Epidemiology of atopic dermatitis in adults: Results from an international survey
Bibliographic record
Abstract
BACKGROUND: There are gaps in our knowledge of the prevalence of adult atopic dermatitis (AD). OBJECTIVE: To estimate the prevalence of AD in adults and by disease severity. METHODS: This international, cross-sectional, web-based survey was performed in the United States, Canada, France, Germany, Italy, Spain, United Kingdom, and Japan. Adult members of online respondent panels were sent a questionnaire for AD identification and severity assessment; demographic quotas ensured population representativeness for each country. A diagnosis of AD required subjects to be positive on the modified UK Working Party/ISAAC criteria and self-report of ever having an AD diagnosis by a physician. The proportion of subjects with AD who reported being treated for their condition was determined and also used to estimate prevalence. Severity scales were Patient-Oriented SCORAD, Patient-Orientated Eczema Measure, and Patient Global Assessment. RESULTS: Among participants by region, the point prevalence of adult AD in the overall/treated populations was 4.9%/3.9% in the US, 3.5%/2.6% in Canada, 4.4%/3.5% in the EU, and 2.1%/1.5% in Japan. The prevalence was generally lower for males vs females, and decreased with age. Regional variability was observed within countries. Severity varied by scale and region; however, regardless of the scale or region, proportion of subjects reporting severe disease was lower than mild or moderate disease. CONCLUSIONS: Prevalence of adult AD ranged from 2.1% to 4.9% across countries. Severe AD represented a small proportion of the overall AD population regardless of measure or region.
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 | 0.002 |
| 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".