Is atopic dermatitis associated with obesity? A systematic review of observational studies
Bibliographic record
Abstract
Obesity has been associated with atopic dermatitis (AD); however, the results have been conflicting. Our aim was to provide an update on current knowledge from observational studies addressing the possible association between obesity and AD. Systematic literature review was performed by identifying studies addressing a possible link between AD and overweight/obesity from PubMed, EMBASE and the Cochrane Library in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. A total of 45 studies (comprising more than 90 000 individuals with AD) fulfilled the criteria and were included in the present review. The available studies revealed inconsistencies, but the majority indicated that obesity is associated with AD. Studies addressing obesity in infancy or early childhood (age < 2 years) and AD reported a positive association. From childhood into adulthood, there is a discrepancy in the observations, as the more recent prospective studies found a positive association, whereas this was not observed in older cross-sectional studies. The inconsistency might be explained by the difference in study design, the diagnostic criteria of AD, regional differences, and by the varied definitions of overweight and obesity used in the studies. In Conclusion, overweight/obesity is associated with an increased risk of AD. Large prospective cohort studies are required to confirm the association between AD and obesity and the possibility that weight control in childhood may help to mitigate or reverse AD symptoms.
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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 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".