Associations of second-hand smoke exposure with hand eczema and atopic dermatitis among college students in China
Bibliographic record
Abstract
Smoking has been identified as a risk factor for atopic dermatitis and hand eczema, but less is known about the association of exposure to second-hand smoke (SHS) with hand eczema. The study aimed to investigate the association of SHS exposure with hand eczema and atopic dermatitis in a group of adolescents. We conducted a cross-sectional study among first-year college students. SHS exposure was measured by a self-administered questionnaire. Skin diseases were diagnosed by dermatologists in the field survey. Mixed models were used to estimate the associations. A total of 20,129 participants that underwent skin examination and a questionnaire survey were included in the analyses. The prevalence rates of atopic dermatitis and hand eczema were 3.86% and 3.35%, respectively. Crude and adjusted estimates consistently showed that exposure to SHS was significantly associated with atopic dermatitis and hand eczema in a dose-response manner. Attention deficit/hyperactivity disorder mediated minimal or no effect of SHS on hand eczema and atopic dermatitis. Subgroup analysis by type of hand eczema, and sensitivity analysis by excluding data with center effect showed consistent results. Exposure to SHS is an independent but modifiable risk factor for hand eczema and atopic dermatitis in adolescents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".