Diabetes-Related Discrimination at Workplace and by Insurances
Diabetic subjects often report of problems at the workplace or when contracting insurances because of their diabetes.
By distributing a self-report questionnaire to insulin-treated Type 1 and Type 2 diabetic subjects we wanted to analyse the frequency of work- and insurance-related discrimination. Furthermore we wanted to detect socio-demographic and diabetes-related factors which are associated with increased discrimination at workplace and by insurances. We hypothesized that diabetes-related discrimination at workplace and by insurances exists and that certain factors like having severe hypoglycaemic events, being type 1 diabetic or being overweight would be associated with more problems at work or with insurances.
Insulin-Treated Diabetes Mellitus
|Study Design:||Observational Model: Cohort
Time Perspective: Cross-Sectional
|Official Title:||Discrimination of Insulin-Treated Diabetic Subjects at the Workplace and by Insurances|
|Study Start Date:||March 2004|
|Study Completion Date:||January 2008|
|Primary Completion Date:||January 2008 (Final data collection date for primary outcome measure)|
insulin-treated diabetic subjects of North-western part of Switzerland
Our self report questionnaire included 83 items to assess treatment goals, quality of life and discrimination at workplace or by insurances. 636 questionnaires were distributed and were answered and returned. Anonymity was ensured. Patients were recruited from the diabetes outpatient clinic of the University of Basel Hospital, 5 regional hospitals, specialist practices and general practitioner practices.
The aims of this study are to investigate the prevalence of discrimination at workplace and by insurances due to diabetes mellitus. Furthermore we want analyse if socio-demographic factors (age,gender,origin) show an impact on diabetes-related discrimination at workplace and by insurances. We hypothesize furthermore that certain diabetes-related factors like having severe hypoglycemias, being type 1 diabetic, having diabetic complications or being overweight/obese is associated with more problems at work and with insurances.
Data will be analysed by a multiple ordinal regression analysis. We will correct data for age, gender, employment status and diabetes type.