100+ datasets found
  1. Mini Demographic and Health Survey 2019 - Ethiopia

    • microdata.worldbank.org
    • catalog.ihsn.org
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    Updated May 11, 2021
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    Central Statistical Agency (CSA) (2021). Mini Demographic and Health Survey 2019 - Ethiopia [Dataset]. https://microdata.worldbank.org/index.php/catalog/3946
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    Dataset updated
    May 11, 2021
    Dataset provided by
    Central Statistical Agencyhttps://ess.gov.et/
    Federal Ministry of Health (FMoH)
    Ethiopian Public Health Institute (EPHI)
    Time period covered
    2019
    Area covered
    Ethiopia
    Description

    Abstract

    The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is a nationwide survey with a nationally representative sample of 9,150 selected households. All women age 15-49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In the selected households, all children under age 5 were eligible for height and weight measurements. The survey was designed to produce reliable estimates of key indicators at the national level as well as for urban and rural areas and each of the 11 regions in Ethiopia.

    The primary objective of the 2019 EMDHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the main objectives of the survey are: ▪ To collect high-quality data on contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; child nutrition; and other health issues relevant to achievement of the Sustainable Development Goals (SDGs) ▪ To collect information on health-related matters such as breastfeeding, maternal and child care (antenatal, delivery, and postnatal), children’s immunizations, and childhood diseases ▪ To assess the nutritional status of children under age 5 by measuring weight and height

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49
    • Health facility

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49 and all children aged 0-5 resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling frame used for the 2019 EMDHS is a frame of all census enumeration areas (EAs) created for the 2019 Ethiopia Population and Housing Census (EPHC) and conducted by the Central Statistical Agency (CSA). The census frame is a complete list of the 149,093 EAs created for the 2019 EPHC. An EA is a geographic area covering an average of 131 households. The sampling frame contains information about EA location, type of residence (urban or rural), and estimated number of residential households.

    Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2019 EMDHS 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 2019 EMDHS 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.

    To ensure that survey precision was comparable across regions, sample allocation was done through an equal allocation wherein 25 EAs were selected from eight regions. However, 35 EAs were selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR).

    In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size (based on the 2019 EPHC frame) and with independent selection in each sampling stratum. A household listing operation was carried out in all selected EAs from January through April 2019. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs for the 2019 EMDHS were large, with more than 300 households. To minimise the task of household listing, each large EA selected for the 2019 EMDHS was segmented. Only one segment was selected for the survey, with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2019 EMDHS cluster is either an EA or a segment of an EA.

    In the second stage of selection, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who slept in the household the night before the survey were eligible to be interviewed. In all selected households, height and weight measurements were collected from children age 0-59 months, and women age 15-49 were interviewed using the Woman’s Questionnaire.

    For further details on sample selection, see Appendix A of the final report.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Five questionnaires were used for the 2019 EMDHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Anthropometry Questionnaire, (4) the Health Facility Questionnaire, and (5) the Fieldworker’s Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. They were shortened substantially to collect data on indicators of particular relevance to Ethiopia and donors to child health programmes.

    Cleaning operations

    All electronic data files were transferred via the secure internet file streaming system (IFSS) to the EPHI 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 open-ended questions. The data were processed by EPHI staff members and an ICF consultant who took part in the main fieldwork training. They were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro System software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing, double data entry from both the anthropometry and health facility questionnaires, and data processing were initiated in April 2019 and completed in July 2019.

    Response rate

    A total of 9,150 households were selected for the sample, of which 8,794 were occupied. Of the occupied households, 8,663 were successfully interviewed, yielding a response rate of 99%.

    In the interviewed households, 9,012 eligible women were identified for individual interviews; interviews were completed with 8,885 women, yielding a response rate of 99%. Overall, there was little variation in response rates according to residence; however, rates were slightly higher in rural than in urban areas.

    Sampling error estimates

    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 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) 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 2019 EMDHS 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 2019 EMDHS 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 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.

    Data appraisal

    Data Quality Tables

    • Household age distribution

    - Age distribution of eligible and interviewed women

  2. w

    Ethiopia - Demographic and Health Survey 2011

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Ethiopia - Demographic and Health Survey 2011 [Dataset]. https://wbwaterdata.org/dataset/ethiopia-demographic-and-health-survey-2011
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    The 2011 Ethiopia Demographic and Health Survey (EDHS) was conducted by the Central Statistical Agency (CSA) under the auspices of the Ministry of Health. The principal objective of the 2011 Ethiopia Demographic and Health Survey (EDHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, use of maternal and child health services, knowledge of HIV/AIDS, and prevalence of HIV/AIDS and anaemia. The specific objectives are these: Collect data at the national level that will allow the calculation of key demographic rates; Analyse the direct and indirect factors that determine fertility levels and trends; Measure the levels of contraceptive knowledge and practice of women and men by family planning method, urban-rural residence, and region of the country; Collect high-quality data on family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under ge five, and maternity care indicators, including antenatal visits and assistance at delivery; Collect data on infant and child mortality and maternal mortality; Obtain data on child feeding practices, including breastfeeding, and collect anthropometric measures to assess the nutritional status of women and children; Collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; Conduct haemoglobin testing on women age 15-49 and children 6-59 months to provide information on the prevalence of anaemia among these groups; Carry out anonymous HIV testing on women and men of reproductive age to provide information on the prevalence of HIV. This information is essential for informed policy decisions, planning, monitoring, and evaluation of programmes on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2011 EDHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries and to Ethiopia’s two previous DHS surveys, conducted in 2000 and 2005. Data collected in the 2011 EDHS add to the large and growing international database of demographic and health indicators. The survey was intentionally planned to be fielded at the beginning of the last term of the MDG reporting period to provide data for the assessment of the Millennium Development Goals (MDGs). The survey interviewed a nationally representative population in about 18,500 households, and all women age 15-49 and all men age 15-59 in these households. In this report key indicators relating to family planning, fertility levels and determinants, fertility preferences, infant, child, adult and maternal mortality, maternal and child health, nutrition, women’s empowerment, and knowledge of HIV/AIDS are provided for the nine regional states and two city administrations. In addition, this report also provides data by urban and rural residence at the country level. Major stakeholders from various government, non-government, and UN organizations have been involved and have contributed in the technical, managerial, and operational aspects of the survey.

  3. The 2016 Ethiopia Demographic and Health Survey (EDHS) - Ethiopia

    • microdata-catalog.afdb.org
    Updated Jun 2, 2022
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    Central Statistical Agency(CSA) (2022). The 2016 Ethiopia Demographic and Health Survey (EDHS) - Ethiopia [Dataset]. https://microdata-catalog.afdb.org/index.php/catalog/123
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    Dataset updated
    Jun 2, 2022
    Dataset provided by
    Central Statistical Agencyhttps://ess.gov.et/
    Authors
    Central Statistical Agency(CSA)
    Time period covered
    2016
    Area covered
    Ethiopia
    Description

    Abstract

    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). Data collection took place from January 18, 2016, to June 27, 2016.

    SURVEY OBJECTIVES 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: - Collected data at the national level that allowed calculation of key demographic indicators, particularly fertility and under-5 and adult mortality rates - Explored the direct and indirect factors that determine levels and trends of fertility and child mortality - Measured levels of contraceptive knowledge and practice - Collected data on key aspects of family 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 - Obtained data on child feeding practices, including breastfeeding - Collected anthropometric measures to assess the nutritional status of children under age 5, women age 15-49, and men age 15-59 - Conducted haemoglobin testing on eligible children age 6-59 months, women age 15-49, and men age 15-59 to provide information on the prevalence of anaemia in these groups - Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviours and condom use - Conducted HIV testing of dried blood spot (DBS) samples collected from women age 15-49 and men age 15-59 to provide information on the prevalence of HIV among adults of reproductive age - Collected data on the prevalence of injuries and accidents among all household members - Collected data on knowledge and prevalence of fistula and female genital mutilation or cutting (FGM/C) among women age 15-49 and their daughters age 0-14 - Obtained data on women’s experience of emotional, physical, and sexual violence.

    As the fourth DHS conducted in Ethiopia, following the 2000, 2005, and 2011 EDHS surveys, 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.

    Geographic coverage

    National coverage

    Analysis unit

    • Households
    • Men
    • Women
    • Children

    Universe

    Household members women age 15-49 men age 15-59 children under age 5

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    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.

    In the first stage, a total of 645 EAs (202 in urban areas and 443 in rural areas) were selected with probability proportional to EA size (based on the 2007 PHC) and with independent selection in each sampling stratum. A household listing operation was carried out in all of the selected EAs from September to December 2015. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs were large, consisting of more than 300 households. To minimise the task of household listing, each large EA selected for the 2016 EDHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2016 EDHS cluster is either an EA or a segment of an EA.

    In the second stage of selection, a fixed number of 28 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 and all men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the selected households, all women age 15-49 were eligible for the FGM/C module, and only one woman per household was selected for the domestic violence module. In all of the selected households, height and weight measurements were collected from children age 0-59 months, women age 15-49, and men age 15-59. Anaemia testing was performed on consenting women age 15-49 and men age 15-59 and on children age 6-59 months whose parent/guardian consented to the testing. In addition, DBS samples were collected for HIV testing in the laboratory from women age 15-49 and men age 15-59 who consented to testing.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    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.

    The Household Questionnaire was used to list all members of and visitors to selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, and flooring materials, as well as on ownership of various durable goods. The Household Questionnaire included an additional module developed by the DHS Program to estimate the prevalence of injuries/accidents among all household members.

    The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: - 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 The Man’s Questionnaire was administered to all eligible men age 15-59. This questionnaire collected much of the same information elicited from the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history, questions on maternal and child health, or questions on domestic violence. The Biomarker Questionnaire was used to record biomarker data

  4. w

    Ethiopia - Demographic and Health Survey 2005

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Ethiopia - Demographic and Health Survey 2005 [Dataset]. https://wbwaterdata.org/dataset/ethiopia-demographic-and-health-survey-2005
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    The 2005 Ethiopia Demographic and Health Survey (2005 EDHS) is part of the worldwide MEASURE DHS project which is funded by the United States Agency for International Development (USAID). The principal objective of the 2005 Ethiopia Demographic and Health Survey (DHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, knowledge of HIV/AIDS and prevalence of HIV/AIDS and anaemia. The specific objectives are to: collect data at the national level which will allow the calculation of key demographic rates; analyze the direct and indirect factors which determine the level and trends of fertility; measure the level of contraceptive knowledge and practice of women and men by method, urban-rural residence, and region; collect high quality data on family health including immunization coverage among children, prevalence and treatment of diarrhoea and other diseases among children under five, and maternity care indicators including antenatal visits and assistance at delivery; collect data on infant and child mortality and maternal and adult mortality; obtain data on child feeding practices including breastfeeding and collect anthropometric measures to use in assessing the nutritional status of women and children; collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; conduct haemoglobin testing on women age 15-49 and children under age five years in a subsample of the households selected for the survey to provide information on the prevalence of anaemia among women in the reproductive ages and young children; collect samples for anonymous HIV testing from women and men in the reproductive ages to provide information on the prevalence of HIV among the adult population. This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2005 Ethiopia DHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first ever Demographic and Health Survey (DHS) in Ethiopia was conducted in the year 2000 as part of the worldwide DHS programme. Data from the 2005 Ethiopia DHS survey, the second such survey, add to the vast and growing international database on demographic and health variables. Wherever possible, the 2005 EDHS data is compared with data from the 2000 EDHS. In addition, where applicable, the 2005 EDHS is compared with the 1990 NFFS, which also sampled women age 15-49. Husbands of currently married women were also covered in this survey. However, for security and other reasons, the NFFS excluded from its coverage Eritrea, Tigray, Asseb, and Ogaden autonomous regions. In addition, fieldwork could not be carried out for Northern Gondar, Southern Gondar, Northern Wello, and Southern Wello due to security reasons. Thus, any comparison between the EDHS and the NFFS has to be interpreted with caution.

  5. i

    Demographic and Health Survey 2005 - Ethiopia

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jul 6, 2017
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    Population and Housing Census Commissions Office (PHCCO) (2017). Demographic and Health Survey 2005 - Ethiopia [Dataset]. https://catalog.ihsn.org/catalog/163
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    Population and Housing Census Commissions Office (PHCCO)
    Time period covered
    2005
    Area covered
    Ethiopia
    Description

    Abstract

    The 2005 Ethiopia Demographic and Health Survey (2005 EDHS) is part of the worldwide MEASURE DHS project which is funded by the United States Agency for International Development (USAID).

    The principal objective of the 2005 Ethiopia Demographic and Health Survey (DHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, knowledge of HIV/AIDS and prevalence of HIV/AIDS and anaemia.

    The specific objectives are to: - collect data at the national level which will allow the calculation of key demographic rates; - analyze the direct and indirect factors which determine the level and trends of fertility; - measure the level of contraceptive knowledge and practice of women and men by method, urban-rural residence, and region; - collect high quality data on family health including immunization coverage among children, prevalence and treatment of diarrhoea and other diseases among children under five, and maternity care indicators including antenatal visits and assistance at delivery; - collect data on infant and child mortality and maternal and adult mortality; - obtain data on child feeding practices including breastfeeding and collect anthropometric measures to use in assessing the nutritional status of women and children; - collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; - conduct haemoglobin testing on women age 15-49 and children under age five years in a subsample of the households selected for the survey to provide information on the prevalence of anaemia among women in the reproductive ages and young children; - collect samples for anonymous HIV testing from women and men in the reproductive ages to provide information on the prevalence of HIV among the adult population.

    This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2005 Ethiopia DHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first ever Demographic and Health Survey (DHS) in Ethiopia was conducted in the year 2000 as part of the worldwide DHS programme. Data from the 2005 Ethiopia DHS survey, the second such survey, add to the vast and growing international database on demographic and health variables.

    Wherever possible, the 2005 EDHS data is compared with data from the 2000 EDHS. In addition, where applicable, the 2005 EDHS is compared with the 1990 NFFS, which also sampled women age 15-49. Husbands of currently married women were also covered in this survey. However, for security and other reasons, the NFFS excluded from its coverage Eritrea, Tigray, Asseb, and Ogaden autonomous regions. In addition, fieldwork could not be carried out for Northern Gondar, Southern Gondar, Northern Wello, and Southern Wello due to security reasons. Thus, any comparison between the EDHS and the NFFS has to be interpreted with caution.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Children under five years
    • Women age 15-49
    • Men age 15-59

    Kind of data

    Sample survey data

    Sampling procedure

    The 2005 EDHS sample was designed to provide estimates for the health and demographic variables of interest for the following domains: Ethiopia as a whole; urban and rural areas of Ethiopia (each as a separate domain); and 11 geographic areas (9 regions and 2 city administrations), namely: Tigray; Affar; Amhara; Oromiya; Somali; Benishangul-Gumuz; Southern Nations, Nationalities and Peoples (SNNP); Gambela; Harari; Addis Ababa and Dire Dawa. In general, a DHS sample is stratified, clustered and selected in two stages. In the 2005 EDHS a representative sample of approximately 14,500 households from 540 clusters was selected. The sample was selected in two stages. In the first stage, 540 clusters (145 urban and 395 rural) were selected from the list of enumeration areas (EA) from the 1994 Population and Housing Census sample frame.

    In the census frame, each of the 11 administrative areas is subdivided into zones and each zone into weredas. In addition to these administrative units, each wereda was subdivided into convenient areas called census EAs. Each EA was either totally urban or rural and the EAs were grouped by administrative wereda. Demarcated cartographic maps as well as census household and population data were also available for each census EA. The 1994 Census provided an adequate frame for drawing the sample for the 2005 EDHS. As in the 2000 EDHS, the 2005 EDHS sampled three of seven zones in the Somali Region (namely, Jijiga, Shinile and Liben). In the Affar Region the incomplete frame used in 2000 was improved adding a list of villages not previously included, to improve the region's representativeness in the survey. However, despite efforts to cover the settled population, there may be some bias in the representativeness of the regional estimates for both the Somali and Affar regions, primarily because the census frame excluded some areas in these regions that had a predominantly nomadic population.

    The 540 EAs selected for the EDHS are not distributed by region proportionally to the census population. Thus, the sample for the 2005 EDHS must be weighted to produce national estimates. As part of the second stage, a complete household listing was carried out in each selected cluster. The listing operation lasted for three months from November 2004 to January 2005. Between 24 and 32 households from each cluster were then systematically selected for participation in the survey.

    Because of the way the sample was designed, the number of cases in some regions appear small since they are weighted to make the regional distribution nationally representative. Throughout this report, numbers in the tables reflect weighted numbers. To ensure statistical reliability, percentages based on 25 to 49 unweighted cases are shown in parentheses and percentages based on fewer than 25 unweighted cases are suppressed.

    Note: See detailed sample implementation table in APPENDIX A of the survey report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    In order to adapt the standard DHS core questionnaires to the specific socio-cultural settings and needs in Ethiopia, its contents were revised through a technical committee composed of senior and experienced demographers of PHCCO. After the draft questionnaires were prepared in English, copies of the household, women’s and men’s questionnaires were distributed to relevant institutions and individual researchers for comments. A one-day workshop was organized on November 22, 2004 at the Ghion Hotel in Addis Ababa to discuss the contents of the questionnaire. Over 50 participants attended the national workshop and their comments and suggestions collected. Based on these comments, further revisions were made on the contents of the questionnaires. Some additional questions were included at the request of MOH, the Fistula Hospital, and USAID. The questionnaires were finalized in English and translated into the three main local languages: Amharic, Oromiffa and Tigrigna. In addition, the DHS core interviewer’s manual for the Women’s and Men’s Questionnaires, the supervisor’s and editor’s manual, and the HIV and anaemia field manual were modified and translated into Amharic.

    The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was used to record height and weight measurements of women age 15-49 and children under the age of five, households eligible for collection of blood samples, and the respondents’ consent to voluntarily give blood samples.

    The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics. - Household and respondent characteristics - Fertility levels and preferences - Knowledge and use of family planning - Childhood mortality - Maternity care - Childhood illness, treatment, and preventative actions - Anaemia levels among women and children - Breastfeeding practices - Nutritional status of women and young children - Malaria prevention and treatment - Marriage and sexual activity - Awareness and behaviour regarding AIDS and STIs - Harmful traditional practices - Maternal mortality

    The Men’s Questionnaire was administered to all men age 15-59 years living in every second household in the sample. The Men’s Questionnaire collected similar information contained in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive

  6. Prevalence of undernutrition, Ethiopia Demographic and Health Survey (EDHS),...

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    xls
    Updated Jun 1, 2023
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    Habtamu Kebebe Kasaye; Firew Tekle Bobo; Mekdes Tigistu Yilma; Mirkuzie Woldie (2023). Prevalence of undernutrition, Ethiopia Demographic and Health Survey (EDHS), 2016 (N = 9,464). [Dataset]. http://doi.org/10.1371/journal.pone.0225996.t002
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    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Habtamu Kebebe Kasaye; Firew Tekle Bobo; Mekdes Tigistu Yilma; Mirkuzie Woldie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Prevalence of undernutrition, Ethiopia Demographic and Health Survey (EDHS), 2016 (N = 9,464).

  7. f

    The individual level characteristics of 6–23 months age children in...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Aberash Abay Tassew; Dejen Yemane Tekle; Abate Bekele Belachew; Beyene Meressa Adhena (2023). The individual level characteristics of 6–23 months age children in Ethiopia, EDHS 2016(n = 2919). [Dataset]. http://doi.org/10.1371/journal.pone.0203098.t002
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    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Aberash Abay Tassew; Dejen Yemane Tekle; Abate Bekele Belachew; Beyene Meressa Adhena
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    The individual level characteristics of 6–23 months age children in Ethiopia, EDHS 2016(n = 2919).

  8. f

    Frequency of individual-level and community-level factors in EMDHS (2019),...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Oct 9, 2024
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    Mulu Tiruneh; Aragaw Tesfaw; Melkalem Mamuye; Desalegn Tesfa; Getaneh Atikilt; Asaye Alamneh Gebeyehu; Wondwosen Teshager (2024). Frequency of individual-level and community-level factors in EMDHS (2019), Ethiopia (n = 4306). [Dataset]. http://doi.org/10.1371/journal.pone.0311700.t001
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    Dataset updated
    Oct 9, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Mulu Tiruneh; Aragaw Tesfaw; Melkalem Mamuye; Desalegn Tesfa; Getaneh Atikilt; Asaye Alamneh Gebeyehu; Wondwosen Teshager
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Frequency of individual-level and community-level factors in EMDHS (2019), Ethiopia (n = 4306).

  9. f

    Predictors of women’s decision to place of delivery among women with a live...

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    xls
    Updated Jun 3, 2023
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    Henock Yebyo; Mussie Alemayehu; Alemayehu Kahsay (2023). Predictors of women’s decision to place of delivery among women with a live birth five years preceding the 2011 EDHS, Ethiopia. [Dataset]. http://doi.org/10.1371/journal.pone.0124718.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Henock Yebyo; Mussie Alemayehu; Alemayehu Kahsay
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Predictors of women’s decision to place of delivery among women with a live birth five years preceding the 2011 EDHS, Ethiopia.

  10. d

    Rank likelihood-based estimation of low birth weight in Ethiopia

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    • data.niaid.nih.gov
    • +1more
    Updated Mar 29, 2024
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    Daniel Biftu Bekalo (2024). Rank likelihood-based estimation of low birth weight in Ethiopia [Dataset]. http://doi.org/10.5061/dryad.3j9kd51sg
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    Dataset updated
    Mar 29, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Daniel Biftu Bekalo
    Area covered
    Ethiopia
    Description

    Low birth weight is a significant risk factor associated with high rates of neonatal and infant mortality, particularly in developing countries. However, most studies conducted on this topic in Ethiopia have small sample sizes, often focusing on specific areas and using standard models employing maximum likelihood estimation, leading to potential bias and inaccurate coverage probability. This study used a novel approach, the Bayesian rank likelihood method, within a latent traits model, to estimate parameters and provide a nationwide estimate of low birth weight and its risk factors in Ethiopia. Data from the Ethiopian Demographic and Health Survey (EDHS) of 2016 were used as a data source for the study. Data stratified all regions into urban and rural areas. Among 15, 680 representative selected households, the analysis included complete cases from 10, 641 children. The evaluation of model performance considered metrics such as the root mean square error, the mean absolute error, and t..., , , # Rank likelihood-based estimation of low birth weight in Ethiopia

    Low birth weight data was obtained from the Ethiopian Demographic and Health Survey (EDHS).

    Raw data: Lowbirthweight.sav

    Description of the data and file structure

    Lowbirthweightdata_data

    childweight: categorical weight of the child at birth motherage: age of the mothers ancvisti: number of antenatal care visits that the mothers attended birthorder: order of birth for the child birthinterval: time between successive births (months) bmi: body mass index of the mothers Regions: the region where the child born CLID: cluster-level ID that indicates from which cluster the information is obtained

    Sharing or accessing information

    Our data is taken from the DHS website (http://dhsprogram.com. Low birth weight data was extracted from the 2016 EDHS. EDHS 2016 was conducted using standardized survey design and data collection procedures.

  11. WASH facilities and prevalence of child growth failure indicators, 2016 EDHS...

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    Updated Jun 3, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). WASH facilities and prevalence of child growth failure indicators, 2016 EDHS (weighted n = 11023). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    WASH facilities and prevalence of child growth failure indicators, 2016 EDHS (weighted n = 11023).

  12. f

    Association between individual and combined access to WASH and wasting among...

    • plos.figshare.com
    xls
    Updated Jun 14, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). Association between individual and combined access to WASH and wasting among children 0–59 months of age, EDHS 2016 (n = 9607). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association between individual and combined access to WASH and wasting among children 0–59 months of age, EDHS 2016 (n = 9607).

  13. f

    Individual and community level characteristics of women who had live births...

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    xls
    Updated Jun 21, 2023
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    Mukemil Awol; Dejene Edosa; Kemal Jemal (2023). Individual and community level characteristics of women who had live births in the last five years preceding (EDHS) 2019, Ethiopia. [Dataset]. http://doi.org/10.1371/journal.pone.0279167.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mukemil Awol; Dejene Edosa; Kemal Jemal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Individual and community level characteristics of women who had live births in the last five years preceding (EDHS) 2019, Ethiopia.

  14. Association between individual and combined access to WASH and stunting...

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    xls
    Updated Jun 6, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). Association between individual and combined access to WASH and stunting among children 0–59 months of age, EDHS 2016 (n = 9588). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association between individual and combined access to WASH and stunting among children 0–59 months of age, EDHS 2016 (n = 9588).

  15. f

    Association between individual and combined access to WASH and being...

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    xls
    Updated May 31, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). Association between individual and combined access to WASH and being underweight among children 0–59 months of age, EDHS 2016 (n = 9752). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association between individual and combined access to WASH and being underweight among children 0–59 months of age, EDHS 2016 (n = 9752).

  16. f

    Socio-demographic and economic characteristics of respondents included in...

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    xls
    Updated Jun 2, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). Socio-demographic and economic characteristics of respondents included in the analysis, 2016 EDHS (n = 11023). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Socio-demographic and economic characteristics of respondents included in the analysis, 2016 EDHS (n = 11023).

  17. f

    Maternal characteristics result of respondents in 2016 EDHS, Ethiopia.

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Berihun Bantie; Gebrie Kassaw Yirga; Yeshiambaw Eshetie Ayenew; Ahmed Nuru Muhamed; Sheganew Fetene Tassew; Yohannes Tesfahun Kassie; Chalie Marew Tiruneh; Natnael Moges; Binyam Minuye Birhane; Denekew Tenaw Anley; Rahel Mulatie Anteneh; Anteneh Mengist Dessie (2023). Maternal characteristics result of respondents in 2016 EDHS, Ethiopia. [Dataset]. http://doi.org/10.1371/journal.pone.0279967.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Berihun Bantie; Gebrie Kassaw Yirga; Yeshiambaw Eshetie Ayenew; Ahmed Nuru Muhamed; Sheganew Fetene Tassew; Yohannes Tesfahun Kassie; Chalie Marew Tiruneh; Natnael Moges; Binyam Minuye Birhane; Denekew Tenaw Anley; Rahel Mulatie Anteneh; Anteneh Mengist Dessie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Maternal characteristics result of respondents in 2016 EDHS, Ethiopia.

  18. Child and maternal characteristics from univariable analyses (n = 11023).

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne (2023). Child and maternal characteristics from univariable analyses (n = 11023). [Dataset]. http://doi.org/10.1371/journal.pone.0239313.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Tolesa Bekele; Bayzidur Rahman; Patrick Rawstorne
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Child and maternal characteristics from univariable analyses (n = 11023).

  19. f

    Socio-demographic, obstetric and community-level characteristics of women in...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 3, 2023
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    Reta Dewau; Amare Muche; Zinabu Fentaw; Melaku Yalew; Gedamnesh Bitew; Erkihun Tadesse Amsalu; Mastewal Arefaynie; Asnakew Molla Mekonen (2023). Socio-demographic, obstetric and community-level characteristics of women in Ethiopia, EDHS 2016. [Dataset]. http://doi.org/10.1371/journal.pone.0246349.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Reta Dewau; Amare Muche; Zinabu Fentaw; Melaku Yalew; Gedamnesh Bitew; Erkihun Tadesse Amsalu; Mastewal Arefaynie; Asnakew Molla Mekonen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    Socio-demographic, obstetric and community-level characteristics of women in Ethiopia, EDHS 2016.

  20. f

    The socio-demography characteristics of 15–59 years old men in Ethiopia: The...

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    bin
    Updated Sep 21, 2023
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    Kirubel Dagnaw Tegegne; Moges Muluneh Boke; Asres Zegeye Lakew; Natnael Atnafu Gebeyehu; Mesfin Wudu Kassaw (2023). The socio-demography characteristics of 15–59 years old men in Ethiopia: The 2016 EDHS source-based study. [Dataset]. http://doi.org/10.1371/journal.pone.0290415.t001
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    binAvailable download formats
    Dataset updated
    Sep 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kirubel Dagnaw Tegegne; Moges Muluneh Boke; Asres Zegeye Lakew; Natnael Atnafu Gebeyehu; Mesfin Wudu Kassaw
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ethiopia
    Description

    The socio-demography characteristics of 15–59 years old men in Ethiopia: The 2016 EDHS source-based study.

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Central Statistical Agency (CSA) (2021). Mini Demographic and Health Survey 2019 - Ethiopia [Dataset]. https://microdata.worldbank.org/index.php/catalog/3946
Organization logo

Mini Demographic and Health Survey 2019 - Ethiopia

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 11, 2021
Dataset provided by
Central Statistical Agencyhttps://ess.gov.et/
Federal Ministry of Health (FMoH)
Ethiopian Public Health Institute (EPHI)
Time period covered
2019
Area covered
Ethiopia
Description

Abstract

The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is a nationwide survey with a nationally representative sample of 9,150 selected households. All women age 15-49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In the selected households, all children under age 5 were eligible for height and weight measurements. The survey was designed to produce reliable estimates of key indicators at the national level as well as for urban and rural areas and each of the 11 regions in Ethiopia.

The primary objective of the 2019 EMDHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the main objectives of the survey are: ▪ To collect high-quality data on contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; child nutrition; and other health issues relevant to achievement of the Sustainable Development Goals (SDGs) ▪ To collect information on health-related matters such as breastfeeding, maternal and child care (antenatal, delivery, and postnatal), children’s immunizations, and childhood diseases ▪ To assess the nutritional status of children under age 5 by measuring weight and height

Geographic coverage

National coverage

Analysis unit

  • Household
  • Individual
  • Children age 0-5
  • Woman age 15-49
  • Health facility

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019 EMDHS is a frame of all census enumeration areas (EAs) created for the 2019 Ethiopia Population and Housing Census (EPHC) and conducted by the Central Statistical Agency (CSA). The census frame is a complete list of the 149,093 EAs created for the 2019 EPHC. An EA is a geographic area covering an average of 131 households. The sampling frame contains information about EA location, type of residence (urban or rural), and estimated number of residential households.

Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2019 EMDHS 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 2019 EMDHS 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.

To ensure that survey precision was comparable across regions, sample allocation was done through an equal allocation wherein 25 EAs were selected from eight regions. However, 35 EAs were selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR).

In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size (based on the 2019 EPHC frame) and with independent selection in each sampling stratum. A household listing operation was carried out in all selected EAs from January through April 2019. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs for the 2019 EMDHS were large, with more than 300 households. To minimise the task of household listing, each large EA selected for the 2019 EMDHS was segmented. Only one segment was selected for the survey, with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2019 EMDHS cluster is either an EA or a segment of an EA.

In the second stage of selection, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who slept in the household the night before the survey were eligible to be interviewed. In all selected households, height and weight measurements were collected from children age 0-59 months, and women age 15-49 were interviewed using the Woman’s Questionnaire.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019 EMDHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Anthropometry Questionnaire, (4) the Health Facility Questionnaire, and (5) the Fieldworker’s Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. They were shortened substantially to collect data on indicators of particular relevance to Ethiopia and donors to child health programmes.

Cleaning operations

All electronic data files were transferred via the secure internet file streaming system (IFSS) to the EPHI 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 open-ended questions. The data were processed by EPHI staff members and an ICF consultant who took part in the main fieldwork training. They were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro System software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing, double data entry from both the anthropometry and health facility questionnaires, and data processing were initiated in April 2019 and completed in July 2019.

Response rate

A total of 9,150 households were selected for the sample, of which 8,794 were occupied. Of the occupied households, 8,663 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 9,012 eligible women were identified for individual interviews; interviews were completed with 8,885 women, yielding a response rate of 99%. Overall, there was little variation in response rates according to residence; however, rates were slightly higher in rural than in urban areas.

Sampling error estimates

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 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) 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 2019 EMDHS 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 2019 EMDHS 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 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.

Data appraisal

Data Quality Tables

  • Household age distribution

- Age distribution of eligible and interviewed women

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