Weak (“+”) to strong (“+++”) positive patch test reactions on the 3rd day after application of the test or, if this was not read, after the 4th day were aggregated as outcome “positive” and contrasted to non-positive (non-allergic) reactions, comprising negative, doubtful (0.69%) and irritant (0.05%) reactions. After descriptive bivariate analyses, a multifactorial analysis (Poisson regression analysis) was performed to adjust for a number of potential confounding factors. Job titles are originally documented in Selleckchem CX-6258 3-digit precision based on the slightly expanded classification

of the German Statistical Service and Labour Office, respectively (Anonymous 1992) with n = 493 categories. For the present analysis, these job titles were aggregated to 27 occupations and occupational groups, respectively, included in the model along with 14 anatomical sites, age Selleck 4SC-202 (categorised

according to the quartiles of the age in our sample), sex, period of patch test, atopic dermatitis (past or present) and the number of additional positive reactions to allergens of the “baseline series”. The adjusted prevalence ratios (PRs) (95% confidence intervals (95% CI)) were derived from the parameter estimates of the Poisson model to quantify the strength of association between single factors and the outcome. Results The overall P505-15 mw prevalence of positive reactions to the thiuram mix was 2.38% (exact 95% CI: 2.29–2.47%), with additional 0.69% doubtful and 0.05% irritant patch test reactions not considered positive 4-Aminobutyrate aminotransferase (allergic). In a first descriptive analysis, the variation of contact allergy to the thiuram mix across the occupational groups was addressed—see Table 1. Table 1 Crude prevalences of contact allergy to the thiuram mix, defined as “at least a weak positive reaction (+)” in different occupations ISCO-88a Job title/group n tested 0/00b per year % +–+++ 8231 Rubber industry workers 81 0.113 7.41 2221, 2222, 3225, (7310) Physicians and dentists 1,900 0.729 5.74 7143, (9130, 9442) Cleaners 2,336 0.167 5.57 7411 Meat and fish processors 436 0.229 5.05

3230 Nursing occupations 5,412 0.247 4.92 7121–3, 7131–5, 7320, 9312–3 Construction and ceramic workers 1,760 0.099 4.72 2230, 3231 Geriatric nurses 934 0.179 4.71 (5220, 5230), 6113, 6141, 9212 Florists, forestry workers 967 0.180 4.45 7430, 7440, (5200), 8265, 8266 Textile or leather worker or salesperson 887 0.270 3.95 5122, 7414 Cooks, food preparers 1,434 0.178 3.63 6110, 6120, 6151–3, (6200, 9211) Farmers, animal keepers 788 0.296 3.17 2224, 3221, 3223 Pharmacist, medical auxiliary personnel 1,230 0.361 3.01 5141 Hairdressers, cosmetologists 2,064 0.716 2.47 3111, 3116, 3131, 7344, 8150, 8220, 8224 Chemical industry and photo lab workers 984 0.159 2.34 – Old age pensioners, students 39,451 – 2.33 3226 Masseurs, physiotherapists 580 0.321 2.24 8110, 9311 Miners 376 0.133 2.13 8232 Plastic material workers 763 0.199 2.