Grant Number:	5U54CA280811-04 Interpret this number
Primary Investigator:	Rehkopf, David
Organization:	Stanford University
Project Title:	The Upstream Center: Income Interventions to Address the Fundamental Causes of Cancer
Fiscal Year:	2026

Persistent poverty areas, a formal geographic classification developed by the United States Department of Agriculture and codified by Congress, is defined as an area with a poverty rate of 20% or higher across four consecutive ten-year time periods, spanning 30 years. Cancer rates are higher in these areas, and improving cancer outcomes in these areas requires transformational, multisector solutions that are co-created with the impacted communities. To address this challenge, we will form the Upstream Research Center, an innovative approach to provide practical policy-relevant solutions to the problems inherent in persistent poverty areas by leveraging state programs for Guaranteed Basic Income and the Earned Income Tax Credit (EITC). Our team science approach to this problem is supported by the unparalleled resources at Stanford University, the University of California, San Francisco and the University of California, Davis. Our work advances multiple conceptual and methodological innovations through two main research projects: 1) an ongoing partnership with the California Department of Social Services to access and evaluate a $35M intervention of Guaranteed Basic Income in persistent poverty areas with a focus on modifiable cancer risk factors and intermediate outcomes; 2) the impact of increases in income support through the EITC, which in California has a unique focus on lower income wage earners. Our Specific Aims are to: Aim 1. Build a collaborative community of residents in persistent poverty areas, policy makers, trainees, cancer and social science researchers and data scientists that co-create programs to address the fundamental impacts of low income, Aim 2. Evaluate the impact of income-based interventions in persistent poverty areas in Northern CA, Aim 3. Develop a mathematical model, with community input, that can assist in predicting long-term impacts of income-focused interventions on cancer incidence, providing community members, policy makers, and researchers with guidance on how best to eliminate the increased burden of cancer in persistent poverty areas, Aim 4. Develop and implement a career enhancement program that will facilitate the training and career development of interdisciplinary early-career scholars who are committed to advancing cancer research in persistent poverty areas and Aim 5. Implement innovative and collaborative cancer prevention and control programs identified through the Upstream Research Center research projects and our community partners to develop long-term sustainable strategies in our Northern CA Catchment Areas and across the Persistent Poverty Centers Network. Results from this novel groundbreaking work will lay the foundation for transformative approaches to address cancer prevention and control programs through capacity building and sustainable partnerships with policymakers, state and local agencies and community partners.




Hereditary gastric cancer checks its balance at the ATM: Broadening risk beyond CDH1.
Authors: Lott P.C. , Carvajal-Carmona L.G. .
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