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TwitterThe 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.
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.
The population covered by the 2002 VNDHS is defined as the universe of all women age 15-49 in Vietnam.
Sample survey data
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.
Face-to-face
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.
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.
The results of the household and individual
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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.
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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
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TwitterThe Profiles of General Demographic Characteristics data are released as individual files for each of the 50 states, the District of Columbia, and Puerto Rico, as well as for all 50 states combined (Part 61) and for the entire United States (Part 60). The files contain the 100-percent data, which is the information compiled from questions asked of all people and about every housing unit. The population items include sex, age, race, Hispanic or Latino, household relationship, household type, group quarters population, housing occupancy, and housing tenure. The profiles include a total of 71 population and 25 housing data items. (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/ICPSR03192.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.
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Evolution of data for Persons (2006-2023) by demographic characteristics, type of ICT use and period. National.
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Background: Clean water is an essential part of human healthy life and wellbeing. More recently, rapid population growth, high illiteracy rate, lack of sustainable development, and climate change; faces a global challenge in developing countries. The discontinuity of drinking water supply forces households either to use unsafe water storage materials or to use water from unsafe sources. The present study aimed to identify the determinants of water source types, use, quality of water, and sanitation perception of physical parameters among urban households in North-West Ethiopia.
Methods: A community-based cross-sectional study was conducted among households from February to March 2019. An interview-based a pretested and structured questionnaire was used to collect the data. Data collection samples were selected randomly and proportional to each of the kebeles' households. MS Excel and R Version 3.6.2 were used to enter and analyze the data; respectively. Descriptive statistics using frequencies and percentages were used to explain the sample data concerning the predictor variable. Both bivariate and multivariate logistic regressions were used to assess the association between independent and response variables.
Results: Four hundred eighteen (418) households have participated. Based on the study undertaken,78.95% of households used improved and 21.05% of households used unimproved drinking water sources. Households drinking water sources were significantly associated with the age of the participant (x2 = 20.392, df=3), educational status(x2 = 19.358, df=4), source of income (x2 = 21.777, df=3), monthly income (x2 = 13.322, df=3), availability of additional facilities (x2 = 98.144, df=7), cleanness status (x2 =42.979, df=4), scarcity of water (x2 = 5.1388, df=1) and family size (x2 = 9.934, df=2). The logistic regression analysis also indicated that those factors are significantly determining the water source types used by the households. Factors such as availability of toilet facility, household member type, and sex of the head of the household were not significantly associated with drinking water sources.
Conclusion: The uses of drinking water from improved sources were determined by different demographic, socio-economic, sanitation, and hygiene-related factors. Therefore, ; the local, regional, and national governments and other supporting organizations shall improve the accessibility and adequacy of drinking water from improved sources in the area.
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TwitterThe 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.
National
Sample survey data
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.
Face-to-face
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.
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.
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
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TwitterThe Bangladesh Demographic and Health Survey (BDHS) is the first of this kind of study conducted in Bangladesh. It provides rapid feedback on key demographic and programmatic indicators to monitor the strength and weaknesses of the national family planning/MCH program. The wealth of information collected through the 1993-94 BDHS will be of immense value to the policymakers and program managers in order to strengthen future program policies and strategies.
The BDHS is intended to serve as a source of population and health data for policymakers and the research community. In general, the objectives of the BDHS are to: - asses the overall demographic situation in Bangladesh, - assist in the evaluation of the population and health programs in Bangladesh, and - advance survey methodology.
More specifically, the BDHS was designed to: - provide data on the family planning and fertility behavior of the Bangladesh population to evaluate the national family planning programs, - measure changes in fertility and contraceptive prevalence and, at the same time, study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding patterns, and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Bangladesh.
National
Sample survey data
Bangladesh is divided into five administrative divisions, 64 districts (zillas), and 489 thanas. In rural areas, thanas are divided into unions and then mauzas, an administrative land unit. Urban areas are divided into wards and then mahallas. The 1993-94 BDHS employed a nationally-representative, two-stage sample. It was selected from the Integrated Multi-Purpose Master Sample (IMPS), newly created by the Bangladesh Bureau of Statistics. The IMPS is based on 1991 census data. Each of the five divisions was stratified into three groups: 1) statistical metropolitan areas (SMAs) 2) municipalities (other urban areas), and 3) rural areas. In rural areas, the primary sampling unit was the mauza, while in urban areas, it was the mahalla. Because the primary sampling units in the IMPS were selected with probability proportional to size from the 1991 census frame, the units for the BDHS were sub-selected from the IMPS with equal probability to make the BDHS selection equivalent to selection with probability proportional to size. A total of 304 primary sampling units were selected for the BDHS (30 in SMAs, 40 in municipalities, and 234 in rural areas), out of the 372 in the IMPS. Fieldwork in three sample points was not possible, so a total of 301 points were covered in the survey.
Since one objective of the BDHS is to provide separate survey estimates for each division as well as for urban and rural areas separately, it was necessary to increase the sampling rate for Barisal Division und for municipalities relative to the other divisions, SMAs, and rural areas. Thus, the BDHS sample is not self-weighting and weighting factors have been applied to the data in this report.
After the selection of the BDHS sample points, field staffs were trained by Mitra and Associates and conducted a household listing operation in September and October 1993. A systematic sample of households was then selected from these lists, with an average "take" of 25 households in the urban clusters and 37 households in rural clusters. Every second household was identified as selected for the husband's survey, meaning that, in addition to interviewing all ever-married women age 10-49, interviewers also interviewed the husband of any woman who was successfully interviewed. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 4,200 of their husbands.
Note: See detailed in APPENDIX A of the survey final report.
Data collected for women 10-49, indicators calculated for women 15-49. A total of 304 primary sampling units were selected, but fieldwork in 3 sample points was not possible.
Face-to-face
Four types of questionnaires were used for the BDHS: a Household Questionnaire, a Women's Questionnaire, a Husbands' Questionnaire, and a Service Availability Questionnaire. The contents of these questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. Additions and modifications to the model questionnaires were made during a series of meetings with representatives of various organizations, including the Asia Foundation, the Bangladesh Bureau of Statistics, the Cambridge Consulting Corporation, the Family Planning Association of Bangladesh, GTZ, the International Centre for Diarrhoeal Disease Research (ICDDR,B), Pathfinder International, Population Communications Services, the Population Council, the Social Marketing Company, UNFPA, UNICEF, University Research Corporation/Bangladesh, and the World Bank. The questionnaires were developed in English and then translated into and printed in Bangla.
The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.
The Women's Questionnaire was used to collect information from ever-married women age 10-49. These women were asked questions on the following topics: - Background characteristics (age, education, religion, etc.), - Reproductive history, - Knowledge and use of family planning methods, - Antenatal and delivery care, - Breastfeeding and weaning practices, - Vaccinations and health of children under age three, - Marriage, - Fertility preferences, and - Husband's background and respondent's work.
The Husbands' Questionnaire was used to interview the husbands of a subsample of women who were interviewed. The questionnaire included many of the same questions as the Women's Questionnaire, except that it omitted the detailed birth history, as well as the sections on maternal care, breastfeeding and child health.
The Service Availability Questionnaire was used to collect information on the family planning and health services available in and near the sampled areas. It consisted of a set of three questionnaires: one to collect data on characteristics of the community, one for interviewing family welfare visitors and one for interviewing family planning field workers, whether government or non-governent supported. One set of service availability questionnaires was to be completed in each cluster (sample point).
All questionnaires for the BDHS were returned to Dhaka for data processing at Mitra and Associates. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing inconsistencies found by the computer programs. One senior staff member, 1 data processing supervisor, questionnaire administrator, 2 office editors, and 5 data entry operators were responsible for the data processing operation. The data were processed on five microcomputers. The DHS data entry and editing programs were written in ISSA (Integrated System for Survey Analysis). Data processing commenced in early February and was completed by late April 1994.
A total of 9,681 households were selected for the sample, of which 9,174 were successfully interviewed. The shortfall is primarily due to dwellings that were vacant, or in which the inhabitants had left for an extended period at the time they were visited by the interviewing teams. Of the 9,255 households that were occupied, 99 percent were successfully interviewed. In these households, 9,900 women were identified as eligible for the individual interview and interviews were completed for 9,640 or 97 percent of these. In one-half of the households that were selected for inclusion in the husbands' survey, 3,874 eligible husbands were identified, of which 3,284 or 85 percent were interviewed.
The principal reason for non-response among eligible women and men was failure to find them at home despite repeated visits to the household. The refusal rate was very low (less than one-tenth of one percent among women and husbands). Since the main reason for interviewing husbands was to match the information with that from their wives, survey procedures called for interviewers not to interview husbands of women who were not interviewed. Such cases account for about one-third of the non-response among husbands. Where husbands and wives were both interviewed, they were interviewed simultaneously but separately.
Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey final report.
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
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Release Date: 2023-05-11.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0262)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. For C-corporations, there is no tax form or business registry that clearly and unequivocally identifies all owners of this type of business. For this reason, the Census Bureau is unable to assign demographic characteristics for C-corporations. Data for C-corporations are included in the published tables but are not shown by the demographic characteristics of the firms....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2019/AB1900NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2019/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell valu...
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Table of INEBase Summary of data on Persons by nationality, demographic characteristics and type of ICT use. Survey on Equipment and Use of Information and Communication Technologies in Households
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| BASE YEAR | 2024 |
| HISTORICAL DATA | 2019 - 2023 |
| REGIONS COVERED | North America, Europe, APAC, South America, MEA |
| REPORT COVERAGE | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
| MARKET SIZE 2024 | 7.05(USD Billion) |
| MARKET SIZE 2025 | 7.55(USD Billion) |
| MARKET SIZE 2035 | 15.0(USD Billion) |
| SEGMENTS COVERED | Data Type, Application, Source, End User, Regional |
| COUNTRIES COVERED | US, Canada, Germany, UK, France, Russia, Italy, Spain, Rest of Europe, China, India, Japan, South Korea, Malaysia, Thailand, Indonesia, Rest of APAC, Brazil, Mexico, Argentina, Rest of South America, GCC, South Africa, Rest of MEA |
| KEY MARKET DYNAMICS | data privacy concerns, demand for personalized services, growth of smart home technology, integration of AI analytics, increasing subscription models |
| MARKET FORECAST UNITS | USD Billion |
| KEY COMPANIES PROFILED | Avenue6, HouseCanary, CoreLogic, D.R. Horton, Verisk Analytics, RealPage, IHS Markit, Lennar Corporation, Toll Brothers, PulteGroup, KB Home, S&P Global, Zonda, CoStar Group, TRI Pointe Group, Owens Corning |
| MARKET FORECAST PERIOD | 2025 - 2035 |
| KEY MARKET OPPORTUNITIES | Rising demand for smart home analytics, Increased focus on personalized marketing strategies, Growth of IoT integration in homes, Expansion of online home service platforms, Enhanced data security solutions for homeowners |
| COMPOUND ANNUAL GROWTH RATE (CAGR) | 7.1% (2025 - 2035) |
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Note: For information on data collection, confidentiality protection, nonsampling error, subject definitions, and guidance on using the data, visit the 2020 Census Demographic and Housing Characteristics File (DHC) Technical Documentation webpage..To protect respondent confidentiality, data have undergone disclosure avoidance methods which add "statistical noise" - small, random additions or subtractions - to the data so that no one can reliably link the published data to a specific person or household. The Census Bureau encourages data users to aggregate small populations and geographies to improve accuracy and diminish implausible results..A household that has at least one member of the household related to the householder by birth, marriage, or adoption is a "Family household." "Nonfamily households" consist of people living alone and households which do not have any members related to the householder..Household Type for the total population is available in table P16..Source: U.S. Census Bureau, 2020 Census Demographic and Housing Characteristics File (DHC)
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Survey on Equipment and Use of Information and Communication Technologies in Households: Persons who, in the last 3 months, have taken some sort of technological security precaution measure, by demographic characteristics and types of measures. National.
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TwitterWorking with partners across NIH, led by NIMHD and the NLM OBSSR-Behavioral Ontology Working Group, MeSH on November 29, 2022 added Federally recognized American Indian and Alaskan Native (AI/AN) tribal names and ethnic/ethnolinguistic minority terms as newly created type 5 SCR designated as “Population Groups”. These minority names (1,700+ terms) were mapped and reviewed by subject matter experts and scientists within NIH and from outside including Network of the National Library of Medicine members.
Structure: All type 5 SCRs have common fields 1. CC=5 Population Group 2. ST=T098 Population Groups 3. HM= At least one HM is to an MH under Population Groups [M01.686] 4. TH= NIMHD(2023)
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TwitterThe primary objective of the 2017 Indonesia Dmographic and Health Survey (IDHS) is to provide up-to-date estimates of basic demographic and health indicators. The IDHS provides a comprehensive overview of population and maternal and child health issues in Indonesia. More specifically, the IDHS was designed to: - provide data on fertility, family planning, maternal and child health, and awareness of HIV/AIDS and sexually transmitted infections (STIs) to help program managers, policy makers, and researchers to evaluate and improve existing programs; - measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as residence, education, breastfeeding practices, and knowledge, use, and availability of contraceptive methods; - evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; - assess married men’s knowledge of utilization of health services for their family’s health and participation in the health care of their families; - participate in creating an international database to allow cross-country comparisons in the areas of fertility, family planning, and health.
National coverage
The survey covered all de jure household members (usual residents), all women age 15-49 years resident in the household, and all men age 15-54 years resident in the household.
Sample survey data [ssd]
The 2017 IDHS sample covered 1,970 census blocks in urban and rural areas and was expected to obtain responses from 49,250 households. The sampled households were expected to identify about 59,100 women age 15-49 and 24,625 never-married men age 15-24 eligible for individual interview. Eight households were selected in each selected census block to yield 14,193 married men age 15-54 to be interviewed with the Married Man's Questionnaire. The sample frame of the 2017 IDHS is the Master Sample of Census Blocks from the 2010 Population Census. The frame for the household sample selection is the updated list of ordinary households in the selected census blocks. This list does not include institutional households, such as orphanages, police/military barracks, and prisons, or special households (boarding houses with a minimum of 10 people).
The sampling design of the 2017 IDHS used two-stage stratified sampling: Stage 1: Several census blocks were selected with systematic sampling proportional to size, where size is the number of households listed in the 2010 Population Census. In the implicit stratification, the census blocks were stratified by urban and rural areas and ordered by wealth index category.
Stage 2: In each selected census block, 25 ordinary households were selected with systematic sampling from the updated household listing. Eight households were selected systematically to obtain a sample of married men.
For further details on sample design, see Appendix B of the final report.
Face-to-face [f2f]
The 2017 IDHS used four questionnaires: the Household Questionnaire, Woman’s Questionnaire, Married Man’s Questionnaire, and Never Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49, the Woman’s Questionnaire had questions added for never married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey Questionnaire. The Household Questionnaire and the Woman’s Questionnaire are largely based on standard DHS phase 7 questionnaires (2015 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were included in the IDHS. Response categories were modified to reflect the local situation.
All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computer-identified errors. Data processing activities were carried out by a team of 34 editors, 112 data entry operators, 33 compare officers, 19 secondary data editors, and 2 data entry supervisors. The questionnaires were entered twice and the entries were compared to detect and correct keying errors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2017 IDHS.
Of the 49,261 eligible households, 48,216 households were found by the interviewer teams. Among these households, 47,963 households were successfully interviewed, a response rate of almost 100%.
In the interviewed households, 50,730 women were identified as eligible for individual interview and, from these, completed interviews were conducted with 49,627 women, yielding a response rate of 98%. From the selected household sample of married men, 10,440 married men were identified as eligible for interview, of which 10,009 were successfully interviewed, yielding a response rate of 96%. The lower response rate for men was due to the more frequent and longer absence of men from the household. In general, response rates in rural areas were higher than those in urban areas.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2017 Indonesia Demographic and Health Survey (2017 IDHS) 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 2017 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability 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 2017 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2017 IDHS is a STATA program. This program used the Taylor linearization method for 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.
A more detailed description of estimates of sampling errors are presented in Appendix C of the survey final report.
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 year - Reporting of age at death in days - Reporting of age at death in months
See details of the data quality tables in Appendix D of the survey final report.
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TwitterA census gives a complete and comprehensive picture of the nation as well as groups of people living in specific areas. In what type of buildings and housing units are we living? What are the amenities and facilities that are available therein? How many rooms are there and what is the extent of overcrowding? How many people live in a given town or locality? How many children are there? How many women are there? How many are old enough to vote? What kind of jobs are we doing? What is our level of education? Do we have the required qualifications or skills to satisfy the needs of the labour market? The census helps to answer these questions and many others.
It provides up-to-date and disaggregated data on the housing conditions, the spatial distribution, and the demographic and socio-economic characteristics of the population. These data are essential for assessing the country's demographic, social and economic performance and for developing sound policies and programmes aimed at fostering the welfare of the country and its population.
Census data are also useful to business, industrial and commercial organisations to estimate and forecast demand for their products and services, and to assess the supply of manpower with the relevant skills to run their activities.
Furthermore, census data are used in the derivation of many important and meaningful social indicators that are needed by local and international organizations. Thus, many social indicators, as defined in the set of indicators recommended by the United Nations Statistics Division, can only be worked out from census data.
Legal framework Census 2000 was conducted according to provisions of the Statistics Act of 7 April 1951. The underlying procedures are given in Sections 5, 6 and 13 of the Act. In March 1998, the Cabinet agreed to the conduct of a housing and population census in year 2000. In June 1999, it gave its approval to the census dates and to the topics to be investigated. The regulations for the Housing Census, prescribing the particulars and information to be collected, were subsequently prepared and approved by the President in November 1999. The regulations were published as Government Notice 170 of 1999. In December 1999, the President made an order to the effect that a census of the population be taken between 19 June and 16 July 2000 in respect of all persons alive at midnight on 2 July 2000. The Order was gazetted in December 1999. The regulations for the Population Census, prescribing the particulars and information to be collected were approved by the President in April 2000 and published as Government Notice 57 of 2000.
Housing and population enumerations were conducted on the Islands of Mauritius, Rodrigues and Agalega. As regards St Brandon islands, only a count of persons spending census night on the islands was made, these islands being fishing stations with no resident population.
The Housing Census enumerated all buildings, housing units, households, commercial and industrial establishments, hotels and boarding houses as well as fruit trees of bearing age on residential premises.
The Population Census enumerated all persons present on census night in all households and communal establishments, as well as usual residents who were away on census night.
Census/enumeration data [cen]
Self administered and face to face
Questionnaire Design Consultation with stakeholders from Government Ministries and Departments started in 1998. Heads of Government Ministries and Departments were invited via a circular letter to submit a list of demographic, social and economic data they considered essential for administration, planning and policy-making and which could be collected at the census. The proposals received were discussed at various levels. In the light of these discussions and taking into account recommendations of the United Nations Statistics Division on subject matters that can be investigated at a census, final selection of topics was made at a meeting with subject matter specialists from our parent Ministry.
The main considerations in the final selection of topics were: - the importance of the topics to the country - the cost for collecting and processing data on a given item - where it was possible by other means to obtain satisfactory information more cheaply, the topic was not selected - the suitability of topics - sensitive and controversial issues as well as questions that were too complicated or difficult for the average respondent to answer were avoided - whether the census was the appropriate method for data collection - topics that required detailed investigation or highly qualified staff were not included since they would be best canvassed by sample surveys.
Housing Census Questionnaire All topics investigated at the 1990 Census were included in the 2000 Housing Census questionnaire. Three new items were however added. These were: “Availability of domestic water tank/reservoir”, “Principal fuel used in bathroom” and “Fruit trees on premises”.
The housing census questionnaire was divided into seven parts. A list of topics and items included in the questionnaire is given below:
Part I - Location
Part II - Type of Building
Part III - Characteristics of buildings
- Storeys above ground floor
- Year of completion
- Principal material of construction used for roof and walls
Part IV - Characteristics of housing units
- Ownership
- Occupancy
- Water supply
- Domestic water tank/reservoir
- Availability of electricity
- Toilet facilities
- Bathing facilities
- Availability of kitchen
- Refuse disposal
Part V - Characteristics of households
- Household type
- Name and address of head of household
- Number of persons by sex
- Tenure
- Number of rooms for living purposes
- Number of rooms for business or profession
- Monthly rent
- Principal fuel used for cooking
- Principal fuel used in bathroom
Part VI - Commercial and industrial establishments, hotels and boarding houses
- Name and address of establishment or working proprietor/manager
- Main activity in which the establishment is engaged
- Number of persons engaged at the time of enumeration
Part VII - Fruit-trees on premises
- Number of fruit trees of bearing age by type
Population Census Questionnaire The 2000 Population Census questionnaire covered most of the topics investigated at the 1990 Population Census. A question on income was added while the questions on education were reviewed to include qualifications, other than those of the primary and secondary levels, of the respondent. The topic, main activity status of person during the year, which was investigated at the previous census was not included.
Topics and items included in the population census questionnaire are given below: (i) Location (ii) Names of persons These information were asked only to ensure that all members of the household were enumerated. Also, the listing of names of each person facilitated the checking for accuracy and completeness of each entry at the time of enumeration and later, if errors or missing information still persisted on the form. It should be pointed out that names were not captured at the data entry stage, so that data collected could not be identified with any individual person, in line with the requirements of the Statistics Act. (iii) Demographic and social characteristics - Relationship to head (only one head is allowed for each household) - Sex - Age - Date of birth (This question served as a verification to the age reported earlier) - Citizenship - Marital Status - Religion - Linguistic group - Language usually spoken (iv) Whether disabled or not - Type of disability, if disabled (v) Migration characteristics - Whereabouts on Census night - Usual address - Usual address five years ago (vi) Fertility - For persons not single: - Age at first marriage - Whether married more than once - Number of children ever born (for women only) (vii) Education characteristics - For persons 2 years and above: - Languages read and written - School attendance - Primary and secondary education (viii) Current economic characteristics (ix) Income
Census Guide and Instructions A census guide and instructions booklet was prepared and distributed to all heads of households. The booklet contained extensive explanations on how to fill in the census form and answered questions that people usually asked about censuses. Thus the objectives of the census, what happened to the census forms once the enumeration was over, the confidential aspect of collected information as well as the usefulness of each item were explained.
Printing of Census Questionnaires and Guides
The census questionnaires, and the census guide and instructions booklets were printed by the Government Printer. The numbers printed were as follows:
(i) Housing Census questionnaires - 16,000 booklets of 25 questionnaires
(ii) Population Census questionnaires - 375,000
(iii) Census guide and instructions booklets - 312,000
Recruitment and Training of Editors and Coders About 15 clerical officers who were previously engaged in the various units of the Office and 10 newly recruited statistical officers were called on to the editing and coding of the census forms while a request for the services of 50 additional clerical officers was made to the Ministry for Civil Service Affairs and Administrative Reform. Between March 2000 and May 2001, small groups of clerical officers from the ministry joined the
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Note: For information on data collection, confidentiality protection, nonsampling error, subject definitions, and guidance on using the data, visit the 2020 Census Demographic and Housing Characteristics File (DHC) Technical Documentation webpage..To protect respondent confidentiality, data have undergone disclosure avoidance methods which add "statistical noise" - small, random additions or subtractions - to the data so that no one can reliably link the published data to a specific person or household. The Census Bureau encourages data users to aggregate small populations and geographies to improve accuracy and diminish implausible results.."Families" consist of a householder and one or more other people related to the householder by birth, marriage, or adoption.."Own children" includes biological, adopted, and stepchildren of the householder..Source: U.S. Census Bureau, 2020 Census Demographic and Housing Characteristics File (DHC)
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