Bibliographic record
Abstract
High-quality diets play an important role in diabetes prevention. Appropriate dietary adherence can improve insulin sensitivity and glycemic control, and thus contribute to lifestyle improvement. However, previous research suggests that dietary adherence is arguably among the most difficult cornerstones of diabetes management. The objectives of this study are (1) to estimate whether and to what extent individuals diagnosed with diabetes show significant differences in diet quality [healthy eating index (HEI)] compared to healthy individuals, (2) to quantify whether and to what extent diabetics experience significantly higher outcomes of body mass index (BMI), and (3) to estimate whether and to what extent dietary supplementation impacts diabetes patient's diet quality and/or BMI outcomes. We use data from the 2007-2008 U.S. National Health and Nutrition Examination Survey (NHANES). The NHANES is the primary, randomized, and nationally representative survey used to assess the health and nutritional status in the U.S. We apply propensity score matching (PSM) to account for selection bias and endogeneity between self-reported diet and health behavir (treatment) and BMI outcomes. We control for an individual's BMI as to capture the impact of past dietary behavior in its impact on HEI. Matching results suggest that regular dietary supplement consumption is associated with significant lower BMI outcomes of almost 1 kg/m(2). The close relationship between diabetes and obesity has been at the center of the diet-health policy debate across Canada and the U.S. Knowledge about this linkage may help to improve the understanding of the factors that impact dietary choices and their overall health outcomes, which may lead to a more efficient and effective promotion of dietary guidelines, healthy food choices, and targeted consumer health and lifestyle policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".