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P284 Gender, occupation, and prescription of medicine for asthma
  1. Jesper Baelum1,2,
  2. David Sherson1,3,
  3. Trine Thilsing2,
  4. Lars Skadhauge4,
  5. Jesper Rasmussen4,
  6. Oyvind Omland5,
  7. Jesper Davidsen3,
  8. Torben Sigsgaard6,
  9. Vivi Schlünssen6
  1. 1Department of Occupational and Environmental Medicine, Odense Universitty Hospital, DK-5000 Odense C, Denmark
  2. 2Research Unit of General Practice, Department of Public Health, University of Southern Denmark, DK-5000 Odense C, Denmark
  3. 3Department of Respiratory Medicine, Odense University Hospital, DK-5000 Odense C, Denmark
  4. 4Department of Occupational Medicine, Hospital of South West Jutland, DK-6700 Esbjerg, Denmark
  5. 5Department of Occupational and Environmental Medicine, Aalborg Hospital, DK-9100 Aalborg, Denmark
  6. 6Section of Environmental and Occupational Medicine, Institute of Public Health, University of Aarhus, DK-8200 Aarhus, Denmark

Abstract

Background A way of tracing the onset of asthma and relation to occupational exposures is monitoring prescription of relevant medication.

Material and methods In our Danish population study of Asthma in Young Adults 7,253 persons had valid responses to the screening questionnaire in 2003–4.

Information of actual or recent job was coded into ISCO-88. To this was applied the ECRHS asthma 26 job categories with clerks etc. as reference group and the Job Exposure Matrix (JEM) summed in high molecular weight (HMW), low molecular weight (LMW), and irritative (IRR) exposures.

From the Danish National Register of Prescriptions all prescriptions were retrieved from 2000 through 2013. The number and “Defined Daily Doses” (DDD) were calculated for each person and year.

Asthma medicine was defined as the sum of inhaled β2-agonists, corticoids, and leucotriene inhibitors. Summary of DDDs in four periods (001–03, 2004–07, 2008–10, and 2011–13) were used and in these periods significant asthma medication (AST-MED) was defined as more than in average 100 DDDs per year.

Differences in outcomes between the groups were analysed by negative binomial regression/logistic regression including smoking and age at baseline. Analyses were made separately for males and females.

Results In all periods exposure to HMW was negatively related to DDDs in females, while IRR was negatively related to DDDs and AST-MED in males but not in females.

Females in food industry and drivers had elevated AST-MED, while nurses had lower AST-MED.

In contrast male cleaners, bakery workers, and agricultural workers had elevated AST-MED and DDDs.

AST-MED correlated to some degree with self-reported

Conclusions A significant gender difference in exposure related medication may be due to differences in the content of work or in personal factors.

Register based information of medication seems to be a reasonable indicator of development of asthma in young adults.

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