A strategy for health surveillance in laboratory animal workers exposed to high molecular weight allergens

Abstract

Aims: To develop a health surveillance strategy with the use of diagnostic and prognostic prediction models to detect and predict occupational allergic diseases efficiently.

Methods: Data from laboratory animal workers (n = 351) participating in an ongoing cohort study were used to develop diagnostic and prognostic models with logistic regression analyses. A diagnostic model was developed from questionnaire items, and exposure measurements to find predictors for the estimation of the probability of sensitisation to workplace allergens. With the resulting questionnaire model workers were divided into subgroups (high/low probability). A prognostic model was established in workers initially low sensitised using follow up data over a 2-3 year period. The accuracy of the models was evaluated by the concordance (c) statistic, and by comparison of the predicted and observed prevalence.

Results: A diagnostic rule, containing five questionnaire items, identified workers with a high risk of sensitisation. These workers showed high rates of work related asthma, allergic symptoms, doctor's visit, and absenteeism. A prognostic rule based on four questionnaire items predicted workers at high risk of near future sensitisation with high rates of future (allergic) respiratory symptoms, and asthmatic attacks.

Conclusion: The risk of (future) sensitisation and the severity of laboratory animal allergy can be predicted accurately with diagnostic and prognostic prediction models based on questionnaire items. Workers with an increased risk of future sensitisation also showed serious allergic symptoms at follow up. Workers with a low risk have a low risk of becoming diseased in the future.