This guide will provide resources on Leadership and Communication. This research guide is not a comprehensive listing of sources, but is intended to be a starting point from which employees can begin their research according to their specific needs. https://dhs-gov.libguides.com/c.php?g=1047434

This Guide is intended to help stakeholders understand the EAB’s role in promoting, operationalizing and supporting EA in the DHS enterprise. The EAB serves as a conduit for marshalling and channeling EA guidance and services to DHS programs and their architecture content developers. These content developers, in collaboration with Headquarters, can then successfully develop program artifacts to meet ALF requirements and timelines. The EAB also helps stakeholders to identify and address technical and programmatic risks and issues. These risks are identified and addressed in conjunction with management oversight entities such as the Acquisition Review Team (ART) and Acquisition Review Board (ARB).

Abstract

The 2010 NEDS is similar to the 2004 Nigeria DHS EdData Survey (NDES) in that it was designed to provide information on education for children age 4–16, focusing on factors influencing household decisions about children’s schooling. The survey gathers information on adult educational attainment, children’s characteristics and rates of school attendance, absenteeism among primary school pupils and secondary school students, household expenditures on schooling and other contributions to schooling, and parents’/guardians’ perceptions of schooling, among other topics.The 2010 NEDS was linked to the 2008 Nigeria Demographic and Health Survey (NDHS) in order to collect additional education data on a subset of the households (those with children age 2–14) surveyed in the 2008 Nigeria DHS survey. The 2008 NDHS, for which data collection was carried out from June to October 2008, was the fourth DHS conducted in Nigeria (previous surveys were implemented in 1990, 1999, and 2003).

The goal of the 2010 NEDS was to follow up with a subset of approximately 30,000 households from the 2008 NDHS survey. However, the 2008 NDHS sample shows that of the 34,070 households interviewed, only 20,823 had eligible children age 2–14. To make statistically significant observations at the State level, 1,700 children per State and the Federal Capital Territory (FCT) were needed. It was estimated that an additional 7,300 households would be required to meet the total number of eligible children needed. To bring the sample size up to the required target, additional households were screened and added to the overall sample. However, these households did not have the NDHS questionnaire administered. Thus, the two surveys were statistically linked to create some data used to produce the results presented in this report, but for some households, data were imputed or not included.

Geographic coverage

National

Analysis unit

Households Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The eligible households for the 2010 NEDS are the same as those households in the 2008 NDHS sample for which interviews were completed and in which there is at least one child age 2-14, inclusive. In the 2008 NDHS, 34,070 households were successfully interviewed, and the goal here was to perform a follow-up NEDS on a subset of approximately 30,000 households. However, records from the 2008 NDHS sample showed that only 20,823 had children age 4-16. Therefore, to bring the sample size up to the required number of children, additional households were screened from the NDHS clusters.

The first step was to use the NDHS data to determine eligibility based on the presence of a child age 2-14. Second, based on a series of precision and power calculations, RTI determined that the final sample size should yield approximately 790 households per State to allow statistical significance for reporting at the State level, resulting in a total completed sample size of 790 × 37 = 29,230. This calculation was driven by desired estimates of precision, analytic goals, and available resources. To achieve the target number of households with completed interviews, we increased the final number of desired interviews to accommodate expected attrition factors such as unlocatable addresses, eligibility issues, and non-response or refusal. Third, to reach the target sample size, we selected additional samples from households that had been listed by NDHS but had not been sampled and visited for interviews. The final number of households with completed interviews was 26,934 slightly lower than the original target, but sufficient to yield interview data for 71,567 children, well above the targeted number of 1,700 children per State.

Mode of data collection

Face-to-face [f2f]

Research instrument

The four questionnaires used in the 2004 Nigeria DHS EdData Survey (NDES)— 1. Household Questionnaire 2. Parent/Guardian Questionnaire 3. Eligible Child Questionnaire 4. Independent Child Questionnaire—formed the basis for the 2010 NEDS questionnaires. These are all available in Appendix D of the survey report available under External Resources.

More than 90 percent of the questionnaires remained the same; for cases where there was a clear justification or a need for a change in item formulation or a specific requirement for additional items, these were updated accordingly. A one day workshop was convened with the NEDS Implementation Team and the NDES Advisory Committee to review the instruments and identify any needed revisions, additions, or deletions. Efforts were made to collect data to ease integration of the 2010 NEDS data into the FMOE’s national education management information system. Instrument issues that were identified as being problematic in the 2004 NDES as well as items identified as potentially confusing or difficult were proposed for revision. Issues that USAID, DFID, FMOE, and other stakeholders identified as being essential but not included in the 2004 NDES questionnaires were proposed for incorporation into the 2010 NEDS instruments, with USAID serving as the final arbiter regarding questionnaire revisions and content.

General revisions accepted into the questionnaires included the following: - A separation of all questions related to secondary education into junior secondary and senior secondary to reflect the UBE policy - Administration of school-based questions for children identified as attending pre-school - Inclusion of questions on disabilities of children and parents - Additional questions on Islamic schooling - Revision to the literacy question administration to assess English literacy for children attending school - Some additional questions on delivery of UBE under the financial questions section

Upon completion of revisions to the English-language questionnaires, the instruments were translated and adapted by local translators into three languages—Hausa, Igbo, and Yoruba—and then back-translated into English to ensure accuracy of the translation. After the questionnaires were finalized, training materials used in the 2004 NDES and developed by Macro International, which included training guides, data collection manuals, and field observation materials, were reviewed. The materials were updated to reflect changes in the questionnaires. In addition, the procedures as described in the manuals and guides were carefully reviewed. Adjustments were made, where needed, based on experience on large-scale survey and lessons learned from the 2004 NDES and the 2008 NDHS, to ensure the highest quality data capture.

Cleaning operations

Data processing for the 2010 NEDS occurred concurrently with data collection. Completed questionnaires were retrieved by the field coordinators/trainers and delivered to NPC in standard envelops, labeled with the sample identification, team, and State name. The shipment also contained a written summary of any issues detected during the data collection process. The questionnaire administrators logged the receipt of the questionnaires, acknowledged the list of issues, and acted upon them if required. The editors performed an initial check on the questionnaires, performed any coding of open-ended questions (with possible assistance from the data entry operators), and left them available to be assigned to the data entry operators. The data entry operators entered the data into the system, with the support of the editors for erroneous or unclear data.

Experienced data entry personnel were recruited from those who have performed data entry activities for NPC on previous studies. The data entry teams composed a data entry coordinator, supervisor and operators. Data entry coordinators oversaw the entire data entry process from programming and training to final data cleaning, made assignments, tracked progress, and ensured the quality and timeliness of the data entry process. Data entry supervisors were on hand at all times to ensure that proper procedures were followed and to help editors resolve any uncovered inconsistencies. The supervisors controlled incoming questionnaires, assigned batches of questionnaires to the data entry operators, and managed their progress. Approximately 30 clerks were recruited and trained as data entry operators to enter all completed questionnaires and to perform the secondary entry for data verification. Editors worked with the data entry operators to review information flagged as “erroneous” or “dubious” in the data entry process and provided follow up and resolution for those anomalies.

The data entry program developed for the 2004 NDES was revised to reflect the revisions in the 2010 NEDS questionnaire. The electronic data entry and reporting system ensured internal consistency and inconsistency checks.

Response rate

A very high overall response rate of 97.9 percent was achieved with interviews completed in 26,934 households out of a total of 27,512 occupied households from the original sample of 28,624 households. The response rates did not vary significantly by urban–rural (98.5 percent versus 97.6 percent, respectively). The response rates for parent/guardians and children were even higher, and the rate for independent children was slightly lower than the overall sample rate, 97.4 percent. In all these cases, the urban/rural differences were negligible.

Sampling error estimates

Estimates derived from a sample survey are affected by two types of errors: (1) non-sampling errors and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as

This guide brings together online resources that contain U.S. government documents. Some are freely available to anyone with Internet access. Others include subscription databases accessible with a DHS device.

The Arlington Profile combines countywide data sources and provides a comprehensive outlook of the most current data on population, housing, employment, development, transportation, and community services. These datasets are used to obtain an understanding of community, plan future services/needs, guide policy decisions, and secure grant funding. A PDF Version of the Arlington Profile can be accessed on the Arlington County website.

This SAS macro generates childhood mortality estimates (neonatal, post-neonatal, infant (1q0), child (4q1) and under-five (5q0) mortality) and standard errors based on birth histories reported by women during a household survey. We have made the SAS macro flexible enough to accommodate a range of calculation specifications including multi-stage sampling frames, and simple random samples or censuses. Childhood mortality rates are the component death probabilities of dying before a specific age. This SAS macro is based on a macro built by Keith Purvis at MeasureDHS. His method is described in Estimating Sampling Errors of Means, Total Fertility, and Childhood Mortality Rates Using SAS (www.measuredhs.com/pubs/pdf/OD17/OD17.pdf, section 4). More information about Childhood Mortality Estimation can also be found in the Guide to DHS Statistics (www.measuredhs.com/pubs/pdf/DHSG1/Guide_DHS_Statistics.pdf, page 93). We allow the user to specify whether childhood mortality calculations should be based on 5 or 10 years of birth histories, when the birth history window ends, and how to handle age of death with it is reported in whole months (rather than days). The user can also calculate mortality rates within sub-populations, and take account of a complex survey design (unequal probability and cluster samples). Finally, this SAS program is designed to read data in a number of different formats.

Reports, significant correspondence, drafts, received comments, and related materials responding to “fundamental classification guidance review” as required by Executive Order 13526 Section 1.9.

This dataset contains locations and attributes of rehabilitation hospitals licensed by the state of Wisconsin. This dataset is derived from the ‘REHABILITATION’ subtype of the ‘HOSPITALS’ type dataset. The data are used for planning, management and analysis by Wisconsin Department of Health Services staff and by other government agencies. For more information please visit the Wisconsin Department of Health Services website: https://www.dhs.wisconsin.gov/guide/hospital.htm

Abstract

The 1991 Indonesia Demographic and Health Survey (IDHS) is a nationally representative survey of ever-married women age 15-49. It was conducted between May and July 1991. The survey was designed to provide information on levels and trends of fertility, infant and child mortality, family planning and maternal and child health. The IDHS was carried out as collaboration between the Central Bureau of Statistics, the National Family Planning Coordinating Board, and the Ministry of Health. The IDHS is follow-on to the National Indonesia Contraceptive Prevalence Survey conducted in 1987.

The DHS program has four general objectives: - To provide participating countries with data and analysis useful for informed policy choices; - To expand the international population and health database; - To advance survey methodology; and - To help develop in participating countries the technical skills and resources necessary to conduct demographic and health surveys.

In 1987 the National Indonesia Contraceptive Prevalence Survey (NICPS) was conducted in 20 of the 27 provinces in Indonesia, as part of Phase I of the DHS program. This survey did not include questions related to health since the Central Bureau of Statistics (CBS) had collected that information in the 1987 National Socioeconomic Household Survey (SUSENAS). The 1991 Indonesia Demographic and Health Survey (IDHS) was conducted in all 27 provinces of Indonesia as part of Phase II of the DHS program. The IDHS received financial assistance from several sources.

The 1991 IDHS was specifically designed to meet the following objectives: - To provide data concerning fertility, family planning, and maternal and child health that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs; - To measure changes in fertility and contraceptive prevalence rates and at the same time study factors which affect the change, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception; - To measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (BKKBN) has divided these provinces into three regions as follows:

• Java-Bali: Jakarta, West Java, Central Java, Yogyakarta, East Java, and Bali
• Outer Java-Bali I: Aceh, North Sumatra, West Sumatra, South Sumatra, Lampung, West Kalimantan, South Kalimantan, North Sulawesi, South Sulawesi, and West Nusa Tenggara
• Outer Java-Bali II: Riau, Jambi, Bengkulu, East Nusa Tenggara, East Timor, Central Kalimantan, East Kalimantan, Central Sulawesi, Southeast Sulawesi, Maluku, and Irian Jaya.

The 1990 Population Census of Indonesia shows that Java-Bali contains about 62 percent of the national population, while Outer Java-Bali I contains 27 percent and Outer Java-Bali II contains 11 percent. The sample for the Indonesia DHS survey was designed to produce reliable estimates of contraceptive prevalence and several other major survey variables for each of the 27 provinces and for urban and rural areas of the three regions.

In order to accomplish this goal, approximately 1500 to 2000 households were selected in each of the provinces in Java-Bali, 1000 households in each of the ten provinces in Outer Java-Bali I, and 500 households in each of the 11 provinces in Outer Java-Bali II for a total of 28,000 households. With an average of 0.8 eligible women (ever-married women age 15-49) per selected household, the 28,000 households were expected to yield approximately 23,000 individual interviews.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The DHS model "A" questionnaire and manuals were modified to meet the requirements of measuring family planning and health program attainment, and were translated into Bahasa Indonesia.

Cleaning operations

The first stage of data editing was done by the field editors who checked the completed questionnaires for completeness and accuracy. Field supervisors also checked the questionnaires. They were then sent to the central office in Jakarta where they were edited again and open-ended questions were coded. The data were processed using 11 microcomputers and ISSA (Integrated System for Survey Analysis).

Data entry and editing were initiated almost immediately after the beginning of fieldwork. Simple range and skip errors were corrected at the data entry stage. Secondary machine editing of the data was initiated as soon as sufficient questionnaires had been entered. The objective of the secondary editing was to detect and correct, if possible, inconsistencies in the data. All of the data were entered and edited by September 1991. A brief report containing preliminary survey results was published in November 1991.

Response rate

Of 28,141 households sampled, 27,109 were eligible to be interviewed (excluding those that were absent, vacant, or destroyed), and of these, 26,858 or 99 percent of eligible households were successfully interviewed. In the interviewed households, 23,470 eligible women were found and complete interviews were obtained with 98 percent of these women.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the IDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate analytically.

Sampling errors, on the other hand, can be measured statistically. The sample of women selected in the IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of standard error of 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 one can reasonably be assured that, apart from non-sampling errors, the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range of plus or minus two times the standard error of that statistic.

If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the IDHS sample design depended on stratification, stages and clusters. Consequently, it was necessary to utilize more complex formulas. The computer package CLUSTERS, developed by the International Statistical Institute for the World Fertility Survey, was used to assist in computing the sampling errors with the proper statistical methodology.

Note: See detailed estimate of sampling error calculation 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 year since birth - 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.

This dataset contains locations and attributes of hospitals licensed by the state of Wisconsin. The data are used for planning, management and analysis by Wisconsin Department of Health Services staff and by other government agencies. For additional attributes, please use the Wisconsin Hospitals Extended Attributes .csv file. The FACILITY_INTERNAL_ID field can be used to join the hospitals dataset with this .csv file.For more information please visit the Wisconsin Department of Health Services website: https://www.dhs.wisconsin.gov/guide/hospital.htm

This dataset for Rwanda combines preprocessed data from two data sources to create a rich source of information that can be used to develop a detailed understanding of poverty in the country.

Content

Demographic & Health Surveys Preprocessed Data

The dataset contains preprocessed data from the DHS for Rwanda. There are five main data files:

1. Household data
2. Household Member data
3. Births data
4. Cluster information
5. Geographic information (shapefile)

The first three files contain all the features required for a complete calculation of the Multidimensional Poverty Index. The household member and births data both contain reference IDs that can be used to join them to a particular household in the household datafile. The cluster file contains information required to link each household to a particular cluster, which in turn can be associated with geographic location information.

For detailed descriptions of the features available, refer to the DHS Recode Manual.

For details on how the preprocessed data was obtained, refer to Part III of my submission for the Kiva Challenge https://www.kaggle.com/taniaj/kiva-crowdfunding-targeting-poverty-sub-nat .

Financial Inclusion Insights Survey Preprocessed Data

The dataset also contains preprocessed data from the FII Survey for Rwanda. It contains features relevant for developing a financial deprivation indicator, such as whether the respondent has a formal bank account, whether they have formal savings and whether they have access to formal borrowing services.

For detailed descriptions of the features available, refer to the documentation.

For details on how the preprocessed data was obtained, refer to Part IV of my submission for the Kiva Challenge https://www.kaggle.com/taniaj/kiva-crowdfunding-adding-a-financial-dimension .

Other data

In addition to the main datafiles, there are a number of "_sjoin" files, which are intermediate steps in my kernel, where a spatial join was run locally and saved to be read back in due partly to sjoin not working on Kaggle servers, partly to save time.

Terms of Use

Please refer to the following pages for the terms of use:

1. DHS Program Terms of Use
2. Intermedia Terms of Use

Acknowledgements

The original data was provided by:

1. The Demographic & Health Surveys Program, USAID
2. The Financial Inclusion Insights Program, Intermedia

Inspiration

This dataset was added for use in the Data Science for Good: Kiva Crowdfunding challenge

Update Frequency: Update frequency: Datasets are refreshed every night to ensure the most current information is available. Even if there are no changes, the data will be updated nightly.

Locations of community living arrangement facilities within Milwaukee County, as recorded by the Wisconsin Department of Health Services and Wisconsin Department of Children and Families. Locations within Milwaukee City limits have been separated into their own layers. https://www.dhs.wisconsin.gov/guide/cbrf.htm https://www.dhs.wisconsin.gov/guide/afh.htm http://dcf.wisconsin.gov/childrenresidential/directories/CW-Directories.HTM

This Enterprise Architecture Board (EAB) Guide is designed to address several major purposes:rn• EAB Process Overview. Help all DHS personnel—especially leadership, program personnel and EAB stakeholders —understand the role of the EAB in supporting Enterprise Architecture (EA) and EA stakeholders within DHS, as well as for DHS enterprise processes.rn• Practitioners’ Guidance. Assist DHS personnel in understanding, aligning their activities with, preparing for, and executing the EAB process.rn• EAB Outreach, Support and Reviews. The EAB’s primary operational activity is planning and performing Reviews. EAB Reviews are comprehensive and right-sized to their position in a specific program’s lifecycle. They support critical recommendations and decisions at key points for managing acquisitions, investments, and capabilities, primarily within the Acquisition Lifecycle Framework (ALF), and specifically prior to an Acquisition Decision Event (ADE). The EAB initiates outreach, provides expert guidance and support to program stakeholders, assesses inputs and artifacts, and provides recommendations.

Abstract

The National Family Health Survey (NFHS) is a large-scale, multi-round survey conducted in a representative sample of households throughout India. Four rounds of the survey have been conducted in 1992-93, 1998-99, 2005-06, and 2015-16. The fifth round of the survey (2019-2020) is currently in the field. All of the surveys are part of the Demographic and Health Surveys (DHS) Program. The surveys provide information on population, health, and nutrition at the national and state level. Since 2015-16, the surveys have also provided information at the district level. Some of the major topics included in NFHS-4 (2015-16) are fertility, infant and child mortality, family planning, maternal and reproductive health, child vaccinations, prevalence and treatment of childhood diseases, nutrition, women’s empowerment, domestic violence, marriage, sexual activity, employment, anemia, anthropometry, HIV/AIDS knowledge and testing, tobacco and alcohol use, biomarker tests (anthropometry, anemia, HIV, blood pressure, and blood glucose), and water, sanitation, and hygiene. The primary objective of the NFHS surveys is to provide essential data on health and family welfare, as well as emerging issues in these areas. The information collected through the NFHS surveys is intended to assist policymakers and program managers in setting benchmarks and examining progress over time in India’s health sector. The Ministry of Health and Family Welfare (MOHFW), Government of India, designated the International Institute for Population Sciences (IIPS), Mumbai, as the agency responsible for providing coordination and technical guidance for all of the surveys. IIPS has collaborated with a large number of field agencies for survey implementation. The Demographic and Health Surveys Program has provided technical assistance for all of the surveys.

Documentation

You can access the data through the DHS website. Data files are available in the following five formats:

• Hierarchical CSPro file
• Flat files: ASCII data with syntax, Stata, SPSS, SAS

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All datasets are distributed in archived ZIP files that include the data file and its associated documentation. The DHS Program is authorized to distribute, at no cost, unrestricted survey data files for legitimate academic research. Registration is required to access the data.

Additional information about the surveys is available on the India page on the DHS Program website. This page provides a list of surveys and reports, plus Country Quickstats for India, and it is the gateway to accessing more information about the India surveys and datasets.

Methodology

2015-16 National Family Health Survey (NFHS-4): Fieldwork for NFHS-4 was conducted in two phases, from January 2015 to December 2016. The fieldwork was conducted by 14 field agencies, including three Population Research Centers. Laboratory testing for HIV was done by seven laboratories throughout India. NFHS-4 collected information from a nationally representative sample of 601,509 households, 699,686 women age 15-49, and 112,122 men age 15-54. The survey covered all 29 states, 7 Union Territories, and 640 districts in India.

Funding for the survey was provided by the Ministry of Health and Family Welfare, Government of India; the United States Agency for International Development (USAID); UKAID/DFID; the Bill & Melinda Gates Foundation; UNICEF; the United Nations Population Fund (UNFPA); and the MacArthur Foundation. Technical Assistance for NFHS-4 was provided by Macro International, Maryland, USA.

2005-06 National Family Health Survey (NFHS-3): Fieldwork for NFHS-3 was conducted in two phases, from November 2005 to August 2006. The fieldwork was conducted by 18 field agencies, including six Population Research Centers. Laboratory testing for HIV was done by the SRL Ranbaxy laboratory in Mumbai. NFHS-3 collected information from a nationally representative sample of 109,041 households, 124,385 women age 15-49, and 74,369 men age 15-54. The survey covered all 29 states. Only the Union Territories were not included.

Funding for the survey was provided by the United States Agency for International Development (USAID); United Kingdom Department for International Development (DFID); the Bill & Melinda Gates Foundation; UNICEF; the United Nations Population Fund (UNFPA); and the Government of India. Technical assistance for NFHS-3 was provided by Macro International, Maryland, USA.

1998-99 National Family Health Survey (NFHS-2): Fieldwork for NFHS-2 was conducted in two phases, from November 1998 to December 1999. The fieldwork was conducted by 13 field agencies, including five Population Research Centers. NFHS-2 collected information from a nationally representative sample of 91,196 households and 89,188 ever-married women age 15-49. Male interviews were not included in the survey. The survey cover

U.S. Citizenship and Immigration Services (USCIS) is committed to providing the best possible customer service before and after you file your case. You can read our customer guides for more information about available services such as information on average wait times and current case status. We generally process cases in the order that we receive them.

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%.

Datasets dating from 1986 to the present are available for 93 countries in which data were collect through Household questionnaires, Women's questionnaires, Men's questionnaires, Biomarker's questionnaires, and Fieldworker's questionnaires. The following data types are produced from the collected data : Household Recode, Household Member Recode, Individual Women's Recode, Births Recode, Children's Recode, Men's Recode, Couple's Recode, Geographic Data, Geospatial Covariates. To view surveys and available datasets go to https://dhsprogram.com/data/available-datasets.cfm. Access to datasets for DHS surveys and their supporting documents may be granted to individuals who register at https://dhsprogram.com/data/new-user-registration.cfm and create a new research project request.

Intervention coverage data for the regression analysis was extracted from LiST model.7LiST uses baseline data mainly from Demographic and Health Surveys (DHS),8Malaria Indicators Survey (MIS),9Multiple Indicator Cluster Surveys (MICS)10as shown in the table above.1http://stats.oecd.org/index.aspx?r=842905 (Accessed August 5, 2010).2http://cherg.org/projects/underlying_causes.html (Accessed August 5, 2010).3http://www.un.org/esa/population/ (Accessed August 5, 2010).4http://www.childinfo.org/mortality_igme.html (Accessed August 5, 2010).5http://www.healthmetricsandevaluation.org/resources/datasets/2010/mortality/results/child/child.html (Accessed August 5, ,2010).6http://www.jhsph.edu/dept/ih/IIP/list/manuals/AIMManual.pdf (Accessed August 5, 2010).7http://www.jhsph.edu/dept/ih/IIP/list/manuals.html for details intervention on coverage data sources (Accessed August 5, 2010).8http://www.measuredhs.com/start.cfm (Accessed August 5, 2010).9http://www.measuredhs.com/aboutsurveys/mis/start.cfm (Accessed August 5, 2010).10http://www.unicef.org/ceecis/resources_10594.html (Accessed August 5, 2010).

Abstract

The principal objective of the 2009-10 Timor-Leste Demographic and Health Survey (TLDHS) was to provide current and reliable data on fertility and family planning behavior, child mortality, adult and maternal mortality, child nutritional status, the utilization of maternal and child health services, and knowledge of HIV/AIDS.

The specific objectives of the survey were to: - collect data at the national level that will allow the calculation of key demographic rates; - analyze the direct and indirect factors that determine the levels and trends in fertility; - measure the level of contraceptive knowledge among women and men, and measure the level of practice among women by method, according to urban or rural residence; - collect quality data on family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under age 5, and maternity care indicators, including antenatal visits, assistance at delivery, and postnatal care; - collect data on infant and child mortality and on maternal and adult mortality; - obtain data on child feeding practices, including breastfeeding, and collect anthropometric measures to use in assessing the nutritional status of women and children; - collect information on knowledge of tuberculosis (TB), knowledge of the spread of TB, and attitudes towards people infected with TB among women and men; - collect data on use of treated and untreated mosquito nets, persons who sleep under the nets, use of drugs for malaria during pregnancy, and use of antimalarial drugs fortreatment of fever among children under age 5; - collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS, and evaluate patterns of recent behavior regarding condom use; - collect information on the sexual practices of women and men; their number of sexual partners in the past 12 months, and over their lifetime; risky sexual behavior, including condom use at last sexual intercourse; and payment for sex; - conduct hemoglobin testing on women age 15-49 and children age 6-59 months in a subsample of households selected for the survey to provide information on the prevalence of anemia among women of reproductive age and young children; - collect information on domestic violence

This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general, and on reproductive health in particular, at both the national and district levels. A long-term objective of the survey is to strengthen the technical capacity of government organizations to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2009-10 TLDHS provides national and district-level estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first Demographic and Health Survey (DHS) in Timor-Leste was done in 2003. Unlike the 2003 DHS, however, the 2009-10 TLDHS was conducted under the worldwide MEASURE DHS program, funded by the United States Agency for International Development (USAID) and with technical assistance provided by ICF Macro. Data from the 2009-10 TLDHS allow for comparison of information gathered over a longer period of time and add to the vast and growing international database on demographic and health variables.

The 2009-10 TLDHS supplements and complements the information collected through the censuses, updates the available information on population and health issues, and provides guidance in planning, implementing, monitoring and evaluating Timor-Leste's health programs. Further, the results of the survey assist in monitoring the progress made towards meeting the Millennium Development Goals (MDGs) and other international initiatives.

The 2009-10 TLDHS includes topics related to fertility levels and determinants; family planning; fertility preferences; infant, child, adult and maternal mortality; maternal and child health; nutrition; malaria; domestic violence; knowledge of HIV/AIDS and women's empowerment. The 2009-10 TLDHS for the first time also includes anemia testing among women age 15-49 and children age 6-59 months. As well as providing national estimates, the survey also provides disaggregated data at the level of various domains such as administrative district, as well as for urban and rural areas. This being the third survey of its kind in the country (after the 2002 MICS and the 2003 DHS), there is considerable trend information on demographic and reproductive health indicators.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary focus of the 2009-10 TLDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key variables for the 13 districts.

Sampling Frame

The TLDHS used the sampling frame provided by the list of census enumeration areas (EAs) with population and household information from the 2004 Population and Housing Census (PHC). Administratively, Timor-Leste is divided into 13 districts. Stratification is achieved by separating each of the 13 districts into urban and rural areas. In total, 26 sampling strata were created. Samples were selected independently in every stratum, through a two-stage selection process. Implicit stratification was achieved at each of the lower administrative levels by sorting the sampling frame before sample selection, both according to administrative units and also by using a probability proportional-to-size selection at the first stage of sampling. The implicit stratification also allowed for the proportional allocation of sample points at each of the lower administrative levels.

Sample Selection

At the first stage of sampling, 455 enumeration areas (116 urban areas and 339 rural areas) were selected with probability proportional to the EA size, which is the number of households residing in the EA at the time of the census. A complete household listing operation in all of the selected EAs is the usual procedure to provide a sampling frame for the second-stage selection of households. However, a complete household listing was only carried out in select clusters in Dili, Ermera, and Viqueque, where more than 20 percent of the households had been destroyed. In all other clusters, a complete household listing was not possible because the country does not have written boundary maps for clusters. Instead, using the GPS coordinate locations for structures in each selected cluster as provided for by the 2004 PHC, households were randomly selected using their Geographic Information System (GIS) location identification in the central office. A map for each cluster was then generated, marking the households to be surveyed with their location identification. The maps also contained all the other households, roads, rivers, and major landmarks for easier location of selected households in the field. To provide statistically reliable estimates of key demographic and health variables and to cater for nonresponse, 27 households each were selected.

The survey was designed to cover a nationally representative sample of 12,285 residential households, taking into account nonresponse; to obtain completed interviews of 11,800 women age 15-49 in every selected household; and to obtain completed interviews of 3,800 men age 15-49 in every third selected household.

Note: See detailed description of the sample design in Appendix A of the report presented in this documentation.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were administered in the TLDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard MEASURE DHS core questionnaires to reflect the population and health issues relevant to Timor-Leste based on a series of meetings with various stakeholders from government ministries and agencies, NGOs, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organized by NSD on March 10, 2009, in Dili. These questionnaires were then translated and back translated from English into the two main local languages-Tetum and Bahasa—and pretested prior to the main fieldwork to ensure that the original meanings of the questions were not lost in translation.

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. For children under age 18, survival status of the parents was determined. 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 of the house, ownership of various durable goods, and ownership of mosquito nets. Additionally, the Household Questionnaire was used to record height and weight measurements for women age 15-49 and children under age 5, and to list hemoglobin measurements for women age 15-49 and children age 6-59 months.

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

Abstract

The 2009 Samoa Demographic and Health Survey (SDHS) is a national survey covering all four regions of the country. The survey was designed to collect, analyze, and disseminate information on housing and household characteristics, education, maternal and child health, nutrition, fertility and family planning, gender, and knowledge and behaviour related to HIV/AIDS and sexually transmitted infections (STI).

The 2009 SDHS is the first DHS survey to be undertaken in Samoa both by the health sector and for an improved health system. The planning and implementation of the survey was carried out jointly by the Samoa Bureau of Statistics (SBS) and the Ministry of Health (MOH) with the technical assistance and guidance of ICF Macro. The Ministry of Women, Community and Social Development assisted by facilitating community support for the survey through villages and mayors.

The Samoa DHS is part of a worldwide survey program. The international MEASURE DHS program is designed to:

• Assist countries in conducting household sample surveys to periodically monitor changes in population, health, and nutrition. • Provide an international database that can be used by researchers investigating topics related to population, health, and nutrition.

As part of the international DHS program, surveys are being carried out in countries in Africa, Latin America and the Caribbean, Asia, Eastern Europe and the Middle East. Data from these surveys are used to better understand the population, health, and nutrition situation in Samoa.

Geographic coverage

National Regional Urban and Rural

Analysis unit

individual (woman aged 15-49, man aged 15-54), household

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and men aged 15-54 years

Kind of data

Sample survey data [ssd]

Sampling procedure

The Survey used a two-stage sample based on the 2006 Population and Housing Census (PHC) to allow reliable estimation of key demographic and health indicators such as fertility, contraceptive prevalence, and infant and child mortality for each of the four geographic regions in Samoa.

The population covered in the 2009 SDHS is the universe of all women age 15-49 in Samoa in a sample of 2,247 selected households. Every other household selected for the women's samplev was also eligible for the men's sample (men age 15-54).

The primary sampling unit (PSU) for the 2009 SDHS was the cluster. The first stage involved selecting clusters from the master sample frame (the 2006 Population and Housing Census). In the second stage, all the households in each selected cluster were listed. Households were then systematically selected from each cluster for participation in the survey. The design did not allow for replacement of clusters or households.

The sample was designed to include10 percent of the households in rural areas and 12 percent of the households in the urban areas. The sample was designed to permit detailed analysis of most indicators for the national level, for urban and rural areas separately, and for each of the four regions (Apia Urban Area, North West Upolu, Rest of Upolu, and Savaii). Overall, a total of 296 primary sampling units or clusters were selected, 104 in urban areas and 196 in the rural areas. Because Samoan household do not move frequently, a fresh household listing was not deemed to be necessary. Instead, a list from the November was used. In the urban clusters, 5 households were selected per cluster, whereas in the rural clusters, 10 households were selected per cluster. The number of clusters in each of the four geographical regions was calculated by diving the total allocated number of households by the sample taken of 5 for Apia Urban Area (the number of households of households in the urban EAs) and 10 for other regions (the number of households for rural EAs). In each region EAs were stratified by urban location first and then by rural location. Clusters were selected systematically, with propability proportional to size.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the SDHS: a Household Questionnaire, a Women's Questionnaire, and a Men's Questionnaire. The household and individual questionnaires were based on model survey instruments developed in the MEASURE DHS program. The model questionnaires were adapted to meet the current needs of Samoa. Each household selected for the SDHS was eligible for interview with the Household Questionnaire.

The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socio-economic status of the household. It was also used to identify the women and men who were eligible for the individual interview (i.e., women age 15-49 and men age 15-54).

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.) - birth history - antenatal, delivery, and postnatal care - knowledge, attitudes, and use of family planning methods - fertility preferences; marriage, woman's work, and husband's background characteristics - breastfeeding and infant feeding practices; vaccinations and childhood illnesses - childhood mortality - knowledge of and attitudes toward aids and other sexually transmitted diseases - knowledge of and attitudes toward tuberculosis - other health issues.

The Men's Questionnaire, administered to all men age 15-54 years living in every other Household (i.e. half of the sample households), collected information similar to that on the Women's Questionnaire but was shorter because it did not contain questions on reproductive history, maternal and child health, and nutrition.

After finalization of the questionnaires in English, they were translated into Samoan.

Cleaning operations

The processing of the SDHS results began shortly after the fieldwork started. Data editing was first done in the field by the field editors and supervisors. Completed and edited questionnaires for each cluster were packed and delivered to the SDHS centre at Motootua where they were entered and edited by data processing personnel. The data processing team was composed of 15 data entry operators, 1 data entry supervisor with 2 assistants and 7 office editors working in two shifts. Data operators and supervisors went through a one-week training programme with the technical assistance of ICF Macro. Data were entered using CSPro, a programme specially developed for use in household based surveys and censuses. All data were entered twice (100 percent verification). The concurrent processing of the data was an advantage because the survey technical staff were able to advise field teams of problems detected during the data entry using tables generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve their performances. The data entry and editing phase of the survey was completed in February 2010.

Response rate

The Samoa DHS 2009 selected 2,247 households for the sample, of which 2,066 were found occupied at the time of the fieldwork. Of these 1947 households were successfully interviewed yielding a household response rate of 94 percent.

In the households interviewed, a total of 3,033 eligible women aged 15-49 were identified, of whom 2657 were interviewed (respond rate of 88 percent). For eligible men aged 15-54 were identified in the sub-sample a total of 1,689 but only 1,307 were successfully interviewed (respond rate of 77 percent).

By area, response rates for households and women are slightly lower in urban (82 and 86 percent, respectively) than in rural areas (95 and 86 percent, respectively). For men on the other hand, response rate is higher in urban areas, 81 percent, than in rural areas, 76 percent.

The principal reason for non-response for eligible women and men was the failure to find them at home despite repeated visits to the households. The substantially lower response rates for men reflect the more frequent and longer absences of men from the home.

Response rates by region and the details on the calculation of the response rates can be found in Appendix A of the 2009 SDHS report.

Sampling error estimates

Sampling errors for the 2009 SDHS were calculated using 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.

Sampling errors for the 2009 SDHS are calculated for selected variables considered to be of primary interest. The results are presented in Appendix B of the 2009 SDHS report for the country as a whole, for urban and rural areas, and for the four geographical regions. Standard errors, design effect, relative standard errors and 95 percent confidence limits for each statistic of a variable are presented in the tables of the Appendix. Details on sampling error calculation are also provided.

In summary, for the total sample, the value of the DEFT, averaged over all variables, is 1.05. This means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.05 over that in an equivalent simple random sample.

Data appraisal

Data quality tables and were generated to assess the quality and reliability of the 2009 SDHS data.