Determinants of Glycated Hemoglobin in Subjects With Impaired Glucose Tolerance: Subanalysis of the Japan Diabetes Prevention Program
Bibliographic record
Abstract
BACKGROUND: Limited evidence is available about the relationship of lifestyle factors with glycated hemoglobin (HbA1c) in subjects with impaired glucose tolerance. The aim of study was to identify such determinant factors of HbA1c in subjects with impaired glucose tolerance. METHODS: This cross-sectional study included 121 men and 124 women with impaired glucose tolerance, who were diagnosed based on a 75-g oral glucose tolerance test. Demographic and biochemical parameters, including the body mass index (BMI), fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and HbA1c, were measured. The pancreatic β-cell function and insulin resistance were assessed using homeostasis model assessment (HOMA-β). Dietary intake was assessed by a food frequency questionnaire. RESULTS: The levels of FPG, 2-h PG, and carbohydrate intake were correlated with the HbA1c level in men, while the FPG and 2-h PG levels were correlated with the HbA1c level in women. In multiple regression analyses, BMI, FPG, 2-h PG, and white rice intake were associated with HbA1c levels in men, while BMI, FPG, HOMA-β, and bread intake were associated with HbA1c levels in women. CONCLUSIONS: The present findings suggest that a substantial portion of HbA1c may be composed of not only glycemic but also several lifestyle factors in men with impaired glucose tolerance. These factors can be taken into consideration as modifiable determinants in assessing the HbA1c level for the diagnosis and therapeutic monitoring of the disease course.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".