Prevalence and Incidence of Atopic Dermatitis: A Systematic Review
Bibliographic record
Abstract
The primary objective of this study was to systematically review and analyse epidemiological studies of the prevalence and incidence of atopic dermatitis (AD) during childhood and adulthood, focusing on data from the 21st century. A systematic search of PubMed, EMBASE and Google (manual search) was performed in June 2019, followed by data abstraction and study quality assessment (Newcastle-Ottawa Scale). Cross-sectional and longitudinal epidemiological studies of individuals with AD (doctor-diagnosed or standardized definition) were included. Of 7,207 references reviewed, 378 moderate/good-quality studies were included: 352 on prevalence of AD and 26 on incidence of AD. In the 21st century, the 1-year prevalence of doctor-diagnosed AD ranged from 1.2% in Asia to 17.1% in Europe in adults, and 0.96% to 22.6% in children in Asia. The 1-year incidence ranged from 10.2 (95% confidence interval (95% CI) 9.9-10.6) in Italy to 95.6 (95% CI 93.4-97.9) per 1,000 person-years in children in Scotland. There were few recent studies on incidence of AD in the 21st century and no studies on adults only; most studies were conducted in Europe and the USA. Epidemiological studies on childhood and adulthood AD in different continents are still needed, especially on the incidence of AD during adulthood.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".