Gestational glucose intolerance modifies the association between magnesium and glycemic variables in mothers and daughters 15 years post-partum
Bibliographic record
Abstract
BACKGROUND: Gestational diabetes mellitus (GDM) and low magnesium (Mg) intake and status are associated with an increased risk of type 2 diabetes. However, Mg homeostasis may be modified by GDM. We sought to determine if a history of GDM prospectively modifies associations between Mg and glycemic variables in mothers and their offspring. METHODS: Plasma and dietary Mg, anthropometric, lifestyle and glycemic variables were assessed in mothers affected by GDM during 1989-1990, a comparative group of normoglycemic women, pregnant during the same time period, and the 15-year-old, nondiabetic daughters of affected and unaffected pregnancies (n = 332). Multivariate regression analyses evaluated the cross-sectional association between plasma and dietary Mg with glycemic variables in mothers and daughters. RESULTS: Plasma Mg was lower in mothers with a history of GDM in comparison to control mothers after adjustment for current type 2 diabetes, race and body mass index (0.90 ± 0.01 versus 0.96 ± 0.01 mmol/L; p = 0.002). Plasma Mg was significantly associated with insulin sensitivity and was inversely associated with fasting insulin in GDM mothers only (p<0.05). Plasma and dietary Mg were significantly inversely associated with glycated hemoglobin and fasting glucose, respectively, in nondiabetic teenage daughters. For fasting glucose, plasma Mg was inversely associated in GDM-born daughters only. CONCLUSIONS: Associations between plasma Mg and some glycemic variables may be stronger in mothers and offspring with a history of GDM.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".