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Regional Oncology Research Center - Assessing Capacity to Address Obesity for CPC

$100,000P30FY2025CANIH

Johns Hopkins University, Baltimore MD

Investigators

Linked publications, trials & patents

Trial NCT02989636Trial NCT02516670Trial NCT02491411Trial NCT02489357Trial NCT02029950Trial NCT01935947Trial NCT01870596Trial NCT01783171Trial NCT01757639Trial NCT01578109Trial NCT01349972Trial NCT01349959Trial NCT01330173Trial NCT01264432Trial NCT01207726Trial NCT01207687Trial NCT01139970Trial NCT01132573Trial NCT01061749Trial NCT00971737Trial NCT00963807Trial NCT00899951Trial NCT00899548Trial NCT00898482Trial NCT00897338Trial NCT00897273Trial NCT00847171Trial NCT00795002Trial NCT00727441Trial NCT00673569Trial NCT00670917Trial NCT00660348Trial NCT00641303Trial NCT00641147Trial NCT00631137Trial NCT00616967Trial NCT00602771Trial NCT00588991Trial NCT00566098Trial NCT00524017Trial NCT00499733Trial NCT00499486Trial NCT00493025Trial NCT00492921Trial NCT00489281Trial NCT00478062Trial NCT00478010Trial NCT00471653Trial NCT00470093Trial NCT00469820Trial NCT00445484Trial NCT00433472Trial NCT00425477Trial NCT00407966Trial NCT00401024Trial NCT00389610Trial NCT00387465Trial NCT00381550Trial NCT00373191Trial NCT00369681Trial NCT00368914Trial NCT00363649Trial NCT00361296Trial NCT00356928Trial NCT00354640Trial NCT00343447Trial NCT00336063Trial NCT00334542Trial NCT00324870Trial NCT00313560Trial NCT00311623Trial NCT00305760Trial NCT00303927Trial NCT00293410Trial NCT00293397Trial NCT00293280Trial NCT00290732Trial NCT00287989Trial NCT00287872Trial NCT00281970Trial NCT00281866Trial NCT00278200Trial NCT00278161Trial NCT00278109Trial NCT00276744Trial NCT00276601Trial NCT00276588Trial NCT00274768Trial NCT00265915Trial NCT00265837Trial NCT00262834Trial NCT00258206Trial NCT00258180Trial NCT00255775Trial NCT00255710Trial NCT00245115Trial NCT00244959Trial NCT00242996Trial NCT00238368Trial NCT00238277

Abstract

Obesity is a leading risk factor for numerous chronic diseases, including cancer, and is expected to soon outweigh the influence of other major risk factors such as smoking. Differences in the food environment, including limited availability and affordability of healthy foods in urban communities, exacerbate disease outcomes and mortality. Policies and programs aimed at modifying the food environment have shown promise in improving dietary behaviors and reducing health risks. However, policymakers and stakeholders currently lack tools to test the potential effectiveness and sustainability of proposed interventions, hindering their ability to make informed decisions. This project focuses on the planning and groundwork needed to develop a simulation model of the Baltimore, Maryland food environment using a whole-of-systems approach (WSA). The proposed future simulation model will allow stakeholders—including policymakers, neighborhood associations, and public health leaders—to virtually test the impact of various policies and programs on dietary behaviors, obesity, and cancer risk. This adaptable tool will equip communities to identify synergistic interventions to improve population health. The project’s Specific Aims are as follows: 1) Data Collection and Synthesis (Gather data on the prevalence of obesity and cancer in Baltimore, incorporating behavioral, household, and community-level determinants; and develop an integrated database to support the parameterization of the simulation model); 2) Stakeholder Engagement and Qualitative Research (Identify and engage key stakeholders, including policymakers, researchers, and community leaders, through targeted outreach and partnerships; and conduct semi-structured interviews and group model-building sessions to identify salient and modifiable features of the food environment that can serve as levers for sustainable change); and 3) Report Development and Simulation Model GUI Design (Synthesize findings into a comprehensive report that outlines a WSA framework for addressing obesity and cancer risk; and develop a prototype of a web-based graphical user interface (dashboard) to support stakeholder decision-making, integrating interactive scenario testing tools, geospatial mapping, and visualized policy impacts). This work is guided by two conceptual frameworks: the Whole-of-Systems Approach (WSA) and the Socio-Ecological Model (SEM). These frameworks will inform the model’s design, ensuring it captures the multilevel factors influencing obesity and cancer risk. Expected outcomes include a robust, integrated database of obesity and cancer determinants, a detailed report on systems-based intervention strategies, and a prototype GUI for policy and program planning. This project lays the foundation for a scalable simulation model that can inform transformative public health strategies in Baltimore and similar urban communities nationwide. By integrating data, stakeholder input, and innovative technology, the project aims to promote community health and advance the science of public health decision-making.

View original record on NIH RePORTER →