Entsisewata’karí:teke (You Will Be Healthy Again): Clinical Outcomes of Returning to a Traditional Haudenosaunee Diet
Bibliographic record
Abstract

 
 
 Haudenosaunee Peoples of eastern North America have a strong agricultural tradition and culture associated with maize horticulture. Traditional foodways and diet were disrupted after the people were dispossessed from traditional lands maintained prior to colonization. As a result, Haudenosaunee have been disconnected from their traditional diet and lifestyle, and chronic diseases such as diabetes and obesity are increasing. Healthy Roots was developed in Six Nations of the Grand River territory by Haudenosaunee community members. It started as a 90-day challenge, in which participants adhere to a diet of traditional foods found in Haudenosaunee territories pre-European contact. The community decided to formally evaluate the impact of the diet in a pilot pre–post intervention study of 22 participants in 2016/17. We investigated the effects of the 3-month dietary intervention on physical measurements, ectopic fat (including visceral and liver adipose tissue), serum lipids, and hemoglobin A1c among Haudenosaunee participants in Six Nations. We provided biweekly Haudenosaunee food boxes, and offered workshops, cooking classes, and individual support from a dietitian. The intervention reduced body weight, body circumferences including waist circumference, hemoglobin A1c, and MRI-detected hepatic fat fraction. There were no adverse events. Engagement in the program was high and trends favoured improved well-being. The intervention shows great potential as a mechanism for improving physical health and restoring cultural connectedness and identity. The implications for improving mental health and community cohesion are also important areas to consider in future research.
 
 
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".