This study was conducted using population based data from the province of Ontario, Canada—with a 2011 population of more than 13 million [14]. The Institute for Clinical Evaluative Sciences (ICES) houses the health administrative data on hospital and physician billings, provided by the provincial health ministry, as well as population survey data. These data have been individually linked using an anonymized identification number.
Population
The sample population included all adults, aged 20 years and older, with a valid Ontario health card who completed the CCHS in 2001, 2003 or 2005, and agreed to have their survey responses linked to their provincial health administrative data. Residents are eligible for the provincial health coverage if they are Canadian citizens, landed immigrants or convention refugees, make their permanent and principal home in Ontario, and are physically present in Ontario 153 days in any 12-month period. A detailed flow chart of this method is included in Additional file 1: Appendix A.
The CCHS survey uses a multi-stage, stratified, clustered design. The survey uses a probability sample and a weighting system that represents approximately 98% of the community dwelling Canadian population aged 12 years and over. Individuals living on Indian Reserves, institutional residents, full-time members of the Canadian Armed Forces, and residents of certain remote regions are excluded from the CCHS. Further details about the methods for the CCHS are reported elsewhere [15].
Chronic disease ascertainment
Health administrative data
We relied on pre-existing validated case definitions, created using Ontario hospital and physician billing codes, for the following seven chronic diseases: diabetes, congestive heart failure, myocardial infarction, stroke, hypertension, asthma, chronic obstructive lung disease (COPD) [7, 8, 16–19]. The technical case definitions we used are presented in Additional file 1: Appendix B.
Canadian community health survey
The CCHS provides cross sectional estimates of health status, health determinants and health system use for Canadians. The survey asks respondents to identify if they have any one of a list of chronic health conditions which are defined as “long-term conditions that have lasted or are expected to last six months or more and that have been diagnosed by a health professional”. The relevant questions from the survey are included in Additional file 1: Appendix C.
Chronic disease prevalence
We calculated chronic disease prevalence in the sample population using both self-reported data and administrative definitions. For self-reported prevalence, all three cycles of the CCHS were used to identify the total number of prevalent cases. For health administrative data disease prevalence, case ascertainment was restricted to the time of the administration of the CCHS survey or earlier. Raw counts were presented for each disease in 2 × 2 tables.
Health utilities index
The self-reported health burden was measured using the Health Utilities Index (HUI) [20]. The HUI is a preference-based, multi-attribute health classification system that estimates a summary value of individual health where 0 = “dead” and 1 = “perfect health”. Each respondent answers questions pertaining to eight attributes of functional health: vision, hearing, speech, mobility, dexterity, emotional state, cognition and level of pain and discomfort and these attributes are assigned individual utility weights and then combined to create a summary value. HUI values were only available for CCHS cycle 1.1 respondents. The HUI values were standardized for age and sex against the 1991 Canadian population.
Analysis
Using the sample survey weights developed by Statistics Canada, weighted prevalence estimates were calculated to determine the total burden of each disease in Ontario in the study time period. Population prevalence was calculated by dividing the total weighted number of cases (separately done for self reported and health administrative definitions) by the total weighted population of the cohort.
The measures of concordance presented included: sensitivity (of self-report), specificity (of self-report), proportion of positive and negative agreement and Cohen’s kappa coefficient. Details on the calculation of these measures are included in Additional file 1: Appendix D. The kappa coefficient, a widely used as a measure of agreement between raters, indicates the proportion of agreement beyond that expected by chance. Levels of agreement for kappa were considered to be poor (κ < 0.20), fair (κ = 0.20 to 0.39), moderate (κ = 0.40 to 0.59), good (κ = 0.60 to 0.79), or very good (κ = 0.80 to 1.00) [4, 21].
We calculated the median and interquartile range (25th percentile- 75th percentile) for the Health Utility Index (HUI) only for participants in cycle 1.1 of CCHS.
All calculations were performed using SAS 9.2.