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). 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.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59
• Health facility

Universe

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.

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.

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

Mode of data collection

Face-to-face [f2f]

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.

Cleaning operations

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.

Response rate

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.

Sampling error estimates

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 appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar

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

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

The principal objective of the Ethiopia Demographic and Health Survey (DHS) is to provide current and reliable data on fertility and family planning behavior, child mortality, children’s nutritional status, the utilization of maternal and child health services, and knowledge of HIV/AIDS. 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 Authority to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2000 Ethiopia DHS is the first survey of its kind in the country to provide national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. As part of the worldwide DHS project, the Ethiopia DHS data add to the vast and growing international database on demographic and health variables. The Ethiopia DHS collected demographic and health information from a nationally representative sample of women and men in the reproductive age groups 15-49 and 15-59, respectively. The Ethiopia DHS was carried out under the aegis of the Ministry of Health and was implemented by the Central Statistical Authority. ORC Macro provided technical assistance through its MEASURE DHS+ project. The survey was principally funded by the Essential Services for Health in Ethiopia (ESHE) project through a bilateral agreement between the United States Agency for International Development (USAID) and the Federal Democratic Republic of Ethiopia. Funding was also provided by the United Nations Population Fund (UNFPA).

Contains data from the DHS data portal. There is also a dataset containing Ethiopia - National Demographic and Health Data on HDX.

The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.

Abstract

The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is the second Mini Demographic and Health Survey conducted in Ethiopia. The Ethiopian Public Health Institute (EPHI) implemented the survey at the request of the Federal Ministry of Health (FMoH). Data collection took place from March 21, 2019, to June 28, 2019.

Financial support for the 2019 EMDHS was provided by the government of Ethiopia, the World Bank via the Ministry of Finance and Economic Development’s Enhancing Shared Prosperity through Equitable Services (ESPES) and Promoting Basic Services (PBS) projects, the United Nations Children’s Fund (UNICEF), and the United States Agency for International Development (USAID). ICF provided technical assistance through The DHS Program, which is funded by USAID and offers support and technical assistance for the implementation of population and health surveys in countries worldwide.

SURVEY OBJECTIVES 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 immunisations, and childhood diseases - To assess the nutritional status of children under age 5 by measuring weight and height

Four full-scale DHS surveys were conducted in 2000, 2005, 2011, and 2016. The first Ethiopia Mini-DHS, or EMDHS, was conducted in 2014. The 2019 EMDHS provides valuable information on trends in key demographic and health indicators over time. The information collected through the 2019 EMDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country's population.

Geographic coverage

National coverage

Analysis unit

Households Women age 15-49 Children age 0-59 months

Universe

Household members Woman aged 15-49 years Children aged 0-59 months

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.

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.

Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After the questionnaires were finalised in English, they were translated into Amarigna, Tigrigna, and Afaan Oromo.

The Household Questionnaire was used to list all of the usual 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, education, and relationship to the head of the household. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women who were eligible for individual interviews. The Household Questionnaire was also used to collect information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the dwelling unit, and ownership of various durable goods.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following main topics: background characteristics, reproduction, contraception, pregnancy and postnatal care, child nutrition, childhood immunisations, and health facility information.

In the Anthropometry Questionnaire, height and weight measurements were recorded for eligible children age 0-59 months in all interviewed households.

The Health Facility Questionnaire was used to record vaccination information for all children without a vaccination card seen during the mother’s interview.

The Fieldworker’s Questionnaire collected background information about interviewers and other fieldworkers who participated in the 2019 EMDHS data collection.

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.

Multilevel logistic regression analysis of individual and community-level factors associated with CBHI enrollment in Ethiopia.

BackgroundUtilization of modern contraceptives is a common healthcare challenge in Ethiopia. Prevalence of modern contraception utilization is varying across different regions. Therefore, this study aimed to investigate Geographic weighted regression analysis of hotspots of modern contraceptive utilization and its associated factors in Ethiopia, using Ethiopian Demographic and Health Survey 2016 data.MethodsBased on the 2016 Ethiopian Demographic Health Survey data, a total weighted sample of 8,673 women was included in this study. For the Geographic Weighted Regression analysis, Arc-GIS version 10.7 and SaTScan version 9.6, statistical software was used. Spatial regression was done to identify factors associated with the hotspots of modern contraceptive utilization and model comparison was carried out using adjusted R2 and AICc. Variables with a p-value < 0.25 in the bi-variable analysis were considered for the multivariable analysis. Multilevel robust Poisson regression analysis was fitted for associated factors since the prevalence of modern contraceptive was >10%. In the multilevel robust Poisson regression analysis, the adjusted prevalence ratio with the 95% confidence interval was reported to declare the statistical significance and strength of association.ResultThe prevalence of modern contraceptive utilization in Ethiopia was 37.25% (95% CI: 36.23%, 38.27%). Most of the hotspot areas were located in Oromia and Amhara regions, followed by the SNNPR region and Addis Ababa City administration. Single Women, poor Women, and more fertility preference were significant predictors of hotspots areas of modern contraceptive utilization. In the multivariable multilevel robust Poisson regression analysis, Women aged 25–34 years (APR = 0.88, 95% CI: 0.79, 0.98), 35–49 years (APR = 0.71, 95% CI: 0.61, 0.83), married marital status (APR = 2.59, 95% CI: 2.18, 3.08), Others religions (APR = 0.76, 95% CI: 0.65, 0.89), number of children 1–4 (APR = 1.18, 95% CI: 1.02, 1.37), no more fertility preference (APR = 1.21, 95% CI: 1.11, 1.32), Afar, Somali, Harari, and Dire Dawa: (APR = 0.42, 95% CI: 0.27, 0.67), (APR = 0.06, 95% CI: 0.03, 0.12), (APR = 0.78, 95% CI: 0.62, 0.98), and (APR = 0.75, 95% CI: 0.58, 0.98), respectively. Amhara region (APR = 1.34, 95% CI: 1.13, 1.57), rural residence (APR = 0.80, 95% CI: 0.67, 0.95) High community wealth index (APR = 0.78, 95% CI: 0.67, 0.91) were significantly associated with modern contraceptive utilization.Conclusion and recommendationThere were significant spatial variations of factors affecting modern contraceptive use across regions in Ethiopia. Therefore, public health interventions targeting areas with low modern contraceptive utilization will help to increase modern contraception use considering significant factors at individual and community levels.The detailed map of modern contraceptive use cold spots among reproductive age group and its predictors could assist program planners and decision-makers to design targeted public health interventions.Government of Ethiopia must develop more geographic targeted strategies for improving socioeconomic status of women and availability & accessibility of health facilities in rural areas of the countries.

Characteristics of community level factors of CBHI enrollment, Mini-EDHS 2019.

Abstract

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.

Geographic coverage

A nationally representative sample of 17,817 households was selected.

Universe

All women 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the survey. A male survey was also conducted. All men 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the male survey.

Kind of data

Sample survey data

Sampling procedure

The sample for the 2011 EDHS was designed to provide population and health indicators at the national (urban and rural) and regional levels. The sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of Ethiopia's 11 geographic/administrative regions (the nine regional states and two city administrations). The 2007 Population and Housing Census, conducted by the CSA, provided the sampling frame from which the 2011 EDHS sample was drawn.

Administratively, regions in Ethiopia are divided into zones, and zones, into administrative units called weredas. Each wereda is further subdivided into the lowest administrative unit, called kebele. During the 2007 census each kebele was subdivided into census enumeration areas (EAs), which were convenient for the implementation of the census. The 2011 EDHS sample was selected using a stratified, two-stage cluster design, and EAs were the sampling units for the first stage. The sample included 624 EAs, 187 in urban areas and 437 in rural areas.

Households comprised the second stage of sampling. A complete listing of households was carried out in each of the 624 selected EAs from September 2010 through January 2011. Sketch maps were drawn for each of the clusters, and all conventional households were listed. The listing excluded institutional living arrangements and collective quarters (e.g., army barracks, hospitals, police camps, and boarding schools). A representative sample of 17,817 households was selected for the 2011 EDHS. Because the sample is not self-weighting at the national level, all data in this report are weighted unless otherwise specified.

In the Somali region, in 18 of the 65 selected EAs listed households were not interviewed for various reasons, such as drought and security problems, and 10 of the 65 selected EAs were not listed due to security reasons. Therefore, the data for Somali may not be totally representative of the region as a whole. However, national-level estimates are not affected, as the percentage of the population in the EAs not covered in the Somali region is proportionally very small.

SAMPLING FRAME

The sampling frame used for 2011 EDHS is the Population and Housing Census (PHC) conducted in 2007 provided by the Central Statistical Agency (CSA, 2008). CSA has an electronic file consisting of 81,654 Enumeration Areas (EA) created for the 2007 census in 10 of its 11 geographic regions. An EA is a geographic area consisting of a convenient number of dwelling units which served as counting unit for the census. The frame file contains information about the location, the type of residence, and the number of residential households for each of the 81,654 EAs. Sketch maps are also available for each EA which delimitate the geographic boundaries of the EA. The 2007 PHC conducted in the Somali region used a different methodology due to difficulty of access. Therefore, the sampling frame for the Somali region is in a different file and in different format. Due to security concerns in the Somali region, in the beginning it was decided that 2011 EDHS would be conducted only in three of nine zones in the Somali region: Shinile, Jijiga, and Liben, same as in the 2000 and 2005 EDHS. However, a later decision was made to include three other zones: Afder, Gode and Warder. This was the first time that these three zones were included in a major nationwide survey such as the 2011 EDHS. The sampling frame for the 2011 EDHS consists of a total of 85,057 EAs.

The sampling frame excluded some special EAs with disputed boundaries. These EAs represent only 0.1% of the total population.

Ethiopia is divided into 11 geographical regions. Each region is sub-divided into zones, each zone into Waredas, each Wareda into towns, and each town into Kebeles. Among the 85,057 EAs, 17,548 (21 percent) are in urban areas and 67,509 (79 percent) are in rural areas. The average size of EA in number of households is 169 in an urban EA and 180 in a rural EA, with an overall average of 178 households per EA. Table A.2 shows the distributions of households in the sampling frame, by region and residence. The data show that 81 percent of the Ethiopia’s households are concentrated in three regions: Amhara, Oromiya and SNNP, while 4 percent of all households are in the five smallest regions: Afar, Benishangul-Gumuz, Gambela, Harari and Dire Dawa.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2011 EDHS used three questionnaires: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed for the MEASURE DHS project to reflect the population and health issues relevant to Ethiopia. Issues were identified at a series of meetings with the various stakeholders. In addition to English, the questionnaires were translated into three major languages—Amharigna, Oromiffa, and Tigrigna.

The Household Questionnaire was used to list all the usual members and visitors of selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on the age and sex of household members obtained in the Household Questionnaire were used 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 of the house, and ownership of various consumer

Percentage distribution of socio-demographic characteristics of respondents 2005, 2011, and 2016 Ethiopia Demographic and Health Surveys.

Socio demographic characteristics of respondents in health centers of Hadiya zone, Southern Ethiopia, 2018 [n = 291].

Ethiopia ET: Life Expectancy at Birth: Male data was reported at 63.617 Year in 2016. This records an increase from the previous number of 63.200 Year for 2015. Ethiopia ET: Life Expectancy at Birth: Male data is updated yearly, averaging 44.737 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 63.617 Year in 2016 and a record low of 36.974 Year in 1960. Ethiopia ET: Life Expectancy at Birth: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Ethiopia ET: Life Expectancy at Birth: Total data was reported at 65.475 Year in 2016. This records an increase from the previous number of 65.037 Year for 2015. Ethiopia ET: Life Expectancy at Birth: Total data is updated yearly, averaging 46.194 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 65.475 Year in 2016 and a record low of 38.419 Year in 1960. Ethiopia ET: Life Expectancy at Birth: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision, or derived from male and female life expectancy at birth from sources such as: (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Introduction: Conflict exacerbates poor complementary feeding and reduces dietary diversity. Before the 2020–2022 war in northern Ethiopia, around 74% of children aged 6–23 months failed to meet minimum dietary diversity (MDD) and post-war prevalence was unknown. This study aims to assess MDD prevalence and associated factors among children aged 6–23 months in a town in northern Ethiopia two years after the ceasefire. Methodology: A health facility-based cross-sectional study of 584 participants was conducted in a town in northern Ethiopia. Sociodemographic and dietary data were collected using a 24-hour dietary recall questionnaire and analyzed in STATA ® version 15. Pre-war dietary diversity was estimated using data from the 2016 and 2019 Ethiopian Demographic and Health Surveys. Results: MDD declined from 33.2% pre-war period to 25.2% (95% CI: 21.6-28.7) in the post-war period. Children aged 18–23 months were 2.8 times more likely to achieve MDD than those aged 6–11 months (p = 0.001..., Study Design and Population This study employed a facility-based cross-sectional design, conducted in late 2024, in a town in northern Ethiopia. The study population comprised mothers/caregivers with children aged 6–23 months who attended Extended Program on Immunization (EPI) services at one of three randomly selected health centers. Participants were recruited through random sampling. Data on sociodemographic characteristics and dietary intake were collected via face-to-face interviews using a pretested and standardized questionnaire. Study Setting This study was conducted in a town in northern Ethiopia two years after the end of the war in northern Ethiopia (2020-2022). The town, located in nothern Ethiopia, has an estimated population of 600,000 as of 2024. It is served by several hospitals and health centers. Study variables The outcome variable was Minimum Dietary Diversity (MDD), defined as the consumption of foods and beverages from at least five of eight defined food groups wit..., , # Postwar dietary diversity among children aged 6-23 months in northern Ethiopia

https://doi.org/10.5061/dryad.djh9w0w9p

Description of the data and file structure

This dataset was collected as part of a cross-sectional comparative study examining the impact of war on child malnutrition by assessing dietary diversity among children aged 6–23 months in northern Ethiopia. Data were obtained from caregiver-reported 24-hour dietary recalls across post-conflict (2024) periods. The study aimed to determine changes in minimum dietary diversity (MDD) prevalence and identify factors influencing child nutrition in a post-war setting. Data collection involved structured interviews in randomly selected health facilities, with additional sociodemographic and household characteristics recorded. The dataset includes nutritional intake, socioeconomic variables, and household composition to facilitate further analysis of war-related disruptions in infant ...

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Ethiopia ET: Life Expectancy at Birth: Female data was reported at 67.366 Year in 2016. This records an increase from the previous number of 66.907 Year for 2015. Ethiopia ET: Life Expectancy at Birth: Female data is updated yearly, averaging 47.720 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 67.366 Year in 2016 and a record low of 39.909 Year in 1960. Ethiopia ET: Life Expectancy at Birth: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Ethiopia ET: People Practicing Open Defecation: % of Population data was reported at 27.163 % in 2015. This records a decrease from the previous number of 30.585 % for 2014. Ethiopia ET: People Practicing Open Defecation: % of Population data is updated yearly, averaging 53.358 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 79.815 % in 2000 and a record low of 27.163 % in 2015. Ethiopia ET: People Practicing Open Defecation: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted Average;

Ethiopia ET: Improved Water Source: % of Population with Access data was reported at 57.300 % in 2015. This records an increase from the previous number of 55.400 % for 2014. Ethiopia ET: Improved Water Source: % of Population with Access data is updated yearly, averaging 33.600 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 57.300 % in 2015 and a record low of 13.200 % in 1990. Ethiopia ET: Improved Water Source: % of Population with Access data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Access to an improved water source refers to the percentage of the population using an improved drinking water source. The improved drinking water source includes piped water on premises (piped household water connection located inside the user’s dwelling, plot or yard), and other improved drinking water sources (public taps or standpipes, tube wells or boreholes, protected dug wells, protected springs, and rainwater collection).; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted average;

Abstract

The 2024 Standardized Expanded Nutrition Survey (SENS) was conducted in Mirqaan Refugee Camp, located in Bokh Woreda, Doolo Zone, Somali Region, Ethiopia. Established in April 2023, the camp hosts over 52,000 refugees and asylum seekers, primarily displaced by the conflict in Lascanood. The survey aimed to assess the nutritional and public health status of the camp population and inform targeted interventions. Using the SENS Version 3 guidelines and SMART methodology, data were collected through a simple random sample of households between January 25–27, 2024. Modules included anthropometry, child health, infant and young child feeding (IYCF), food security (administered to a 50% household sub-sample), demography, and mortality. Results indicate a critical nutrition situation, with a Global Acute Malnutrition (GAM) rate of 24.2% and Severe Acute Malnutrition (SAM) prevalence of 3.8%, both exceeding emergency thresholds. The survey also highlights suboptimal IYCF practices, limited vaccination coverage, and gaps in preventive nutrition programming. Findings underscore the urgent need for multisectoral support to restore and strengthen nutrition and health services in Mirqaan camp.

Geographic coverage

Mirqaan Refugee Camp, Bokh Woreda, Doolo Zone, Somali Region, Ethiopia.

Analysis unit

Household

Universe

Refugees and asylum seekers residing in Mirqaan Refugee Camp as of January 2024.

Kind of data

Sample survey data [ssd]

Sampling procedure

Simple random sampling was used in Mirqaan Refugee Camp. The sample size was calculated using ENA for SMART. A 10% non-response rate was assumed. Finite population correction was applied due to a small under-5 population. Household verification and labelling were conducted by OWDA prior to the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Standard SENS version 3 questionnaires were used, covering demographic, mortality, anthropometry, child health, IYCF, food security, and WASH modules.