Abstract

The first recorded cases of COVID 19 in São Tomé and Príncipe (STP) emerged on April 6, 2020. Since then, the Government has implemented strict measures to contain the spread of the virus. In addition, the closure of air space has drastically reduced air transport activities, making it difficult to carry out one of the most important activities in the country, which is Hotel and Catering (Tourism) as well as non-food trade activities.

The COVID-19 pandemic and its economic and social impacts on families have created an urgent need for up-to-date data to help monitor and mitigate the impacts of the crisis and protect the well-being of the least favored in STP society. To monitor how the COVID-19 pandemic affects STP’s economy and population and to substantiate response policies with data, the National Statistical Institute (INE), with technical support from the World Bank, has designed and conducted a telephone Household Monitoring Survey (HMS). With support from the United Nations, the survey was expanded to include a questionnaire aimed at informal businesses.

Geographic coverage

This survey included all districts: Lembá, Lobata, Água Grande, Me Zochi, Cantagalo, Cauê, and the Príncipe Autonomous Region (RAP).

Analysis unit

Household

Universe

Each round of the STP COVID-19 HMS has ONE RESPONDENT per household. The respondent was the household head or a knowledgeable adult household member. The respondent must be a member of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The STP COVID-19 HMS sample consists of a subsample of the Multiple Indicator Cluster Survey (MICS) carried out by INE in collaboration with UNICEF in 2019. Households with access to a telephone are represented in the HMS, covering urban and rural areas in all STP regions. The HMS called all households with a valid telephone number listed in MICS, completing 1,025 interviews (413 in rural areas and 612 in urban areas).

Among the 3,426 households interviewed in the MICS 2019, 1,400 (40.8%) provided at least one phone number. From these, 1,081 were successfully contacted by INE interviewers and 1,025 accepted and answered all the questions made in the first round of the HMS.

To mitigate bias in a sample that contains only households with a working telephone, a procedure for adjusting the sample weights was carried out using the Propensity Score Weighting (PSW) methodology. Following this procedure, the HMS results were brought closer to the national representativeness of surveys carried out in person, such as MICS 2019.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire is structured and available for download in Portuguese, under the Documentation tab.

Cleaning operations

Data Cleaning The data cleaning process was done in two main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork. The second stage of cleaning involved a comprehensive review of the final raw data following the first stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) formatting. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

Response rate

Sample size was 1,400 households, of which 1,025 completed the forms in full.

Abstract

The 2021-22 Cambodia Demographic and Health Survey (2021-22 CDHS) was implemented by the National Institute of Statistics (NIS) in collaboration with the Ministry of Health (MoH). Data collection took place from September 15, 2021, to February 15, 2022.

The primary objective of the 2021-22 CDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2021-22 CDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of Cambodia’s population. The survey also provides data on indicators relevant to the Sustainable Development Goals (SDGs) for Cambodia.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used in the 2021-22 CDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Cambodia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

The processing of the 2021-22 CDHS data began as soon as the fieldwork started. When data collection was completed in each cluster, the electronic data files were transferred via the IFSS to the NIS central office in Phnom Penh. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary editing, done by NIS data processors, was carried out in the central office and included resolving inconsistencies and coding open-ended questions. The paper Biomarker Questionnaires were collected by field coordinators and then compared with the electronic data files to assess whether any inconsistencies arose during data entry. Data processing and editing were carried out using the CSPro software package. The concurrent data collection and processing offered an advantage because it maximized the likelihood of the data being error-free. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in March 2022.

Response rate

A total of 21,270 households were selected for the CDHS sample, of which 20,967 were found to be occupied. Of the occupied households, 20,806 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 19,845 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 19,496 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 9,079 men age 15-49 were identified as eligible for individual interviews and 8,825 were successfully interviewed, yielding a response rate of 97%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are errors that were made during data collection and data processing such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2021-22 Cambodia Demographic and Health Survey (CDHS) to minimize this type of error, nonsampling errors are impossible to eliminate completely and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2021-22 CDHS is only one of many possible samples that could have been selected from the same population, using exactly the same design. 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.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% 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 2021-22 CDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2021-22 CDHS was an SAS program. This program used the Taylor linearization method for estimate variances for survey estimates that are means or proportions. 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 report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in anthropometric measurements for children (digit preference)
• Observation of handwashing facility
• School attendance by single-year age
• Vaccination cards photographed
• Number of enumeration areas completed by month and province
• Sibship size and sex ratio of siblings
• Pregnancy-related mortality trends
• Pregnancy-related mortality

See details of the data quality tables in Appendix C of the final report.

Abstract

The 2023 Tajikistan Demographic and Health Survey (TjDHS) is the third Demographic and Health Survey conducted in Tajikistan. The primary objective of the 2023 TjDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility and contraceptive use, maternal and child health and nutrition, childhood mortality, domestic violence against women, child discipline, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2023 TjDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Tajikistan.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2023 TjDHS is the 2020 Tajikistan Population and Housing Census (TPHC), conducted by Tajstat. Administratively, Tajikistan is divided into five administrative regions: Dushanbe City, Districts of Republican Subordination (DRS), Sughd, Khatlon, and Gorno-Badakhshan Autonomous Oblast (GBAO). Each region is subdivided into urban and rural areas. The country is divided into 68 cities and rayons (districts) distributed over the country’s regions. Each city or rayon (district) is further divided into census divisions, which are subdivided into instruction areas. Each instruction area is divided into enumeration areas (EAs).

The 2023 TjDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were drawn with a probability proportional to their size within each sampling stratum. A total of 370 clusters were selected, 166 in urban areas and 204 in rural areas. The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 22 households per cluster were selected through an equal probability systematic selection process, for a total sample size of approximately 8,140 households.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Hemoglobin testing was performed in each household among eligible women age 15-49 who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anemia in each household. Height and weight information was collected from eligible women age 15-49 and children age 0-59 months in all households. Also, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence.

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

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Three questionnaires were used in the 2023 TjDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Tajikistan. Suggestions were solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Russian and Tajik.

Cleaning operations

The 2023 TjDHS used a Windows-based system. All electronic data files were transferred via a secure SyncCloud server to the Tajstat central office in Dushanbe, 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 five IT specialists/secondary editors who took part in the main fieldwork training, the training of trainers, and a refresher secondary editing training session; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in December 2023 and completed in February 2024.

Response rate

A total of 8,140 households were selected for the TjDHS sample, of which 8,070 were found to be occupied. Of the occupied households, 8,035 were successfully interviewed, yielding a response rate of over 99%. In the interviewed households, 9,930 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 9,879 women, yielding a response rate of over 99%.

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 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 2023 Tajikistan Demographic and Health Survey (2023 TjDHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2023 TjDHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2023 TjDHS sample was the result of a multistage stratified cluster design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS 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.

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 - Age displacement at age 14/15 - Age displacement at age 49/50 - Pregnancy outcomes by years preceding the survey - Completeness of reporting - Standardization exercise results from anthropometry training - Height and weight data completeness and quality for children - Height measurements from random subsample of measured children - Interference in height and weight measurements of children - Interference in height and weight measurements of women - Heaping in anthropometric measurements for children (digit preference) - Observation of handwashing facility - School attendance by single year of age - Vaccination cards photographed - Prevalence of anemia in children based on 2011 WHO guidelines - Prevalence of anemia in women based on 2011 WHO guidelines - Population pyramid - Five-year mortality rates See details of the data quality tables in Appendix C of the final report.

These data are from the 2013 California Dietary Practices Surveys (CDPS), 2012 California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and 2013 California Children’s Healthy Eating and Exercise Practices Surveys (CalCHEEPS). These surveys have been discontinued. Adults, adolescents, and children (with parental assistance) were asked for their current height and weight, from which, body mass index (BMI) was calculated. For adults, a BMI of 30.0 and above is considered obese. For adolescents and children, obesity is defined as having a BMI at or above the 95th percentile, according to CDC growth charts.

The California Dietary Practices Surveys (CDPS), the California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and the California Children’s Healthy Eating and Exercise Practices Surveys (CalCHEEPS) (now discontinued) were the most extensive dietary and physical activity assessments of adults 18 years and older, adolescents 12 to 17, and children 6 to 11, respectively, in the state of California. CDPS and CalCHEEPS were administered biennially in odd years up through 2013 and CalTEENS was administered biennially in even years through 2014. The surveys were designed to monitor dietary trends, especially fruit and vegetable consumption, among Californias for evaluating their progress toward meeting the Dietary Guidelines for Americans and the Healthy People 2020 Objectives. All three surveys were conducted via telephone. Adult and adolescent data were collected using a list of participating CalFresh households and random digit dial, and child data were collected using only the list of CalFresh households. Older children (9-11) were the primary respondents with some parental assistance. For younger children (6-8), the primary respondent was parents. Data were oversampled for low-income and African American to provide greater sensitivity for analyzing trends among the target population. Wording of the question used for these analyses varied by survey (age group). The questions were worded are as follows: Adult:1) How tall are you without shoes?2) How much do you weigh?Adolescent:1) About how much do you weigh without shoes?2) About how tall are you without shoes? Child:1) How tall is [child's name] now without shoes on?2) How much does [child's name] weigh now without shoes on?

Overview

The Associated Press is sharing data from the COVID Impact Survey, which provides statistics about physical health, mental health, economic security and social dynamics related to the coronavirus pandemic in the United States.

Conducted by NORC at the University of Chicago for the Data Foundation, the probability-based survey provides estimates for the United States as a whole, as well as in 10 states (California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon and Texas) and eight metropolitan areas (Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix and Pittsburgh).

The survey is designed to allow for an ongoing gauge of public perception, health and economic status to see what is shifting during the pandemic. When multiple sets of data are available, it will allow for the tracking of how issues ranging from COVID-19 symptoms to economic status change over time.

The survey is focused on three core areas of research:

• Physical Health: Symptoms related to COVID-19, relevant existing conditions and health insurance coverage.
• Economic and Financial Health: Employment, food security, and government cash assistance.
• Social and Mental Health: Communication with friends and family, anxiety and volunteerism. (Questions based on those used on the U.S. Census Bureau’s Current Population Survey.) ## Using this Data - IMPORTANT This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use our queries linked below or statistical software such as R or SPSS to weight the data.

Queries

If you'd like to create a table to see how people nationally or in your state or city feel about a topic in the survey, use the survey questionnaire and codebook to match a question (the variable label) to a variable name. For instance, "How often have you felt lonely in the past 7 days?" is variable "soc5c".

Nationally: Go to this query and enter soc5c as the variable. Hit the blue Run Query button in the upper right hand corner.

Local or State: To find figures for that response in a specific state, go to this query and type in a state name and soc5c as the variable, and then hit the blue Run Query button in the upper right hand corner.

The resulting sentence you could write out of these queries is: "People in some states are less likely to report loneliness than others. For example, 66% of Louisianans report feeling lonely on none of the last seven days, compared with 52% of Californians. Nationally, 60% of people said they hadn't felt lonely."

Margin of Error

The margin of error for the national and regional surveys is found in the attached methods statement. You will need the margin of error to determine if the comparisons are statistically significant. If the difference is:

• At least twice the margin of error, you can report there is a clear difference.
• At least as large as the margin of error, you can report there is a slight or apparent difference.
• Less than or equal to the margin of error, you can report that the respondents are divided or there is no difference. ## A Note on Timing Survey results will generally be posted under embargo on Tuesday evenings. The data is available for release at 1 p.m. ET Thursdays.

About the Data

The survey data will be provided under embargo in both comma-delimited and statistical formats.

Each set of survey data will be numbered and have the date the embargo lifts in front of it in the format of: 01_April_30_covid_impact_survey. The survey has been organized by the Data Foundation, a non-profit non-partisan think tank, and is sponsored by the Federal Reserve Bank of Minneapolis and the Packard Foundation. It is conducted by NORC at the University of Chicago, a non-partisan research organization. (NORC is not an abbreviation, it part of the organization's formal name.)

Data for the national estimates are collected using the AmeriSpeak Panel, NORC’s probability-based panel designed to be representative of the U.S. household population. Interviews are conducted with adults age 18 and over representing the 50 states and the District of Columbia. Panel members are randomly drawn from AmeriSpeak with a target of achieving 2,000 interviews in each survey. Invited panel members may complete the survey online or by telephone with an NORC telephone interviewer.

Once all the study data have been made final, an iterative raking process is used to adjust for any survey nonresponse as well as any noncoverage or under and oversampling resulting from the study specific sample design. Raking variables include age, gender, census division, race/ethnicity, education, and county groupings based on county level counts of the number of COVID-19 deaths. Demographic weighting variables were obtained from the 2020 Current Population Survey. The count of COVID-19 deaths by county was obtained from USA Facts. The weighted data reflect the U.S. population of adults age 18 and over.

Data for the regional estimates are collected using a multi-mode address-based (ABS) approach that allows residents of each area to complete the interview via web or with an NORC telephone interviewer. All sampled households are mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Interviews are conducted with adults age 18 and over with a target of achieving 400 interviews in each region in each survey.Additional details on the survey methodology and the survey questionnaire are attached below or can be found at https://www.covid-impact.org.

Attribution

Results should be credited to the COVID Impact Survey, conducted by NORC at the University of Chicago for the Data Foundation.

AP Data Distributions

​To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

To adjust for underreporting of marijuana use, researchers multiply the proportion of individuals who reported using marijuana by a constant factor, such as the US Office of National Drug Control Policy’s 1.3. Although the current adjustments are simple, they do not account for changes in reporting over time. This article presents a novel way to explore relative changes in reporting from one survey to another simply by using data already available in a self-reported survey, the National Survey on Drug Use and Health. Using domain estimation to examine the stability in reported marijuana use by age 25 in individuals older than 25, this analysis provides estimates of the trends in marijuana reporting and standard errors, as long as the survey weights properly account for sampling variability. There was no significant evidence of an upward or downward trend in reporting changes from 1979 to 2016 for all birth cohorts, although there were significant differences in reporting between years and a slight downward trend in later years. These results suggest that individuals have become increasingly less willing to report their drug use in recent years, and thus the ONDCP likely underestimated the already drastic increase in use from 1992 to 2016.

Abstract

FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). FAO conducted a Round 3 household survey using computer-assisted telephone interviews from 17 July to 8 August 2022 to monitor agricultural livelihoods and food security in Lebanon. The survey targeted the agricultural population. It took place across 7 governorates –Akkar, Baalbeck El Hermel, Bekaa, El Nabatieh, North Lebanon, Mount Lebanon and South Lebanon– with 150 households selected in each governorate using probability proportional to size. A total of 1 050 interviews were completed, in which 98 percent of respondents identified as agricultural households. For more information: https://data-in-emergencies.fao.org/pages/monitoring.

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey targeted the rural population in Lebanon using remote panel data collection. Respondents were drawn from the Agricultural Production Survey (APS), which sampled individuals listed in the 2010 Agricultural Census. This approach was also supported by the Lebanese Ministry of Agriculture, which has been conducting a similar household tracking survey for the past 10 years. The survey used a one-stage sample design, drawing a Simple Random Sample with Probability Proportional to Size (PPS) from the agricultural population census. The sample was stratified by activity type and farm size using a genetic stratification algorithm (Ballin & Barcaroli1) to optimize homogeneity within strata and maximize sample efficiency. The APS sample size is larger than required for the monitoring survey, as APS stratifies at a more detailed level. Additionally, due to APS's stratification method, large specialized farms were overrepresented, requiring weighting adjustments to properly represent smaller farms and non-agricultural households. After review by the OER Needs Assessment team and ESS, it was confirmed that the APS sample could serve as a valid sampling frame, with households selected proportional to their assigned weights. The third round (July 2022) followed the same respondents as the first two rounds, creating an additional panel dimension. No quotas were set.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the DIEM team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

STATISTICAL DISCLOSURE CONTROL (SDC)

The dataset was anonymized using Statistical Disclosure methods by the Data in Emergencies Hub team and reviewed by the Statistics Division at FAO. All direct identifiers have been removed prior to data submission.

Abstract

The Jordan Population and Family Health Survey (JPFHS) is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 2012 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, and fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policymakers to evaluate and improve existing programs. The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 2012 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and for the two special domains: the Badia areas and people living in refugee camps. To facilitate comparisons with previous surveys, the sample was also designed to produce estimates for the three regions (North, Central, and South). The grouping of the governorates into regions is as follows: the North consists of Irbid, Jarash, Ajloun, and Mafraq governorates; the Central region consists of Amman, Madaba, Balqa, and Zarqa governorates; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba governorates.

The 2012 JPFHS sample was selected from the 2004 Jordan Population and Housing Census sampling frame. The frame excludes the population living in remote areas (most of whom are nomads), as well as those living in collective housing units such as hotels, hospitals, work camps, prisons, and the like. For the 2004 census, the country was subdivided into convenient area units called census blocks. For the purposes of the household surveys, the census blocks were regrouped to form a general statistical unit of moderate size (30 households or more), called a "cluster", which is widely used in surveys as a primary sampling unit (PSU).

Stratification was achieved by first separating each governorate into urban and rural areas and then, within each urban and rural area, by Badia areas, refugee camps, and other. A two-stage sampling procedure was employed. In the first stage, 806 clusters were selected with probability proportional to the cluster size, that is, the number of residential households counted in the 2004 census. A household listing operation was then carried out in all of the selected clusters, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the second stage of selection, a fixed number of 20 households was selected in each cluster with an equal probability systematic selection. A subsample of two-thirds of the selected households was identified for anthropometry measurements.

Refer to Appendix A in the final report (Jordan Population and Family Health Survey 2012) for details of sampling weights calculation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 JPFHS used two questionnaires, namely the Household Questionnaire and the Woman’s Questionnaire (see Appendix D). The Household Questionnaire was used to list all usual members of the sampled households, and visitors who slept in the household the night before the interview, and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of the household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. Moreover, the questionnaire included questions about child discipline. The Household Questionnaire was also used to identify women who were eligible for the individual interview (ever-married women age 15-49 years). In addition, all women age 15-49 and children under age 5 living in the subsample of households were eligible for height and weight measurement and anemia testing.

The Woman’s Questionnaire was administered to ever-married women age 15-49 and collected information on the following topics: • Respondent’s background characteristics • Birth history • Knowledge, attitudes, and practice of family planning and exposure to family planning messages • Maternal health (antenatal, delivery, and postnatal care) • Immunization and health of children under age 5 • Breastfeeding and infant feeding practices • Marriage and husband’s background characteristics • Fertility preferences • Respondent’s employment • Knowledge of AIDS and sexually transmitted infections (STIs) • Other health issues specific to women • Early childhood development • Domestic violence

In addition, information on births, pregnancies, and contraceptive use and discontinuation during the five years prior to the survey was collected using a monthly calendar.

The Household and Woman’s Questionnaires were based on the model questionnaires developed by the MEASURE DHS program. Additions and modifications to the model questionnaires were made in order to provide detailed information specific to Jordan. The questionnaires were then translated into Arabic.

Anthropometric data were collected during the 2012 JPFHS in a subsample of two-thirds of the selected households in each cluster. All women age 15-49 and children age 0-4 in these households were measured for height using Shorr height boards and for weight using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children in the field to measure their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Cleaning operations

Fieldwork and data processing activities overlapped. Data processing began two weeks after the start of the fieldwork. After field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman, where they were registered and stored. Special teams were formed to carry out office editing and coding of the openended questions.

Data entry and verification started after two weeks of office data processing. The process of data entry, including 100 percent reentry, editing, and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by early January 2013. A data processing specialist from ICF International made a trip to Jordan in February 2013 to follow up on data editing and cleaning and to work on the tabulation of results for the survey preliminary report, which was published in March 2013. The tabulations for this report were completed in April 2013.

Response rate

In all, 16,120 households were selected for the survey and, of these, 15,722 were found to be occupied households. Of these households, 15,190 (97 percent) were successfully interviewed.

In the households interviewed, 11,673 ever-married women age 15-49 were identified and interviews were completed with 11,352 women, or 97 percent of all eligible women.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) 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 2012 Jordan Population and Family Health Survey (JPFHS) 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 2012 JPFHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 JPFHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer

Abstract

The Tonga Multiple Indicator Cluster Survey (MICS) was conducted in 2019 by the Tonga Statistics Department in collaboration with Ministry of Health with technical support of Ministry of Internal Affairs – Women’s Affairs and Gender Equality Division (WAGED) and other key Government Ministries UNICEF, UNFPA, the Pacific Community (SPC) and other partners. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programs, and for monitoring progress toward national goals and global commitments.

The Tonga MICS 2019 has as its primary objectives: • To provide high quality data for assessing the situation of children, adolescents, women and households in Tonga; • To furnish data needed for monitoring progress toward national goals, as a basis for future action; • To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable; • To validate data from other sources and the results of focused interventions; • To generate data on national and global SDG indicators; • To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; • To generate behavioural and attitudinal data not available in other data sources.

Geographic coverage

National Coverage: covering rural-urban areas and the five district/island groups of the country (Tongatapu, Vava'u, Ha'apai, 'Eua and Ongo Niua).

Analysis unit

-Household; -Household member; -Women in reproductive age; -Birth history; -Men in reproductive age; -Mothers or primary caretakers of children under 5; -Mothers or primary caretakers of children age 5-17.

Universe

The survey covered all de jure household members (usual residents), all women aged between 15 to 49 years, all men aged between 15 to 49 years, all children under 5 and those aged 5 to 17 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

-SAMPLE DESIGN: The primary objective of the sample design for the Tonga MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the five divisions of the country: Tongatapu, Vavaú, Haápai, 'Eua and Ongo Niua. Urban and rural areas in each of the five divisions were defined as the sampling strata. In designing the sample for the Tonga MICS, it was useful to review the sample design and results of the Demographic and Health Survey conducted in 2012, documented in the Final Report of that survey. A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The sampling frame was based on the 2016 Tonga Census of Population and Housing. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs) defined for the census enumeration. A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

Since the overall sample size for the Tonga MICS partly depends on the geographic domains of analysis that are defined for the survey tables, the distribution of EAs and households in Tonga from the 2016 Census sampling frame was first examined by division, urban and rural strata.

The overall sample size for the Tonga MICS was calculated as 2,750 households. For the calculation of the sample size, the key indicator used was use of any contraceptive method for women aged 15-49 years. Since the survey results are tabulated at the divisional level, it was necessary to determine the minimum sample size for each division.

The sample for the Tonga MICS 2019 was designed to provide estimates for a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for the five divisions: Tongatapu, Vava'u, Ha'apai, 'Eua and Ongo Niua. The urban and rural areas in each of the five divisions were identified as the main sampling strata, and the sample of households was selected in two stages. Within each stratum, a specified number of census enumeration areas (EA) were selected systematically with probability proportional to size. After a household listing was carried out within the selected EAs, a systematic sample of 20 households was drawn in each sample EA. A total of 139 sample EAs and 2,751 sample households were selected at the national level (some of the sampled EA's had less than 20 households). All of the selected EAs were visited during the fieldwork data collection. As the sample is not self-weighting, sample weights are used for reporting survey results. A more detailed description of the sample design can be found in the Survey Findings Report's "Appendix A: Sample Design".

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

-QUESTIONNAIRE DESCRIPTION: Six questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 5 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) a questionnaire for individual men administered in every second household to all men age 15-49 years; 5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; 6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household

For all children age 0-2 years with a completed Questionnaire for Children Under Five, the Questionnaire for Vaccination Records at Health Facility, was also used to record vaccinations from the records maintained at health facilities. In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, measured the weights and heights of children age under 5 years, and tested household and source water for E. coli levels. Details and findings of these observations and measurements are provided in the respective sections of the report. Further, the questionnaire for children age 5-17 years included a reading and mathematics assessment administered to children age 7-14 years. The questionnaires were based on the MICS6 standard questionnaires.3 From the MICS6 model English, version, the questionnaires were customised and translated into Tongan Language and were pre-tested in urban (Ma’ufanga and Kolofo’ou) and rural EAs (Lapaha and Kala’au) in Tongatapu in August 2019. Based on the results of the pretest, modifications were made to the wording and translation of the questionnaires. A copy of the Tonga MICS 2019 questionnaires is provided in the External Resources of this documentation.

-COMPOSITION OF THE QUESTIONNAIRES: The questionnaires included the following modules: -Household questionnaire: List of household members, Education, Household characteristics, Social transfers, Household energy use, Food insecurity Experience, Water and sanitation, Handwashing, Salt iodisation.

-Water Quality Testing questionnaire: Water quality tests, Water quality testing results.

-Individual Women questionnaire: Background, Mass Media and ICT, Fertility/Birth history, Desire for last birth, Maternal and newborn health, Post-natal health checks, Contraception, Unmet need, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, Human Papillomavirus, STI, Tobacco and alcohol use, Domestic violence, Life satisfaction.

-Individual Men questionnaire: Background, Mass Media and ICT, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, STI, Tobacco and alcohol use, Life satisfaction.

-Children Under 5 questionnaire: Background, Birth registration, Early childhood development, Child discipline, Child functioning, Breastfeeding and dietary intake, Immunisation, Care of illness, Anthropometry.

-Children Age 5-17 Years questionnaire: Background, Child labour, Child discipline, Child functioning, Parental involvment, Foundational learning skills.

-Vaccination Records at Health Facillity (for children aged 0-2 years): Background, Immunization.

Cleaning operations

Data were received at the Tonga Statistics Department central office via Internet File Streaming System (IFSS) integrated into the management application on the supervisors’ tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) During data collection b) Structure checking and completeness c) Secondary editing d) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines on mics.unicef.org.

Response rate

Of 2,751 households selected for the sample, 2,543 were found occupied. Of these, 2,498 were successfully interviewed for a household response rate

Abstract

The 2023 Jordan Population and Family Health Survey (JPFHS) is the eighth Population and Family Health Survey conducted in Jordan, following those conducted in 1990, 1997, 2002, 2007, 2009, 2012, and 2017–18. It was implemented by the Department of Statistics (DoS) at the request of the Ministry of Health (MoH).

The primary objective of the 2023 JPFHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the 2023 JPFHS: • Collected data at the national level that allowed calculation of key demographic indicators • Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality • Measured 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, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15–49 • Conducted haemoglobin testing with eligible children age 6–59 months and women age 15–49 to gather information on the prevalence of anaemia • Collected data on women’s and men’s knowledge and attitudes regarding sexually transmitted infections and HIV/AIDS • Obtained data on women’s experience of emotional, physical, and sexual violence • Gathered data on disability among household members

The information collected through the 2023 JPFHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Jordan.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2023 JPFHS was the 2015 Jordan Population and Housing Census (JPHC) frame. The survey was designed to produce representative results for the country as a whole, for urban and rural areas separately, for each of the country’s 12 governorates, and for four nationality domains: the Jordanian population, the Syrian population living in refugee camps, the Syrian population living outside of camps, and the population of other nationalities. Each of the 12 governorates is subdivided into districts, each district into subdistricts, each subdistrict into localities, and each locality into areas and subareas. In addition to these administrative units, during the 2015 JPHC each subarea was divided into convenient area units called census blocks. An electronic file of a complete list of all of the census blocks is available from DoS. The list contains census information on households, populations, geographical locations, and socioeconomic characteristics of each block. Based on this list, census blocks were regrouped to form a general statistical unit of moderate size, called a cluster, which is widely used in various surveys as the primary sampling unit (PSU). The sample clusters for the 2023 JPFHS were selected from the frame of cluster units provided by the DoS.

The sample for the 2023 JPFHS was a stratified sample selected in two stages from the 2015 census frame. Stratification was achieved by separating each governorate into urban and rural areas. In addition, the Syrian refugee camps in Zarqa and Mafraq each formed a special sampling stratum. In total, 26 sampling strata were constructed. Samples were selected independently in each sampling stratum, through a twostage selection process, according to the sample allocation. Before the sample selection, the sampling frame was sorted by district and subdistrict within each sampling stratum. By using a probability proportional to size selection at the first stage of sampling, an implicit stratification and proportional allocation were achieved at each of the lower administrative levels.

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2023 JPFHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Man’s Questionnaire, (4) the Biomarker Questionnaire, and (5) the Fieldworker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Jordan. 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 Arabic.

Cleaning operations

All electronic data files for the 2023 JPFHS were transferred via SynCloud to the DoS central office in Amman, 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. 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 July and completed in September 2023.

Response rate

A total of 20,054 households were selected for the sample, of which 19,809 were occupied. Of the occupied households, 19,475 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 13,020 eligible women age 15–49 were identified for individual interviews; interviews were completed with 12,595 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 6,506 men age 15–59 were identified as eligible for individual interviews and 5,873 were successfully interviewed, yielding a response rate of 90%.

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 in 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 2023 Jordan Population and Family Health Survey (2023 JPFHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2023 JPFHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2023 JPFHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardization exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in

Abstract

The Government's efforts aimed at formulating and implementing policies and programmes that would have a positive impact on the situation of children and women in Sudan in particular, and on the achievement of the MDGs in general, necessitates periodic collection of relevant data/information for assessing progress towards achievement of the defined developmental goals and targets. The Sudan Household Survey represents one of the major tools to make available the data/information required for assessing progress towards achievement of the defined national and international developmental goals and targets and for the formulation and implementat ion of policies and programmes to improve the situation of children and women in Sudan.

The Sudan Household Health Survey (SHHS), conducted in 2006, was the first nationally representative survey covering the entire Sudan in two decades covering key social development indicators.The national and state-level data generated by the SHHS helped in creating a baseline for assessing the progress towards some of the key MDG goals and targets, assisting in monitoring of MDG commitments and in informed decision making with regard to development planning. In 2009, the decision was taken to repeat the SHHS to provide up-to date data on social development indicators.

the Sudan Household Health Survey second round (SHHS2), conducted jointly by the Federal Ministry of Health (FMOH) and the Central Bureau of Statistics with financial and technical assistance from the United Nations agencies and other partners. The SHHS2 is a customized version of the Multiple Indicator Cluster Survey (MICS) Round 4 and the Pan Arab Project for Family Health (PAPFAM) survey. The survey is part of the fourth round of the MICS (MICS4), which is a global survey program, originally developed to measure progress towards an internationally agreed set of goals that emerged from the 1990 World Summit for Children.

In parallel, a maternal mortality survey was conducted as part of the listing operations of the SHHS2 and other country specific testing for anaemia were conducted at the field. Random samples of blood drawn during this process we re also tested in central laboratories for hepatitis, syphilis and HIV. The maternal mortality survey and the testing processes are not considered as part of the MICS modules and therefore did not benefit from the technical assistance and quality assurance processes of the MICS programme.

The survey was conducted at a time when Sudan was undergoing the separation from South Sudan region with unprecedented socioeconomic challenges which had direct implications on the welfare of children and women.

Geographic coverage

The sample for the 2010 Sudan Household Health Survey (SHHS2) was designed to provide estimates for some key indicators, for urban and rural areas and for the 15 states (Northern, River Nile, Red Sea, Kassala, Gedarif, Khartoum, Gezlra, Sinnar, Blue Nile, White Nile, North Kordofan, South Kordofan, North Darfur, West Darfur, South Darfur)

Analysis unit

Households Women Children under five years Men

Universe

The survey covered : - All household members (usual residents) - All women aged 15-49 years - All men aged 15-49 years - All children under five years

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2010 Sudan Household Health Survey (SHHS2) was designed to provide estimates for some key indicators on the situation of children and women at the national level, for urban and rural areas and for the 15 states (Northern, River Nile, Red Sea, Kassala, Gedarif, Khartoum, Gezlra, Sinnar, Blue Nile, White Nile, North Kordofan, South Kordofan, North Darfur, West Darfur, South Darfur). The target universe for the SHHS2 includes the households and members of individual households, including nomadic households camping at a location/place at the time of the survey. The population living in institutions and group quarters such as hospitals, military basesand prisons, were excluded from the sampling frame.

The states constitute the main sampling domains and in each state a two stage cluster sampling design was employed to draw the sample for the SHHS2. The villages or quarters (in the case of urban areas) constituted the Primary Sampling Units (PSUs) for the SHHS2. The PSU represented the smallest area or administrative unit which could be identified in the field with commonly recognized boundaries. The sampling frame for 15 states was compiled using the list of villages and quarters and estimated population updated by the Central Bureau of Statistics on the basis of the updated frame from the 2008 Population Census. In the 15 States, clusters were distributed to urban and rural areas, proportional to the size of urban and rural populations in each state. The urban and rural clusters in each of these states were selected randomly with probability of selection proportional to size.

The sample size for the survey was determined by the accuracy and degree of precision required for the survey estimates for each state. It was judged that a minimum sample of 900 households would be necessary to make estimates/results with some degree of precision at the state level. Allowing for some non-response in the survey, it was decided to take a sample of 1,000 households in each state. Since a similar level of precision was required for the survey results from each state, it was decided to draw 40 clusters from each state and 25 households from each cluster. The sampling frame of villages/quarters was compiled separately for each state based on the best available population measures. In cases where a selected village/quarter could not be reached because of security or access problems, it was replaced by a neighbouring village/quarter in the sampling frame. All selected clusters (villages/quarters) in each state were fully covered. After a household listing was carried out within the selected clusters; a sample of 25 households was drawn from each selected cluster using the method of systematic random sampling.

Although each state sample can be considered as self-weighting, the total sample for Sudan is not self-weighting since a fixed sample of househo lds was drawn from each state, irrespective of its population size. Therefore, to derive estimates for Sudan as a whole it was necessary to assign a weight to each state-level sample. For reporting national level results, and to obtain unbiased estimates from the data, appropriate weights were applied to the sample data based on the probabilities of selection. Measures of sampling variability for key survey estimates were also calculated. Sample weights were calculated fo r each state-level sample and these were used in the subsequent analyses of the survey data. A more detailed description of the sample design can be found in Appendix A.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey tools consisted of five sets of questionnaires: (i) a Household questionnaire which was used to collect information on all de jure household members and the household; (ii) a Women's questionnaire administered to all women aged 15-49 years in each household; (iii) a children's questionnaire administered to mothers or caretakers of all children under five years of age living in the household; (iv) Men's questionnaire administered to all men living in the household; (v) the Food Security Questionnaire which was administered in each household.

The questionnaires were pre-tested during the last quarter of 2009 and the first quarter of 2010 and modifications were made to the wording and translation of the questionnaires based on the results of the pre-test. In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, tested blood for all household members and measured the weights and heights of children under-5 years of age. Details and findings of these measurements are provided in the respective sections of the report. However, the results of the anaemia testing and blood testing are not provided in the report in view of the very low response rates for these tests.

The first three questionnaires are based on the MICS4 and PAPFAM model questionnaires. A copy of the SHHS2 questionnaires is provided in Appendix F.

Cleaning operations

Data were entered using the CSPro software. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS4 project and adapted to the SHHS2 questionnaires were used throughout. Data processing was concluded in August -2010. Data were analysed using the Statistical Package for Social Sciences (SPSS) software programme (Version 18), and the model syntax and tabulation plans developed for the SHHS2 were largely based on the standard MfCS Syntax. Food security indicators were calculated using the standard WFP food score syntax.

Response rate

Of the 15,000 households selected for the sample, 14,921 were found to be occupied. Of these, 14,778 households were interviewed successfully for a household response rate of 99.0 percent. In those households interviewed, 18,614 women (aged 15-49 years) were identified. Of these, 17,174 women were interviewed, yielding a response rate of 92 percent within interviewed households. In addition, 13,587 children under age five were listed in the household questionnaire. Questionnaires were completed for 13,282 of these children, corresponding to a response rate of 98 percent. An

Abstract

The primary objective of the 2018 ZDHS was to provide up-to-date estimates of basic demographic and health indicators. Specifically, the ZDHS collected information on: - Fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; and gender, nutrition, and awareness regarding HIV/AIDS and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) - Ownership and use of mosquito nets as part of the national malaria eradication programmes - Health-related matters such as breastfeeding, maternal and childcare (antenatal, delivery, and postnatal), children’s immunisations, and childhood diseases - Anaemia prevalence among women age 15-49 and children age 6-59 months - Nutritional status of children under age 5 (via weight and height measurements) - HIV prevalence among men age 15-59 and women age 15-49 and behavioural risk factors related to HIV - Assessment of situation regarding violence against women

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women age 15-49, all men age 15-59, and all children age 0-5 years who are usual members of the selected households or who spent the night before the survey in the selected households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 ZDHS is the Census of Population and Housing (CPH) of the Republic of Zambia, conducted in 2010 by ZamStats. Zambia is divided into 10 provinces. Each province is subdivided into districts, each district into constituencies, and each constituency into wards. In addition to these administrative units, during the 2010 CPH each ward was divided into convenient areas called census supervisory areas (CSAs), and in turn each CSA was divided into enumeration areas (EAs). An enumeration area is a geographical area assigned to an enumerator for the purpose of conducting a census count; according to the Zambian census frame, each EA consists of an average of 110 households.

The current version of the EA frame for the 2010 CPH was updated to accommodate some changes in districts and constituencies that occurred between 2010 and 2017. The list of EAs incorporates census information on households and population counts. Each EA has a cartographic map delineating its boundaries, with identification information and a measure of size, which is the number of residential households enumerated in the 2010 CPH. This list of EAs was used as the sampling frame for the 2018 ZDHS.

The 2018 ZDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters. During the listing, an average of 133 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the 2018 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Zambia. Input on questionnaire content was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international cooperating partners. After all questionnaires were finalised in English, they were translated into seven local languages: Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

All electronic data files were transferred via a secure internet file streaming system to the ZamStats central office in Lusaka, 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 two IT specialists and one secondary editor who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro 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 and data processing were initiated in July 2018 and completed in March 2019.

Response rate

Of the 13,595 households in the sample, 12,943 were occupied. Of these occupied households, 12,831 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 14,189 women age 15-49 were identified as eligible for individual interviews; 13,683 women were interviewed, yielding a response rate of 96% (the same rate achieved in the 2013-14 survey). A total of 13,251 men were eligible for individual interviews; 12,132 of these men were interviewed, producing a response rate of 92% (a 1 percentage point increase from the previous survey).

Of the households successfully interviewed, 12,505 were interviewed in 2018 and 326 in 2019. As the large majority of households were interviewed in 2018 and the year for reference indicators is 2018.

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 2018 Zambia Demographic and Health Survey (ZDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2018 ZDHS 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 2018 ZDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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 - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Completeness of information on siblings - Sibship size and sex ratio of siblings - Height and weight data completeness and quality for children - Number of enumeration areas completed by month, according to province, Zambia DHS 2018

Note: Data quality tables are presented in APPENDIX C of the report.

Abstract

This Child and Development Survey - 2000 is a multiple indicator clutster survey (MICS) that was conducted among women and children, with the financial and technical support of UNICEF. The purpose of this survey is to establish comprehensive statistical data to monitor the implementation of Mongolia's National Program of Action for the Development of Children in the 1990s, and to aid future planning and organisation. Overall, the findings of the Child and Development Survey -2000 will be a valuable source of information in determining the current level of infant, child and women's health and education in Mongolia and the factors which influence those levels, and it will be extremely helpful in assessing government efforts towards improving the status of women and children in the country in the past 10 years. The 2000 Mongolia Multiple Indicator Cluster Survey has as its primary objectives:

· To provide up-to-date information for assessing the situation of children and women in Mongolia at the end of the decade and for looking forward to the next decade; · To furnish data needed for monitoring progress toward goals established at the World Summit for Children and as a basis for future action; · To contribute to the improvement of data and monitoring systems in Mongolia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Geographic coverage

The whole country.

Analysis unit

• Households
• Women
• Children

Universe

The survey covered all Mongolian households/population and foreigners residing in Mongolia. However, it excluded Mongolian citizens residing outside the country or who had been residing, for more than 6 months, in institutions such as military camps, orphanages, care centers for the aged, hospitals, prisons and other correctional institutions.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected in two stages. At the first stage, 300 census enumeration areas were selected with probability proportional to size. After a household listing was carried out within the selected enumeration areas, a systematic sample of 6000 households was drawn. Because the sample was stratified by region, it is selfweighting. For reporting the national level results, sample weights have not been used.

Survey population: According to the survey objectives, the current survey subjects were women aged 15-49, children under 5 or of pre-school and general education school age, and disabled children under 18 years in the households of the interviewees.

The sample size necessary to achieve the desired level of precision was calculated according to the formula described in the MICS manual.2 Since the MICS survey was intended to provide information on a variety of indicators and several specific target groups, the required sample size is based on the number of households needed to yield valid results with the desired level of precision for the "rarest" indicator-target group combination. This ensures that findings on the less "rare" combinations will also be valid at the chosen level of precision or better. For the Mongolian survey the key indicator for calculating the required sample size was the measles immunization rate in the target group of children aged 12-23 months. Using the formula from the MICS manual it was determined that a sample of 6000 households would be needed to obtain data on all survey indicators with a margin of error not greater than +/-5 percentage points at national level with a 95 per cent confidence level.

Sampling stratification: In the survey, sampling used 2 different stratification's: 1. By region: Most tabulations in this report are disagregated by 6 regions: Western, Northern, Eastern, Southern, Central 1 and Central 2. This is an official government classification based on petrol prices. Specifically, this regional delineation is as follows:

• Western (Uvs, Zavkhan, Gobi-Altai, Bayan-Ulgii, and Khovd aimags)
• Northern (Arhangai, Hovsgol, Bayankhongor, Uverhkangai and Bulgan aimags)
• Eastern (Dornod, Hentii and Suhkbaatar aimags)
• Southern (Omnogobi, Dundgovi, Dornogovi and Govisumber aimags)
• "Central-1" (Tuv, Selenge, Darhkan-Uul and Orhkon aimags)
• "Central-2" (Ulaanbaatar- capital city)

1. By urban and rural: The attached tabulations in this report are classified into urban and rural.

   • "Urban" population and households are defined as those located in the capital city of Ulaanbaatar and any aimag centers. • "Rural " - The rest of the population and all other households are classified as rural.

   Sample unit: The sample unit is a household. A household is a single person or group of people residing in one dwelling, accumulating their income together, having a common food and clothing source.

Sampling deviation

The sample for the Mongolia Multiple Indicator Cluster Survey (MICS) was designed to provide estimates of health indicators at the national level, for urban and rural areas, and for six regions: West, South, North, East, Central-1 and Central-2. The sample for the survey was designed to provide national estimates for the main indicators covered by the survey, with a margin of error of ±5 percentage points at a 95 per cent level of confidence.

Mode of data collection

Face-to-face [f2f]

Research instrument

In addition to a household questionnaire, questionnaires were administered in each household for women aged 15-49 and children under age five. The questionnaires are based on the MICS model questionnaire with the inclusion of the child disability module. From the MICS model English version, the questionnaires were translated into Mongolian. Questionnaires were translated back in to English from the Mongolian version. The questionnaires were pretested during Apr. 2000. Based on the results of the pretest, modifications were made to the wording and translation of the questionnaires.

The questionnaire used in the Mongolian "Child and Development Survey-2000” closely followed the content and format of the model MICS questionnaire recommended by UNICEF5, with some revisions and adjustments to suit specific local circumstances. The MICS model actually consists of 3 types of questionnaires; each designed to collect information on specific topics and distinct target groups.

The household questionnaire collected information such as the construction of the housing, the sex, age, literacy, and marital and orphaned status of the household members. Also included in this questionnaire were questions on education, child labor, supply of water and sanitation, and the use of iodized salt.

The questionnaire for women aged 15-49 included modules on: - Information about women - Child mortality - Maternal and infant health - Contraceptive use - HIV/AIDS. - Vitamin "D" deficiency

 The questionnaire on children under age 5 covered:

• Birth registration
• Early childhood learning
• Vitamin A supplementation
• Breastfeeding
• Hepatitis
• Child immunization
• Anthropometry (measurement of height and weight)

Cleaning operations

After the completion of the data processing of the survey materials, statisticians analyzed particular indicators, checked consistency with other data sources, reviewed results, edited errors, and reviewed concepts and definitions of unclear indicators. Finally based on these, they developed a working document, which would be useful for the next survey, and wrote the survey report.

Data pre-entry preparation, quality control and data entry was carried out in July- August 2000 at a highly professional level and in a shorter time than expected. At this stage of the survey, the working group stayed in close contact with the survey regional office and some questions raised concerning software and mathematical methodology were solved very efficiently. Survey data were processed using software based on the given designed questionnaire. The data processing was carried out in two stages. The goal of the first stage was to obtain a complete file of raw data according to the processing technology order and to ensure the quality of the data. This included following:

• Data entry
• Verification
• Secondary editing
• Production of verified and confirmed data set

The second stage aimed to produce cross tables enabling further analysis to be carried out. This included the following: - Entry of a variety of options and simulations - Production of output tables

Response rate

The selected 6000 households for the "Child and Development Survey -2000" completed the interview (Table 1). About 8606 women aged between 15-49, identified as the select group, were eligible for the women's questionnaire. Out of these, 8257 were interviewed successfully, with a response rate of 95.9 per cent. In addition, 6199 children under the age of 5 were found to be living in the selected households. Children's questionnaires were completed for 6184 of these, yielding a response rate of 99.8 per cent.

Abstract

The JPFHS is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

As in the previous Demographic and Health Surveys (DHS) in Jordan, conducted in 1990, 1997 and 2002, the primary objective of the Jordan Population and Family Health Survey 2007 (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policy makers to evaluate and improve existing programs. In addition, a subsample of women and children were tested for anemia and anthropometry (height and weight). The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional or cross-national studies.

The content of the 2007 JPFHS was significantly expanded from the 2002 survey to include additional questions on women’s status, reproductive health, domestic violence, and early childhood development.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The 2007 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and badia and non-badia areas. In order to ensure comparability with the previous surveys, the sample was designed to provide estimates for the three regions, North, Central and South. The grouping of the governorates into the regions is as follows: the North region consists of Irbid, Jarash, Ajloun, and Mafraq; the Central region consists of Amman, Madaba, Balqa and Zarqa; and the South region consists of Karak, Tafielah, Ma'an and Aqaba.

The 2007 JPFHS sample was designed using the 2004 Population and Housing Census as the sampling frame. The sampling frame was stratified by governorate, major cities, other urban, and rural within each stratum. A two-stage sampling procedure was employed. First, blocks were selected systematically as primary sampling units (PSUs) with a probability proportional to the size of the PSU. A total of 930 PSUs were selected at this stage. In the second stage, a fixed number of 16 households were selected as final sampling units in each PSU, resulting in a sample size of about 15,000 households. Blood testing (anemia) and the measurements of height and weight were conducted among eligible individuals in the selected households in 465 PSUs (half of the sample). In addition, 310 selected PSUs (one third of the sample) which were not selected for the above measurements were chosen for collecting data on domestic violence in the household.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 2007 JPFHS used two questionnaires – namely, the Household Questionnaire and the Individual Questionnaire. Both questionnaires were developed in English and Arabic, based on the questionnaires used in the 2002 survey, in collaboration with Macro International Inc. The Household Questionnaire was used to list all usual members of the sampled households and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of household, and marital status. In addition, questions were included on the socio-economic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. The Household Questionnaire was also used to identify women who are eligible for the individual interview: ever-married women aged 15-49. In addition, in half of the households, all women aged 15-49 and children under five years of age were measured to determine nutritional status and tested for anemia.

The household and women’s questionnaires were based on the DHS standard Questionnaire. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990, 1997 and 2002 Jordan Population and Family Health Surveys. For each ever-married woman aged 15-49, information on the following topics was collected:

• Respondent’s general background
• Birth history
• Family planning
• Pregnancy, postnatal health care and breastfeeding
• Children immunization and children and mothers nutrition.
• Marriage
• Fertility preferences
• Husband’s background and respondent’s employment
• AIDS and STIs
• Other health issues
• Domestic violence
• Early childhood development

The last two sections of the questionnaire (domestic violence and early childhood development) use and discontinuation, and marriage during the five years prior to the survey was collected using a monthly calendar.

Response rate

A total of 14,880 households were selected for the survey from the sampling frame; among those selected households, 14,748 households were found. Of those households, 14,564 (99 percent) were successfully interviewed. In those households, 11,113 eligible women were identified, and complete interviews were obtained with 10,876 of them (98 percent of all eligible women). The overall response rate (the households response rate multiplied by the eligible woman response rate) was about 97 percent.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

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 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 2007 Jordan Population and Family Health Survey (2007 JPFHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2007 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2007 JPFHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2007 JPFHS is a Macro SAS procedure. This procedure used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: See detailed description of sample design in APPENDIX B of the survey report

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

Abstract

The 2022 Kenya Demographic and Health Survey (2022 KDHS) is the seventh DHS survey implemented in Kenya. The Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Health (MoH) and other stakeholders implemented the survey. Survey planning began in late 2020 with data collection taking place from February 17 to July 19, 2022. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organizations that facilitated the successful implementation of the survey through technical or financial support were the Bill & Melinda Gates Foundation, the World Bank, the United Nations Children's Fund (UNICEF), the United Nations Population Fund (UNFPA), Nutrition International, the World Food Programme (WFP), the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), the World Health Organization (WHO), the Clinton Health Access Initiative, and the Joint United Nations Programme on HIV/AIDS (UNAIDS).

SURVEY OBJECTIVES The primary objective of the 2022 KDHS is to provide up-to-date estimates of demographic, health, and nutrition indicators to guide the planning, implementation, monitoring, and evaluation of population and health-related programs at the national and county levels. The specific objectives of the 2022 KDHS are to: Estimate fertility levels and contraceptive prevalence Estimate childhood mortality Provide basic indicators of maternal and child health Estimate the Early Childhood Development Index (ECDI) Collect anthropometric measures for children, women, and men Collect information on children's nutrition Collect information on women's dietary diversity Obtain information on knowledge and behavior related to transmission of HIV and other sexually transmitted infections (STIs) Obtain information on noncommunicable diseases and other health issues Ascertain the extent and patterns of domestic violence and female genital mutilation/cutting

Geographic coverage

National coverage

Analysis unit

Household, individuals, county and national level

Universe

The survey covered sampled households

Sampling procedure

The sample for the 2022 KDHS was drawn from the Kenya Household Master Sample Frame (K-HMSF). This is the frame that KNBS currently operates to conduct household-based sample surveys in Kenya. In 2019, Kenya conducted a Population and Housing Census, and a total of 129,067 enumeration areas (EAs) were developed. Of these EAs, 10,000 were selected with probability proportional to size to create the K-HMSF. The 10,000 EAs were randomized into four equal subsamples. The survey sample was drawn from one of the four subsamples. The EAs were developed into clusters through a process of household listing and geo-referencing. To design the frame, each of the 47 counties in Kenya was stratified into rural and urban strata, resulting in 92 strata since Nairobi City and Mombasa counties are purely urban.

The 2022 KDHS was designed to provide estimates at the national level, for rural and urban areas, and, for some indicators, at the county level. Given this, the sample was designed to have 42,300 households, with 25 households selected per cluster, resulting into 1,692 clusters spread across the country with 1,026 clusters in rural areas and 666 in urban areas.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Eight questionnaires were used for the 2022 KDHS: 1. A full Household Questionnaire 2. A short Household Questionnaire 3. A full Woman's Questionnaire 4. A short Woman's Questionnaire 5. A Man's Questionnaire 6. A full Biomarker Questionnaire 7. A short Biomarker Questionnaire 8. A Fieldworker Questionnaire.

The Household Questionnaire collected information on: o Background characteristics of each person in the household (for example, name, sex, age, education, relationship to the household head, survival of parents among children under age 18) o Disability o Assets, land ownership, and housing characteristics o Sanitation, water, and other environmental health issues o Health expenditures o Accident and injury o COVID-19 (prevalence, vaccination, and related deaths) o Household food consumption

The Woman's Questionnaire was used to collect information from women age 15-49 on the following topics: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Maternal health care and breastfeeding o Vaccination and health of children o Children's nutrition o Woman's dietary diversity o Early childhood development o Marriage and sexual activity o Fertility preferences o Husbands' background characteristics and women's employment activity o HIV/AIDS, other sexually transmitted infections (STIs), and tuberculosis (TB) o Other health issues o Early Childhood Development Index 2030 o Chronic diseases o Female genital mutilation/cutting o Domestic violence

The Man's Questionnaire was administered to men age 15-54 living in the households selected for long Household Questionnaires. The questionnaire collected information on: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Marriage and sexual activity o Fertility preferences o Employment and gender roles o HIV/AIDS, other STIs, and TB o Other health issues o Chronic diseases o Female genital mutilation/cutting o Domestic violence

The Biomarker Questionnaire collected information on anthropometry (weight and height). The long Biomarker Questionnaire collected anthropometry measurements for children age 0-59 months, women age 15-49, and men age 15-54, while the short questionnaire collected weight and height measurements only for children age 0-59 months.

The Fieldworker Questionnaire was used to collect basic background information on the people who collected data in the field. This included team supervisors, interviewers, and biomarker technicians.

All questionnaires except the Fieldworker Questionnaire were translated into the Swahili language to make it easier for interviewers to ask questions in a language that respondents could understand.

Cleaning operations

Data were downloaded from the central servers and checked against the inventory of expected returns to account for all data collected in the field. SyncCloud was also used to generate field check tables to monitor progress and flag any errors, which were communicated back to the field teams for correction.

Secondary editing was done by members of the central office team, who resolved any errors that were not corrected by field teams during data collection. A CSPro batch editing tool was used for cleaning and tabulation during data analysis.

Response rate

A total of 42,022 households were selected for the sample, of which 38,731 (92%) were found to be occupied. Among the occupied households, 37,911 were successfully interviewed, yielding a response rate of 98%. The response rates for urban and rural households were 96% and 99%, respectively. In the interviewed households, 33,879 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 32,156 women, yielding a response rate of 95%. The response rates among women selected for the full and short questionnaires were the similar (95%). In the households selected for the male survey, 16,552 men age 15-54 were identified as eligible for individual interviews and 14,453 were successfully interviewed, yielding a response rate of 87%.

Abstract

The 2013 Liberia Demographic and Health Survey (LDHS) is designed to provide data for monitoring the population and health situation in Liberia. The 2013 LDHS is the fourth Demographic and Health Survey conducted in Liberia since 1986. The primary objective of the 2013 LDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2013 LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, and HIV/AIDS and other sexually transmitted infections (STIs). In addition, the 2013 LDHS provides estimates on HIV prevalence among adult Liberians.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual/ person
• Children age 0-5 years
• Woman age 15 to 49 years
• Man age 15 to 49 years

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sampling frame for the 2013 LDHS was developed by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) after the 2008 National Population and Housing Census (NPHC). The sampling frame is similar to that used for the 2009 and 2011 Liberia Malaria Indicator Surveys (LMIS), except that the classification of localities as urban or rural was updated through the application of standardized definitions. The sampling frame excluded nomadic and institutional populations such as residents of hotels, barracks, and prisons. Notably, the sampling frame for the 2013 LDHS differs markedly from that used for the 2007 LDHS, which was based on the 1984 NPHC. Taken together, these differences may complicate data comparisons between surveys.

The 2013 LDHS followed a two-stage sample design that allowed estimates of key indicators for the country as a whole, for urban and rural areas separately, for Greater Monrovia and other urban areas separately, and for each of 15 counties. To facilitate estimates of geographical differentials for certain demographic indicators, the 15 counties were collapsed into five regions as follows: North Western: Bomi, Grand Cape Mount, and Gbarpolu South Central: Montserrado, Margibi, and Grand Bassa South Eastern A: River Cess, Sinoe, and Grand Gedeh South Eastern B: River Gee, Grand Kru, and Maryland North Central: Bong, Nimba, and Lofa

Regional data were presented in the 2007 LDHS, the 2009 LMIS, and the 2011 LMIS. However, in contrast with these past surveys, the South Central region now includes Monrovia. Thus, data presented for the South Central region in this report is not directly comparable to that presented in the 2007 LDHS, the 2009 LMIS, or the 2011 LMIS.

The first stage of sample selection involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2008 NPHC. Overall, the sample included 322 sample points, 119 in urban areas and 203 in rural areas. To allow for separate estimates of Greater Monrovia and Montserrado as a whole, 44 sample points were selected in Montserrado; 16 to 26 sample points were selected in each of the other 14 counties.

The second stage of selection involved the systemic sampling of households. A household listing operation was undertaken in all the selected EAs from mid-September to mid-October 2012. From these lists, households to be included in the survey were selected. Approximately 30 households were selected from each sample point for a total sample size of 9,677 households. During the listing, geographic coordinates (latitude and longitude) were taken in the center of the populated area of each EA using global positioning system (GPS) units.

Because of the approximately equal sample sizes in each region, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

All women age 15-49 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 households, all men age 15-49 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 the subsample of households selected for the male survey, blood samples were collected for laboratory testing to detect HIV from eligible women and men who consented; in this same subsample of households, height and weight information was collected from eligible women, men, and children 0-59 months.

Further details on the sample design and implementation are given in Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2013 LDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires are based on MEASURE DHS standard survey questionnaires and were adapted to reflect the population and health issues relevant to Liberia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors.

Given that there are dozens of local languages in Liberia, most of which have no accepted written script and are not taught in the schools, and given that English is widely spoken, it was decided not to attempt to translate the questionnaires into vernaculars. However, many of the questions were broken down into a simpler form of Liberian English that interviewers could use with respondents.

The Household Questionnaire was used to list all the usual members of and visitors to selected households. Some 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. For children under age 18, survival status of the parents 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 interview and HIV testing. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facility, materials used for the floor of the house, ownership of various durable goods, ownership and use of mosquito nets, and information on household out-of-pocket health-related expenditures. The Household Questionnaire was also used to record height and weight measurements of children 0-59 months and eligible adults. Also recorded was whether or not eligible adults consented to HIV testing.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49.

The Man’s Questionnaire was administered to all men age 15-49 in the subsample of households selected for the male survey in the 2013 LDHS sample. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

Cleaning operations

All questionnaires were returned to the LISGIS central office in Monrovia for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. The data were processed by a team of 12 data entry clerks, two data editors, one data entry supervisor, and two administrators of questionnaires; the latter checked that the clusters were completed according to the sample selection and that all members of the household eligible for individual interview were identified. Secondary editing was led by an LDHS coordinator. Several LISGIS staff took on the responsibility of receiving the blood samples from the field and checking them before sending them to the Montserrado Regional Blood Bank for storage. Data entry and editing using CSPro software was initiated in April 2013 and completed in late August 2013.

Response rate

A total of 9,677 households were selected for the sample, of which 9,386 were occupied. Of the occupied households, 9,333 were successfully interviewed, yielding a response rate of 99 percent.

In the interviewed households, 9,462 eligible women were identified for individual interview; of these, complete interviews were conducted with 9,239 women, yielding a response rate of 98 percent. In the subsample of households selected for the male survey, 4,318 eligible men were identified and 4,118 were successfully interviewed, yielding a response rate of 95 percent. The lower response rate for men was likely due to their more frequent and longer absences from the household.

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 2013 Liberia Demographic and Health Survey 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 2013 LDHS is only one of many samples that could have been selected from the same population,

Abstract

The 2007 Liberia Demographic and Health Survey (LDHS) was carried out from late December 2006 to April 2007, using a nationally representative sample of over 7,000 households. All women and men age 15-49 years in these households were eligible to be individually interviewed and were asked to provide a blood sample for HIV testing. The blood samples were dried and carried to the National Laboratory of the Ministry of Health and Social Welfare (MOHSW) on the JFK Hospital compound in Monrovia where they were tested for the human immunodeficiency virus (HIV).

The 2007 LDHS was designed to provide data to monitor the population and health situation in Liberia. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood and maternal mortality, maternal and child health, domestic violence, and awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs).

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

The LDHS sample was designed to produce most of the key indicators for the country as a whole, for urban and rural areas separately, and for Monrovia and each of five regions that were formed by grouping the 15 counties. The regional groups are as follows: 1 Greater Monrovia
2 North Western: Bomi, Grand Cape Mount, Gbarpolu
3 South Central: Montserrado (outside Monrovia), Margibi, Grand Bassa
4 Southeastern A: River Cess, Sinoe, Grand Gedeh
5 Southeastern B: Rivergee, Grand Kru, Maryland
6 North Central: Bong, Nimba, Lofa

Thus the sample was not spread geographically in proportion to the population, but rather more or less equally across the regions. As a result, the LDHS sample is not self-weighting at the national level and sample weighting factors have been applied to the survey records in order to bring them into proportion.

The survey utilised a two-stage sample design. The first stage involved selecting 300 sample points or clusters from the list of 4,602 enumeration areas (EAs) covered in the 1984 Population Census. This sampling 'frame' is more than 20 years old and in the intervening years Liberia has experienced a civil war and considerable population change. Many people left the country altogether, others lost their lives, while others moved within the country. For example, some households in rural areas relocated into larger villages in order to be better protected. New communities were established, while existing ones had expanded or contracted or even disappeared. Furthermore, as urban areas-especially Monrovia-expanded, some EAs that were previously considered rural may have become urban, but this will not be reflected in the sample frame. Taking all these factors into account, it is obvious that the 1984 census frame is not ideal to be used as sampling frame; however, it is still the only national frame which covers the whole country.

LISGIS conducted a fresh listing of the households residing in the selected sample points, along with identifying the geographic coordinates (latitude and longitude) of the center of each cluster (GPS coding). The listing was conducted from March to May 2006. The second stage of selection involved the systematic sampling of 25 of the households listed in each cluster. It later turned out that there was a problem with the sample frame for Monrovia that resulted in two areas being erroneously oversampled. To correct this error, two clusters were dropped altogether, while five others were replaced in order to provide more balance in the selection. Thus the survey covered a total of 298 clusters-114 urban and 184 rural.

All women and men aged 15-49 years who were either permanent residents of the households in the sample or visitors present in the household on the night before the survey were eligible to be interviewed in the survey and to give a few drops of blood for HIV testing.

Note: See detailed description of the sample design in Appendix A of the survey final report.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires—a Household Questionnaire, a Women’s Questionnaire, and a Men’s Questionnaire—were used in the survey. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program.

In consultation with a group of stakeholders, LISGIS and Macro staff modified the DHS model questionnaires to reflect relevant issues in population, family planning, HIV/AIDS, and other health issues in Liberia. Given that there are dozens of local languages in Liberia, most of which have no accepted written script and are not taught in the schools, and given that English is widely spoken, it was decided not to attempt to translate the questionnaires into vernaculars. However, many of the questions were broken down into a simpler form of Liberian English that interviewers could use with respondents.

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 also used to record height and weight measurements of women age 15-49 years and of children under the age of 5 years and women’s and men’s consent to volunteer to give blood samples. The HIV testing procedures are described in detail in the next section.

The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics: - Background characteristics (education, residential history, media exposure, etc.) - Reproductive history and child mortality - Knowledge and use of family planning methods - Fertility preferences - Prenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant and child feeding practices - Awareness and behavior about HIV/AIDS and other STIs - Adult mortality including maternal mortality.

The Women’s Questionnaire also included a series of questions to obtain information on women’s experience of domestic violence. These questions were administered to one woman per household. In households with two or more eligible women, special procedures were followed in order to ensure that there was random selection of the woman to be interviewed and that these questions were administered in privacy.

The Men’s Questionnaire collected similar information contained in the Woman’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, or domestic violence.

All aspects of the LDHS data collection were pretested in July 2006. For the pretest, LISGIS recruited 19 people to attend the training, most of whom were LISGIS staff with a few from other organizations involved in the survey, e.g., the NACP. Training was held at the Liberia Bible Society for 11 days from June 20 through July 1. Twelve of the 19 participants were selected to implement the pretest interviewing. Two teams were formed for the pretest, each with one supervisor, three female interviewers. and two male interviewers. Each team covered one rural and one urban EA. Because the work was being done during the period of heavy rainfall, the rural areas selected were off a main paved road, about 1-2 hours’ drive from Monrovia, and the urban areas were both in Monrovia itself. Pretest interviewing took six days, from July 4 through July 9. In total, the teams completed interviews with 95 households, 82 women and 60 men, and collected 118 blood samples. The pretest resulted in deleting some questions and making modifications in others.

Response rate

A total of 7,471 households were selected in the sample, of which 7,021 were found occupied at the time of the fieldwork. The shortfall is largely due to households that were away for an extended period of time and structures that were found to be vacant or destroyed. Of the existing households, 6,824 were successfully interviewed, yielding a household response rate of 97 percent.

In the households interviewed in the survey, a total of 7,448 eligible women were identified, of whom 7,092 were successfully interviewed yielding a response rate of 95 percent. With regard to the male survey results, 6,476 eligible men were identified, of whom 6,009 were successfully interviewed, yielding a response rate of 93 percent. The response rates are lower in the urban than rural sample, especially for men.

The principal reason for non-response among both eligible men and women was the failure to find individuals at home despite repeated visits to the household, followed by refusal to be interviewed. The substantially lower response rate for men reflects the more frequent and longer absence of men from the

The Personal Social Services Adult Social Care Survey (ASCS) is an annual survey for England that took place for the fifth time in 2014-15. The survey covers all service users aged 18 and over in receipt, at the point that data are extracted, of long-term support services funded or managed by the social services following a full assessment of need. It seeks to learn more about how effectively services are helping service users to live safely and independently in their own homes, and the impact that these services have on their quality of life. Service users were sent questionnaires, issued by Councils with Adult Social Services Responsibilities (CASSRs), in the period January to March 2015. Further information about the survey, including the methodology, can be found in the 'Methodology and Further Information' document in the Resources section of this page. The numbers in the report are rounded to the nearest five. The percentages in the report are rounded to the nearest whole number thus the figures given for each question may not add up to 100 per cent. National-level information is provided in this report. Further national-level data, data for all CASSRs in England and final, national-level data for the ASCS for 2010-11 to 2014-15 are provided as annex files. The data used to produce the report are available in a CSV file. These are available in the Resources section below. There have been a number of changes to the survey methodology for 2014-15 which are detailed in full in the methodological change notice that was published by the HSCIC in July 2015, which is available via the Related Links section of this page. The text of the methodological change notice is reproduced in Appendix C of the report. The most important changes to note are: • The population covered by the survey now includes only those in receipt of long-term support services; those in receipt of low-level support only (e.g. equipment and adaptations, professional support, short-term residential care) are not included in the survey population or sample. • The population covered by the survey now includes those service users who receive support from CASSRs in terms of assessment and care management but who pay in full for the cost of their services (full cost clients); previously service users were included only where the CASSR made a contribution towards the costs of services received. • The methodology used to weight the results has been enhanced to improve the accuracy of the estimates presented. Because of these changes, it is not possible to make direct comparisons between data for 2014-15 and previous years. Therefore, comparisons are not included in this report. The effects of the above changes, in reference to 2013-14 and 2014-15 data, are described in Appendix B of the report. Findings from the survey are used to populate a number of measures in the Adult Social Care Outcomes Framework; these outcome scores have been published and can be found in the 'Measures from the Adult Social Care Outcomes Framework, England - 2014-15' report, a link to which is provided in the Related Links section. CASSRs reported that at the point that data for the survey were extracted from local systems, there were 673,860 service users aged 18 and over in receipt of long-term support services funded or managed by the social services following a full assessment of need. 69,510 out of a sample of 192,995 service users responded to the survey, which is a response rate of 36 per cent (whereas it was 38 per cent in 2013-14). UPDATE: The comma-separated values (CSV) data file was enhanced in December 2015 to include fields showing all of the categories in Support Setting and Mechanism of Delivery. These fields ('SupportSetting' and 'MechanismDelivery') are described in the CSV guidance and data dictionary workbook. Please note: (15/02/16). The 'CSV guidance and data dictionary' annex for this publication has been replaced in order to correct the labelling of the 'Variable Descriptions' columns for gender, ethnicity and age in the 'DataDictionary' worksheet. The HSCIC would like to apologise for any inconvenience caused.

The data presented here are summarized from annual National Marine Fisheries Service (NMFS), Southeast Fisheries Science Center (SEFSC) fishery independent Bottom Longline Surveys. The surveys were started in 1995, to assess the distribution and abundance of large and small coastal sharks across their known or suspected ranges. The fishing depths were selected based on commercial shark fishing log summaries, which indicated that the primary depths of effort were 18-73 m (10 to 40 fm). A random stratified sampling design with three depth strata; 18-36 m (10-20 fm), 36-55 m (20-30 fm) and 55-73 m (30-40 fm) were used and uniform effort across contiguous 60 nautical mile sampling zones was achieved. Based on analysis of the first two survey years, the 1997 survey was modified by eliminating depth stratification and changing the survey depths to 10-55 m (5-30 fm). The depth reduction was at the request of the SEFSC to ensure that the full range of several coastal sharks was encompassed by the survey. Elimination of depth stratification was to avoid over-sampling strata which represented the least available habitat (the 30-40 fm strata represented very little of the available bottom, but was receiving 33% of the effort). A significant event in the evolution of our longline surveys occurred in 1999 when we were requested to implement a longline survey targeting red snapper (Lutjanus campechanus). At the time, red snapper were not specifically targeted as part of the shark surveys; a different hook type (circle hook) was used, and different depth strata were sampled. The snapper work was conducted between 64-146 m (35-80 fm) in an area from east of the Mississippi River to south of Perdido Key, Florida. Random sampling without proportional allocation was used and sampling units were 10 nautical mile blocks given the small geographical area to be covered. In 2001, the shark and red snapper surveys were combined into a single annual survey of the U.S. Gulf of Mexico. Proportional allocation based on shelf width within statistical zones was adopted and the survey was stratified by depth with 50% allocation in 9-55 m, 40% allocation from 55-183 m and 10% allocation from 188-366 m. This allocation provided effort in the 9-55 m strata comparable to that achieved in previous shark surveys, thereby preserving the time series back to 1995. The major change in the shark surveys was adoption of the Circle hook as the standard for these surveys. A small longline spool holds approximately 5 nautical mile 4.0 mm diameter monofilament line (900 - 1200 lb; 401.8 - 535.7 kg test); up to 10 nautical miles for large spools. Prior to bottom longline deployment, the mainline is attached to a high flyer (radar reflecting buoy). High flyers are attached at both ends of the deployed mainline for visual reference and to facilitate gear retrieval. As the bottom longline is deployed the vessel’s GPS is used to determine distance covered. Because of the constant cutting and reattachment of the mainline and potential loss of sections of line over the course of a survey, the mainline is not marked in sections and the length of mainline deployed is based on GPS intervals. One-hundred gangions (monofilament leaders with AK snap attachment clip and hook) are attached to 1 nautical mile of mainline approximately equidistantly (about every 60 ft or 31 m) throughout the set. Gangion spacing is determined by GPS (i.e., at 1/10 nautical mile 10 evenly spaced gangions should have been deployed) and nautical mile increments are relayed to the gear set crew by hand-held 2-way radios. An electronic beeper (interval based on vessel speed) is often used to determine component attachment intervals. Weights (5 - 10 kg) are attached to the beginning, middle and end of the bottom longline to prevent gear from rising in the water column, as well as to minimize horizontal movement. After the end weight is attached to the bottom longline gear, the mainline is cut and attached to the second high flyer. Prior to the gear haul back, the mainline is reattached to the remaining line on the spool. Buoy lines (or drop lines) are continuations of the mainline and are not separate gear components but are created by deploying an adequate amount of mainline monofilament for tethering high flyer buoys to the bottom longline gear. Buoys/high flyers are used only on the distal ends without a mid-set buoy. To properly calculate catch per unit effort (CPUE) and a variety of additional statistical analyses, it is important to document longline set, gear soak and longline haul back events. There are 4 critical events; first high flyer deployed (beginning of the set), last high flyer deployed (end of the set), first high flyer retrieved (beginning of haul back) and last high flyer retrieved (end of haul back). Minimum data elements required for each event are the date, time, bottom depth, latitude and longitude. Standard sets are 1 hr in duration with 100 hooks attached along 1 nautical mile of mainline. There are a number of situations that can affect the haul back duration including; high catch rates where data reporting requirements and tagging necessitate slowing the retrieval process, large fish entangling gangions and other gear components, gear entanglement with bottom obstructions and turtle encounters. If the haul back is delayed, some of the hooks deployed near the end of the set soak for more than the 1 hr standard. However, since the time event is recorded for the final high flyer brought aboard to end the haul back, extended haul back times are documented. Gear soak time is an important element in calculating fishing effort (catch per unit effort, CPUE, expressed as the number of captures by species/100 hook hr). Soak time is defined during SEFSC surveys, and often for other surveys, as the time between deployment of the last high flyer to end the set to the time of retrieval of the first high flyer to begin haul back. Since the beginning and end of the soak period are essential data elements, soaks that deviate from the standard 1 hr can be accounted for during data analysis. It is possible to use critical events for re-evaluating effort calculations if needed since the 4 critical events are data elements (begin set, end set, begin haul back and end haul back). Ideally, sets are conducted parallel to depth contours with reasonable effort made to maintain a uniform bottom depth and vessel speed throughout the set. Maintaining a uniform set depth can be difficult and may not be feasible when setting gear along areas of high relief or in high winds or currents. Gear is set from the stern of the vessel and communications between the deck crew and helmsman are maintained via hand held two-way radios. Set procedures are generally standard and should be maintained for consistent effort. Primary set procedures and events include; wheel house to deck notification of the set event, deploying the first high flyer, attachment of the first weight, attaching gangions at approximately equidistant increments, attachment of the mid-weight, completing gangion deployment, attaching the last weight, and deploying the last high flyer to mark the set termination point. Data is summarized here from all Bottom Longline Survey stations fished with circle hooks from 2000 to 2009 by 15 minute longitude by latitude blocks in which sampling occurred. CPUE (number/100 hook hr) data is summarized here from all Bottom Longline Survey stations fished with circle hooks from 2000 to 2009 by 15 minute longitude by latitude blocks in which sampling occurred.

Abstract

The Government of the Kyrgyz Republic, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Kyrgyz Republic draw a comprehensive picture of the lives of children and women in Kyrgyzstan and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Kyrgyzstan MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Kyrgyzstan;

• To furnish data needed for monitoring progress toward national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;

• To generate behavioural and attitudinal data not available in other data sources.

Geographic coverage

The sample for the Kyrgyz Republic MICS 2018 was designed to provide estimates at the national/area/sub-population level, for urban and rural areas. Specifically, the sample for the Kyrgyz Republic MICS 2018 survey included 7 regions and two cities of the country: Batken, Jalal-abad, Issyk-kul, Naryn, Talas, Chui region and Bishkek, Osh cities.

Analysis unit

• Individuals

• Households

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years, and mothers (or caretakers) of children 0 to 17 years living in the houshold. Additionally a basic skills assessment was administered to children age 7 - 14 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A two-stage, stratified cluster sampling approach was used for the selection of the survey sample. The sampling frame was based on the 2009 Country Census of Population and Housing. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs) defined for the census enumeration. After conducting the listing of households in the sample enumeration areas, in a random systematic sample of 20 households was selected in each EA.

SAMPLE SIZE AND SAMPLE ALLOCATION

The overall sample size for the 2018 Kyrgyz Republic MICS was calculated as 7,200 households. For the calculation of the sample size, the key indicator used was the underweight prevalence among children age 0-4 years. Since the survey results are tabulated at the regional level, it was necessary to determine the minimum sample size for each region. Variables considered to determine the minimum sample size for the region: underweight prevalence, design effect, and mean household size (more details are provided in Appendix A in the report available in related materials.

The estimated sample size requirements for obtaining a relative margin of error of 10% for stunting prevalence of children under-five (with a 2014 estimate of 13%, and calculated sample size of 6,858 households). It is also necessary to determine the sample size for each region, although sometimes the requirements for the level of precision are relaxed for sub-national domains. So, all regional level sample size estimates were also done for regions of the Kyrgyz Republic for stunting children (calculated sample size of 7,466 households).

It was also desired to have about minimum of 70 and max 110 "Children age 12-23 months" in every region (only 60 reserved for Osh city). Based on a review of the 2014 results, and above requirements, it was decided to have a minimum of sample size of 400 households and a maximum sample size of 1,300 HHs for Bishkek. These calculations resulted a final sample size of 7,200 households within 360 clusters.

Within each region, the sample EAs are allocated to the 30% urban and 70% rural strata proportionately to the number of households in each stratum, except for two urban strata Bishkek and Osh city since they do not have any rural strata. The purpose of this disproportionate allocation is to have more cases in urban domains of such regions since their actual proportion of rural is very high already. This allocation of the sample results in an urban sample of 174 sample EAs and 3,480 households, and a rural sample of 186 EAs and 3,720 households, which should be sufficient for providing reliable estimates for the urban and rural domain at the national level.

SELECTION OF ENUMERATION AREAS (CLUSTERS)

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the 2009 Census frame. The first stage of sampling was thus completed by selecting the required number of sample EAs from each of the nine regions, separately for the urban and rural strata.

LISTING ACTIVITIES

Given that there had been many changes in the households enumerated in the 2009 Census, a new listing of households was conducted in all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were trained to visit all the selected enumeration areas and list all households in each enumeration area. Listing of households and enumeration areas was done by the National Statistical Committee from May to July 2018. One team was trained in each area. The segmentation procedures were applied in only two of the enumeration areas with large size in the city of Bishkek. EAs were divided in almost three equal size segments and one of them was selected randomly in which full listing and selection procedures were implemented.

SELECTION OF HOUSEHOLDS

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the National Statistical Committee, where the selection of 20 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a questionnaire for individual women administered in each household to all women age 15-49 years; 3) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 4) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

Additionally, for all children age 0-2 years with a completed Questionnaire for Children Under Five, the Questionnaire Form for Vaccination Records, was used to record vaccinations from medical vaccinations card (form No 63).

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, availability of water and soup, measured the weights and heights of children age under 5 years. Details and findings of these observations and measurements are provided in the respective sections of the report. Further, the questionnaire for children age 5-17 years included basic skills that are necessary for learning (reading and mathematics assessment) administered to children age 7-14 years.

The questionnaires were based on the MICS6 standard questionnaires.2 From the MICS6 model Russian version, the questionnaires were customised and translated into the Kyrgyz language and were pre-tested in the Chui region and Bishkek during May, 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the central office of National Statistical Committee via the Internet File Streaming System (IFSS) integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 24. Model syntax and tabulation plan developed by UNICEF were customised and used for this purpose.

Response rate

Of 7,200 households selected for the sample, 7,065 were found occupied. Of these, 6,968 were successfully interviewed for a household response rate of 98.6% percent.

In the interviewed households, 5,826 women age 15-49 years were identified. Of these, 5,742 women