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Grant Details

Grant Number: 5R21CA174469-02 Interpret this number
Primary Investigator: Shariff-Marco, Salma
Organization: Cancer Prevention Instit Of California
Project Title: Developing Neighborhood Archetypes for Understanding Disparities in Cancer
Fiscal Year: 2015


Abstract

DESCRIPTION (provided by applicant): Disparities in cancer survival continue to persist by race/ethnicity, socioeconomic status (SES) and nativity. Neighborhood factors are critical pathways through which disparities are shaped and perpetuated. However, the literature has shown mixed results and neighborhood-based interventions have had limited success. To advance research on neighborhoods and health, new approaches need to reflect the fact that neighborhood effects on health arise through complex and dynamic processes, underscoring the importance of studying not only the individual effects of neighborhood features on health outcomes, but also their synergistic effects. A promising approach is to encompass multiple dimensions within a single classification system, archetypes, that capture meaningful distinctions across neighborhoods (e.g., Low SES, rural; Poor, urban minority; Middle-class suburban/exurban families). The archetype approach is an efficient way to maximally integrate multiple sources of available information on neighborhood characteristics and has the potential to identify improved opportunities for intervening and reducing health disparities. Leveraging a comprehensive database of small- area level data on social and built neighborhood environments and applying novel statistical approaches, this application proposes to develop neighborhood archetypes around two time periods, 2000 and 2010, for the large, diverse state of California. The central hypotheses are that 1) multiple neighborhood factors can be combined together to form neighborhood archetypes; and 2) that cancer mortality among breast and prostate cancer patients will vary by these neighborhood archetypes, and these associations will vary by race/ethnicity and nativity. The specific aims of this study are to: 1) Investigate the utiity of the archetypes approach to characterize distinct neighborhoods across California. Specifically, we will extend to the census block group level previously developed census tract neighborhood archetypes using confirmatory latent class analysis (LCA). We will also expand, with additional built and social environment features, prior neighborhood archetypes using exploratory LCA. 2) Examine the associations between neighborhood archetypes and survival among a population-based, racially/ethnically diverse set of breast and prostate cancer patients. Specifically, we will test whether neighborhood archetypes are associated with all cause and cancer- specific mortality and whether this association is moderated by race/ethnicity. We will also test whether nativity moderates the neighborhood archetype associations among Hispanics and Asian Americans. The resulting neighborhood archetypes will provide an innovative resource for future research. Applying the archetypes to investigate breast and prostate cancer survival among California's diverse population, this research will yield insights into how neighborhood characteristics work synergistically with each other and interact with individual characteristics to influence health. This research has the potential to contribute to a broader, more fundamental understanding of place effects on health, with applications to both population health and health disparities research.



Publications

Disparities in Prostate Cancer Survival According to Neighborhood Archetypes, A Population-Based Study.
Authors: DeRouen M.C. , Yang J. , Jain J. , Weden M.M. , Gomez S.L. , Shariff-Marco S. .
Source: Urology, 2022 May; 163, p. 138-147.
EPub date: 2021-07-22.
PMID: 34303761
Related Citations

Neighborhood archetypes and breast cancer survival in California.
Authors: Shariff-Marco S. , DeRouen M.C. , Yang J. , Jain J. , Nelson D.O. , Weden M.M. , Gomez S.L. .
Source: Annals of epidemiology, 2021 May; 57, p. 22-29.
EPub date: 2021-02-10.
PMID: 33577928
Related Citations




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