Prevalence of chronic hand eczema in adults: a cross-sectional survey of over 60 000 respondents from the general population of Canada, France, Germany, Italy, Spain and the UK
Bibliographic record
Abstract
BACKGROUND: The lack of attention paid to chronic hand eczema (CHE) and the lack of a specific International Classification of Diseases code for it may have limited assessment of its prevalence. To date, prevalence estimates have primarily been derived from (partly small) single-country studies. OBJECTIVES: To estimate the annual prevalence of self-reported physician-diagnosed CHE across sociodemographic characteristics in adults living in Canada, France, Germany, Italy, Spain and the UK. METHODS: In the observational Chronic Hand Eczema epidemiology, Care, and Knowledge of real-life burden (CHECK) study, a questionnaire was administered to adults aged 18-69 years in the general population, recruited through online panels. Quotas and minor weighting adjustments were performed to ensure that the participants were representative of the general population with regard to sex, age, region, employment status, urban/rural setting and - in the UK only - ethnicity. Additional weights were applied to account for population size differences when aggregating country results. Information on self-reported physician-diagnosed CHE was collected. CHE was defined, in accordance with the European Society of Contact Dermatitis, as having had hand eczema continuously for ≥ 3 months or at least two flares in the past 12 months. The annual prevalence of CHE was determined for each country, and by subgroups of sex, age, employment and urban/rural setting. RESULTS: Of 60 131 participants, 2847 self-reported physician-diagnosed CHE, yielding an annual prevalence of 4.7% [95% confidence interval (CI) 4.6-4.9]. Subgroup analyses revealed that the prevalence of CHE was significantly higher in women than in men [5.6% (95% CI 5.4-5.9) vs. 3.8% (95% CI 3.6-4.1); P < 0.001], in employed vs. unemployed people [5.3% (95% CI 5.1-5.6) vs. 3.3% (95% CI 3.1-3.6); P < 0.001] and in urban vs. rural residents [5.0% (95% CI 4.8-5.2) vs. 3.7% (95% CI 3.4-4.1); P < 0.001). Prevalence was highest in those aged 30-39 years (6.5%, 95% CI 6.0-7.0) and lowest in those aged 60-69 years (2.6%, 95% CI 2.3-3.0). CONCLUSIONS: This large multinational study is the first to assess the prevalence of CHE in Europe and Canada using a consistent definition across a broad geographical population. This study reveals that CHE is a common skin disease with annual prevalence of 4.7%, with a higher prevalence in women, people aged 30-39, employed people and those living in urban areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".