abstract

This study assesses the relationship between rent assistance and health in a longitudinal, population-representative sample collected in the Detroit metro area. Previous research has found that rent assistance recipients are less healthy than otherwise similar non-recipients in the cross-section, but the evidence about the effects of rent assistance on health in the long run is ambiguous. Our study uses panel survey data to compare the health of recipients and eligible non-recipients at the study’s onset and four years later at follow-up with respect to an extensive set of physical, mental and behavioural health outcomes. Our results demonstrate that rent assistance recipients are in worse overall health than non-recipients, but also provide suggestive evidence that the programme may buffer health declines in the medium term. However, the positive buffering effects may be erased in the long run, as we simultaneously observed an increase in smoking among rent assistance recipients. Our study shows that the current shortage of rent assistance may have implications for population health.

Keywords:

• Health
• housing
• vouchers
• rent
• health disparities

Acknowledgements

Authors thank Sarah Burgard, Kristin Seefeldt, Huiyun Kim, Sarah Seeley, Roshanak Mehdipanah, and Natasha Pilkauskas for feedback on earlier drafts of this paper. The authors gratefully acknowledge use of the services and facilities of the Population Studies Center at the University of Michigan, funded by NICHD Center Grant R24 HD041028.

Notes

1. United States Housing Act of 1937, P.L. 93–383; 88 Stat. 653; 42 USC 1437 et seq.

2. Vouchers may also go to families displaced from other HUD programmes, for example, because of the demolition of public housing. Public housing agencies also have discretion to project-base vouchers by attaching them to specific housing units, or to allow first-time homebuyers to apply vouchers to monthly mortgage payments.

3. Chronic conditions included diabetes, asthma, hypertension, stroke and arthritis.

4. Marginal effects for continuous variables, such as age, measure instantaneous rate of change. The instantaneous rate of change is not always the same as the change associated with a one-unit change in the independent variable. Using the Stata spost13 package, we compared the instantaneous change reported in the tables with the one-unit change (Long & Freese, 2014). For simplicity, we will refer to a one-unit change in the text, while noting when there is a substantial difference between the instantaneous and one-unit rate of change.

5. The average marginal effects from linear regression models are identical to the estimated coefficients.

6. In contrast to earlier tables, we do not include a measure for ‘any chronic condition’ in Table 5, because having a chronic condition at baseline perfectly predicts having a chronic condition at follow.

7. We estimated all models in Table 5 with rent assistance recipients as the reference group to compare rent assistance recipients with ineligible respondents. The difference in marginal effects for these groups was statistically significant (p < 0.05) for Models 9, 11, 13 and 14.

8. See Instituting Smoke-Free Public Housing, 24 CFR §§ 965–966 (2016).