Accumulation of adverse childhood events and overweight in children: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: This study systematically summarizes the evidence of all observational studies investigating the relation between accumulation of adverse life events and measures of overweight in children <18 years. METHODS: MEDLINE, Embase, PsycINFO, and CINAHL were systematically searched (last search date 18 February 2015). The Newcastle-Ottawa Scale was used for methodological quality assessment. Study estimates were pooled using a random-effects model, and sources of heterogeneity were explored (PROSPERO registration number CRD42014014927). RESULTS: Eighteen articles were included, containing five longitudinal (n = 6,361) and fourteen cross-sectional and case-control study results (n = 52,318). The pooled estimate of the longitudinal studies showed that accumulation of adverse life events is positively related to childhood overweight measures (OR [95% CI] = 1.12 [1.01-1.25]). Cross-sectional and case-control study results were heterogeneous. Subgroup analyses showed that cross-sectional and case-control studies using a continuous adverse events measure, studies using a continuous overweight measure, and studies in children >6-12 years also generated positive pooled estimates, while the pooled estimate of studies assessing recent adverse events (past 2 years) was indicative of no relation with overweight. CONCLUSIONS: Accumulation of adverse life events and childhood overweight measures are positively associated. However, increases in overweight measures in response to adverse childhood events do not seem to occur instantaneously.
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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 | 0.020 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".