Dietary Total Antioxidant Capacity and Gestational Diabetes Mellitus: A Case-Control Study
Bibliographic record
Abstract
Background . Elevated oxidative stress status has been reported among pregnant women with gestational diabetes mellitus (GDM). In diabetic condition, glucose and lipid peroxidation, and alteration in antioxidant defense lead to increased free radicals. The objective of this study was to investigate the association between dietary total antioxidant capacity (DTAC) and GDM. Methods . This hospital-based case-control study was conducted in 463 pregnant women (healthy,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>263</mml:mn></mml:math>; GDM,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>200</mml:mn></mml:math>). Anthropometric indices, blood pressure, and biochemical analyses were measured. Dietary intake was assessed by the average of three 24-hour dietary intake records. DTAC was calculated by three indices: ferric reducing ability of plasma (FRAP), total radical-trapping antioxidant parameter (TRAP), and Trolox equivalent antioxidant capacity (TEAC). Multivariable logistic regression was performed to examine the relationship between DTAC and GDM risk in crude and adjusted models. Results . The mean age and BMI were<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mn>28.33</mml:mn><mml:mo>±</mml:mo><mml:mn>6.23</mml:mn></mml:math>years and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mn>29.67</mml:mn><mml:mo>±</mml:mo><mml:mn>4.73</mml:mn></mml:math> kg/m 2 , respectively. Total energy, protein, and selenium intakes were significantly higher in cases than controls (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.05</mml:mn></mml:math>). Moreover, intakes of carbohydrate, vitamins C, B6, and A, manganese, fruits, fruit juices, vegetables, legumes, and FRAP were significantly lower in cases than controls (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.05</mml:mn></mml:math>). The risk of gestational diabetes mellitus was 85% lower among those in the highest tertile of FRAP (OR: 0.15; 95% CI: 0.08-0.29). There was no significant association between the risk of GDM and TRAP (OR: 1.62; 95% CI: 0.94-2.79) as well as TEAC (OR: 1.56; 95% CI: 0.89-2.72). Conclusion . Pregnant women who were in the highest tertile of FRAP were at lower risk of GDM. However, larger prospective studies are needed to confirm our findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".