100+ datasets found
  1. w

    Demographic and Health Survey 2002 - Viet Nam

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Oct 26, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    General Statistical Office (GSO) (2023). Demographic and Health Survey 2002 - Viet Nam [Dataset]. https://microdata.worldbank.org/index.php/catalog/1518
    Explore at:
    Dataset updated
    Oct 26, 2023
    Dataset authored and provided by
    General Statistical Office (GSO)
    Time period covered
    2002
    Area covered
    Vietnam
    Description

    Abstract

    The 2002 Vietnam Demographic and Health Survey (VNDHS 2002) is a nationally representative sample survey of 5,665 ever-married women age 15-49 selected from 205 sample points (clusters) throughout Vietnam. It provides information on levels of fertility, family planning knowledge and use, infant and child mortality, and indicators of maternal and child health. The survey included a Community/ Health Facility Questionnaire that was implemented in each of the sample clusters.

    The survey was designed to measure change in reproductive health indicators over the five years since the VNDHS 1997, especially in the 18 provinces that were targeted in the Population and Family Health Project of the Committee for Population, Family and Children. Consequently, all provinces were separated into “project” and “nonproject” groups to permit separate estimates for each. Data collection for the survey took place from 1 October to 21 December 2002.

    The Vietnam Demographic and Health Survey 2002 (VNDHS 2002) was the third DHS in Vietnam, with prior surveys implemented in 1988 and 1997. The VNDHS 2002 was carried out in the framework of the activities of the Population and Family Health Project of the Committee for Population, Family and Children (previously the National Committee for Population and Family Planning).

    The main objectives of the VNDHS 2002 were to collect up-to-date information on family planning, childhood mortality, and health issues such as breastfeeding practices, pregnancy care, vaccination of children, treatment of common childhood illnesses, and HIV/AIDS, as well as utilization of health and family planning services. The primary objectives of the survey were to estimate changes in family planning use in comparison with the results of the VNDHS 1997, especially on issues in the scope of the project of the Committee for Population, Family and Children.

    VNDHS 2002 data confirm the pattern of rapidly declining fertility that was observed in the VNDHS 1997. It also shows a sharp decline in child mortality, as well as a modest increase in contraceptive use. Differences between project and non-project provinces are generally small.

    Geographic coverage

    The 2002 Vietnam Demographic and Health Survey (VNDHS 2002) is a nationally representative sample survey. The VNDHS 1997 was designed to provide separate estimates for the whole country, urban and rural areas, for 18 project provinces and the remaining nonproject provinces as well. Project provinces refer to 18 focus provinces targeted for the strengthening of their primary health care systems by the Government's Population and Family Health Project to be implemented over a period of seven years, from 1996 to 2002 (At the outset of this project there were 15 focus provinces, which became 18 by the creation of 3 new provinces from the initial set of 15). These provinces were selected according to criteria based on relatively low health and family planning status, no substantial family planning donor presence, and regional spread. These criteria resulted in the selection of the country's poorer provinces. Nine of these provinces have significant proportions of ethnic minorities among their population.

    Analysis unit

    • Household
    • Women age 15-49

    Universe

    The population covered by the 2002 VNDHS is defined as the universe of all women age 15-49 in Vietnam.

    Kind of data

    Sample survey data

    Sampling procedure

    The sample for the VNDHS 2002 was based on that used in the VNDHS 1997, which in turn was a subsample of the 1996 Multi-Round Demographic Survey (MRS), a semi-annual survey of about 243,000 households undertaken regularly by GSO. The MRS sample consisted of 1,590 sample areas known as enumeration areas (EAs) spread throughout the 53 provinces/cities of Vietnam, with 30 EAs in each province. On average, an EA comprises about 150 households. For the VNDHS 1997, a subsample of 205 EAs was selected, with 26 households in each urban EA and 39 households for each rural EA. A total of 7,150 households was selected for the survey. The VNDHS 1997 was designed to provide separate estimates for the whole country, urban and rural areas, for 18 project provinces and the remaining nonproject provinces as well. Because the main objective of the VNDHS 2002 was to measure change in reproductive health indicators over the five years since the VNDHS 1997, the sample design for the VNDHS 2002 was as similar as possible to that of the VNDHS 1997.

    Although it would have been ideal to have returned to the same households or at least the same sample points as were selected for the VNDHS 1997, several factors made this undesirable. Revisiting the same households would have held the sample artificially rigid over time and would not allow for newly formed households. This would have conflicted with the other major survey objective, which was to provide up-to-date, representative data for the whole of Vietnam. Revisiting the same sample points that were covered in 1997 was complicated by the fact that the country had conducted a population census in 1999, which allowed for a more representative sample frame.

    In order to balance the two main objectives of measuring change and providing representative data, it was decided to select enumeration areas from the 1999 Population Census, but to cover the same communes that were sampled in the VNDHS 1997 and attempt to obtain a sample point as close as possible to that selected in 1997. Consequently, the VNDHS 2002 sample also consisted of 205 sample points and reflects the oversampling in the 20 provinces that fall in the World Bank-supported Population and Family Health Project. The sample was designed to produce about 7,000 completed household interviews and 5,600 completed interviews with ever-married women age 15-49.

    Mode of data collection

    Face-to-face

    Research instrument

    As in the VNDHS 1997, three types of questionnaires were used in the 2002 survey: the Household Questionnaire, the Individual Woman's Questionnaire, and the Community/Health Facility Questionnaire. The first two questionnaires were based on the DHS Model A Questionnaire, with additions and modifications made during an ORC Macro staff visit in July 2002. The questionnaires were pretested in two clusters in Hanoi (one in a rural area and another in an urban area). After the pretest and consultation with ORC Macro, the drafts were revised for use in the main survey.

    a) The Household Questionnaire was used to enumerate all usual members and visitors in selected households and to collect information on age, sex, education, marital status, and relationship to the head of household. The main purpose of the Household Questionnaire was to identify persons who were eligible for individual interview (i.e. ever-married women age 15-49). In addition, the Household Questionnaire collected information on characteristics of the household such as water source, type of toilet facilities, material used for the floor and roof, and ownership of various durable goods.

    b) The Individual Questionnaire was used to collect information on ever-married women aged 15-49 in surveyed households. These women were interviewed on the following topics:
    - Respondent's background characteristics (education, residential history, etc.); - Reproductive history; - Contraceptive knowledge and use;
    - Antenatal and delivery care; - Infant feeding practices; - Child immunization; - Fertility preferences and attitudes about family planning; - Husband's background characteristics; - Women's work information; and - Knowledge of AIDS.

    c) The Community/Health Facility Questionnaire was used to collect information on all communes in which the interviewed women lived and on services offered at the nearest health stations. The Community/Health Facility Questionnaire consisted of four sections. The first two sections collected information from community informants on some characteristics such as the major economic activities of residents, distance from people's residence to civic services and the location of the nearest sources of health care. The last two sections involved visiting the nearest commune health centers and intercommune health centers, if these centers were located within 30 kilometers from the surveyed cluster. For each visited health center, information was collected on the type of health services offered and the number of days services were offered per week; the number of assigned staff and their training; medical equipment and medicines available at the time of the visit.

    Cleaning operations

    The first stage of data editing was implemented by the field editors soon after each interview. Field editors and team leaders checked the completeness and consistency of all items in the questionnaires. The completed questionnaires were sent to the GSO headquarters in Hanoi by post for data processing. The editing staff of the GSO first checked the questionnaires for completeness. The data were then entered into microcomputers and edited using a software program specially developed for the DHS program, the Census and Survey Processing System, or CSPro. Data were verified on a 100 percent basis, i.e., the data were entered separately twice and the two results were compared and corrected. The data processing and editing staff of the GSO were trained and supervised for two weeks by a data processing specialist from ORC Macro. Office editing and processing activities were initiated immediately after the beginning of the fieldwork and were completed in late December 2002.

    Response rate

    The results of the household and individual

  2. S

    San Joaquin County Demographic Data (ACS 1-Year Estimates)

    • opendata.sjgov.org
    csv
    Updated Jun 6, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Survey Data (2025). San Joaquin County Demographic Data (ACS 1-Year Estimates) [Dataset]. https://opendata.sjgov.org/dataset/demographic-data
    Explore at:
    csv(4707), csv(3644), csv(2488)Available download formats
    Dataset updated
    Jun 6, 2025
    Dataset authored and provided by
    Survey Data
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Area covered
    San Joaquin County
    Description

    This dataset provides demographic statistics for San Joaquin County CA, based on the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates.

    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.

  3. d

    US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct...

    • datarade.ai
    Updated Jun 1, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Giant Partners (2022). US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct Dials Accuracy [Dataset]. https://datarade.ai/data-products/consumer-business-data-postal-phone-email-demographics-giant-partners
    Explore at:
    Dataset updated
    Jun 1, 2022
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States
    Description

    Premium B2C Consumer Database - 269+ Million US Records

    Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

    Core Database Statistics

    Consumer Records: Over 269 million

    Email Addresses: Over 160 million (verified and deliverable)

    Phone Numbers: Over 76 million (mobile and landline)

    Mailing Addresses: Over 116,000,000 (NCOA processed)

    Geographic Coverage: Complete US (all 50 states)

    Compliance Status: CCPA compliant with consent management

    Targeting Categories Available

    Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

    Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

    Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

    Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

    Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

    Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

    Multi-Channel Campaign Applications

    Deploy across all major marketing channels:

    Email marketing and automation

    Social media advertising

    Search and display advertising (Google, YouTube)

    Direct mail and print campaigns

    Telemarketing and SMS campaigns

    Programmatic advertising platforms

    Data Quality & Sources

    Our consumer data aggregates from multiple verified sources:

    Public records and government databases

    Opt-in subscription services and registrations

    Purchase transaction data from retail partners

    Survey participation and research studies

    Online behavioral data (privacy compliant)

    Technical Delivery Options

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download

    Processing: Real-time NCOA, email validation, phone verification

    Custom Selections: 1,000+ selectable demographic and behavioral attributes

    Minimum Orders: Flexible based on targeting complexity

    Unique Value Propositions

    Dual Spouse Targeting: Reach both household decision-makers for maximum impact

    Cross-Platform Integration: Seamless deployment to major ad platforms

    Real-Time Updates: Monthly data refreshes ensure maximum accuracy

    Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

    Compliance Management: Built-in opt-out and suppression list management

    Ideal Customer Profiles

    E-commerce retailers seeking customer acquisition

    Financial services companies targeting specific demographics

    Healthcare organizations with compliant marketing needs

    Automotive dealers and service providers

    Home improvement and real estate professionals

    Insurance companies and agents

    Subscription services and SaaS providers

    Performance Optimization Features

    Lookalike Modeling: Create audiences similar to your best customers

    Predictive Scoring: Identify high-value prospects using AI algorithms

    Campaign Attribution: Track performance across multiple touchpoints

    A/B Testing Support: Split audiences for campaign optimization

    Suppression Management: Automatic opt-out and DNC compliance

    Pricing & Volume Options

    Flexible pricing structures accommodate businesses of all sizes:

    Pay-per-record for small campaigns

    Volume discounts for large deployments

    Subscription models for ongoing campaigns

    Custom enterprise pricing for high-volume users

    Data Compliance & Privacy

    VIA.tools maintains industry-leading compliance standards:

    CCPA (California Consumer Privacy Act) compliant

    CAN-SPAM Act adherence for email marketing

    TCPA compliance for phone and SMS campaigns

    Regular privacy audits and data governance reviews

    Transparent opt-out and data deletion processes

    Getting Started

    Our data specialists work with you to:

    1. Define your target audience criteria

    2. Recommend optimal data selections

    3. Provide sample data for testing

    4. Configure delivery methods and formats

    5. Implement ongoing campaign optimization

    Why We Lead the Industry

    With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

    Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

  4. d

    Factori USA Consumer Graph Data | socio-demographic, location, interest and...

    • datarade.ai
    .json, .csv
    Updated Jul 23, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Factori (2022). Factori USA Consumer Graph Data | socio-demographic, location, interest and intent data | E-Commere |Mobile Apps | Online Services [Dataset]. https://datarade.ai/data-products/factori-usa-consumer-graph-data-socio-demographic-location-factori
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Jul 23, 2022
    Dataset authored and provided by
    Factori
    Area covered
    United States of America
    Description

    Our consumer data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

    Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences.

    1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc.
    2. Demographics - Gender, Age Group, Marital Status, Language etc.
    3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc
    4. Persona - Consumer type, Communication preferences, Family type, etc
    5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc.
    6. Household - Number of Children, Number of Adults, IP Address, etc.
    7. Behaviours - Brand Affinity, App Usage, Web Browsing etc.
    8. Firmographics - Industry, Company, Occupation, Revenue, etc
    9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc.
    10. Auto - Car Make, Model, Type, Year, etc.
    11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

    Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

    Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

    Consumer Graph Use Cases:

    360-Degree Customer View:Get a comprehensive image of customers by the means of internal and external data aggregation.

    Data Enrichment:Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment

    Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity.

    Advertising & Marketing:Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

    Using Factori Consumer Data graph you can solve use cases like:

    Acquisition Marketing Expand your reach to new users and customers using lookalike modeling with your first party audiences to extend to other potential consumers with similar traits and attributes.

    Lookalike Modeling

    Build lookalike audience segments using your first party audiences as a seed to extend your reach for running marketing campaigns to acquire new users or customers

    And also, CRM Data Enrichment, Consumer Data Enrichment B2B Data Enrichment B2C Data Enrichment Customer Acquisition Audience Segmentation 360-Degree Customer View Consumer Profiling Consumer Behaviour Data

  5. Decennial Census: 110th Congressional District Demographic Profile (Sample)

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Census Bureau (2023). Decennial Census: 110th Congressional District Demographic Profile (Sample) [Dataset]. https://catalog.data.gov/dataset/decennial-census-110th-congressional-district-demographic-profile-sample
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The 110th Congressional District Summary File (Sample) (110CDSAMPLE) contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals; urban and rural; households and families; marital status; grandparents as caregivers; language and ability to speak English; ancestry; place of birth, citizenship status, and year of entry; migration; place of work; journey to work (commuting); school enrollment and educational attainment; veteran status; disability; employment status; industry, occupation, and class of worker; income; and poverty status. Housing items include basic housing totals; urban and rural; number of rooms; number of bedrooms; year moved into unit; household size and occupants per room; units in structure; year structure built; heating fuel; telephone service; plumbing and kitchen facilities; vehicles available; value of home; monthly rent; and shelter costs. The file contains subject content identical to that shown in Summary File 3 (SF 3).

  6. i

    Population and Family Health Survey 2002 - Jordan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +2more
    Updated Mar 29, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Statistics (DOS) (2019). Population and Family Health Survey 2002 - Jordan [Dataset]. http://catalog.ihsn.org/catalog/183
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Department of Statistics (DOS)
    Time period covered
    2002
    Area covered
    Jordan
    Description

    Abstract

    The JPFHS is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health. The primary objective of the Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, fertility preferences, as well as maternal and child health and nutrition that can be used by program managers and policy makers to evaluate and improve existing programs. In addition, the JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional or crossnational studies.

    The content of the 2002 JPFHS was significantly expanded from the 1997 survey to include additional questions on women’s status, reproductive health, and family planning. In addition, all women age 15-49 and children less than five years of age were tested for anemia.

    Geographic coverage

    National

    Analysis unit

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

    Kind of data

    Sample survey data

    Sampling procedure

    The estimates from a sample survey are affected by two types of errors: 1) nonsampling errors and 2) sampling errors. Nonsampling errors are the result 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 2002 JPFHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2002 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2002 JPFHS sample is the result of a multistage stratified design and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2002 JPFHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

    Mode of data collection

    Face-to-face

    Research instrument

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

    The household and women’s questionnaires were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990 and 1997 Jordan Population and Family Health Surveys. For each evermarried woman age 15 to 49, information on the following topics was collected:

    1. Respondent’s background
    2. Birth history
    3. Knowledge and practice of family planning
    4. Maternal care, breastfeeding, immunization, and health of children under five years of age
    5. Marriage
    6. Fertility preferences
    7. Husband’s background and respondent’s employment
    8. Knowledge of AIDS and STIs

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

    Cleaning operations

    Fieldwork and data processing activities overlapped. After a week of data collection, and after field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman where they were registered and stored. Special teams were formed to carry out office editing and coding of the open-ended questions.

    Data entry and verification started after one week of office data processing. The process of data entry, including one hundred percent re-entry, editing and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by the end of October 2002. A data processing specialist from ORC Macro made a trip to Jordan in October and November 2002 to follow up data editing and cleaning and to work on the tabulation of results for the survey preliminary report. The tabulations for the present final report were completed in December 2002.

    Response rate

    A total of 7,968 households were selected for the survey from the sampling frame; among those selected households, 7,907 households were found. Of those households, 7,825 (99 percent) were successfully interviewed. In those households, 6,151 eligible women were identified, and complete interviews were obtained with 6,006 of them (98 percent of all eligible women). The overall response rate was 97 percent.

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

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: 1) nonsampling errors and 2) sampling errors. Nonsampling errors are the result 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 2002 JPFHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2002 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2002 JPFHS sample is the result of a multistage stratified design and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2002 JPFHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    Note: See detailed

  7. w

    Demographic and Health Survey 1998 - Ghana

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +2more
    Updated Jun 6, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ghana Statistical Service (GSS) (2017). Demographic and Health Survey 1998 - Ghana [Dataset]. https://microdata.worldbank.org/index.php/catalog/1385
    Explore at:
    Dataset updated
    Jun 6, 2017
    Dataset authored and provided by
    Ghana Statistical Service (GSS)
    Time period covered
    1998 - 1999
    Area covered
    Ghana
    Description

    Abstract

    The 1998 Ghana Demographic and Health Survey (GDHS) is the latest in a series of national-level population and health surveys conducted in Ghana and it is part of the worldwide MEASURE DHS+ Project, designed to collect data on fertility, family planning, and maternal and child health.

    The primary objective of the 1998 GDHS is to provide current and reliable data on fertility and family planning behaviour, child mortality, children’s nutritional status, and the utilisation of maternal and child health services in Ghana. Additional data on knowledge of HIV/AIDS are also provided. This information is essential for informed policy decisions, planning and monitoring and evaluation of programmes at both the national and local government levels.

    The long-term objectives of the survey include strengthening the technical capacity of the Ghana Statistical Service (GSS) to plan, conduct, process, and analyse the results of complex national sample surveys. Moreover, the 1998 GDHS provides comparable data for long-term trend analyses within Ghana, since it is the third in a series of demographic and health surveys implemented by the same organisation, using similar data collection procedures. The GDHS also contributes to the ever-growing international database on demographic and health-related variables.

    Geographic coverage

    National

    Analysis unit

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

    Kind of data

    Sample survey data

    Sampling procedure

    The major focus of the 1998 GDHS was to provide updated estimates of important population and health indicators including fertility and mortality rates for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of key variables for the ten regions in the country.

    The list of Enumeration Areas (EAs) with population and household information from the 1984 Population Census was used as the sampling frame for the survey. The 1998 GDHS is based on a two-stage stratified nationally representative sample of households. At the first stage of sampling, 400 EAs were selected using systematic sampling with probability proportional to size (PPS-Method). The selected EAs comprised 138 in the urban areas and 262 in the rural areas. A complete household listing operation was then carried out in all the selected EAs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, a systematic sample of 15 households per EA was selected in all regions, except in the Northern, Upper West and Upper East Regions. In order to obtain adequate numbers of households to provide reliable estimates of key demographic and health variables in these three regions, the number of households in each selected EA in the Northern, Upper West and Upper East regions was increased to 20. The sample was weighted to adjust for over sampling in the three northern regions (Northern, Upper East and Upper West), in relation to the other regions. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata.

    The survey was designed to obtain completed interviews of 4,500 women age 15-49. In addition, all males age 15-59 in every third selected household were interviewed, to obtain a target of 1,500 men. In order to take cognisance of non-response, a total of 6,375 households nation-wide were selected.

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

    Mode of data collection

    Face-to-face

    Research instrument

    Three types of questionnaires were used in the GDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were based on model survey instruments developed for the international MEASURE DHS+ programme and were designed to provide information needed by health and family planning programme managers and policy makers. The questionnaires were adapted to the situation in Ghana and a number of questions pertaining to on-going health and family planning programmes were added. These questionnaires were developed in English and translated into five major local languages (Akan, Ga, Ewe, Hausa, and Dagbani).

    The Household Questionnaire was used to enumerate all usual members and visitors in a selected household and to collect information on the socio-economic status of the household. The first part of the Household Questionnaire collected information on the relationship to the household head, residence, sex, age, marital status, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. For this purpose, all women age 15-49, and all men age 15-59 in every third household, whether usual residents of a selected household or visitors who slept in a selected household the night before the interview, were deemed eligible and interviewed. The Household Questionnaire also provides basic demographic data for Ghanaian households. The second part of the Household Questionnaire contained questions on the dwelling unit, such as the number of rooms, the flooring material, the source of water and the type of toilet facilities, and on the ownership of a variety of consumer goods.

    The Women’s Questionnaire was used to collect information on the following topics: respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunisation and health, marriage, fertility preferences and attitudes about family planning, husband’s background characteristics, women’s work, knowledge of HIV/AIDS and STDs, as well as anthropometric measurements of children and mothers.

    The Men’s Questionnaire collected information on respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, as well as knowledge of HIV/AIDS and STDs.

    Response rate

    A total of 6,375 households were selected for the GDHS sample. Of these, 6,055 were occupied. Interviews were completed for 6,003 households, which represent 99 percent of the occupied households. A total of 4,970 eligible women from these households and 1,596 eligible men from every third household were identified for the individual interviews. Interviews were successfully completed for 4,843 women or 97 percent and 1,546 men or 97 percent. The principal reason for nonresponse among individual women and men was the failure of interviewers to find them at home despite repeated callbacks.

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

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of shortfalls 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 1998 GDHS 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 1998 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1998 GDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 GDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    Data appraisal

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

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

  8. d

    Demographic Data | USA Coverage

    • datarade.ai
    .csv
    Updated Jun 19, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    BIGDBM (2025). Demographic Data | USA Coverage [Dataset]. https://datarade.ai/data-products/bigdbm-us-consumer-demographics-core-package-bigdbm
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Jun 19, 2025
    Dataset authored and provided by
    BIGDBM
    Area covered
    United States
    Description

    The Consumer Demographic database is comprised of over 80 sources and includes over 400 different data points for each individual in a household with complete PII. The fields provided include demographics, psychographic, lifestyle criteria, buying behavior, and real property identification.

    Each record is ranked by confidence and only the highest quality data is used. The database is multi-sourced and contains both compiled and originated U.S. data. Additionally, the data goes through intensive cleansing including deceased processing and NCOA.

    BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

  9. c

    Census of Population and Housing, 1960: Public Use Sample, 1 in 100

    • archive.ciser.cornell.edu
    Updated Feb 13, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Bureau of the Census (2020). Census of Population and Housing, 1960: Public Use Sample, 1 in 100 [Dataset]. http://doi.org/10.6077/j5/ohycfx
    Explore at:
    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    Bureau of the Census
    Variables measured
    Individual, Household
    Description

    This collection contains individual-level and 1-percent national sample data from the 1960 Census of Population and Housing conducted by the Census Bureau. It consists of a representative sample of the records from the 1960 sample questionnaires. The data are stored in 30 separate files, containing in total over two million records, organized by state. Some files contain the sampled records of several states while other files contain all or part of the sample for a single state. There are two types of records stored in the data files: one for households and one for persons. Each household record is followed by a variable number of person records, one for each of the household members. Data items in this collection include the individual responses to the basic social, demographic, and economic questions asked of the population in the 1960 Census of Population and Housing. Data are provided on household characteristics and features such as the number of persons in household, number of rooms and bedrooms, and the availability of hot and cold piped water, flush toilet, bathtub or shower, sewage disposal, and plumbing facilities. Additional information is provided on tenure, gross rent, year the housing structure was built, and value and location of the structure, as well as the presence of air conditioners, radio, telephone, and television in the house, and ownership of an automobile. Other demographic variables provide information on age, sex, marital status, race, place of birth, nationality, education, occupation, employment status, income, and veteran status. The data files were obtained by ICPSR from the Center for Social Analysis, Columbia University. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07756.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  10. w

    Demographic and Health Survey 1996 - Uzbekistan

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 21, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Institute of Obstetrics & Gynecology (2017). Demographic and Health Survey 1996 - Uzbekistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/1516
    Explore at:
    Dataset updated
    Jun 21, 2017
    Dataset authored and provided by
    Institute of Obstetrics & Gynecology
    Time period covered
    1996
    Area covered
    Uzbekistan
    Description

    Abstract

    The 1996 Uzbekistan Demographic and Health Survey (UDHS) is a nationally representative survey of 4,415 women age 15-49. Fieldwork was conducted from June to October 1996. The UDHS was sponsored by the Ministry of Health (MOH), and was funded by the United States Agency for International Development. The Institute of Obstetrics and Gynecology implemented the survey with technical assistance from the Demographic and Health Surveys (DHS) program.

    The 1996 UDHS was the first national-level population and health survey in Uzbekistan. It was implemented by the Research Institute of Obstetrics and Gynecology of the Ministry of Health of Uzbekistan. The 1996 UDHS was funded by the United States Agency for International development (USAID) and technical assistance was provided by Macro International Inc. (Calverton, Maryland USA) through its contract with USAID.

    OBJECTIVES AND ORGANIZATION OF THE SURVEY

    The purpose of the 1996 Uzbekistan Demographic and Health Survey (UDHS) was to provide an information base to the Ministry of Health for the planning of policies and programs regarding the health of women and their children. The UDHS collected data on women's reproductive histories, knowledge and use of contraception, breastfeeding practices, and the nutrition, vaccination coverage, and episodes of illness among children under the age of three. The survey also included, for all women of reproductive age and for children under the age of three, the measurement of the hemoglobin level in the blood to assess the prevalence of anemia and measurements of height and weight to assess nutritional status.

    A secondary objective of the survey was to enhance the capabilities of institutions in Uzbekistan to collect, process and analyze population and health data so as to facilitate the implementation of future surveys of this type.

    MAIN RESULTS

    • Fertility Rates. Survey results indicate a total fertility rate (TFR) for all of Uzbekistan of 3.3 children per woman. Fertility levels differ for different population groups. The TFR for women living in urbml areas (2.7 children per woman) is substantially lower than for women living in rural areas (3.7). The TFR for Uzbeki women (3.5 children per woman) is higher than for women of other ethnicities (2.5). Among the regions of Uzbekistan, the TFR is lowest in Tashkent City (2.3 children per woman).
    • Family Planning. Knowledge. Knowledge of contraceptive methods is high among women in Uzbekistan. Knowledge of at least one method is 89 percent. High levels of knowledge are the norm for women of all ages, all regions of the country, all educational levels, and all ethnicities. However, knowledge of sterilization was low; only 27 percent of women reported knowing of this method.
    • Fertility Preferences. A majority of women in Uzbekistan (51 percent) indicated that they desire no more children. Among women age 30 and above, the proportion that want no more children increases to 75 percent. Thus, many women come to the preference to stop childbearing at relatively young ages when they have 20 or more potential years of childbearing ahead of them. For some of these women, the most appropriate method of contraception may be a long-acting method such as female sterilization, However, there is a deficiency of both knowledge and use of this method in Uzbekistan. In the interest of providing couples with a broad choice of safe and effective methods, information about this method and access to it should be made available so that informed choices about its suitability can be made by individual women and couples.
    • Induced Aboration : Abortion Rates. From the UDHS data, the total abortion rate (TAR)--the number of abortions a woman will have in her lifetime based on the currently prevailing abortion rates--was calculated. For Uzbekistan, the TAR for the period from mid-1993 to mid-1996 is 0.7 abortions per woman. As expected, the TAR for Uzbekistan is substantially lower than recent estimates of the TAR for other areas of the former Soviet Union such as Kazakstan (1.8), Romania (3.4 abortions per woman), and Yekaterinburg and Perm in Russia (2.3 and 2.8, respectively).
    • Infant mortality : In the UDHS, infant mortality data were collected based on the international definition of a live birth which, irrespective of the duration of pregnancy, is a birth that breathes or shows any sign of life (United Nations, 1992).
    • Mortality Rates. For the five-year period before the survey (i.e., approximately mid- 1992 to mid- 1996), infant mortality in Uzbekistan is estimated at 49 infant deaths per 1,000 births. The estimates of neonatal and postneonatal mortality are 23 and 26 per 1,000.
    • Maternal and child health : Uzbekistan has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. This system includes special delivery hospitals, the obstetrics and gynecology departments of general hospitals, women's consulting centers, and doctor's assistant/midwife posts (FAPs). There is an extensive network of FAPs throughout rural areas.
    • Nutrition : Breastfeeding. Breastfeeding is almost universal in Uzbekistan; 96 percent of children born in the three years preceding the survey are breastfed. Overall, 19 percent of children are breastfed within an hour of delivery and 40 percent within 24 hours of delivery. The median duration of breastfeeding is lengthy (17 months). However, durations of exclusive breastfeeding, as recommended by WHO, are short (0.4 months).
    • Prevalence of anemia : Testing of women and children for anemia was one of the major efforts of the 1996 UDHS. Anemia has been considered a major public health problem in Uzbekistan for decades. Nevertheless, this was the first anemia study in Uzbekistan done on a national basis. The study involved hemoglobin (Hb) testing for anemia using the Hemocue system. Women. Sixty percent of the women in Uzbekistan suffer from some degree of anemia. The great majority of these women have either mild (45 percent) or moderate anemia (14 percent). One percent have severe anemia.

    Geographic coverage

    National Seven raions were excluded from the survey because they were considered too remote and sparsely inhabited.

    Analysis unit

    • Household
    • Women age 15-49

    Universe

    The population covered by the 1996 UDHS is defined as the universe of all women age 15-49 in Uzbekistan

    Kind of data

    Sample survey data

    Sampling procedure

    The UDHS employed a probability sample of women age 15 to 49, representative of 98.7 percent of the country. Seven raions were excluded from the survey because they were considered too remote and sparsely inhabited. These raions are: Kungradskiyi, Muyinakskiyi, and Takhtakupyrskiyi in Karakalpakstan; Uchkudukskiyi, Tamdynskiyi, and Kanimekhskiyi in Navoiiskaya; and Romitanskiyi in Bukharskaya. The remainder of the country was divided into five survey regions. Tashkent City constituted a survey region by itself, while the remaining four survey regions consisted of groups of contiguous oblasts. The five survey regions were defined as follows: Region 1: Karakalpakstan and Khoresmskaya. Region 2: Navoiyiskaya, Bukharskaya, Kashkadarinskaya, and Surkhandarinskaya. Region 3: Samarkandskaya, Dzhizakskaya, Syrdarinskaya, and Tashkentskaya. Region 4: Namanganskaya, Ferganskaya, and Andizhanskaya. Region 5: Tashkent City.

    CHARACTERISTICS OF THE UDHS SAMPLE

    The sample for the UDHS was selected in three stages. In the rural areas, the primary sampling units (PSUs) corresponded to the raions which were selected with probabilities proportional to size, the size being the 1994 population. At the second stage, one village was selected in each selected raion. A complete listing of the households residing in each selected village was carried out. The lists of households obtained were used as the frame for third-stage sampling, which is the selection of the households to be visited by the UDHS interviewing teams during the main survey fieldwork. In each selected household, women between the ages of 15 and 49 were identified and interviewed.

    In the urban areas, the PSUs were the cities and towns themselves. In the second stage, one health block was selected from each town except in self-representing cities (large cities that were selected with certainty), where more than one health block was selected. The selected health blocks were segmented prior to the household listing operation which provided the household lists for the third-stage selection of households.

    SAMPLE ALLOCATION

    The regions, stratified by urban and rural areas, were the sampling strata. There were thus nine strata with Tashkent City constituting an entire stratum. A proportional allocation of the target number of 4,000 women to the 9 strata would yield the sample distribution.

    The proportional allocation would result in a completely self-weighting sample but would not allow for reliable estimates for at least two of the five survey regions, namely Region 1 and Tashkent City. Results of other demographic and health surveys show that a minimum sample of 1,000 women is required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors. Given that the total sample size for the UDHS could not he increased so as to achieve the required level of sampling errors, it was decided that the sample would be divided equally among the five regions, and within each region, it would be distributed proportionally to the urban and the rural areas. With this type of allocation, demographic rates (fertility and mortality) could not be produced for regions separately.

    The number of sample points (or clusters) to be selected for each stratum was calculated by dividing the

  11. Demographic and Health Survey 2013 - Turkiye

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 13, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hacettepe University Institute of Population Studies (HUIPS) (2022). Demographic and Health Survey 2013 - Turkiye [Dataset]. https://microdata.worldbank.org/index.php/catalog/3453
    Explore at:
    Dataset updated
    Jun 13, 2022
    Dataset provided by
    Hacettepe University Institute of Population Studies
    Authors
    Hacettepe University Institute of Population Studies (HUIPS)
    Time period covered
    2013 - 2014
    Area covered
    Türkiye
    Description

    Abstract

    The 2013 Turkey Demographic and Health Survey (TDHS-2013) is a nationally representative sample survey. The primary objective of the TDHS-2013 is to provide data on socioeconomic characteristics of households and women between ages 15-49, fertility, childhood mortality, marriage patterns, family planning, maternal and child health, nutritional status of women and children, and reproductive health. The survey obtained detailed information on these issues from a sample of women of reproductive age (15-49). The TDHS-2013 was designed to produce information in the field of demography and health that to a large extent cannot be obtained from other sources.

    Specifically, the objectives of the TDHS-2013 included: - Collecting data at the national level that allows the calculation of some demographic and health indicators, particularly fertility rates and childhood mortality rates, - Obtaining information on direct and indirect factors that determine levels and trends in fertility and childhood mortality, - Measuring the level of contraceptive knowledge and practice by contraceptive method and some background characteristics, i.e., region and urban-rural residence, - Collecting data relative to maternal and child health, including immunizations, antenatal care, and postnatal care, assistance at delivery, and breastfeeding, - Measuring the nutritional status of children under five and women in the reproductive ages, - Collecting data on reproductive-age women about marriage, employment status, and social status

    The TDHS-2013 information is intended to provide data to assist policy makers and administrators to evaluate existing programs and to design new strategies for improving demographic, social and health policies in Turkey. Another important purpose of the TDHS-2013 is to sustain the flow of information for the interested organizations in Turkey and abroad on the Turkish population structure in the absence of a reliable and sufficient vital registration system. Additionally, like the TDHS-2008, TDHS-2013 is accepted as a part of the Official Statistic Program.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Women age 15-49
    • Children under age of five

    Universe

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

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample design and sample size for the TDHS-2013 makes it possible to perform analyses for Turkey as a whole, for urban and rural areas, and for the five demographic regions of the country (West, South, Central, North, and East). The TDHS-2013 sample is of sufficient size to allow for analysis on some of the survey topics at the level of the 12 geographical regions (NUTS 1) which were adopted at the second half of the year 2002 within the context of Turkey’s move to join the European Union.

    In the selection of the TDHS-2013 sample, a weighted, multi-stage, stratified cluster sampling approach was used. Sample selection for the TDHS-2013 was undertaken in two stages. The first stage of selection included the selection of blocks as primary sampling units from each strata and this task was requested from the TURKSTAT. The frame for the block selection was prepared using information on the population sizes of settlements obtained from the 2012 Address Based Population Registration System. Settlements with a population of 10,000 and more were defined as “urban”, while settlements with populations less than 10,000 were considered “rural” for purposes of the TDHS-2013 sample design. Systematic selection was used for selecting the blocks; thus settlements were given selection probabilities proportional to their sizes. Therefore more blocks were sampled from larger settlements.

    The second stage of sample selection involved the systematic selection of a fixed number of households from each block, after block lists were obtained from TURKSTAT and were updated through a field operation; namely the listing and mapping fieldwork. Twentyfive households were selected as a cluster from urban blocks, and 18 were selected as a cluster from rural blocks. The total number of households selected in TDHS-2013 is 14,490.

    The total number of clusters in the TDHS-2013 was set at 642. Block level household lists, each including approximately 100 households, were provided by TURKSTAT, using the National Address Database prepared for municipalities. The block lists provided by TURKSTAT were updated during the listing and mapping activities.

    All women at ages 15-49 who usually live in the selected households and/or were present in the household the night before the interview were regarded as eligible for the Women’s Questionnaire and were interviewed. All analysis in this report is based on de facto women.

    Note: A more technical and detailed description of the TDHS-2013 sample design, selection and implementation is presented in Appendix B of the final report of the survey.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Two main types of questionnaires were used to collect the TDHS-2013 data: the Household Questionnaire and the Individual Questionnaire for all women of reproductive age. The contents of these questionnaires were based on the DHS core questionnaire. Additions, deletions and modifications were made to the DHS model questionnaire in order to collect information particularly relevant to Turkey. Attention also was paid to ensuring the comparability of the TDHS-2013 findings with previous demographic surveys carried out by the Hacettepe Institute of Population Studies. In the process of designing the TDHS-2013 questionnaires, national and international population and health agencies were consulted for their comments.

    The questionnaires were developed in Turkish and translated into English.

    Cleaning operations

    TDHS-2013 questionnaires were returned to the Hacettepe University Institute of Population Studies by the fieldwork teams for data processing as soon as interviews were completed in a province. The office editing staff checked that the questionnaires for all selected households and eligible respondents were returned from the field. A total of 29 data entry staff were trained for data entry activities of the TDHS-2013. The data entry of the TDHS-2013 began in late September 2013 and was completed at the end of January 2014.

    The data were entered and edited on microcomputers using the Census and Survey Processing System (CSPro) software. CSPro is designed to fulfill the census and survey data processing needs of data-producing organizations worldwide. CSPro is developed by MEASURE partners, the U.S. Bureau of the Census, ICF International’s DHS Program, and SerPro S.A. CSPro allows range, skip, and consistency errors to be detected and corrected at the data entry stage. During the data entry process, 100% verification was performed by entering each questionnaire twice using different data entry operators and comparing the entered data.

    Response rate

    In all, 14,490 households were selected for the TDHS-2013. At the time of the listing phase of the survey, 12,640 households were considered occupied and, thus, eligible for interview. Of the eligible households, 93 percent (11,794) households were successfully interviewed. The main reasons the field teams were unable to interview some households were because some dwelling units that had been listed were found to be vacant at the time of the interview or the household was away for an extended period.

    In the interviewed 11,794 households, 10,840 women were identified as eligible for the individual interview, aged 15-49 and were present in the household on the night before the interview. Interviews were successfully completed with 9,746 of these women (90 percent). Among the eligible women not interviewed in the survey, the principal reason for nonresponse was the failure to find the women at home after repeated visits to the household.

    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 TDHS-2013 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 TDHS-2013 is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

    A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall

  12. Sample data for analysis of demographic potential of the 15-minute city in...

    • zenodo.org
    bin, txt
    Updated Aug 29, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joan Perez; Joan Perez; Giovanni Fusco; Giovanni Fusco (2024). Sample data for analysis of demographic potential of the 15-minute city in northern and southern France [Dataset]. http://doi.org/10.5281/zenodo.13456826
    Explore at:
    bin, txtAvailable download formats
    Dataset updated
    Aug 29, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Joan Perez; Joan Perez; Giovanni Fusco; Giovanni Fusco
    License

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

    Area covered
    France, Southern France
    Description
    This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. 
    The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")
    extracted from version 3.3 of the French dataset BD TOPO®3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,
    Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinité in southern France
    (Geopackage "DPC_06.gpkg").
     
    Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf
     
    Additionally, this upload contains the results of the following algorithms available in GitHub (https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file)
     
    1. The identification of main streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") 
    https://plugins.qgis.org/plugins/morpheo/
    2. The identification of main streets in local contexts – connectivity locally weighted (layer "road_LocRelCon")
    3. Basic morphometry of buildings (layer "building_morpho")
    4. Evaluation of the number of dwellings within inhabited buildings (layer "building_dwellings")
    5. Projecting population potential accessible from main streets (layer "road_pop_results")
     
    Project website: http://emc2-dut.org/
     
    Publications using this sample data: 
    Perez, J. and Fusco, G., 2024. Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance. In: O. Gervasi, B. Murgante, C. Garau, D. Taniar, A.M.A.C. Rocha and M.N. Faginas Lago, eds. Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. https://doi.org/10.1007/978-3-031-65238-7_4.

    Acknowledgement. This work is part of the emc2 project, which received the grant ANR-23-DUTP-0003-01 from the French National Research Agency (ANR) within the DUT Partnership.

  13. d

    Demographic Data Append (Age, Gender, Marital Status, etc) Append API, USA,...

    • datarade.ai
    .json, .csv
    Updated Mar 16, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Versium (2023). Demographic Data Append (Age, Gender, Marital Status, etc) Append API, USA, CCPA Compliant [Dataset]. https://datarade.ai/data-products/versium-reach-consumer-basic-demographic-age-gender-mari-versium
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Mar 16, 2023
    Dataset authored and provided by
    Versium
    Area covered
    United States
    Description

    With Versium REACH Demographic Append you will have access to many different attributes for enriching your data.

    Basic, Household and Financial, Lifestyle and Interests, Political and Donor.

    Here is a list of what sorts of attributes are available for each output type listed above:

    Basic: - Senior in Household - Young Adult in Household - Small Office or Home Office - Online Purchasing Indicator
    - Language - Marital Status - Working Woman in Household - Single Parent - Online Education - Occupation - Gender - DOB (MM/YY) - Age Range - Religion - Ethnic Group - Presence of Children - Education Level - Number of Children

    Household, Financial and Auto: - Household Income - Dwelling Type - Credit Card Holder Bank - Upscale Card Holder - Estimated Net Worth - Length of Residence - Credit Rating - Home Own or Rent - Home Value - Home Year Built - Number of Credit Lines - Auto Year - Auto Make - Auto Model - Home Purchase Date - Refinance Date - Refinance Amount - Loan to Value - Refinance Loan Type - Home Purchase Price - Mortgage Purchase Amount - Mortgage Purchase Loan Type - Mortgage Purchase Date - 2nd Most Recent Mortgage Amount - 2nd Most Recent Mortgage Loan Type - 2nd Most Recent Mortgage Date - 2nd Most Recent Mortgage Interest Rate Type - Refinance Rate Type - Mortgage Purchase Interest Rate Type - Home Pool

    Lifestyle and Interests: - Mail Order Buyer - Pets - Magazines - Reading
    - Current Affairs and Politics
    - Dieting and Weight Loss - Travel - Music - Consumer Electronics - Arts
    - Antiques - Home Improvement - Gardening - Cooking - Exercise
    - Sports - Outdoors - Womens Apparel
    - Mens Apparel - Investing - Health and Beauty - Decorating and Furnishing

    Political and Donor: - Donor Environmental - Donor Animal Welfare - Donor Arts and Culture - Donor Childrens Causes - Donor Environmental or Wildlife - Donor Health - Donor International Aid - Donor Political - Donor Conservative Politics - Donor Liberal Politics - Donor Religious - Donor Veterans - Donor Unspecified - Donor Community - Party Affiliation

  14. i

    Interim Demographic and Health Survey 2009 - Jordan

    • dev.ihsn.org
    • catalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Statistics (DoS) (2019). Interim Demographic and Health Survey 2009 - Jordan [Dataset]. https://dev.ihsn.org/nada/catalog/71999
    Explore at:
    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    Department of Statistics (DoS)
    Time period covered
    2009
    Area covered
    Jordan
    Description

    Abstract

    As in the previous Demographic and Health Surveys (DHS) conducted in 1990, 1997, 2002 and 2007 in Jordan, the primary objective of the 2009 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, family planning, fertility preferences, and child mortality as well as the nutritional status of women and children. The data from these surveys can be used by program managers and policy makers to evaluate and improve existing programs. In addition, the JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

    The content of the 2009 JPFHS has been significantly decreased from the 2007 survey: it does not include data on mother and child health, reproductive health, women’s status, domestic violence, and early childhood development. However, a sub-sample of women age 15-49 and children age 6-59 months were tested to measure the prevalence of anemia. Height and weight of all women age 15-49 and children age five and under were also measured to assess their nutritional status.

    Geographic coverage

    National

    Analysis unit

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

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    SAMPLE DESIGN

    The 2009 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and Badia and non-Badia areas. To ensure comparability with the previous surveys, the sample was also designed to provide estimates for the three regions, North, Central and South. The grouping of the governorates into the regions is as follows: the North region consists of Irbid, Jarash, Ajloun, and Mafraq; the Central region consists of Amman, Madaba, Balqa, and Zarqa; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba.

    The 2009 JPFHS sample was designed using the 2004 Population and Housing Census as the sampling frame. The sampling frame was stratified by governorate, major cities, other urban, and other rural within each stratum. A two-stage sampling procedure was employed. First, blocks were selected systematically as primary sampling units (PSUs) with a probability proportional to the size of the PSU. A total of 930 PSUs were selected at this stage. In the second stage, a fixed number of 16 households were selected as final sampling units in each PSU, resulting in a sample size of about 15,000 households. Blood testing (for anemia) and the measurements of height and weight were conducted among eligible individuals in the selected households in 465 PSUs (half of the sample).

    UPDATING OF SAMPLING FRAME

    Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated, and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings, housing units, and households were updated, listed, and documented, along with the name of the owner/tenant of the housing unit and the name of the household head. These activities were completed during the second quarter of 2009.

    Note: See detailed description of sample design in APPENDIX A of the final report which is presented in this documentation.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 2009 JPFHS used two questionnaires—namely, the Household Questionnaire and the Individual Questionnaire. Both questionnaires were developed in English and Arabic, based on the questionnaires used in the 2007 survey, in collaboration with ICF Macro. The Household Questionnaire was used to list all usual members and visitors of the sampled households and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and availability of durable goods.

    The Household Questionnaire was also used to identify women who were eligible for the individual interview: ever-married women age 15-49. In addition, in half of the households, all women age 15-49 and children under five years of age were measured to determine nutritional status. Children age 6-59 months and women age 15-49 were tested for anemia.

    The household and women’s questionnaires were based on the DHS standard questionnaire. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990, 1997, 2002, and 2007 JPFHS. For each ever-married woman age 15-49, information on the following topics was collected: • Respondent’s general background • Birth history • Family planning • Marriage • Fertility preferences • Respondent’s employment

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

    As previously mentioned, anthropometric data were collected during the 2009 JPFHS in a subsample of 50 percent of clusters. All women age 15-49 and children age 0-4 in these households were measured using Shorr height boards and weighed using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children age 6-59 months to measure, in the field, their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

    Response rate

    A total of 14,872 households were selected for the survey from the sampling frame; among those selected households, 13,959 households were found. Of those households, 13,577 (97 percent) were successfully interviewed. In those households, 10,401 eligible women were identified, and complete interviews were obtained with 10,109 of them (97 percent of all eligible women). The overall response rate (the household’s response rate multiplied by the eligible woman response rate) was about 95 percent.

    Note: See summarized response rates by place of residence in Table 1.1 of the final report which is presented in this documentation.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2009 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2009 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2009 JPFHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2009 JPFHS is a Macro SAS procedure. This procedure used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    Note: See detailed estimate of sampling error calculation in APPENDIX B of the report which is presented in this documentation.

    Data appraisal

    Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children (JPFHS 2002 based on the WHO Child Growth Standards)

    Note: See for the detail in APPENDIX C of the final report which is presented in this documentation.

  15. O

    Resident Survey 2024 Demographics

    • data.norfolk.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Sep 24, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ETC Institute (2024). Resident Survey 2024 Demographics [Dataset]. https://data.norfolk.gov/Government/Resident-Survey-2024-Demographics/ez9d-udp9
    Explore at:
    csv, application/rdfxml, xml, json, application/rssxml, tsvAvailable download formats
    Dataset updated
    Sep 24, 2024
    Dataset authored and provided by
    ETC Institute
    Description

    The City of Norfolk is committed to using data to inform decisions and allocate resources. An important source of data is input from residents about their priorities and satisfaction with the services we provide. Norfolk last conducted a citywide survey of residents in 2022.

    To provide up-to-date information regarding resident priorities and satisfaction, Norfolk contracted with ETC Institute to conduct a survey of residents. This survey was conducted in May and June 2024; surveys were sent via the U.S. Postal Service, and respondents were given the choice of responding by mail or online. This survey represents a random and statistically valid sample of residents from across the city, including each Ward. ETC Institute monitored responses and followed up to ensure all sections of the city were represented. Additionally, an opportunity was provided for residents not included in the random sample to take the survey and express their views. This dataset includes all random sample survey data including demographic information; it excludes free-form comments to protect privacy. It is grouped by Question Category, Question, Response, Demographic Question, and Demographic Question Response. This dataset will be updated every two years.

  16. C

    China Population: City: Age 15 to 64: Guangdong

    • ceicdata.com
    Updated Apr 4, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2018). China Population: City: Age 15 to 64: Guangdong [Dataset]. https://www.ceicdata.com/en/china/population-sample-survey-by-age-and-region-city
    Explore at:
    Dataset updated
    Apr 4, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    China
    Variables measured
    Population
    Description

    Population: City: Age 15 to 64: Guangdong data was reported at 57.726 Person th in 2023. This records a decrease from the previous number of 58.178 Person th for 2022. Population: City: Age 15 to 64: Guangdong data is updated yearly, averaging 32.179 Person th from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 59,155.611 Person th in 2020 and a record low of 10.178 Person th in 1999. Population: City: Age 15 to 64: Guangdong data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Sample Survey: By Age and Region: City.

  17. n

    National Longitudinal Mortality Study

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Jul 2, 2011
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2011). National Longitudinal Mortality Study [Dataset]. http://identifiers.org/RRID:SCR_008946
    Explore at:
    Dataset updated
    Jul 2, 2011
    Description

    A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

  18. Demographic and Health Survey 1996-1997 - Bangladesh

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated May 26, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Mitra & Associates/ NIPORT (2017). Demographic and Health Survey 1996-1997 - Bangladesh [Dataset]. https://microdata.worldbank.org/index.php/catalog/1335
    Explore at:
    Dataset updated
    May 26, 2017
    Dataset provided by
    National Institute of Population Research and Traininghttp://niport.gov.bd/
    Authors
    Mitra & Associates/ NIPORT
    Time period covered
    1996 - 1997
    Area covered
    Bangladesh
    Description

    Abstract

    The Bangladesh Demographic and Health Survey (BDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.

    The 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: - assess 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 objective of the BDHS is to provide up-to-date information on fertility and childhood mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; nutrition levels; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in the country.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Children under five years
    • Women age 10-49
    • Men age 15-59

    Kind of data

    Sample survey data

    Sampling procedure

    Bangladesh is divided into six administrative divisions, 64 districts (zillas), and 490 thanas. In rural areas, thanas are divided into unions and then mauzas, a land administrative unit. Urban areas are divided into wards and then mahallas. The 1996-97 BDHS employed a nationally-representative, two-stage sample that was selected from the Integrated Multi-Purpose Master Sample (IMPS) maintained by the Bangladesh Bureau of Statistics. Each division was stratified into three groups: 1 ) statistical metropolitan areas (SMAs), 2) municipalities (other urban areas), and 3) rural areas. 3 In the 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 so as to retain the overall probability proportional to size. A total of 316 primary sampling units were utilized for the BDHS (30 in SMAs, 42 in municipalities, and 244 in rural areas). In order to highlight changes in survey indicators over time, the 1996-97 BDHS utilized the same sample points (though not necessarily the same households) that were selected for the 1993-94 BDHS, except for 12 additional sample points in the new division of Sylhet. Fieldwork in three sample points was not possible (one in Dhaka Cantonment and two in the Chittagong Hill Tracts), so a total of 313 points were covered.

    Since one objective of the BDHS is to provide separate estimates for each division as well as for urban and rural areas separately, it was necessary to increase the sampling rate for Barisal and Sylhet Divisions and 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.

    Mitra and Associates conducted a household listing operation in all the sample points from 15 September to 15 December 1996. A systematic sample of 9,099 households was then selected from these lists. Every second household was selected for the men's survey, meaning that, in addition to interviewing all ever-married women age 10-49, interviewers also interviewed all currently married men age 15-59. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 3,000 currently married men age 15-59.

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

    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 Men' s Questionnaire and a Community 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. These model questionnaires were adapted for use in Bangladesh during a series of meetings with a small Technical Task Force that consisted of representatives from NIPORT, Mitra and Associates, USAID/Bangladesh, the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B), Population Council/Dhaka, and Macro International Inc (see Appendix D for a list of members). Draft questionnaires were then circulated to other interested groups and were reviewed by the BDHS Technical Review Committee (see Appendix D for list of members). The questionnaires were developed in English and then translated into and printed in Bangla (see Appendix E for final version in English).

    The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including 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 the 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 five, - Marriage, - Fertility preferences, - Husband's background and respondent's work, - Knowledge of AIDS, - Height and weight of children under age five and their mothers.

    The Men's Questionnaire was used to interview currently married men age 15-59. It was similar to that for women except that it omitted the sections on reproductive history, antenatal and delivery care, breastfeeding, vaccinations, and height and weight. The Community Questionnaire was completed for each sample point and included questions about the existence in the community of income-generating activities and other development organizations and the availability of health and family planning services.

    Response rate

    A total of 9,099 households were selected for the sample, of which 8,682 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 8,762 households occupied, 99 percent were successfully interviewed. In these households, 9,335 women were identified as eligible for the individual interview (i.e., ever-married and age 10-49) and interviews were completed for 9,127 or 98 percent of them. In the half of the households that were selected for inclusion in the men's survey, 3,611 eligible ever-married men age 15-59 were identified, of whom 3,346 or 93 percent were interviewed.

    The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was low.

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

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as 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 BDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

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

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

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the BDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the BDHS is the ISSA Sampling Error Module. This module used the Taylor

  19. Decennial Census: State Legislative District Demographic Profile (Sample)

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Census Bureau (2023). Decennial Census: State Legislative District Demographic Profile (Sample) [Dataset]. https://catalog.data.gov/dataset/decennial-census-state-legislative-district-demographic-profile-sample
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The State Legislative District Summary File (Sample) (SLDSAMPLE) contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals; urban and rural; households and families; marital status; grandparents as caregivers; language and ability to speak English; ancestry; place of birth, citizenship status, and year of entry; migration; place of work; journey to work (commuting); school enrollment and educational attainment; veteran status; disability; employment status; industry, occupation, and class of worker; income; and poverty status. Housing items include basic housing totals; urban and rural; number of rooms; number of bedrooms; year moved into unit; household size and occupants per room; units in structure; year structure built; heating fuel; telephone service; plumbing and kitchen facilities; vehicles available; value of home; monthly rent; and shelter costs. The file contains subject content identical to that shown in Summary File 3 (SF 3).

  20. V

    State Employment Status Demographic Data By Gender, Race, Ethnicity- VA

    • data.virginia.gov
    csv
    Updated Apr 16, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Datathon 2024 (2024). State Employment Status Demographic Data By Gender, Race, Ethnicity- VA [Dataset]. https://data.virginia.gov/dataset/expanded-state-employment-status-demographic-data-va
    Explore at:
    csv(40308)Available download formats
    Dataset updated
    Apr 16, 2024
    Dataset authored and provided by
    Datathon 2024
    Description

    Statewide VA data on the demographic and economic characteristics of the labor force are published on an annual-average basis from the Current Population Survey (CPS), the sample survey of households used to calculate the U.S. unemployment rate. For VA state ,employment status data are tabulated for 67 sex, race, Hispanic or Latino ethnicity, marital status, and detailed age categories and evaluated against a minimum base, calculated to reflect an expected maximum coefficient of variation (CV) of 50 percent, to determine reliability for publication

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
General Statistical Office (GSO) (2023). Demographic and Health Survey 2002 - Viet Nam [Dataset]. https://microdata.worldbank.org/index.php/catalog/1518

Demographic and Health Survey 2002 - Viet Nam

Explore at:
Dataset updated
Oct 26, 2023
Dataset authored and provided by
General Statistical Office (GSO)
Time period covered
2002
Area covered
Vietnam
Description

Abstract

The 2002 Vietnam Demographic and Health Survey (VNDHS 2002) is a nationally representative sample survey of 5,665 ever-married women age 15-49 selected from 205 sample points (clusters) throughout Vietnam. It provides information on levels of fertility, family planning knowledge and use, infant and child mortality, and indicators of maternal and child health. The survey included a Community/ Health Facility Questionnaire that was implemented in each of the sample clusters.

The survey was designed to measure change in reproductive health indicators over the five years since the VNDHS 1997, especially in the 18 provinces that were targeted in the Population and Family Health Project of the Committee for Population, Family and Children. Consequently, all provinces were separated into “project” and “nonproject” groups to permit separate estimates for each. Data collection for the survey took place from 1 October to 21 December 2002.

The Vietnam Demographic and Health Survey 2002 (VNDHS 2002) was the third DHS in Vietnam, with prior surveys implemented in 1988 and 1997. The VNDHS 2002 was carried out in the framework of the activities of the Population and Family Health Project of the Committee for Population, Family and Children (previously the National Committee for Population and Family Planning).

The main objectives of the VNDHS 2002 were to collect up-to-date information on family planning, childhood mortality, and health issues such as breastfeeding practices, pregnancy care, vaccination of children, treatment of common childhood illnesses, and HIV/AIDS, as well as utilization of health and family planning services. The primary objectives of the survey were to estimate changes in family planning use in comparison with the results of the VNDHS 1997, especially on issues in the scope of the project of the Committee for Population, Family and Children.

VNDHS 2002 data confirm the pattern of rapidly declining fertility that was observed in the VNDHS 1997. It also shows a sharp decline in child mortality, as well as a modest increase in contraceptive use. Differences between project and non-project provinces are generally small.

Geographic coverage

The 2002 Vietnam Demographic and Health Survey (VNDHS 2002) is a nationally representative sample survey. The VNDHS 1997 was designed to provide separate estimates for the whole country, urban and rural areas, for 18 project provinces and the remaining nonproject provinces as well. Project provinces refer to 18 focus provinces targeted for the strengthening of their primary health care systems by the Government's Population and Family Health Project to be implemented over a period of seven years, from 1996 to 2002 (At the outset of this project there were 15 focus provinces, which became 18 by the creation of 3 new provinces from the initial set of 15). These provinces were selected according to criteria based on relatively low health and family planning status, no substantial family planning donor presence, and regional spread. These criteria resulted in the selection of the country's poorer provinces. Nine of these provinces have significant proportions of ethnic minorities among their population.

Analysis unit

  • Household
  • Women age 15-49

Universe

The population covered by the 2002 VNDHS is defined as the universe of all women age 15-49 in Vietnam.

Kind of data

Sample survey data

Sampling procedure

The sample for the VNDHS 2002 was based on that used in the VNDHS 1997, which in turn was a subsample of the 1996 Multi-Round Demographic Survey (MRS), a semi-annual survey of about 243,000 households undertaken regularly by GSO. The MRS sample consisted of 1,590 sample areas known as enumeration areas (EAs) spread throughout the 53 provinces/cities of Vietnam, with 30 EAs in each province. On average, an EA comprises about 150 households. For the VNDHS 1997, a subsample of 205 EAs was selected, with 26 households in each urban EA and 39 households for each rural EA. A total of 7,150 households was selected for the survey. The VNDHS 1997 was designed to provide separate estimates for the whole country, urban and rural areas, for 18 project provinces and the remaining nonproject provinces as well. Because the main objective of the VNDHS 2002 was to measure change in reproductive health indicators over the five years since the VNDHS 1997, the sample design for the VNDHS 2002 was as similar as possible to that of the VNDHS 1997.

Although it would have been ideal to have returned to the same households or at least the same sample points as were selected for the VNDHS 1997, several factors made this undesirable. Revisiting the same households would have held the sample artificially rigid over time and would not allow for newly formed households. This would have conflicted with the other major survey objective, which was to provide up-to-date, representative data for the whole of Vietnam. Revisiting the same sample points that were covered in 1997 was complicated by the fact that the country had conducted a population census in 1999, which allowed for a more representative sample frame.

In order to balance the two main objectives of measuring change and providing representative data, it was decided to select enumeration areas from the 1999 Population Census, but to cover the same communes that were sampled in the VNDHS 1997 and attempt to obtain a sample point as close as possible to that selected in 1997. Consequently, the VNDHS 2002 sample also consisted of 205 sample points and reflects the oversampling in the 20 provinces that fall in the World Bank-supported Population and Family Health Project. The sample was designed to produce about 7,000 completed household interviews and 5,600 completed interviews with ever-married women age 15-49.

Mode of data collection

Face-to-face

Research instrument

As in the VNDHS 1997, three types of questionnaires were used in the 2002 survey: the Household Questionnaire, the Individual Woman's Questionnaire, and the Community/Health Facility Questionnaire. The first two questionnaires were based on the DHS Model A Questionnaire, with additions and modifications made during an ORC Macro staff visit in July 2002. The questionnaires were pretested in two clusters in Hanoi (one in a rural area and another in an urban area). After the pretest and consultation with ORC Macro, the drafts were revised for use in the main survey.

a) The Household Questionnaire was used to enumerate all usual members and visitors in selected households and to collect information on age, sex, education, marital status, and relationship to the head of household. The main purpose of the Household Questionnaire was to identify persons who were eligible for individual interview (i.e. ever-married women age 15-49). In addition, the Household Questionnaire collected information on characteristics of the household such as water source, type of toilet facilities, material used for the floor and roof, and ownership of various durable goods.

b) The Individual Questionnaire was used to collect information on ever-married women aged 15-49 in surveyed households. These women were interviewed on the following topics:
- Respondent's background characteristics (education, residential history, etc.); - Reproductive history; - Contraceptive knowledge and use;
- Antenatal and delivery care; - Infant feeding practices; - Child immunization; - Fertility preferences and attitudes about family planning; - Husband's background characteristics; - Women's work information; and - Knowledge of AIDS.

c) The Community/Health Facility Questionnaire was used to collect information on all communes in which the interviewed women lived and on services offered at the nearest health stations. The Community/Health Facility Questionnaire consisted of four sections. The first two sections collected information from community informants on some characteristics such as the major economic activities of residents, distance from people's residence to civic services and the location of the nearest sources of health care. The last two sections involved visiting the nearest commune health centers and intercommune health centers, if these centers were located within 30 kilometers from the surveyed cluster. For each visited health center, information was collected on the type of health services offered and the number of days services were offered per week; the number of assigned staff and their training; medical equipment and medicines available at the time of the visit.

Cleaning operations

The first stage of data editing was implemented by the field editors soon after each interview. Field editors and team leaders checked the completeness and consistency of all items in the questionnaires. The completed questionnaires were sent to the GSO headquarters in Hanoi by post for data processing. The editing staff of the GSO first checked the questionnaires for completeness. The data were then entered into microcomputers and edited using a software program specially developed for the DHS program, the Census and Survey Processing System, or CSPro. Data were verified on a 100 percent basis, i.e., the data were entered separately twice and the two results were compared and corrected. The data processing and editing staff of the GSO were trained and supervised for two weeks by a data processing specialist from ORC Macro. Office editing and processing activities were initiated immediately after the beginning of the fieldwork and were completed in late December 2002.

Response rate

The results of the household and individual

Search
Clear search
Close search
Google apps
Main menu