ETH_2016_DHS_v01_M
Demographic and Health Survey 2016
Name | Country code |
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Ethiopia | ETH |
Demographic and Health Survey (Standard) - DHS VII
Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition.
The 2016 Ethiopia Demographic and Health Survey (2016 EDHS) is the fourth in a series of Demographic and Health Surveys conducted in Ethiopia in 2000, 2005, and 2011. As the fourth DHS conducted in Ethiopia, the 2016
EDHS provides valuable information on trends in key demographic and health indicators over time. The information collected through the 2016 EDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.
Additionally, the 2016 EDHS included a health facility component that recorded data on children’s vaccinations, which were then combined with the household data on vaccinations.
The 2016 Ethiopia Demographic and Health Survey (EDHS) is the fourth Demographic and Health Survey conducted in Ethiopia. It was implemented by the Central Statistical Agency (CSA) at the request of the Federal Ministry of Health (FMoH). The primary objective of the 2016 EDHS is to provide up-to-date estimates of key demographic and health indicators. The EDHS provides a comprehensive overview of population, maternal, and child health issues in Ethiopia. More specifically, the 2016 EDHS:
Sample survey data [ssd]
The 2016 Ethiopia Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Identification
• Household schedule, 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, and birth registration
• Characteristics of the household's dwelling unit, such as the source of water (drinking and other purposes), where the water source located and how long it takes to go there, toilet facilities, number of rooms in the dwelling, type of fuel used for cooking, materials used for the floor, roof and walls of the house, ownership of livestock, and possessions of durable goods (including land)
• Injuries/ accidents
INDIVIDUAL WOMAN
• Identification
• Respondent background characteristics (including age, education, and media exposure)
• Birth history and childhood mortality
• Family planning, including knowledge, use, and sources of contraceptive methods
• Fertility preferences
• Antenatal, delivery, and postnatal care
• Breastfeeding and infant feeding practices
• Vaccinations and childhood illnesses
• Women’s work and husbands’ background characteristics
• Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted diseases (STDs)
• Knowledge, attitudes, and behaviours related to other health issues (e.g., injections, smoking, use of chat)
• Adult and maternal mortality
• Female genital mutilation or cutting
• Fistula
• Violence against women
INDIVIDUAL MAN
• Identification
• Respondent background
• Reproduction
• Contraception
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles and decision making
• HIV/AIDS
• Other health issues
BIOMARKER
• Identification
• Weight, height, and hemoglobin measurement for children age 0-5
• Weight, height, hemoglobin measurements and HIV testing for women age 15-49
• Weight, height, hemoglobin measurements and HIV testing for men age 15-59
HEALTH FACILITY
• Identification
• Health facility form
• Immunization records form health facility
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.
Name | Affiliation |
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Central Statistical Agency (CSA) | Government of Ethiopia |
Name | Role |
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ICF | Provided technical assistance through The DHS Program |
Name | Role |
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Government of Ethiopia | Funded the study |
United States Agency for International Development | Funded the study |
Government of Netherlands | Funded the study |
Global Fund | Funded the study |
Irish Aid | Funded the study |
World Bank | Funded the study |
United Nations Population Fund | Funded the study |
United Nations Children’s Fund | Funded the study |
UN Women | Funded the study |
The sampling frame used for the 2016 EDHS is the Ethiopia Population and Housing Census (PHC), which was conducted in 2007 by the Ethiopia Central Statistical Agency. The census frame is a complete list of 84,915 enumeration areas (EAs) created for the 2007 PHC. An EA is a geographic area covering on average 181 households. The sampling frame contains information about the EA location, type of residence (urban or rural), and estimated number of residential households. With the exception of EAs in six zones of the Somali region, each EA has accompanying cartographic materials. These materials delineate geographic locations, boundaries, main access, and landmarks in or outside the EA that help identify the EA. In Somali, a cartographic frame was used in three zones where sketch maps delineating the EA geographic boundaries were available for each EA; in the remaining six zones, satellite image maps were used to provide a map for each EA.
Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2016 EDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities.
The 2016 EDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.
For further details on sample design, see Appendix A of the final report.
A total of 18,008 households were selected for the sample, of which 17,067 were occupied. Of the occupied households, 16,650 were successfully interviewed, yielding a response rate of 98%.
In the interviewed households, 16,583 eligible women were identified for individual interviews. Interviews were completed with 15,683 women, yielding a response rate of 95%. A total of 14,795 eligible men were identified in the sampled households and 12,688 were successfully interviewed, yielding a response rate of 86%. Although overall there was little variation in response rates according to residence, response rates among men were higher in rural than in urban areas.
A spreadsheet with all sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weight. The design weight was adjusted for household non-response and as well as individual non-response to obtain the sampling weights for households, and for the women and men surveys respectively. The differences of the household sampling weight and the individual sampling weights are introduced by individual non-response. The final sampling weights were normalized to give the total number of unweighted cases equal to the total number of weighted cases at the national level, for both household weight and individual weight, respectively. The normalized weights are relative weights that are valid for estimating means, proportions, and ratios, but not valid for estimating the population totals and for pooled data.
For further details on sampling weights, see Appendix A.4 of the final report.
Five questionnaires were used for the 2016 EDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Health Facility 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 Ethiopia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After all questionnaires were finalised in English, they were translated into Amarigna, Tigrigna, and Oromiffa.
Start | End |
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2016-01-18 | 2016-06-27 |
Name | Affiliation |
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Central Statistical Agency | Government of Ethiopia |
Data collection took place over a 5.5-month period, from January 18, 2016, to June 27, 2016. Fieldwork was carried out by 33 field teams, each consisting of one team supervisor, one field editor, three female interviewers, one male interviewer, two biomarker technicians, and one driver. In addition, 28 quality controllers (14 for interviews and 14 for biomarkers) were dispatched during data collection to support and monitor fieldwork. Electronic data files were transferred to the CSA central office in Addis Ababa every few days via the secured IFSS. Staff from CSA, FMoH, and EPHI and specialists from the DHS Program coordinated and supervised fieldwork activities.
All electronic data files for the 2016 EDHS were transferred via IFSS to the CSA central office in Addis Ababa, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of openended questions; it also required generating a file for the list of children for whom a vaccination card was not seen by the interviewers and whose vaccination records had to be checked at health facilities. The data were processed by two individuals who took part in the main fieldwork training; they were supervised by two senior staff from CSA. Data editing was accomplished using CSPro software. During the duration of fieldwork, tables were generated to check various data quality parameters and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in January 2016 and completed in August 2016.
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 the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2016 Ethiopia DHS (EDHS) to minimise this type of error, non-sampling errors are impossible to avoid and are difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2016 EDHS is only one of many samples that could have been selected from the same population, by using the same design and the expected size. Each of those 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.
Sampling error is usually measured in terms of the standard error for a particular statistic (such as mean or percentage), 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 EDHS sample is the result of a multi-stage stratified design and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, with programs developed by ICF International. These programs use the Taylor linearisation 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
See details of the data quality tables in Appendix C of the survey final report.
Name | URL | |
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The DHS Program | http://www.DHSprogram.com | archive@dhsprogram.com |
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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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Name | Affiliation | URL | |
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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 |