Survey on Maternal Health (SMH)

Detailed information for 2018 and 2019

The main objective of the Survey on Maternal Health is to collect information from biological mothers about their pregnancy and postpartum experiences.

Data release - June 24, 2019

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Results from the survey will be used by researchers and policy makers to monitor maternal health and to improve the health and wellness of women.

Subjects

• Health
• Mental health and well-being
• Pregnancy and births

Data sources and methodology

Target population

The target population for the survey is the set of biological mothers who have given birth between January 1 and June 30 2018, living in Canada's ten provinces. Persons living in institutions or residents of First Nations communities are excluded from the target population.

Instrument design

The content for the Survey on Maternal Health electronic questionnaire was drafted in consultation with the Public Health Agency of Canada.

The questionnaire underwent cognitive testing in the form of in-depth interviews in both of Canada's official languages, conducted by Statistics Canada's Questionnaire Design Resource Centre. The goal of the qualitative study was to test the survey content.

Sampling

This is a sample survey with a cross-sectional design.

Frame
The frame was extracted from the October 2018 version of the Canada Child Benefit file (CCB). Persons from Yukon, the Northwest Territories and Nunavut were excluded, as well as residents of First Nations communities.

Sample design
A random cross-sectional sample stratified by province.

Sampling unit
The SMH is a targeted respondent survey. The sampling unit is the birth mother of a child that was born between January 1 and June 30, 2018.

Stratification method
The Survey on Maternal Health frame was stratified by province and a simple random sample of mothers was selected independently within each province.

Sampling and sub-sampling
Sufficient sample was allocated to each of the provinces so that the survey could produce province level estimates. An initial sample of 13,000 mothers was selected and sent to collection.

Data sources

Data collection for this reference period: 2018-11-29 to 2019-02-05

Responding to this survey is voluntary.

Data are collected directly from survey respondents either through an electronic questionnaire (EQ) or through CATI (computer-assisted telephone interviewing).

View the Questionnaire(s) and reporting guide(s) .

Error detection

Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.

In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.

After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.

Imputation

This methodology type does not apply to this statistical program.

Estimation

The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The process of computing survey weights for each survey respondent involves several steps.

1) Each selected respondent is given an initial weight equal to the inverse of its selection probability from the sampling frame (CCB). Respondents identified as out-of-scope during collection are dropped from the sample.

2)The person weights are obtained by taking into account the non-response based on the province and the number of children. Then share weights are also computed and are obtained by modeling the response using different survey variables, such as the province and the age of the mother.

Note that the person weights are not calibrated since there are no demographic counts for the population of mothers of young children other than the ones from the frame (CCB).

Variance estimation is based on a re-sampling method called the bootstrap.

The Generalized Estimation System from Statistics Canada(G-Est) was used to generate the survey weights and bootstrap weights.

Quality evaluation

While rigorous quality assurance mechanisms are applied at all stages of the statistical process, the validation and detailed review of data by statisticians is the ultimate verification of quality prior to release. Many validation measures were implemented, they include:

a. Verification of estimates through cross-tabulations
b. Consultation with stakeholders internal to Statistics Canada
c. Consultation with external stakeholders

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval(CI) or coefficient of variation(CV).

The following are approximate sampling error estimates for Canada level estimates. These are based on average results; these are not results for a specific variable.

- Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 4.0%
- Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 2.5%
- Approximate coefficients of variation (CVs) for a proportion of 10% (Canada level): 6%

Response rates
The response rate for the Survey on Maternal Health was 54.74%.

Non-sampling error
The first type of errors treated were errors in questionnaire flow. For skips based on answered questions, all skipped questions were set to "Valid skip" (6, 96, 996, etc.). For skips based on "Non-response", all skipped questions were set to "Not stated" (9, 99, 999, etc.). The remaining empty items were filled with a numeric value (9, 99, 999, etc., depending on variable length). These codes are reserved for processing purposes and mean that the item was "Not stated".

Non-response bias
The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding persons differ from the rest of the sample, the results may be biased.

Coverage error
Coverage errors arise when there are differences between the target population and the observed population. The target population is mothers of children born between January 1st 2018 and June 30th 2018. The survey frame is the Canada Child Benefit (CCB) file and it contains every parent who is registered to receive a benefit. It is estimated that the frame represents 96% of the children population of all ages. To the extent that the excluded population differs from the rest of the target population, the results may be biased.