The 2015-16 Myanmar Demographic and Health Survey (2015-16 MDHS) is the first DHS survey to be conducted in Myanmar. A nationally representative sample of about 13,260 households was selected. All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey. Apart from the women’s survey, a men’s survey was also conducted at the same time in a subsample consisting of one household in every second household selected for the female survey. All men age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for the male survey.
In all of the selected households, parents or guardians of children age 6-59 months asked permission to collect a blood sample through a finger prick, also used to test for anemia. These children were also weighed and measured to obtain anthropometric indicators. Anemia testing and anthropometric measurements were also obtained for women age 15-49 in the sample households.
The primary objective of the 2015-16 MDHS was to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility levels, marital status, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, mother and child mortality and health, HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues, such as smoking and knowledge of tuberculosis.
The information collected through the 2015-16 MDHS is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population. Moreover, this survey has come at a beneficial time for Myanmar, as the results will be used to develop the next 5-year National Health Plan (2017-2021) and to update the national comprehensive development plan.
Kind of data
Sample survey data [ssd]
Unit of analysis
- Children age 0-5
- Woman age 15-49
- Man age 15-49
The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-49 years resident in the household.
Producers and sponsors
Ministry of Health and Sports (MoHS)
Government of Republic of the Union of Myanmar
Provided technical assistance
Government of Republic of the Union of Myanmar
Funded the study
United States Agency for International Development
Funded the study
Three Millennium Development Goal Fund
Funded the study
The sample was based on the 2014 census frame, which is used to coordinate household-based surveys conducted in Myanmar, including the current 2015-16 MDHS. The master sample is a large, nationally representative sample consisting of 4,000 PSUs drawn from the entire census frame; these can be used for sub-selecting multi-stage household-based survey samples.
The 2015-16 MDHS followed a stratified two-stage sample design and was intended to allow estimates of key indicators at the national level, in urban and rural areas, and for each of the seven States and eight Regions of Myanmar. The first stage involved selecting sample points (clusters) consisting of EAs or ward/village tracts. A total of 442 clusters (123 urban and 319 rural) were selected from the master sample.
At the second stage, a fixed number of 30 households was selected from each of the selected clusters (a total of 13,260 households), using equal probability systematic sampling. For the clusters, which were completely enumerated during the population census, the census household listings were taken as the base and updated in the field by the household listing teams. These updated lists were used for selecting the sample households. For the clusters that were not enumerated or partially enumerated during the census, an independent household listing operation was carried out. Because of the non-proportional sample allocation, the sample was not a self-weighting sample. Weighting factors had to be calculated, added to the data file, and applied so that results are representative at the national as well as regional level.
All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. In half of the selected households (every second household), all men age 15-49 who were either residents or visitors who stayed in the household the night before the survey were eligible to be interviewed.
For further details on sample selection, see Appendix A of the final report.
Deviations from sample design
During the course of the fieldwork, 4 clusters were identified as insecure and were replaced with other clusters in the vicinity. In addition, 1 urban cluster had to be dropped due to worsening security.
The total number of households selected was 13,238, of which 12,780 households were occupied. Of those occupied, 12,500 households were interviewed, yielding a 98% response rate.
In the interviewed households, 13,454 women were identified as eligible for the individual Woman’s Questionnaire. Interviews were successfully completed with 12,885 women, yielding a 96% response rate. In the subsample of one-half of the households, 5,218 men were identified as eligible for individual interview. Interviews were completed for 4,737 men, with a 91% response rate.
A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for household nonresponse and also for individual nonresponse to get the sampling weights for female and male surveys, respectively. The differences of the household sampling weights and the individual sampling weights are introduced by individual nonresponse. Sampling weights for the domestic violence survey were calculated based on the number of eligible respondents in the households selected for the domestic violence module. The final sampling weights were normalized to give the total number of unweighted cases equal to the total number of weighted cases at national level, for both household weights and individual weights, respectively. The normalized weights are relative weights, which are valid for estimating means, proportions, and ratios, but not valid for estimating population totals and for pooled data.
For further details on sampling weight calculations, see Appendix A.4 of the final report.
Dates of collection
Mode of data collection
Data collection supervision
Field supervision was carried out by the state and regional public health directors and officers. A standard supervisory protocol was developed to monitor coverage, and an orientation was conducted by the MDHS team. Technical monitoring was carried out by the MDHS core team and the master trainers. In addition, field supervision visits were conducted by the Deputy Health Minister, two Deputy Survey Managers, the DHS resident advisor from ICF, and other members of the MDHS Technical Committee. The DHS Program survey manager from ICF conducted field monitoring at different stages of field data collection. Additionally, a mechanism was developed to generate weekly field check tables to monitor the data quality, and immediate feedback was provided to the field teams.
Three sets of questionnaires were used in the 2015-16 MDHS: a Household Questionnaire, a Woman’s Questionnaire, and a Man’s Questionnaire. These questionnaires, developed for the worldwide DHS program, were revised to accord with Myanmar culture as well as to reflect some country-specific health issues.
The 2015-16 MDHS used computer-assisted field editing (CAFE) procedures with tablet computers. Thus, data processing began simultaneously with the fieldwork. All completed questionnaires were entered into the tablets while in the field by the field editors after they edited them on paper. Entries were checked by the supervisors before the questionnaires were dispatched to the data processing center at the MoHS central office in Nay Pyi Taw. These completed questionnaires were reviewed and re-entered by 13 data processing personnel specially trained for this task. All data were thus entered twice (100 percent verification), once in the field by the field editors and then again in the data processing center in Nay Pyi Taw. Data were entered using the CSPro computer package. The operation included secondary editing, using CSPro software, to resolve computer-identified inconsistencies and to code open-ended questions. The concurrent processing of the data offered a distinct advantage, because it maximized the likelihood of the data being error-free and accurate. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. Inconsistencies were resolved by tallying with the paper questionnaire entries.
The secondary editing was implemented by four editors and was completed in the second week of July 2016. The final cleaning of the data set was carried out by the DHS Program data processing specialist by the end of July 2016.
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2015-16 Myanmar Demographic and Health Survey (2015-16 MDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2015-16 MDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2015-16 MDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.
Other forms of data appraisal
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Sibship size and sex ratio of siblings
Note: See details of the data quality tables in APPENDIX C of the report.
The DHS Program
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The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
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DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
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A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
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- the survey reference number
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The DHS Program
Original archive where collection stored
The DHS Program
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Information about The DHS Program
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Data and Data Related Resources
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Development Data Group
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Documentation of the DDI
Version 01 (March 2017). Metadata is excerpted from "Myanmar Demographic and Health Survey 2015-16" Report.