# Exploring the Effectiveness of Housing Policy as a Structural Intervention to Reduce Community Violence: An Evaluation of Choice Neighborhoods and Source of Income Anti-Discrimination Laws

> **NIH ALLCDC R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2024 · $397,402

## Abstract

Exploring the Effectiveness of Housing Policy as a Structural Intervention to Reduce Community
Violence: An Evaluation of Choice Neighborhoods and Source of Income Anti-Discrimination Laws
Project Summary/Abstract
The objective of the proposed study is to evaluate housing policy as a modifiable structural driver of community
violence and violence disparities among youth and young adults. We propose to evaluate two distinct housing
policies, each representing a different approach to addressing segregation and/or concentrated disadvantage.
We hypothesize that these policies will have downstream preventive effects on youth community violence via
their ameliorative effects on segregation and/or concentrated disadvantage, which are known causes of
violence. This proposal is responsive to Objective Three of the RFA: effectiveness research to evaluate
approaches that improve the social or structural conditions that contribute to community violence and
racial and ethnic inequities in risk for community violence. It also addresses the National Center for Injury
Prevention and Control’s research priority of youth violence. We will evaluate two policies: 1) the US
Department of Housing and Urban Development’s Choice Neighborhoods program, which provides
neighborhood revitalization grants to neighborhoods subject to historical disinvestment and with distressed
public housing, and 2) source-of-income (SOI) anti-discrimination laws, which prevent landlords from
discriminating against potential tenants that receive rental assistance via the Housing Choice Voucher program
(formerly called Section 8). We will accomplish our study objective through the completion of the following
specific aims: 1) to evaluate the effectiveness of Choice Neighborhoods and SOI anti-discrimination laws at
reducing community violence among youth and young adults; 2) to evaluate the effectiveness of Choice
Neighborhoods and SOI anti-discrimination laws at reducing racial and ethnic disparities in community violence
among youth and young adults; and 3) to identify and quantify mediators of the relationship between Choice
Neighborhoods and SOI anti-discrimination laws and community violence among youth and young adults. The
Choice Neighborhoods evaluation will use a quasi-experimental design, staggered difference-in-differences, to
estimate the average treatment effect associated with receiving a revitalization grant compared to not receiving
a grant (among grant applicants). The SOI anti-discrimination law evaluation will be a serial cross-sectional
study of approximately 80 cities using generalized estimating equations to estimate the association between
having these laws and youth community violence (and disparities therein). Youth community violence will be
measured as fatal and nonfatal assaultive injuries among people aged 10-34 years, measured with
comprehensive hospitalization and vital statistics data. Sophisticated causal inference methods, including
causal mediation analyses, ...

## Key facts

- **NIH application ID:** 10993951
- **Project number:** 1R01CE003644-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Rose Kagawa
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2024
- **Award amount:** $397,402
- **Award type:** 1
- **Project period:** 2024-09-30 → 2027-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10993951

## Citation

> US National Institutes of Health, RePORTER application 10993951, Exploring the Effectiveness of Housing Policy as a Structural Intervention to Reduce Community Violence: An Evaluation of Choice Neighborhoods and Source of Income Anti-Discrimination Laws (1R01CE003644-01). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/10993951. Licensed CC0.

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