Author ORCID Identifier

https://orcid.org/0000-0001-7144-9073

Date of Award

Fall 9-12-2024

Degree Type

Dissertation

Degree Name

Doctor of Public Health (DrPH)

Department

Public Health

First Advisor

Kimberley Freire, PhD MPH

Second Advisor

Harry Heiman, MD MPH

Third Advisor

Julianna Reece, MD, MBA MPH

Fourth Advisor

Syreeta Skelton-Wilson, PhD MPA

Abstract

Background: The Social Determinants of Health (SDOH) profoundly impact chronic disease outcomes but are not universal for all populations within the United States. SDOH factors impacting American Indian and Alaska Native (AI/AN) communities are distinct but frequently do not appear in peer-reviewed literature, making it challenging to locate publicly available data for tracking, monitoring, and measuring the impacts of health interventions. These issues are further complicated by notable gaps concerning racial misclassification that profoundly impact the undercounting and underreporting of AI/AN individuals in national data systems.

Purpose: The primary goal of this project is to develop a set of indicators and data tools that public health agencies and organizations can use to measure the impacts of SDOH in the AI/AN communities they serve. This knowledge can then be applied to improve program planning, evaluation, and prevention efforts, as well as to identify and address gaps in national data sources, thereby enhancing the quality of public health data for AI/AN communities.

Methods: This project used a modified version of the CDC’s Sexual Violence Indicator Framework to conduct a systematic review of publicly available data sources. Five tribal health experts participated in the project, ensuring it remained community-centered and that the findings could be quickly implemented in public health practice.

Results: Out of 60 data sources (e.g., surveillance systems, surveys, and administrative systems), 30 data sources comprising ~252 indicators were selected as indicators for measuring SDOH for AI/AN but notable gaps appeared across cultural constructs which are viewed as protective factors. Of note, one-third (or 30%) of data sources included in this study collapsed racial identities into ‘AI/AN’ race only or classified biracial AI/AN individuals as ‘Two or More Races,’ which further restricted the sample size, making it challenging to use public data in practice.

Implications for Public Health Practice: Based on the results identified in this project, recommendations to improve SDOH data quality and cultural relevance include: (1) Create partnerships with Tribes that center on developing uniform AI/AN racial definitions and culturally responsive strategies to increase data collection across federal data sources; (2) Develop asset-based SDOH and culturally appropriate measures that can be used in the Tribal Public Health System, and (3) Incorporate qualitative evidence in AI/AN population health assessment which can increase information and relevance in small sample sizes.

DOI

https://doi.org/10.57709/37740391

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