Lifestyle factors and hand eczema: A systematic review and meta‐analysis of observational studies
Bibliographic record
Abstract
Evidence regarding the association between lifestyle factors and hand eczema is limited.To extensively investigate the association between lifestyle factors (smoking, alcohol consumption, stress, physical activity, body mass index, diet, and sleep) and the prevalence, incidence, subtype, severity, and prognosis of hand eczema, a systematic review and meta-analysis were conducted in accordance with the Meta-analysis Of Observational Studies in Epidemiology consensus statement. MEDLINE, Embase, and Web of Science were searched up to October 2021. The (modified) Newcastle-Ottawa Scale was used to judge risk of bias. Quality of the evidence was rated using the Grades of Recommendation, Assessment, Development and Evaluation approach. Eligibility and quality were blindly assessed by two independent investigators; disagreements were resolved by a third investigator. Data were pooled using a random-effects model, and when insufficient for a meta-analysis, evidence was narratively summarized. Fifty-five studies were included. The meta-analysis (17 studies) found very low quality evidence that smoking is associated with a higher prevalence of hand eczema (odds ratio 1.18, 95% confidence interval 1.09-1.26). No convincing evidence of associations for the other lifestyle factors with hand eczema were found, mostly due to heterogeneity, conflicting results, and/or the limited number of studies per outcome.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.007 | 0.009 |
| 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".