Health Inequities in Manitoba: Is the Socioeconomic Gap

Health Inequities in Manitoba: Is the Socioeconomic Gap in Health Widening or Narrowing Over Time?
• vital statistics (records of births, deaths, and causes of death)
• pharmaceutical claims (pharmaceutical use from the Drug Program Information Network
(DPIN))
• the 1986, 1991, 1996, 2001, and 2006 census files (for socioeconomic information at the
dissemination area level)
• education enrolment and achievement data
• public access census files
Depending upon the source of data, rates and prevalence are generated for either fiscal years or
calendar years. For example, “2006/07” represents the fiscal year April 1, 2006 to March 31, 2007,
whereas 2006 represents calendar year January 1, 2006 to December 31, 2006. Most healthcare use
data are reported in fiscal years, whereas most mortality data (such as premature mortality rates) are
reported in calendar years. Some indicators are analysed by one–year time periods. However, many of
the indicators are analysed by a group of years (three to 12 years, depending on the indicator), but the
rate has been annualized to report an “average” annual rate over the time period chosen.
For purposes of this particular study, MCHP obtained ethical approval, from the University of Manitoba’s
Faculty of Medicine Human Research Ethics Board and from the Health Information Privacy Committee
of the Manitoba government, to access the Population Health Research Data Repository. As well,
trustees of various non–health data gave permission for use of these data for the report—Ministry of
Education, Citizenship & Youth and the Ministry of Family Services & Consumer Affairs.
How rates were generated
To compare and estimate rates of events in this report, the count of events for each indicator was
“modelled” using a statistical technique called a generalized linear model (GLM), suitable for non–
normally distributed data such as counts. Various distributions were used for different indicators
depending upon which fit the data best, including Poisson distribution (very rare events) and negative
binomial distribution (relatively rare but highly variable). In the models that created the time graphs,
covariates of age and sex (male/female) were included in the model to “adjust” for differences in
underlying neighbourhood income quintile age/sex distributions.
In order to obtain neighbourhood income quintile rates for the various graphs, relative risks were
estimated for each group. To estimate relative risks of rates rather than counts of events, the log of the
population count was included in the model as an offset. Estimated rates were calculated for each group
by multiplying the Manitoba crude reference rate by the appropriate relative risk estimate.
Adjusted rates, crude rates, and statistical testing of rates
Most of the indicators are given as adjusted rates, adjusted for age (and sex where relevant) through
the statistical modelling described earlier. This means that the rate has been adjusted to create a fair
comparison among neighbourhood income quintile groupings with different age distributions. All rates are
adjusted to reflect what the rate would be if each area’s population had the same age (and sex, in some
indicators) distribution as the Manitoba overall population for that particular time period.
Rates are suppressed (that is, not reported) where the counts upon which the rates are based represent
five events or less (unless the rate is truly 0, in which case it can be reported). This is to avoid breeches
of confidentiality, and this data protocol is similar to the way in which Statistics Canada reports data.
Throughout the report, the letter “s” in tables indicates a suppressed rate.
Appendix 2 contains tables listing the crude rates or prevalence (the actual count divided by the
actual population) without any adjustment for age and sex distributions. These tables also include the
‘observed’ number of events for each indicator where possible (unless this information is suppressed
Manitoba Centre for Health Policy 7