An algorithm to differentiate diabetic respondents in the Canadian Community Health Survey
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by Edward Ng, Kaberi Dasgupta and Jeffrey A. Johnson
Abstract
Objectives
This article describes an algorithm to classify respondents to cycle 1.1 (2000/2001) of the Canadian Community Health Survey (CCHS) according to whether they have type 1, type 2 or gestational diabetes.
Data source
The data are from the chronic disease module and the drug module of cycle 1.1 of the CCHS.
Analytical techniques
A total of 6,361 respondents to cycle 1.1 of the CCHS reported that a health care professional had diagnosed them as having diabetes. The Ng-Dasgupta-Johnson algorithm classifies this group according to whether they have type 1, type 2 or gestational diabetes, based on their answers to CCHS questions about diabetes during pregnancy, use of oral medications to control diabetes, use of insulin, timing of initiation of insulin treatment, and age at diagnosis.
Main results
Application of an earlier algorithm to CCHS cycle 1.1 results in a 10%-90% split for type 1 and type 2 diabetes. By contrast, the Ng-Dasgupta-Johnson algorithm yields a 5%-95% split. This is not unreasonable, given the rapid rise in obesity, a major risk factor for type 2 diabetes, in Canada.
Keywords
Chronic disease, classification, data collection, health surveys, insulin
Findings
Diabetes is a serious chronic condition characterized by high levels of glucose, the body's primary fuel. Normally, glucose is transferred from the circulation system into tissue cells through the action of insulin, a hormone produced by the pancreas. In patients with type 1 diabetes, high glucose levels result from a lack of insulin production. For patients with type 2 or gestational diabetes, glucose levels rise because of resistance to the action of insulin. Although gestational diabetes may resolve post-partum, women with this condition are at increased risk of developing type 2. [Full text]
References
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Authors
Edward Ng (613-951-5308; Edward.Ng@statcan.gc.ca) is with the Health Information and Research Division at Statistics Canada in Ottawa, Ontario K1A 0T6; Kaberi Dasgupta is with the Division of Internal Medicine and Epidemiology at McGill University in Montreal, Quebec; and Jeffrey A. Johnson is with the School of Public Health at the University of Alberta in Calgary, Alberta.
Acknowledgements
Kaberi Dasgupta holds a CIHR New Investigator Award. Jeffrey A. Johnson is a Health Scholar with the Alberta Heritage Foundation for Medical Research and holds a Canada Research Chair in Diabetes Health Outcomes.
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