# Health, Neighborhood Context, and Mobility

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2020 · $483,010

## Abstract

Neighborhood context may be an upstream cause of economic mobility, yet few neighborhood studies are
experimental, weakening causal inference and limiting policy translation. Our study proposes to analyze newly-
available data from a large, federal government initiated social experiment of voluntary neighborhood
relocation using housing vouchers in 5 US cities (the Moving to Opportunity, MTO, Study). Our project will test
whether, how, and among whom random assignment of an offer to move to a lower-poverty neighborhood
influenced the economic mobility of 4600 low-income families over a 15 year period. The goal of MTO was to
interrupt the cascading effects of neighborhood poverty for minority low-income families, by increasing area-
based access to opportunities, and thereby promote economic mobility. Although the MTO voucher
intervention did not consistently affect economic outcomes, it did profoundly affect health. Unfortunately, health
researchers have had limited access to MTO data, compromising the scientific payoff of the $70+ million
investment. So as of yet, we have no clear understanding of why results might differ across outcomes, groups,
or what mechanisms are at play, since few studies have tested mediation or moderation. Since health is one of
the most important barriers to economic self-sufficiency among low-income parents, it is conceivable that
economic and employment gains were concentrated among families who first experienced health
improvements. However testing whether factors that occurred after random assignment are precursors for
other outcomes is methodologically challenging. Fortunately, recent methodological developments in the
epidemiology discipline offer cogent solutions to model this complexity and bound any bias. We propose
secondary data analyses with newly available 15 year follow-up data from this experiment, to test whether
health influenced the economic effects of the randomized MTO housing voucher treatment. Paired with this
experimental design, we propose to apply innovative causal methods and machine learning techniques for
assessing mediation and effect modification, to overcome limitations and potential bias of traditional
approaches, and strengthen causal inference. Our R01 project builds on a productive, interdisciplinary team,
experienced with the MTO data, and draws on a barriers-to-employment framework. We propose 4 aims to
determine: whether the effect of MTO on economic outcomes was modified by baseline health vulnerability;
whether MTO improved parental economic outcomes, if they or their children experienced health gains;
whether MTO improved children’s employment and education, if they experienced health gains; whether MTO
improved economic outcomes, if families moved to neighborhoods with fewer spatial barriers to employment.
Our findings have direct policy relevance since they address a key policy question in housing voucher
implementation: incorporating elements from non-housing sectors (e.g., h...

## Key facts

- **NIH application ID:** 9949737
- **Project number:** 5R01HD090014-04
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** THERESA LOUISE OSYPUK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $483,010
- **Award type:** 5
- **Project period:** 2017-09-19 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9949737

## Citation

> US National Institutes of Health, RePORTER application 9949737, Health, Neighborhood Context, and Mobility (5R01HD090014-04). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/9949737. Licensed CC0.

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