Demographic and Health Survey 2016
Uganda, 2016
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UGA_2016_DHS_v01_M
Demographic and Health Survey 2016
| Name | Country code |
|---|---|
| Uganda | UGA |
Demographic and Health Survey (Standard) - DHS VII
The 2016 Uganda Demographic and Health Survey (2016 UDHS) is the sixth in a series of Demographic and Health Surveys conducted in Uganda in 1988-89, 1995, 2000-01, 2006, and 2011. As with the prior surveys, the main objective of the 2016 UDHS is to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; domestic violence; knowledge and attitudes toward HIV/AIDS; and maternal mortality.
The 2016 Uganda Demographic and Health Survey (2016 UDHS) was implemented by the Uganda Bureau of Statistics. The survey sample was designed to provide estimates of population and health indicators including fertility and child mortality rates for the country as a whole, for the urban and rural areas separately, and for each of the 15 regions in Uganda (South Central, North Central, Busoga, Kampala, Lango, Acholi, Tooro, Bunyoro, Bukedi, Bugisu, Karamoja, Teso, Kigezi, Ankole, and West Nile).
The primary objective of the 2016 UDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2016 UDHS collected information on:
• Key demographic indicators, particularly fertility and under-5, adult, and maternal mortality rates
• Direct and indirect factors that determine levels of and trends in fertility and child mortality
• Contraceptive knowledge and practice
• Key aspects of maternal and child health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery
• Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of women, men, and children
• Knowledge and attitudes of women and men about sexually transmitted infections (STIs) and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviours and condom use), and coverage of HIV testing and counselling (HTC) and other key HIV/AIDS programmes
• Anaemia in women, men, and children
• Malaria prevalence in children as a follow-up to the 2014-15 Uganda Malaria Indicator Survey
• Vitamin A deficiency (VAD) in children
• Key education indicators, including school attendance ratios, level of educational attainment, and literacy levels
• The extent of disability
• Early childhood development
• The extent of gender-based violence
The information collected through the 2016 UDHS is intended to assist policymakers 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 15-54
Scope
The 2016 Uganda 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, domestic violence, birth registration, and disability
• Child discipline
• 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), mosquito nets, and road traffic accidents.
INDIVIDUAL WOMAN
• Background characteristics: age, education, and media exposure
• Reproduction: children ever born, birth history, and current pregnancy
• Family planning: knowledge and use of contraception, sources of contraceptive methods, and information on family planning
• Maternal and child health, breastfeeding, and nutrition: prenatal care, delivery, postnatal care, breastfeeding and complementary feeding practices, vaccination coverage, prevalence and treatment of diarrhoea, symptoms of acute respiratory infection (ARI), fever, knowledge of oral rehydration salts (ORS), and use of oral rehydration therapy (ORT)
• Marriage and sexual activity: marital status, age at first marriage, number of unions, age at first sexual intercourse, recent sexual activity, number and type of sexual partners, use of condoms, knowledge and experience of obstetric fistula, and female genital cutting
• Fertility preferences: desire for more children, ideal number of children, gender preferences, and intention to use family planning
• Husbands’ background characteristics and women’s work: husbands’ age, level of education, and occupation and women’s occupation and sources of earnings
• STIs and HIV/AIDS: knowledge of STIs and AIDS and methods of transmission, sources of information, behaviours to avoid STIs and HIV, and stigma
• Knowledge, attitudes, and behaviours related to other health issues such as injections and smoking
• Adult and maternal mortality
• Domestic violence (questions asked of one woman per household)
• Early childhood development
INDIVIDUAL MAN
• Respondent background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
BIOMARKER
• Weight, height, hemoglobin measurement and malaria, Vitamin A testing for children age 0-5
• Weight, height, and hemoglobin measurement for women age 15-49
• Weight, height, and hemoglobin measurement for men age 15-54
Coverage
National coverage
Producers and sponsors
| Name | Affiliation |
|---|---|
| Bureau of Statistics (UBOS) | Government of Uganda |
| Name | Role |
|---|---|
| ICF | Provided technical assistance through The DHS Program |
| Name | Role |
|---|---|
| Government of Uganda | Funded the survey |
| United States Agency for International Development | Funded the survey |
| United Nations Children’s Fund | Funded the survey |
| United Nations Population Fund | Funded the survey |
Sampling
The sampling frame used for the 2016 UDHS is the frame of the Uganda National Population and Housing Census (NPHC), conducted in 2014; the sampling frame was provided by the Uganda Bureau of Statistics. The census frame is a complete list of all census enumeration areas (EAs) created for the 2014 NPHC. In Uganda, an EA is a geographic area that covers an average of 130 households. The sampling frame contains information about EA location, type of residence (urban or rural), and the estimated number of residential households.
The 2016 UDHS sample was stratified and selected in two stages. In the first stage, 697 EAs were selected from the 2014 Uganda NPHC: 162 EAs in urban areas and 535 in rural areas. One cluster from Acholi subregion was eliminated because of land disputes. Households constituted the second stage of sampling.
For further details on sample design, see Appendix A of the final report.
A total of 20,791 households were selected for the sample, of which 19,938 were occupied. Of the occupied households, 19,588 were successfully interviewed, which yielded a response rate of 98%.
In the interviewed households, 19,088 eligible women were identified for individual interviews. Interviews were completed with 18,506 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 5,676 eligible men were identified and 5,336 were successfully interviewed, yielding a response rate of 94%. Response rates were higher in rural than in urban areas, with the ruralurban difference being more pronounced among men (95% and 90%, respectively) than among women (98% and 95%, respectively).
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 individual nonresponse to obtain the sampling weights for households and for women and men, respectively. Nonresponse is adjusted at the sampling stratum level. For the household sampling weight, the household design weight is multiplied by the inverse of the household response rate, by stratum. For the women’s individual sampling weight, the household sampling weight is multiplied by the inverse of the women’s individual response rate, by stratum. For the men’s individual sampling weight, the household sampling weight for the male subsample is multiplied by the inverse of the men’s individual response rate, by stratum. Similarly, domestic violence weights were calculated for women and men, where the design weights were adjusted for the within-household selection and the nonresponse for the domestic violence module. After adjusting for nonresponse, the sampling weights were normalized to get the final standard weights that appear in the data files. The normalization process is aimed at obtaining a total number of unweighted cases equal to the total number of weighted cases using normalized weights at the national level, for the total number of households, women, and men. Normalization is done by multiplying the sampling weight by the estimated total sampling fraction obtained from the survey for the household weight, the individual woman’s weight, and the individual man’s weight. The normalized weights are relative weights that are valid for estimating means, proportions, ratios, and rates, but they are not valid for estimating population totals or for pooled data.
For further details on sampling weights, see Appendix A.4 of the final report.
Data collection
| Start | End |
|---|---|
| 2016-06-16 | 2016-06-20 |
| Name | Affiliation |
|---|---|
| Bureau of Statistics | Government of Uganda |
Data collection was conducted by 21 field teams, each consisting of one team leader, one field data manager, three female interviewers, one male interviewer, one health technician, and one driver. The health technicians were responsible for anthropometric measurements, blood sample collection for haemoglobin and malaria testing, and DBS specimen collection for vitamin A testing. Electronic data files were transferred from each interviewer’s tablet computer to the team supervisor’s tablet computer every day. The field supervisors transferred data to the central data processing office via IFSS. Senior staff from the Makerere University School of Public Health, the Ministry of Health, and UBOS and a survey technical specialist from The DHS Program coordinated and supervised fieldwork activities. Data collection took place over a 6-month period, from 20 June 2016 through 16 December 2016.
Data processing
All electronic data files for the 2016 UDHS were transferred via IFSS to the UBOS central office in Kampala, where they were stored on a password-protected computer. 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 four staff (two programmers and two data editors) who took part in the main fieldwork training. They were supervised by three senior staff from UBOS. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in August 2016 and completed in January 2017.
Data appraisal
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 2016 Uganda Demographic and Health Survey (UDHS) to minimise 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 2016 UDHS 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 2016 UDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation 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.
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
- 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 |