# Urban American Indian/Alaska Native Cultural Eating Values and Behaviors: Community-based, mixed methods research to inform a holistic and culturally-informed diabetes prevention intervention program

> **NIH NIH F31** · JOHNS HOPKINS UNIVERSITY · 2024 · $32,487

## Abstract

PROJECT SUMMARY/ABSTRACT
Background. Type 2 diabetes (T2D) disproportionately affects American Indian and Alaska Native (AI/AN)
communities, with even greater burden on under-resourced urban AI/AN communities. Past research has
shown that nutrition is deeply important for prevention of T2D, yet achieving proper nutrition requires a healthy
mental relationship with eating, something that may be difficult to achieve for many AI/ANs who experience a
disproportionate burden of mental illness. A promising intervention for improving holistic wellbeing is Intuitive
Eating (IE), an adaptive eating style that utilizes aspects of positive psychology to promote connection to
internal physiological cues to hunger and satiety. IE is a promising intervention for improving psychological
relationships with food, eating behaviors, and mental health but to date there have been no efforts to assess
IE’s compatibility with AI/AN cultural food values
or
the acceptability of IE to AI/AN communities.
Study Goals and Aims. The candidate will collaborate with two urban AI/AN communities in Minneapolis and
Baltimore to conduct an Exploratory Sequential Mixed Methods Community-Based Participatory Research
(CBPR) study. Specific aims are to: 1) qualitatively explore AI/AN cultural eating values and perceptions of IE;
2) Culturally adapt the Intuitive Eating Scale 2 (IES-2) for urban AI/AN cultural and social contexts using
community engaged participatory methods; and 3) Examine
construct
validity of the adapted IES-2 through
factor analysis and its associations with health outcome data.
Approach. Aim 1 of the study will utilize in-depth interviews with 30-40 urban AI/ANs to explore cultural eating
values, eating behaviors, and perceptions of IE. This qualitative data will be analyzed using an inductive
approach to gain a nuanced understanding of cultural eating values and eating behaviors within urban AI/AN
communities. Aim 2 will utilize CBPR methods to engage community research councils (CRCs) in the
integration of Aim 1 findings into the IES-2. Aim 3 will involve pilot testing the adapted measure alongside
relevant health data with
250
AI/AN adults. Confirmatory Factor Analysis will be used to examine the
construct
validity of the adapted IES-2. Secondarily, multiple linear and logistic regression will be used to assess
relationships between intuitive/cultural eating values and health outcome data (mental health, cultural
connectedness, fruit/vegetable intake, physical activity).
Fellowship Information. The proposed NRSA research will serve as the doctoral dissertation of Ms. Maudrie,
an American Indian PhD student at the Johns Hopkins Bloomberg School of Public Health, her research and
training are supported by a mentorship team of AI/AN health experts. This NRSA research builds upon the
candidate’s previous CBPR research with urban AI/AN communities and is aligned with the NIDDK’s mission to
improve the prevention of T2D & advance health equity for a high priority popu...

## Key facts

- **NIH application ID:** 10885925
- **Project number:** 5F31DK135323-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Tara Lauren Maudrie
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $32,487
- **Award type:** 5
- **Project period:** 2023-07-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10885925

## Citation

> US National Institutes of Health, RePORTER application 10885925, Urban American Indian/Alaska Native Cultural Eating Values and Behaviors: Community-based, mixed methods research to inform a holistic and culturally-informed diabetes prevention intervention program (5F31DK135323-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10885925. Licensed CC0.

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