Childhood obesity as a predictor of type 2 diabetes mellitus in adults: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Despite government-developed prevention programs, type 2 diabetes mellitus (DM) has continued to increase, suggesting that the programs are ineffective. Other potential risk factors, such as childhood obesity, may influence adult-onset diabetes. Objective To assess for a potential association between childhood obesity and adult type 2 DM by meta-analysis of the literature. Methods This review was conducted according to the PRISMA Statements’ Flow Diagram and Checklist to improve quality of reporting. Cohort studies were chosen for their long-term follow-up. Newcastle-Ottawa Scale for Cohorts (NOS-Cohort) was used to assess for bias and quality of the included studies, in addition to the Cochrane Handbook. Analysis was done with forest and funnel plots using RevMan 5.3 software for Macintosh. Results A total of 237 records with 73,533 participants were retrieved, of which 10 studies were included in our systematic review and 5 studies were included in the meta-analysis. The most common bias based on NOS-Cohort was inadequate follow-up. Forest plot revealed a significant association between childhood obesity and adult diabetes (OR 3.89; 95%CI 2.97-5.09; I2 0%; P<0.00001). Individuals with childhood obesity were 3.89 times more likely to have adult-onset diabetes. Funnel plot assessment was symmetrical. Studies suggested that childhood obesity led to early insulin resistance and adiposity rebound, which promotes adulthood obesity, a diabetic risk factor. Conclusion Childhood obesity can be used as a predictor for adult-onset diabetes. Early diabetes screening and prevention guidelines should include childhood obesity as a plausible risk factor.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".