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Health Rep. 2008 Mar;19(1):71-9.

An algorithm to differentiate diabetic respondents in the Canadian Community Health Survey.

Author information

1
Health Information and Research Division at Statistics Canada in Ottawa, Ontario K1A 0T6. Edward.Ng@statcan.ca

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.

PMID:
18457213
[Indexed for MEDLINE]
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