Association of large for gestational age with cardiovascular metabolic risks: a systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to clarify the relationships among large for gestational age (LGA) and cardiometabolic risk factors. METHODS: PubMed, Web of Science, and the Cochrane Library databases were searched to identify studies on LGA and outcomes of interest, including BMI, blood pressure, glucose metabolism, and lipid profiles. Data were independently extracted by two reviewers. A meta-analysis was performed using a random-effects model. The Newcastle-Ottawa Scale and funnel graph were used to assess the quality and publication bias, respectively. RESULTS: Overall, 42 studies involving 841,325 individuals were included. Compared with individuals born appropriate for gestational age, individuals born LGA had higher odds of overweight and obesity (odds ratios [OR] = 1.44, 95% CI: 1.31-1.59), type 1 diabetes (OR = 1.28, 95% CI: 1.15-1.43), hypertension (OR = 1.23, 95% CI: 1.01-1.51), and metabolic syndrome (OR = 1.43, 95%; CI: 1.05-1.96). No significant difference was found in hypertriglyceridemia and hypercholesterolemia. Stratified analyses showed that, compared with individuals born appropriate for gestational age, individuals born LGA had higher odds for overweight and obesity from toddler age to puberty age (toddler age: OR = 2.12, 95% CI: 1.22-3.70; preschool: OR = 1.81, 95% CI: 1.55-2.12; school age: OR = 1.53, 95% CI: 1.09-2.14; puberty: OR = 1.40, 95% CI: 1.11-1.77). CONCLUSIONS: LGA is associated with increased odds of obesity and metabolic syndrome later in life. Future studies should focus on elucidating the potential mechanisms and identifying risk factors.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.028 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".