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The Canadian Health Measures Survey (CHMS) is conducted by Statistics Canada in part­nership with the Public Health Agency of Canada and Health Canada. The survey was designed to produce nationally repre­sentative estimates.^Note15 It excludes people living on reserves and other Aboriginal settlements in the provinces, full-time members of the Canadian Forces, the institutionalized population, and resi­dents of some remote regions, all of whom together make up less than 4% of the target population.^Note16 Ethics approval for the CHMS was obtained from Health Canada’s Research Ethics Board.^Note17

Data collection was completed in two steps: an interview at the respondent’s home and a visit by the respondent to the CHMS mobile examination centre where physical measures and blood and urine samples were taken.

Cycle 1 took place from March 2007 through February 2009, and collected information from respondents aged 6 to 79 living in private households in 15 locations across Canada. Cycle 2 took place from August 2009 through November 2011, and col­lected data from respondents aged 3 to 79 living in private households in 18 locations.

Of households selected for cycles 1 and 2, 72.7% agreed to participate, and 89.3% of selected household members completed the household questionnaire. A total of 11,387 respon­dents completed the mobile examination centre compo­nent. After adjustments for the sampling strategy, the final response rate for 6- to 79-year-olds for the two cycles combined was 53.5%.^Note16

The sample for the present study consists of 11,386 respondents aged 6 to 79 from both cycles who provided viable information about their use of prescription drugs. One record was dropped because all prescription medication-related fields were missing.

To account for survey design effects, coefficients of variation and 95% confidence inter­vals were estimated with the bootstrap technique.^Note18 Differences between ­prevalence estimates were calculated with t-tests. All analyses were conducted in SUDAAN v.10 (RTI International, Research Triangle Institute, NC, USA), using weighted data and DDF = 24 in the procedure statements to account for the degrees of freedom of the combined datasets. Details about the CHMS, including sampling, design, quality assurance and combining cycles, are available elsewhere.^Note15-17

Drug identification numbers (DINs) were collected from medication containers during the household interview and verified during the mobile examination centre visit. Current medication use was defined as any medication taken by the respondent on either the day of the household interview or the previous day; up to 15 medications were recorded for each respondent.

Each DIN has a World Health Organization (WHO) Anatomical Therapeutic Chemical (ATC) classification code assigned by Health Canada.^Note19 The ATC structure divides active substances into groups according to the organ or system on which they act and their therapeutic, pharmacological and chemical properties. There are five levels of classification. The first level is the main group. The second defines pharmacological/therapeutic subgroups; the third and fourth define chemical/pharmacological/therapeutic subgroups. The fifth level represents the chemical substance.

For this analysis, the leading prescription medication classes are defined using level-3 ATC codes, which represent major therapeutic or pharmacological subgroups (Appendix). Respondents who reported taking more than one drug in a level-3 ATC subgroup were represented only once in that group. DINs provided by 147 respondents, which could not be coded, were retained in the analysis as part of a “missing” category.

Based on the literature and availability in the CHMS, prescription medication use was examined by selected socio-demographic and health status indicators. Five age groups were specified: 6 to 14, 15 to 24, 25 to 44, 45 to 64, and 65 to 79. The prevalence of eight health conditions (diagnosed by a health professional) was determined—hypertension (including individuals who reported taking high blood pressure medication), asthma, diabetes, heart disease (including health attack), arthritis, cancer, chronic obstructive pulmonary disorder (COPD) (including emphysema, chronic bronchitis, chronic pulmonary disease), and mood disorders such as depression or bipolar disorder. The number of conditions reported by each respondent was categorized as 0, 1, 2, 3, or 4 or more. Four disability levels (no, mild, moderate or severe) were assigned based on respondents’ Health Utility Index scores. Respondents were categorized as usually free of pain and discomfort or not, and by health status ( excellent/very good, good or fair/poor.

Logistical and budgetary constraints limited the number of CHMS collection sites and sample size.^Note16 Consequently, this analysis sometimes uses more general covariate categories than would have been desirable.  As well, not all relevant covariates were available—for example, insurance coverage and prescription medication dose and duration. Small sample sizes may also have reduced the ability to identify statistical significance.

Because the CHMS was designed to produce national estimates,^Note16 it was not possible to examine prescription medication use by province.

The survey captured a maximum of 15 prescription medications; consequently, use may be underestimated. Also, the use of medications or equivalents that are available both as prescriptions and over-the-counter may be underestimated. As well, the CHMS excludes people aged 80 or older and residents of institutions, estimates of prescription medication use are lower than they would have been if these populations had been included.

Although survey weights ensured that the sample is representative of the target population, bias may exist if the medication use of respondents and non-respondents differed systematically.

Self-reported data are susceptible to social desirability and recall biases. However, this study may overcome problems associated with administrative or billings-based data. Because patients do not always take dispensed medication,^Note20 data on prescription medication use rather than acquisition, which is what is normally captured by dispensary and retail sales data, may be more accurate.  Also, population-based survey data are more generalizable than administrative or billings-based data, which pertain only to people with insurance or public drug program coverage.