An Intensive Lifestyle Intervention to Treat Type 2 Diabetes in the Republic of the Marshall Islands: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: The Republic of the Marshall Islands has the highest prevalence of type 2 diabetes (T2D) in the world, with the country’s rapid rise of T2D attributed to its reliance on imported and refined foods laden with salt, sugar, and fat. As much as lifestyle factors can increase the risk of T2D, they can also reverse or treat the disease, with multiple studies demonstrating that plant-based diets and/or moderate exercise improve glycemic control and cardiovascular risk factors in T2D patients. Objective: We therefore tested the hypothesis that a community-based, intensive, plant-rich lifestyle intervention with exercise is more effective for treating and managing T2D in the Republic of the Marshall Islands than the standard of diabetes care. Methods: Building on a successful lifestyle program used at the Guam Seventh-day Adventist Clinic, we conducted a randomized controlled trial to test the effectiveness of an intensive lifestyle intervention involving a plant-rich diet and moderate exercise or the standard of care in T2D patients for 24 weeks. In this manuscript, we describe the clinical trial protocol, including the rationale, design, and methods of the clinical trial and the lifestyle program. The lifestyle intervention included a step-wise, intensive 12-week program of counseling and instruction on healthy eating, exercise, and stress management. The prescribed diet focused on high-fiber, whole plant foods, with foods grouped into a four-tiered system. The lifestyle intervention also involved hands-on cooking classes, meals prepared for participants, and group exercise classes—all tailored to be culturally appropriate. The study’s main endpoints were glycemic control and cardiovascular disease risk factors. Discussion: The present study is the first randomized clinical trial conducted in the Republic of the Marshall Islands and the first lifestyle intervention trial conducted in Micronesia. The results of this study will help guide future medical care for indigenous populations in the Pacific Islands and will also shed light on how to effectively design and deliver intensive lifestyle interventions to treat and manage diabetes.
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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 | 0.030 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.076 | 0.012 |
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".