Demographic and Health Survey 2016
Timor-Leste, 2016
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TLS_2016_DHS_v01_M
Demographic and Health Survey 2016
| Name | Country code |
|---|---|
| Timor-Leste | TLS |
Demographic and Health Survey (Standard) - DHS VII
The 2016 Timor-Leste Demographic and Health Survey (TLDHS 2016) is the third one of its kind following the one conducted in 2003, and 2009-10. TLDHS 2016 used a nationally representative sample of 11,830 residential households. All women age 15-49 who are usual residents of the selected households or who slept in the households the night before the survey are eligible for the survey. The survey was expected to yield about 12,830 completed interviews of women age 15-49.
The primary objective of the 2016 TLDHS project is to provide up-to-date estimates of basic demographic and health indicators. The TLDHS provides a comprehensive overview of population, maternal, and child health issues in Timor-Leste. More specifically, the 2016 TLDHS:
• Collected data at the national level, which allows the calculation of key demographic indicators, particularly fertility, and child, adult, and maternal mortality rates
• Provided data to explore the direct and indirect factors that determine the levels and trends of fertility and child mortality
• Measured the levels of contraceptive knowledge and practice
• Obtained data on key aspects of maternal and child health, including immunization coverage, prevalence and treatment of diarrhea and other diseases among children under age 5, and maternity care, including antenatal visits and assistance at delivery
• Obtained data on child feeding practices, including breastfeeding, and collected anthropometric measures to assess nutritional status in children, women, and men
• Tested for anemia in children, women, and men
• Collected data on the knowledge and attitudes of women and men about sexually-transmitted diseases and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviors and condom use), and coverage of HIV testing and counseling
• Measured key education indicators, including school attendance ratios, level of educational attainment, and literacy levels
• Collected information on the extent of disability
• Collected information on non-communicable diseases
• Collected information on early childhood development
• Collected information on domestic violence
• The information collected through the 2016 TLDHS 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.
Sample survey data [ssd]
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-59
Scope
The 2016 Timor-Leste Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, school attendance, highest educational attainment, birth registration, disability, domestic violence, and birth registration
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, type of fuel used for cooking, materials used for the floor, roof and walls of the house, possessions of durable goods (including land) and mosquito nets.
INDIVIDUAL WOMAN
• Identification
• Background characteristics (age, education, literacy, religion, etc.)
• Reproductive history
• Knowledge and use of contraceptive methods
• Antenatal, delivery, and postnatal care
• Breastfeeding and infant feeding practices
• Immunization, child health, and nutrition
• Marriage and recent sexual activity
• Fertility preferences
• Husband’s background and respondent’s work
• Knowledge about HIV/AIDS and other sexually transmitted diseases
• Other health issues, for example, recent injections, smoking habits, and alcohol use
• Adult and maternal mortality
• Domestic violence (one woman per household)
• Early childhood development
• Questions specific to youth
• Non-communicable diseases
INDIVIDUAL MAN
• Identification
• Respondent background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
• Non-communicable diseases
• Youth
BIOMARKER
• Weight, height, and hemoglobin measurement for children age 0-5
• Weight, height, and hemoglobin measurement for women age 15-49
• Weight, height, and hemoglobin measurement for men age 15-59
Coverage
National
The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-59 years resident in the household.
Producers and sponsors
| Name | Affiliation |
|---|---|
| General Directorate of Statistics (GDS) | Ministry of Finance, Government of Timor-Leste |
| Name | Affiliation | Role |
|---|---|---|
| ICF | The DHS Program | Provided technical assistance through The DHS Program |
| Ministry of Health | Government of Timor-Leste | Collaborated in the implementation of the survey |
| Name | Role |
|---|---|
| Government of Timor-Leste | Funded the survey |
| United States Agency for International Development | Funded the survey |
| United Nations Population Fund | Funded the survey |
| World Health Organization | Funded the survey |
| European Union | Funded the survey |
| World Bank | Funded the survey |
Sampling
The sampling frame used for the TLDHS 2016 survey is the 2015 Timor-Leste Population and Housing Census (TLPHC 2015), provided by the General Directorate of Statistics. The sampling frame is a complete list of 2320 non-empty Enumeration Areas (EAs) created for the 2015 population census. An EA is a geographic area made up of a convenient number of dwelling units which served as counting units for the census, with an average size of 89 households per EA. The sampling frame contains information about the administrative unit, the type of residence, the number of residential households and the number of male and female population for each of the EAs. Among the 2320 EAs, 413 are urban residence and 1907 are rural residence.
There are five geographic regions in Timor-Leste, and these are subdivided into 12 municipalities and special administrative region (SAR) of Oecussi. The 2016 TLDHS sample was designed to produce reliable estimates of indicators for the country as a whole, for urban and rural areas, and for each of the 13 municipalities. A representative probability sample of approximately 12,000 households was drawn; the sample was stratified and selected in two stages. In the first stage, 455 EAs were selected with probability proportional to EA size from the 2015 TLPHC: 129 EAs in urban areas and 326 EAs in rural areas. In the second stage, 26 households were randomly selected within each of the 455 EAs; the sampling frame for this household selection was the 2015 TLPHC household listing available from the census database.
For further details on sample design, see Appendix A of the final report.
A total of 11,829 households were selected for the sample, of which 11,660 were occupied. Of the occupied households, 11,502 were successfully interviewed, which yielded a response rate of 99 percent.
In the interviewed households, 12,998 eligible women were identified for individual interviews. Interviews were completed with 12,607 women, yielding a response rate of 97 percent. In the subsample of households selected for the men’s interviews, 4,878 eligible men were identified and 4,622 were successfully interviewed, yielding a response rate of 95 percent. Response rates were higher in rural than in urban areas, with the difference being more pronounced among men (97 percent versus 90 percent, respectively) than among women (98 percent versus 94 percent, respectively). The lower response rates for men were likely due to their more frequent and longer absences from the household.
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 non-response and as well as for individual non-response to get the sampling weights, for women and men surveys respectively. The differences of the household sampling weights and the individual sampling weights are introduced by individual non-response. The final sampling weights were normalized in order to get 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. There are four sets of weights calculated:
• one set for all households selected for the survey
• one set for women individual survey
• one set for households selected for the male survey
• one set for male individual survey
It is important to note that 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. Also the number of weighted case by using the normalized weight has no direct relation with the survey precision because it is relative, especially for oversampled areas, the number of weighted cases will be much smaller than the number of un-weighted cases, the later one is directly related to survey precision.
Survey instrument
Four questionnaires were used for the 2016 TLDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Timor-Leste.
Data collection
| Start | End |
|---|---|
| 2016-09-16 | 2016-12-22 |
| Name | Affiliation |
|---|---|
| General Directorate of Statistics | Ministry of Finance, Government of Timor-Leste |
Data collection was conducted by 20 field teams, each consisting of one supervisor, one editor, three female interviewers, one male interviewer, and one driver. Supervisors were responsible for the team, contacting local officials, locating and assigning the selected households, maintaining the pace of work, conducting household interviews as needed, and assisting with and providing oversight to anthropometry measurement.
Editors were responsible for transferring questionnaires to interviewers, collecting completed questionnaires, resolving inconsistencies in questionnaires, completing the cluster data file, transferring data to the central office, and observing interviews. Interviewers were responsible for conducting household and individual interviews with eligible respondents, anthropometry measurement, and anemia testing. Electronic data files were collected from each interviewer’s tablet computer every day. Data were transferred to the central data processing office via IFSS. Staff from GDS, MOH, USAID, UNFPA, and The DHS Program coordinated and supervised fieldwork activities. Data collection took place over a 3-month period, from 16 September to 22 December, 2016.
Data processing
The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two staff who took part in the main fieldwork training. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in October 2016 and completed in February 2017.
Data appraisal
The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 TLDHS 2016 to minimize this type of error, non-sampling 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 TLDHS 2016 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A 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 percent 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 TLDHS 2016 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the TLDHS 2016 is a SAS program. This program used the Taylor linearization method of variance estimation 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.
A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.
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
- Height and weight data completeness and quality for children
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
- Pregnancy-related mortality trends
See details of the data quality tables in Appendix C of the survey final report.
Data Access
| Name | URL | |
|---|---|---|
| The DHS Program | http://www.DHSprogram.com | archive@dhsprogram.com |
Request Dataset Access
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.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
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.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
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.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Information about The DHS Program | The DHS Program | reports@DHSprogram.com | http://www.DHSprogram.com |
| General Inquiries | The DHS Program | info@dhsprogram.com | http://www.DHSprogram.com |
| Data and Data Related Resources | The DHS Program | archive@dhsprogram.com | http://www.DHSprogram.com |
Metadata production
DDI_TLS_2016_DHS_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank | Documentation of the DDI |
Metadata version
Version 01 (April 2018). Metadata is excerpted from "Timor-Leste Demographic and Health Survey 2016" Report.