Abstract

The data was collected using the High Frequency Survey (HFS), the new regional data collection tool & methodology launched in the Americas. The survey allowed for better reaching populations of interest with new remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest's demographic profile, difficulties during their journey, specific protection needs, access to documentation & regularization, health access, coverage of basic needs, coping capacity & negative mechanisms used, and well-being & local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Geographic coverage

Whole country

Analysis unit

Household

Universe

All people of concern.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the absence of a well-developed sampling-frame for forcibly displaced populations in the Americas, the High Frequency Survey employed a multi-frame sampling strategy where respondents entered the sample through one of three channels: (i) those who opt-in to complete an online self-administered version of the questionnaire which was widely circulated through refugee social media; (ii) persons identified through UNHCR and partner databases who were remotely-interviewed by phone; and (iii) random selection from the cases approaching UNHCR for registration or assistance. The total sample size was 3950 households. At the time of the survey, the population of concern was estimated at around 500000 individuals.

Mode of data collection

Other [oth]

Research instrument

Questionaire contained the following sections: journey, family composition, vulnerability, basic Needs, coping capacity,well-being,COVID-19 Impact.

Abstract

The Bangladesh Demographic and Health Survey (BDHS) is the first of this kind of study conducted in Bangladesh. It provides rapid feedback on key demographic and programmatic indicators to monitor the strength and weaknesses of the national family planning/MCH program. The wealth of information collected through the 1993-94 BDHS will be of immense value to the policymakers and program managers in order to strengthen future program policies and strategies.

The BDHS is intended to serve as a source of population and health data for policymakers and the research community. In general, the objectives of the BDHS are to: - asses the overall demographic situation in Bangladesh, - assist in the evaluation of the population and health programs in Bangladesh, and - advance survey methodology.

More specifically, the BDHS was designed to: - provide data on the family planning and fertility behavior of the Bangladesh population to evaluate the national family planning programs, - measure changes in fertility and contraceptive prevalence and, at the same time, study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding patterns, and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Bangladesh.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 10-49
• Men

Kind of data

Sample survey data

Sampling procedure

Bangladesh is divided into five administrative divisions, 64 districts (zillas), and 489 thanas. In rural areas, thanas are divided into unions and then mauzas, an administrative land unit. Urban areas are divided into wards and then mahallas. The 1993-94 BDHS employed a nationally-representative, two-stage sample. It was selected from the Integrated Multi-Purpose Master Sample (IMPS), newly created by the Bangladesh Bureau of Statistics. The IMPS is based on 1991 census data. Each of the five divisions was stratified into three groups: 1) statistical metropolitan areas (SMAs) 2) municipalities (other urban areas), and 3) rural areas. In rural areas, the primary sampling unit was the mauza, while in urban areas, it was the mahalla. Because the primary sampling units in the IMPS were selected with probability proportional to size from the 1991 census frame, the units for the BDHS were sub-selected from the IMPS with equal probability to make the BDHS selection equivalent to selection with probability proportional to size. A total of 304 primary sampling units were selected for the BDHS (30 in SMAs, 40 in municipalities, and 234 in rural areas), out of the 372 in the IMPS. Fieldwork in three sample points was not possible, so a total of 301 points were covered in the survey.

Since one objective of the BDHS is to provide separate survey estimates for each division as well as for urban and rural areas separately, it was necessary to increase the sampling rate for Barisal Division und for municipalities relative to the other divisions, SMAs, and rural areas. Thus, the BDHS sample is not self-weighting and weighting factors have been applied to the data in this report.

After the selection of the BDHS sample points, field staffs were trained by Mitra and Associates and conducted a household listing operation in September and October 1993. A systematic sample of households was then selected from these lists, with an average "take" of 25 households in the urban clusters and 37 households in rural clusters. Every second household was identified as selected for the husband's survey, meaning that, in addition to interviewing all ever-married women age 10-49, interviewers also interviewed the husband of any woman who was successfully interviewed. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 4,200 of their husbands.

Note: See detailed in APPENDIX A of the survey final report.

Sampling deviation

Data collected for women 10-49, indicators calculated for women 15-49. A total of 304 primary sampling units were selected, but fieldwork in 3 sample points was not possible.

Mode of data collection

Face-to-face

Research instrument

Four types of questionnaires were used for the BDHS: a Household Questionnaire, a Women's Questionnaire, a Husbands' Questionnaire, and a Service Availability Questionnaire. The contents of these questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. Additions and modifications to the model questionnaires were made during a series of meetings with representatives of various organizations, including the Asia Foundation, the Bangladesh Bureau of Statistics, the Cambridge Consulting Corporation, the Family Planning Association of Bangladesh, GTZ, the International Centre for Diarrhoeal Disease Research (ICDDR,B), Pathfinder International, Population Communications Services, the Population Council, the Social Marketing Company, UNFPA, UNICEF, University Research Corporation/Bangladesh, and the World Bank. The questionnaires were developed in English and then translated into and printed in Bangla.

The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his/her 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 individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.

The Women's Questionnaire was used to collect information from ever-married women age 10-49. These women were asked questions on the following topics: - Background characteristics (age, education, religion, etc.), - Reproductive history, - Knowledge and use of family planning methods, - Antenatal and delivery care, - Breastfeeding and weaning practices, - Vaccinations and health of children under age three, - Marriage, - Fertility preferences, and - Husband's background and respondent's work.

The Husbands' Questionnaire was used to interview the husbands of a subsample of women who were interviewed. The questionnaire included many of the same questions as the Women's Questionnaire, except that it omitted the detailed birth history, as well as the sections on maternal care, breastfeeding and child health.

The Service Availability Questionnaire was used to collect information on the family planning and health services available in and near the sampled areas. It consisted of a set of three questionnaires: one to collect data on characteristics of the community, one for interviewing family welfare visitors and one for interviewing family planning field workers, whether government or non-governent supported. One set of service availability questionnaires was to be completed in each cluster (sample point).

Cleaning operations

All questionnaires for the BDHS were returned to Dhaka for data processing at Mitra and Associates. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing inconsistencies found by the computer programs. One senior staff member, 1 data processing supervisor, questionnaire administrator, 2 office editors, and 5 data entry operators were responsible for the data processing operation. The data were processed on five microcomputers. The DHS data entry and editing programs were written in ISSA (Integrated System for Survey Analysis). Data processing commenced in early February and was completed by late April 1994.

Response rate

A total of 9,681 households were selected for the sample, of which 9,174 were successfully interviewed. The shortfall is primarily due to dwellings that were vacant, or in which the inhabitants had left for an extended period at the time they were visited by the interviewing teams. Of the 9,255 households that were occupied, 99 percent were successfully interviewed. In these households, 9,900 women were identified as eligible for the individual interview and interviews were completed for 9,640 or 97 percent of these. In one-half of the households that were selected for inclusion in the husbands' survey, 3,874 eligible husbands were identified, of which 3,284 or 85 percent were interviewed.

The principal reason for non-response among eligible women and men was failure to find them at home despite repeated visits to the household. The refusal rate was very low (less than one-tenth of one percent among women and husbands). Since the main reason for interviewing husbands was to match the information with that from their wives, survey procedures called for interviewers not to interview husbands of women who were not interviewed. Such cases account for about one-third of the non-response among husbands. Where husbands and wives were both interviewed, they were interviewed simultaneously but separately.

Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey final 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

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2007-2008 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2006. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey.

In the 1999-2000 wave, the NHANES includes more than 100 datasets. Most have been combined into three datasets for convenience. Each starts with the Demographic dataset and includes datasets of a specific type.

1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 1999-2000 (The base of the Demographic dataset + all data from medical examinations).

2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 1999-2000 (The base of the Demographic dataset + all data from medical laboratories).

3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 1999-2000 (The base of the Demographic dataset + all data from questionnaires)

Not all files from the 1999-2000 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e. some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.htm" Target="_blank">NHANES website at the CDC:

Examination: Dietary Interview (Individual Foods File)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Questionnaire: Analgesics Pain Relievers
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications

Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.

Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.htm" Target="_blank">NHANES website.

Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities.

The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous.

Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation.

Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages.
Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated

The Thai Demographic and Health Survey (TDHS) was a nationally representative sample survey conducted from March through June 1988 to collect data on fertility, family planning, and child and maternal health. A total of 9,045 households and 6,775 ever-married women aged 15 to 49 were interviewed. Thai Demographic and Health Survey (TDHS) is carried out by the Institute of Population Studies (IPS) of Chulalongkorn University with the financial support from USAID through the Institute for Resource Development (IRD) at Westinghouse. The Institute of Population Studies was responsible for the overall implementation of the survey including sample design, preparation of field work, data collection and processing, and analysis of data. IPS has made available its personnel and office facilities to the project throughout the project duration. It serves as the headquarters for the survey. The Thai Demographic and Health Survey (TDHS) was undertaken for the main purpose of providing data concerning fertility, family planning and maternal and child health to program managers and policy makers to facilitate their evaluation and planning of programs, and to population and health researchers to assist in their efforts to document and analyze the demographic and health situation. It is intended to provide information both on topics for which comparable data is not available from previous nationally representative surveys as well as to update trends with respect to a number of indicators available from previous surveys, in particular the Longitudinal Study of Social Economic and Demographic Change in 1969-73, the Survey of Fertility in Thailand in 1975, the National Survey of Family Planning Practices, Fertility and Mortality in 1979, and the three Contraceptive Prevalence Surveys in 1978/79, 1981 and 1984.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Abstract

The data was collected using the High Frequency Survey (HFS), the new regional data collection tool & methodology launched in the Americas. The survey allowed for better reaching populations of interest with new remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest's demographic profile, difficulties during their journey, specific protection needs, access to documentation & regularization, health access, coverage of basic needs, coping capacity & negative mechanisms used, and well-being & local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Geographic coverage

National coverage

Analysis unit

Household

Universe

All people of concern.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the absence of a well-developed sampling-frame for forcibly displaced populations in the Americas, the High Frequency Survey employed a multi-frame sampling strategy where respondents entered the sample through one of three channels: (i) those who opt-in to complete an online self-administered version of the questionnaire which was widely circulated through refugee social media; (ii) persons identified through UNHCR and partner databases who were remotely-interviewed by phone; and (iii) random selection from the cases approaching UNHCR for registration or assistance. The total sample size was 129 households. At the time of the survey, the population of concern was estimated at around 11000 individuals.

Mode of data collection

Other [oth]

Research instrument

The questionnaire contained the following sections: journey, family composition, vulnerability, basic Needs, coping capacity, well-being, COVID-19 Impact.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The 60 years and over column of data refers to the age of the householder for the estimates of households, occupied housing units, owner-occupied housing units, and renter-occupied housing units lines..The age specified on the population 15 years and over, population 25 years and over, population 30 years and over, civilian population 18 years and over, civilian population 5 years and over, population 1 years and over, population 5 years and over, and population 16 years and over lines refer to the data shown in the "Total" column while the second column is limited to the population 60 years and over..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

About this dataset

Context

The dataset tabulates the Lake View population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Lake View. The dataset can be utilized to understand the population distribution of Lake View by age. For example, using this dataset, we can identify the largest age group in Lake View.

Key observations

The largest age group in Lake View, AR was for the group of age 50-54 years with a population of 53 (11.57%), according to the 2021 American Community Survey. At the same time, the smallest age group in Lake View, AR was the 35-39 years with a population of 7 (1.53%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Lake View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Lake View total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lake View Population by Age. You can refer the same here

This data collection supplies standard monthly labor force data as well as supplemental data on work experience, income, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 14 years old and older. Additional data are available concerning weeks worked and hours per week worked, reason not working full-time, total income and income components, and residence. Information on demographic characteristics, such as age, sex, race, educational attainment, marital status, veteran status, household relationship, and Hispanic origin, is available for each person in the household enumerated.

Abstract

The 2008-09 Kenya Demographic and Health Survey (KDHS) is a population and health survey that Kenya conducts every five years. It was designed to provide data to monitor the population and health situation in Kenya and also to be used as a follow-up to the previous KDHS surveys in 1989, 1993, 1998, and 2003.

From the current survey, information was collected 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; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The 2008-09 KDHS is the second survey to collect data on malaria and the use of mosquito nets, domestic violence, and HIV testing of adults.

The specific objectives of the 2008-09 KDHS were to: - Provide data, at the national and provincial levels, that allow the derivation of demographic rates, particularly fertility and childhood mortality rates, to be used to evaluate the achievements of the current national population policy for sustainable development - Measure changes in fertility and contraceptive prevalence use and study the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and other important social and economic factors - Examine the basic indicators of maternal and child health in Kenya, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, use of immunisation services, use of mosquito nets, and treatment of children and pregnant women for malaria - Describe the patterns of knowledge and behaviour related to the transmission of HIV/AIDS and other sexually transmitted infections - Estimate adult and maternal mortality ratios at the national level - Ascertain the extent and pattern of domestic violence and female genital cutting in the country - Estimate the prevalence of HIV infection at the national and provincial levels and by urban-rural residence, and use the data to corroborate the rates from the sentinel surveillance system

The 2008-09 KDHS information provides data to assist policymakers and programme implementers as they monitor and evaluate existing programmes and design new strategies for demographic, social, and health policies in Kenya. The data will be useful in many ways, including the monitoring of the country’s achievement of the Millennium Development Goals.

As in 2003, the 2008-09 KDHS survey was designed to cover the entire country, including the arid and semi-arid districts, and especially those areas in the northern part of the country that were not covered in the earlier KDHS surveys. The survey collected information on demographic and health issues from a sample of women at the reproductive age of 15-49 and from a sample of men age 15-54 years in a one-in-two subsample of households.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

The survey is household-based, and therefore the sample was drawn from the population residing in households in the country. A representative sample of 10,000 households was drawn for the 2008-09 KDHS. This sample was constructed to allow for separate estimates for key indicators for each of the eight provinces in Kenya, as well as for urban and rural areas separately. Compared with the other provinces, fewer households and clusters were surveyed in North Eastern province because of its sparse population. A deliberate attempt was made to oversample urban areas to get enough cases for analysis. As a result of these differing sample proportions, the KDHS sample is not self-weighting at the national level; consequently, all tables except those concerning response rates are based on weighted data.

The KNBS maintains master sampling frames for household-based surveys. The current one is the fourth National Sample Survey and Evaluation Programme (NASSEP IV), which was developed on the platform of a two-stage sample design. The 2008-09 KDHS adopted the same design, and the first stage involved selecting data collection points ('clusters') from the national master sample frame. A total of 400 clusters-133 urban and 267 rural-were selected from the master frame. The second stage of selection involved the systematic sampling of households from an updated list of households. The Bureau developed the NASSEP frame in 2002 from a list of enumeration areas covered in the 1999 population and housing census. A number of clusters were updated for various surveys to provide a more accurate selection of households. Included were some of the 2008-09 KDHS clusters that were updated prior to selection of households for the data collection.

All women age 15-49 years who were either usual residents or visitors present in sampled households on the night before the survey were eligible to be interviewed in the survey. In addition, in every second household selected for the survey, all men age 15-54 years were also eligible to be interviewed. All women and men living in the households selected for the Men's Questionnaire and eligible for the individual interview were asked to voluntarily 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 were used to collect the survey data: the Household, Women’s, and Men’s Questionnaires. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS programme that underwent only slight adjustments to reflect relevant issues in Kenya. Adjustment was done through a consultative process with all the relevant technical institutions, government agencies, and local and international organisations. The three questionnaires were then translated from English into Kiswahili and 10 other local languages (Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Maasai, Meru, Mijikenda, and Somali). The questionnaires were further refined after the pretest and training of the field staff.

In each of the sampled households, the Household Questionnaire was the first to be administered and was used to list all the usual members and visitors. 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 age 15-49 and men age 15-54 who were eligible for the individual interviews. The 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, walls, and roof of the house, ownership of various durable goods, ownership of agricultural land, ownership of domestic animals, and ownership and use of mosquito nets. In addition, this questionnaire was used to capture information on height and weight measurements of women age 15-49 years and children age five years and below, and, in households eligible for collection of blood samples, to record the respondents’ consent to voluntarily give blood samples. A detailed description of HIV testing procedures is given in Section 1.10 below.

The Women’s Questionnaire was used to capture information from all women age 15-49 years and covered the following topics: - Respondent’s background characteristics (e.g., education, residential history, media exposure) - Reproductive history - Knowledge and use of family planning methods - Antenatal, delivery, and postnatal care - Breastfeeding - Immunisation, nutrition, and childhood illnesses - Fertility preferences - Husband’s background characteristics and woman’s work - Marriage and sexual activity - Infant and child feeding practices - Childhood mortality - Awareness and behaviour about HIV/AIDS and other sexually transmitted diseases - Knowledge of tuberculosis - Health insurance - Adult and maternal mortality - Domestic violence - Female genital cutting

The set of questions on domestic violence sought to obtain information on women’s experience of violence. The questions were administered to one woman per household. In households with more eligible women, special procedures (use of a ‘Kish grid’) were followed to ensure that the woman interviewed about domestic violence was randomly selected.

The Men’s Questionnaire was administered to all men age 15-54 years living in every second household in the sample. The Men’s Questionnaire collected information similar to that collected in the Women’s Questionnaire, but it was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, and domestic violence.

Two pilot projects were conducted in 12 districts for the KDHS, the first from July 1-7, 2008, and the second from October 13-17, 2008, to test the questionnaires, which were written in English and then translated into eleven other languages. The pilot was repeated because the first pilot did not include the HIV blood testing component. Twelve teams (one for each language) were formed, each with one female interviewer, one male interviewer, and one health worker. A total of 260 households were covered in the pilots. The lessons learnt from the pilot surveys were used to finalise the survey instruments and set up strong, logistical arrangements to ensure the success of the survey.

Response

Abstract

The 2012-13 Pakistan Demographic and Health Survey was undertaken to provide current and reliable data on fertility and family planning, childhood mortality, maternal and child health, women’s and children’s nutritional status, women’s empowerment, domestic violence, and knowledge of HIV/AIDS. The survey was designed with the broad objective of providing policymakers with information to monitor and evaluate programmatic interventions based on empirical evidence.

The specific objectives of the survey are to: • collect high-quality data on topics such as fertility levels and preferences, contraceptive use, maternal and child health, infant (and especially neonatal) mortality levels, awareness regarding HIV/AIDS, and other indicators related to the Millennium Development Goals and the country’s Poverty Reduction Strategy Paper • investigate factors that affect maternal and neonatal morbidity and mortality (i.e., antenatal, delivery, and postnatal care) • provide information to address the evaluation needs of health and family planning programs for evidence-based planning • provide guidelines to program managers and policymakers that will allow them to effectively plan and implement future interventions

Geographic coverage

National coverage

Analysis unit

• Household
• Ever married women age 15-49
• Ever married men age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The primary objective of the 2012-13 PDHS is to provide reliable estimates of key fertility, family planning, maternal, and child health indicators at the national, provincial, and urban and rural levels. NIPS coordinated the design and selection of the sample with the Pakistan Bureau of Statistics. The sample for the 2012-13 PDHS represents the population of Pakistan excluding Azad Jammu and Kashmir, FATA, and restricted military and protected areas. The universe consists of all urban and rural areas of the four provinces of Pakistan and Gilgit Baltistan, defined as such in the 1998 Population Census. PBS developed the urban area frame. All urban cities and towns are divided into mutually exclusive, small areas, known as enumeration blocks, that were identifiable with maps. Each enumeration block consists of about 200 to 250 households on average, and blocks are further grouped into low-, middle-, and high-income categories. The urban area sampling frame consists of 26,543 enumeration blocks, updated through the economic census conducted in 2003. In rural areas, lists of villages/mouzas/dehs developed through the 1998 population census were used as the sample frame. In this frame, each village/mouza/deh is identifiable by its name. In Balochistan, Islamabad, and Gilgit Baltistan, urban areas were oversampled and proportions were adjusted by applying sampling weights during the analysis.

A sample size of 14,000 households was estimated to provide reasonable precision for the survey indicators. NIPS trained 43 PBS staff members to obtain fresh listings from 248 urban and 252 rural survey sample areas across the country. The household listing was carried out from August to December 2012.

The second stage of sampling involved selecting households. At each sampling point, 28 households were selected by applying a systematic sampling technique with a random start. This resulted in 14,000 households being selected (6,944 in urban areas and 7,056 in rural areas). The survey was carried out in a total of 498 areas. Two areas of Balochistan province (Punjgur and Dera Bugti) were dropped because of their deteriorating law and order situations. Overall, 24 areas (mostly in Balochistan) were replaced, mainly because of their adverse law and order situation.

Refer to Appendix B in the final report for details of sample design and implementation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012-13 PDHS used four types of questionnaires: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, and Community Questionnaire. The contents of the Household, Woman’s, and Man’s Questionnaires were based on model questionnaires developed by the MEASURE DHS program. However, the questionnaires were modified, in consultation with a broad spectrum of research institutions, government departments, and local and international organizations, to reflect issues relevant to the Pakistani population, including migration status, family planning, domestic violence, HIV/AIDS, and maternal and child health. A series of questionnaire design meetings were organized by NIPS, and discussions from these meetings were used to finalize the survey questionnaires. The questionnaires were then translated into Urdu and Sindhi and pretested, after which they were further refined. The questionnaires were presented to the Technical Advisory Committee for final approval.

The Household Questionnaire was used to list the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, marital status, education, and relationship to the head of the household. Data on current school attendance, migration status, and survivorship of parents among those under age 18 were also collected. The questionnaire also provided the opportunity to identify ever-married women and men age 15-49 who were eligible for individual interviews and children age 0-5 eligible for anthropometry measurements. The Household Questionnaire collected information on characteristics of the dwelling unit as well, such as the source of drinking water; type of toilet facilities; type of cooking fuel; materials used for the floor, roof, and walls of the house; and ownership of durable goods, agricultural land, livestock/farm animals/poultry, and mosquito nets.

The Woman’s Questionnaire was used to collect information from ever-married women age 15-49 on the following topics: • Background characteristics (education, literacy, native tongue, marital status, etc.) • Reproductive history • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Woman’s work and husband’s background characteristics • Infant and childhood mortality • Women’s decision making • Awareness about AIDS and other sexually transmitted infections • Other health issues (e.g., knowledge of tuberculosis and hepatitis, injection safety) • Domestic violence

Similarly, the Man’s Questionnaire, used to collect information from ever-married men age 15-49, covered the following topics: • Background characteristics • Knowledge and use of family planning methods • Fertility preferences • Employment and gender roles • Awareness about AIDS and other sexually transmitted infections • Other health issues

The Community Questionnaire, a brief form completed for each rural sample point, included questions about the availability of various types of health facilities and other services, particularly transportation, education, and communication facilities.

All elements of the PDHS data collection activities were pretested in June 2012. Three teams were formed for the pretest, each consisting of a supervisor, a male interviewer, and three female interviewers. One team worked in the Sukkur and Khairpur districts in the province of Sindh, another in the Peshawar and Charsadda districts in Khyber Pakhtunkhwa, and the third in the district of Rawalpindi in Punjab. Each team covered one rural and one urban non-sample area.

Cleaning operations

The processing of the 2012-13 PDHS data began simultaneously with the fieldwork. Completed questionnaires were edited and data entry was carried out immediately in the field by the field editors. The data were uploaded on the same day to enable retrieval in the central office at NIPS in Islamabad, and the Internet File Streaming System was used to transfer data from the field to the central office. The completed questionnaires were then returned periodically from the field to the NIPS office in Islamabad through a courier service, where the data were again edited and entered by data processing personnel specially trained for this task. Thus, all data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data offered a distinct advantage because of the assurance that the data were error-free and authentic. Moreover, the double entry of data enabled easy identification of errors and inconsistencies, which were resolved via comparisons with the paper questionnaire entries. The secondary editing of the data was completed in the first week of May 2013.

As noted, the PDHS used the CAFE system in the field for the first time. This application was developed and fully tested before teams were deployed in the field. Field editors were selected after careful screening from among the participants who attended the main training exercise. Seven-day training was arranged for field editors so that each editor could enter a sample cluster’s data under the supervision of NIPS senior staff, which enabled a better understanding of the CAFE system. The system was deemed efficient in capturing data immediately in the field and providing immediate feedback to the field teams. Early transfer of data back to the central office enabled the generation of field check tables on a regular basis, an efficient tool for monitoring the fieldwork.

Response rate

A total of 13,944 households were selected for the sample, of which

Abstract

Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

· Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

Analysis unit

Household. Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

Sampling deviation

-

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

Response Rates= 79%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. The Comparison Profiles include the following geographies: nation, all states (including DC and Puerto Rico), all metropolitan areas, all congressional districts, all counties, all places and all tracts. Comparison Profiles contain broad social, economic, housing, and demographic information. The data are presented as both counts and percentages. There are over 2,400 variables in this dataset.

These data include the individual responses for the City of Tempe Annual Community Survey conducted by ETC Institute. This dataset has two layers and includes both the weighted data and unweighted data. Weighting data is a statistical method in which datasets are adjusted through calculations in order to more accurately represent the population being studied. The weighted data are used in the final published PDF report.These data help determine priorities for the community as part of the City's on-going strategic planning process. Averaged Community Survey results are used as indicators for several city performance measures. The summary data for each performance measure is provided as an open dataset for that measure (separate from this dataset). The performance measures with indicators from the survey include the following (as of 2023):1. Safe and Secure Communities1.04 Fire Services Satisfaction1.06 Crime Reporting1.07 Police Services Satisfaction1.09 Victim of Crime1.10 Worry About Being a Victim1.11 Feeling Safe in City Facilities1.23 Feeling of Safety in Parks2. Strong Community Connections2.02 Customer Service Satisfaction2.04 City Website Satisfaction2.05 Online Services Satisfaction Rate2.15 Feeling Invited to Participate in City Decisions2.21 Satisfaction with Availability of City Information3. Quality of Life3.16 City Recreation, Arts, and Cultural Centers3.17 Community Services Programs3.19 Value of Special Events3.23 Right of Way Landscape Maintenance3.36 Quality of City Services4. Sustainable Growth & DevelopmentNo Performance Measures in this category presently relate directly to the Community Survey5. Financial Stability & VitalityNo Performance Measures in this category presently relate directly to the Community SurveyMethods:The survey is mailed to a random sample of households in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used. To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city. Additionally, demographic data were used to monitor the distribution of responses to ensure the responding population of each survey is representative of city population. Processing and Limitations:The location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city. The weighted data are used by the ETC Institute, in the final published PDF report.The 2023 Annual Community Survey report is available on data.tempe.gov or by visiting https://www.tempe.gov/government/strategic-management-and-innovation/signature-surveys-research-and-dataThe individual survey questions as well as the definition of the response scale (for example, 1 means “very dissatisfied” and 5 means “very satisfied”) are provided in the data dictionary.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData Dictionary

Abstract

The Ministry of Health and Social Welfare (MOHSW) initiated the 2004 Lesotho Demographic and Health Survey (LDHS) to collect population-based data to inform the Health Sector Reform Programme (2000-2009). The 2004 LDHS will assist in monitoring and evaluating the performance of the Health Sector Reform Programme since 2000 by providing data to be compared with data from the first baseline survey, which was conducted when the reform programme began. The LDHS survey will also provide crucial information to help define the targets for Phase II of the Health Sector Reform Programme (2005-2008). Additionally, the 2004 LDHS results will serve as the main source of key demographic indicators in Lesotho until the 2006 population census results are available.

The LDHS was conducted using a representative sample of women and men of reproductive age.

The specific objectives were to: - Provide data at national and district levels that allow the determination of demographic indicators, particularly fertility and childhood mortality rates; - Measure changes in fertility and contraceptive use and at the same time analyse the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding patterns, and important social and economic factors; - Examine the basic indicators of maternal and child health in Lesotho, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and immunisation coverage for children; - Describe the patterns of knowledge and behaviour related to the transmission of HIV/AIDS, other sexually transmitted infections, and tuberculosis; - Estimate adult and maternal mortality ratios at the national level; - Estimate the prevalence of anaemia among children, women and men, and the prevalence of HIV among women and men at the national and district levels.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The sample for the 2004 LDHS covered the household population. A representative probability sample of more than 9,000 households was selected for the 2004 LDHS sample. This sample was constructed to allow for separate estimates for key indicators in each of the ten districts in Lesotho, as well as for urban and rural areas separately.

The survey utilized a two-stage sample design. In the first stage, 405 clusters (109 in the urban and 296 in the rural areas) were selected from a list of enumeration areas from the 1996 Population Census frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey.

All women age 15-49 who were either permanent household residents in the 2004 LDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In addition, in every second household selected for the survey, all men age 15-59 years were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. In the households selected for the men's survey, height and weight measurements were taken for eligible women and children under five years of age. Additionally, eligible women, men, and children under age five were tested in the field for anaemia, and eligible women and men were asked for an additional blood sample for anonymous testing for HIV.

Note: See detailed sample implementation in the APPENDIX A of the final 2004 Lesotho Demographic and Health Survey Final Report.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used for the 2004 LDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. To reflect relevant issues in population and health in Lesotho, the questionnaires were adapted during a series of technical meetings with various stakeholders from government ministries and agencies, nongovernmental organizations and international donors. The final draft of the questionnaire was discussed at a large meeting of the LDHS Technical Committee organized by the MOHSW and BOS. The adapted questionnaires were translated from English into Sesotho and pretested during June 2004.

The Household Questionnaire was used to list all of the usual members and visitors in the selected households. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. Some basic information was also collected on the characteristics of each person listed, including age, sex, education, residence and emigration status, and relationship to the head of the household. For children under 18, survival status of the parents was determined. 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 access to health facilities. For households selected for the male survey subsample, the questionnaire was used to record height, weight, and haemoglobin measurements of women, men and children, and the respondents’ decision about whether to volunteer to give blood samples for HIV.

The Women’s Questionnaire was used to collect information from all women age 15-49. The women were asked questions on the following topics: - Background characteristics (education, residential history, media exposure, etc.) - Birth history and childhood mortality - Knowledge and use of family planning methods - Fertility preferences - Antenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Awareness and behaviour regarding AIDS, other sexually transmitted infections (STIs), and tuberculosis (TB) - Maternal mortality

The Men’s Questionnaire was administered to all men age 15-59 living in every other household in the 2004-05 LDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health, nutrition, and maternal mortality.

Geographic coordinates were collected for each EA in the 2004 LDHS.

Cleaning operations

The processing of the 2004 LDHS results began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to BOS headquarters, where they were entered and edited by data processing personnel who were specially trained for this task. The data processing personnel included two supervisors, two questionnaire administrators/office editors-who ensured that the expected number of questionnaires from each cluster was received-16 data entry operators, and two secondary editors. The concurrent processing of the data was an advantage because BOS was able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in May 2005.

Response rate

Response rates are important because high non-response may affect the reliability of the results. A total of 9,903 households were selected for the sample, of which 9,025 were found to be occupied during data collection. Of the 9,025 existing households, 8,592 were successfully interviewed, yielding a household response rate of 95 percent.

In these households, 7,522 women were identified as eligible for the individual interview. Interviews were completed with 94 percent of these women. Of the 3,305 eligible men identified, 85 percent were successfully interviewed. The response rate for urban women and men is somewhat higher than for rural respondents (96 percent compared with 94 percent for women and 88 percent compared with 84 percent for men). The principal reason for non-response among eligible women and men was the failure to find individuals at home despite repeated visits to the household. The lower response rate for men reflects the more frequent and longer absences of men from the household, principally because of employment and life style.

Response rates for the HIV testing component were lower than those for the interviews.

See summarized response rates in Table 1.2 of the Final Report.

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 2004 Lesotho Demographic and Health Survey (LSDHS) 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 2004 LSDHS 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

Abstract

The 2013 NDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). DHS surveys are designed to collect data on fertility, family planning, and maternal and child health; assist countries in monitoring changes in population, health, and nutrition; and provide an international database that can be used by researchers investigating topics related to population, health, and nutrition.

The overall objective of the survey is to provide demographic, socioeconomic, and health data necessary for policymaking, planning, monitoring, and evaluation of national health and population programmes. In addition, the survey measured the prevalence of anaemia, HIV, high blood glucose, and high blood pressure among adult women and men; assessed the prevalence of anaemia among children age 6-59 months; and collected anthropometric measurements to assess the nutritional status of women, men, and children.

A long-term objective of the survey is to strengthen the technical capacity of local organizations to plan, conduct, and process and analyse data from complex national population and health surveys. At the global level, the 2013 NDHS data are comparable with those from a number of DHS surveys conducted in other developing countries. The 2013 NDHS adds to the vast and growing international database on demographic and health-related variables.

Geographic coverage

National coverage

Analysis unit

• Households
• Children aged 0-5
• Women aged 15 to 49
• Men aged 15 to 64

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The primary focus of the 2013 NDHS 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. In addition, the sample was designed to provide estimates of most key variables for the 13 administrative regions.

Each of the administrative regions is subdivided into a number of constituencies (with an overall total of 107 constituencies). Each constituency is further subdivided into lower level administrative units. An enumeration area (EA) is the smallest identifiable entity without administrative specification, numbered sequentially within each constituency. Each EA is classified as urban or rural. The sampling frame used for the 2013 NDHS was the preliminary frame of the 2011 Namibia Population and Housing Census (NSA, 2013a). The sampling frame was a complete list of all EAs covering the whole country. Each EA is a geographical area covering an adequate number of households to serve as a counting unit for the population census. In rural areas, an EA is a natural village, part of a large village, or a group of small villages; in urban areas, an EA is usually a city block. The 2011 population census also produced a digitised map for each of the EAs that served as the means of identifying these areas.

The sample for the 2013 NDHS was a stratified sample selected in two stages. In the first stage, 554 EAs-269 in urban areas and 285 in rural areas-were selected with a stratified probability proportional to size selection from the sampling frame. The size of an EA is defined according to the number of households residing in the EA, as recorded in the 2011 Population and Housing Census. Stratification was achieved by separating every region into urban and rural areas. Therefore, the 13 regions were stratified into 26 sampling strata (13 rural strata and 13 urban strata). Samples were selected independently in every stratum, with a predetermined number of EAs selected. A complete household listing and mapping operation was carried out in all selected clusters. In the second stage, a fixed number of 20 households were selected in every urban and rural cluster according to equal probability systematic sampling.

Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis using the 2013 NDHS data to ensure the representativeness of the survey results at the national as well as the regional level. Since the 2013 NDHS sample was a two-stage stratified cluster sample, sampling probabilities were calculated separately for each sampling stage and for each cluster.

See Appendix A in the final report for details

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were administered in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Namibia at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organised by the MoHSS from September 25-28, 2012, in Windhoek. The questionnaires were then translated from English into the six main local languages—Afrikaans, Rukwangali, Oshiwambo, Damara/Nama, Otjiherero, and Silozi—and back translated into English. The questionnaires were finalised after the pretest, which took place from February 11-25, 2013.

The Household Questionnaire was used to list all usual household members as well as visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. In addition, the Household Questionnaire included questions on knowledge of malaria and use of mosquito nets by household members, along with questions regarding health expenditures. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and the interview on domestic violence. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. The results of tests assessing iodine levels were recorded as well.

In half of the survey households (the same households selected for the male survey), the Household Questionnaire was also used to record information on anthropometry and biomarker data collected from eligible respondents, as follows: • All eligible women and men age 15-64 were measured, weighed, and tested for anaemia and HIV. • All eligible women and men age 35-64 had their blood pressure and blood glucose measured. • All children age 0 to 59 months were measured and weighed. • All children age 6 to 59 months were tested for anaemia.

The Woman’s Questionnaire was also used to collect information from women age 50-64 living in half of the selected survey households on background characteristics, marriage and sexual activity, women’s work and husbands’ background characteristics, awareness and behaviour regarding AIDS and other STIs, and other health issues.

The Man’s Questionnaire was administered to all men age 15-64 living in half of the selected survey households. 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 or nutrition.

Cleaning operations

CSPro—a Windows-based integrated census and survey processing system that combines and replaces the ISSA and IMPS packages—was used for entry, editing, and tabulation of the NDHS data. Prior to data entry, a practical training session was provided by ICF International to all data entry staff. A total of 28 data processing personnel, including 17 data entry operators, one questionnaire administrator, two office editors, three secondary editors, two network technicians, two data processing supervisors, and one coordinator, were recruited and trained on administration of questionnaires and coding, data entry and verification, correction of questionnaires and provision of feedback, and secondary editing. NDHS data processing was formally launched during the week of June 22, 2013, at the National Statistics Agency Data Processing Centre in Windhoek. The data entry and editing phase of the survey was completed in January 2014.

Response rate

A total of 11,004 households were selected for the sample, of which 10,165 were found to be occupied during data collection. Of the occupied households, 9,849 were successfully interviewed, yielding a household response rate of 97 percent.

In these households, 9,940 women age 15-49 were identified as eligible for the individual interview. Interviews were completed with 9,176 women, yielding a response rate of 92 percent. In addition, in half of these households, 842 women age 50-64 were successfully interviewed; in this group of women, the response rate was 91 percent.

Of the 5,271 eligible men identified in the selected subsample of households, 4,481 (85 percent) were successfully interviewed.

Response rates were higher in rural than in urban areas, with the rural-urban difference more marked among men than among women.

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

Abstract

The 1993 Kenya Demographic and Health Survey (KDHS) was a nationally representative survey of 7,540 women age 15-49 and 2,336 men age 20-54. The KDHS was designed to provide information on levels and trends of fertility, infant and child mortality, family planning knowledge and use, maternal and child health, and knowledge of AIDS. In addition, the male survey obtained data on men's knowledge and attitudes towards family planning and awareness of AIDS. The data are intended for use by programme managers and policymakers to evaluate and improve family planning and matemal and child health programmes. Fieldwork for the KDHS took place from mid-February until mid-August 1993. All areas of Kenya were covered by the survey, except for seven northem districts which together contain less than four percent of the country's population.

The KDHS was conducted by the National Council for Population and Development (NCPD) and the Central Bureau of Statistics of the Government of Kenya. Macro International Inc. provided financial and technical assistance to the project through the intemational Demographic and Health Surveys (DHS) contract with the U.S. Agency for International Development.

OBJECTIVES

The KDHS is intended to serve as a source of population and health data for policymakers and the research community. It was designed as a follow-on to the 1989 KDHS, a national-level survey of similar size that was implemented by the same organisations. In general, the objectives of KDHS are to: - assess the overall demographic situation in Kenya, - assist in the evaluation of the population and health programmes in Kenya, - advance survey methodology, and - assist the NCPD to strengthen and improve its technical skills to conduct demographic and health surveys.

The KDHS was specifically designed to: - provide data on the family planning and fertility behaviour of the Kenyan population to enable the NCPD to evaluate and enhance the National Family Planning Programme, - measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding habits and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Kenya.

KEY FINDINGS

The 1993 KDHS reinforces evidence of a major decline in fertility which was first revealed by the findings of the 1989 KDHS. Fertility continues to decline and family planning use has increased. However, the disparity between knowledge and use of family planning remains quite wide. There are indications that infant and under five child mortality rates are increasing, which in part might be attributed to the increase in AIDS prevalence.

Geographic coverage

The 1993 KDHS sample is national in scope, with the exclusion of all three districts in North Eastern Province and four other northern districts (Samburu and Turkana in Rift Valley Province and Isiolo and 4 Marsabit in Eastern Province). Together the excluded areas account for less than 4 percent of Kenya's population.

Analysis unit

• Household
• Women age 15-49
• Men age 20-54
• Children under five

Universe

The population covered by the 1993 KDHS is defined as the universe of all women age 15-49 in Kenya and all husband age 20-54 living in the household.

Kind of data

Sample survey data

Sampling procedure

The sample for the 1993 KDHS was national in scope, with the exclusion of all three districts in Northeastern Province and four other northern districts (Isiolo and Marsabit from Eastern Province and Samburu and Turkana from Rift Valley Province). Together the excluded areas account for less than four percent of Kenya's population. The KDHS sample points were selected from a national master sample maintained by the Central Bureau of Statistics, the third National Sample Survey and Evaluation Programme (NASSEP-3), which is an improved version of NASSEP2 used in the 1989 survey. This master sample follows a two-stage design, stratified by urban-rural residence, and within the rural stratum, by individual district. In the first stage, 1989 census enumeration areas (EAs) were selected with probability proportional to size. The selected EAs were segmented into the expected number of standard-sized clusters to form NASSEP clusters. The entire master sample consists of 1,048 rural and 325 urban ~ sample points ("clusters"). A total of 536 clusters---92 urban and 444 rural--were selected for coverage in the KDHS. Of these, 520 were successfully covered. Sixteen clusters were inaccessible for various reasons.

As in the 1989 KDHS, selected districts were oversampled in the 1993 survey in order to produce more reliable estimates for certain variables at the district level. Fifteen districts were thus targetted in the 1993 KDHS: Bungoma, Kakamega, Kericho, Kilifi, Kisii, Machakos, Meru, Murang'a, Nakuru, Nandi, Nyeri, Siaya, South Nyanza, Taita-Taveta, and Uasin Gishu; in addition, Nairobi and Mombasa were also targetted. Although six of these districts were subdivided shortly before the sample design was finalised) the previous boundaries of these districts were used for the KDHS in order to maintain comparability with the 1989 survey. About 400 rural households were selected in each of these 15 districts, just over 1000 rural households in other districts, and about 18130 households in urban areas, for a total of almost 9,000 households. Due to this oversampling, the KDHS sample is not self-weighting at the national level.

After the selection of the KDHS sample points, fieldstaff from the Central Bureau of Statistics conducted a household listing operation in January and early February 1993, immediately prior to the launching of the fieldwork. A systematic sample of households was then selected from these lists, with an average "take" of 20 households in the urban clusters and 16 households in rural clusters, for a total of 8,864 households selected. Every other household was identified as selected for the male survey, meaning that, in addition to interviewing all women age 15-49, interviewers were to also interview all men age 20-54. It was expected that the sample would yield interviews with approximately 8,000 women age 15-49 and 2,500 men age 20-54.

Mode of data collection

Face-to-face

Research instrument

Four types of questionnaires were used for the KDHS: a Household Questionnaire, a Woman's Questionnaire, a Man's Questionnaire and a Services Availability Questionnaire. The contents of these questionnaires were based on the DHS Model B Questionnaire, which is designed for use in countries with low levels of contraceptive use. Additions and modifications to the model questionnaires were made during a series of meetings organised around specific topics or sections of the questionnaires (e.g., fertility, family planning). The NCPD invited staff from a variety of organisations to attend these meetings, including the Population Studies Research Institute and other departments of the University of Nairobi, the Woman's Bureau, and various units of the Ministry of Health. The questionnaires were developed in English and then translated into and printed in Kiswahili and eight of the most widely spoken local languages in Kenya (Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Meru, and Mijikenda).

a) The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his/her 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 individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.

b) The Woman's Questionnaire was used to collect information from women aged 15-49. These women were asked questions on the following topics: Background characteristics (age, education, religion, etc.), Reproductive history, Knowledge and use of family planning methods, Antenatal and delivery care, Breastfeeding and weaning practices, Vaccinations and health of children under age five, Marriage, Fertility preferences, Husband's background and respondent's work, Awareness of AIDS. In addition, interviewing teams measured the height and weight of children under age five (identified through the birth histories) and their mothers.

c) Information from a subsample of men aged 20-54 was collected using a Man's Questionnaire. Men were asked about their background characteristics, knowledge and use of family planning methods, marriage, fertility preferences, and awareness of AIDS.

d) The Services Availability Questionnaire was used to collect information on the health and family planning services obtained within the cluster areas. One service availability questionnaire was to be completed in each cluster.

Cleaning operations

All questionnaires for the KDHS were returned to the NCPD headquarters for data processing. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing errors found by the computer programs. One NCPD officer, one data processing supervisor, one questionnaire administrator, two office editors, and initially four data entry operators were responsible for the data processing operation. Due to attrition and the need to speed up data processing, another four data entry operators were later hired

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Abstract

The main purpose of a Household Income and Expenditure Survey (HIES) was to present high quality and representative national household data on income and expenditure in order to update Consumer Price Index (CPI), improve statistics on National Accounts and measure poverty within the country.

The main objectives of this survey - update the weight of each expenditure item (from COICOP) and obtain weights for the revision of the Consumer Price Index (CPI) for Funafuti - provide data on the household sectors contribution to the National Accounts - design the structure of consumption for food secutiry - To provide information on the nature and distribution of household income, expenditure and food consumption patterns household living standard useful for planning purposes - To provide information on economic activity of men and women to study gender issues - To generate the income distribution for poverty analysis

The 2010 Household Income and Expenditure Survey (HIES) is the third HIES that was conducted by the Central Statistics Division since Tuvalu gained political independence in 1978.

This survey deals mostly with expenditure and income on the cash side and non cash side (gift, home production). Moreover, a lot of information are collected:

at a household level: - goods possession - description of the dwelling - water tank capacity - fruits and vegetables in the garden - livestock

at an individual level: - education level - employment - health

Geographic coverage

National Coverage: Funafuti and /Outer islands.

Analysis unit

• Household level
• Individual level

Universe

The scope of the 2010 Household Income and Expenditure Survey (HIES) was all occupied households in Tuvalu. Households are the sampling unit, defined as a group of people (related or not) who pool their money, and cook and eat together. It is not the physical structure (dwelling) in which people live. HIES covered all persons who were considered to be usual residents of private dwellings (must have been living in Tuvalu for a period of 12-months, or have intention to live in Tuvalu for a period of 12-months in order to be included in the survey). Usual residents who are temporary away are included as well (e.g., for work or a holiday).

All the private household are included in the sampling frame. In each household selected, the current resident are surveyed, and people who are usual resident but are currently away (work, health, holydays reasons, or border student for example. If the household had been residing in Tuvalu for less than one year: - but intend to reside more than 12 months => he is included - do not intend to reside more than 12 months => out of scope.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tuvalu 2010 Household Income and Expenditure Survey (HIES) outputs breakdowns at the domain level which is Funafuti and Outer Islands. To achieve this, and to match the budget constraint, a third of the households were selected in both domains. It was decided that 33% (one third) sample was sufficient to achieve suitable levels of accuracy for key estimates in the survey. So the sample selection was spread proportionally across all the islands except Niulakita as it was considered too small. The selection method used is the simple random survey, meaning that within each domain households were directly selected from the population frame (which was the updated 2009 household listing). All islands were included in the selection except Niulakita that was excluded due to its remoteness, and size.

For selection purposes, in the outer island domain, each island was treated as a separate strata and independent samples were selected from each (one third). The strategy used was to list each dwelling on the island by their geographical position and run a systematic skip through the list to achieve the 33% sample. This approach assured that the sample would be spread out across each island as much as possible and thus more representative.

Population and sample counts of dwellings by islands for 2010 HIES Islands: -Nanumea: Population: 123; sample: 41 -Nanumaga: Population: 117; sample: 39 -Niutao: Population: 138; sample: 46 -Nui: Population: 141; sample: 47 -Vaitupu: Population: 298; sample: 100 -Nukufetau: Population: 141; sample: 47 -Nukulaelae: Population: 78; sample: 26 -Funafuti: Population: 791; sample: 254 -TOTAL: Population: 1827; sample: 600.

Mode of data collection

Face-to-face [f2f]

Research instrument

3 forms were used. Each question is writen in English and translated in Tuvaluan on the same version of the questionnaire. The questionnaire was highly based on the previous one (2004 survey).

Household Schedule This questionnaire, to be completed by interviewers, is used to collect information about the household composition, living conditions and is also the main form for collecting expenditure on goods and services purchased infrequently.

• composition of the household and demographic profile of each members
• dwelling information
• dwelling expenditure
• transport expenditure
• education expenditure
• health expenditure
• land and property expenditure
• household furnishing
• home appliances
• cultural and social payments
• holydays/travel costs
• Loans and saving
• clothing
• other major expenditure items

Individual Schedule There will be two individual schedules: - health and education - labor force (individual aged 15 and above) - employment activity and income (individual aged 15 and above): wages and salaries working own business agriculture and livestock fishing income from handicraft income from gambling small scale activies jobs in the last 12 months other income childreen income tobacco and alcohol use other activities seafarer

Diary (one diary per week, on a 2 weeks period, 2 diaries per household were required) The diaries are used to record all household expenditure and consumption over the two week diary keeping period. The diaries are to be filled in by the household members, with the assistance from interviewers when necessary. - All kind of expenses - Home production - food and drink (eaten by the household, given away, sold) - Goods taken from own business (consumed, given away) - Monetary gift (given away, received, winning from gambling) - Non monetary gift (given away, received, winning from gambling).

Cleaning operations

Consistency of the data: - each questionnaire was checked by the supervisor during and after the collection - before data entry, all the questionnaire were coded - the CSPRo data entry system included inconsistency checks which allow the National Statistics Office staff to point some errors and to correct them with imputation estimation from their own knowledge (no time for double entry), 4 data entry operators. 1. presence of all the form for each household 2. consistency of data within the questionnaire

at this stage, all the errors were corrected on the questionnaire and on the data entry system in the meantime.

• after data entry, the extreme amount of each questionnaire where selected in order to check their consistency. at this stage, all the inconsistency were corrected by imputation on CSPRO editing.

Response rate

The final response rates for the survey was very pleasing with an average rate of 97 per cent across all islands selected. The response rates were derived by dividing the number of fully responding households by the number of selected households in scope of the survey which weren't vacant.

Response rates for Tuvalu 2010 Household Income and Expenditure Survey (HIES): - Nanumea 100% - Nanumaga 100% - Niutao 98% - Nui 100% - Vaitupu 99% - Nukufetau 89% - Nukulaelae 100% - Funafuti 96%

As can be seen in the table, four of the islands managed a 100 per cent response, whereas only Nukufetau had a response rate of less than 90 per cent.

Further explanation of response rates can be located in the external resource entitled Tuvalu 2010 HIES Report Table 1.2.

Sampling error estimates

The quality of the results can be found in the report provided in this documentation.