This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES and rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:

Use this application to identify locale classifications for public, private, and postsecondary schools.What are locales? Locales are general geographic indicators that reflect the type of community where a school is located. NCES creates and uses the indicators for a variety of statistical purposes, and some educational programs use them to identify schools in specific types of areas.The locale data layer used in the Locale Lookup was produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program. The data provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2016 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2016. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, and rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:City – Large (11): Territory inside an urban area with population of 50,000 or more and inside a principal city with population of 250,000 or more.City – Midsize (12): Territory inside an urban area with population of 50,000 or more and inside a principal city with population less than 250,000 and greater than or equal to 100,000.City – Small (13): Territory inside an urban area with population of 50,000 or more and inside a principal city with population less than 100,000.Suburban – Large (21): Territory outside a principal city and inside an urban area with population of 250,000 or more.Suburban – Midsize (22): Territory outside a principal city and inside an urban area with population less than 250,000 and greater than or equal to 100,000.Suburban – Small (23): Territory outside a principal city and inside an urban area with population less than 100,000 and greater than or equal to 50,000.Town – Fringe (31): Territory inside an urban area with population less than 50,000 that is less than or equal to 10 miles from an urban area with population of 50,000 or more.Town – Distant (32): Territory inside an urban area with population less than 50,000 that is more than 10 miles and less than or equal to 35 miles from an urban area with population of 50,000 or more.Town – Remote (33): Territory inside an urban area with population less than 50,000 that is more than 35 miles from an urban area with population of 50,000 or more.Rural – Fringe (41): Territory outside an urban area that is less than or equal to 5 miles from an urban area with population of 50,000 or more, as well as territory outside an urban area that is less than or equal to 2.5 miles from an urban area with population less than 50,000.Rural – Distant (42): Territory outside an urban area that is more than 5 miles but less than or equal to 25 miles from an urban area with population of 50,000 or more, as well as territory outside an urban area that is more than 2.5 miles but less than or equal to 10 miles from an urban area with population less than 50,000.Rural – Remote (43): Territory outside an urban area that is more than 25 miles from an urban area with population of 50,000 or more and is also more than 10 miles from an urban area with population less than 50,000.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

🇺🇸 미국 English This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2019 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2019. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:

This dataset contains records for each public elementary and secondary school in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside the United States for 1995-1996. Records in this file provide the National Center for Education Statistics and state identification numbers, name and ID number of the agency operating the school, name, address, and phone number of the school, school type (regular, special education, vocational education, alternative), locale code (seven categories from urban to rural), number of students by grade and ungraded, number of students eligible for free lunch, and number of students by five race/ethnic categories.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2020 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2020. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include: City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more. City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000. City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000. Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more. Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000. Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area. Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area. Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area. Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster. Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster. Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Cambodia Education: Rural: Other data was reported at 0.000 % in 2021. This stayed constant from the previous number of 0.000 % for 2020. Cambodia Education: Rural: Other data is updated yearly, averaging 0.000 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 0.000 % in 2021 and a record low of 0.000 % in 2021. Cambodia Education: Rural: Other data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

Cambodia Education: Rural: None or Only Some Education data was reported at 19.400 % in 2021. This records a decrease from the previous number of 23.600 % for 2020. Cambodia Education: Rural: None or Only Some Education data is updated yearly, averaging 21.500 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 23.600 % in 2020 and a record low of 19.400 % in 2021. Cambodia Education: Rural: None or Only Some Education data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

Cambodia Education: Rural: Lower Secondary Completed data was reported at 8.600 % in 2021. This stayed constant from the previous number of 8.600 % for 2020. Cambodia Education: Rural: Lower Secondary Completed data is updated yearly, averaging 8.600 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 8.600 % in 2021 and a record low of 8.600 % in 2021. Cambodia Education: Rural: Lower Secondary Completed data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files.

This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

Abstract

The 2014 Bangladesh Demographic and Health Survey (BDHS) is the seventh DHS undertaken in Bangladesh, following those implemented in 1993-94, 1996-97, 1999-2000, 2004, 2007, and 2011. The main objectives of the 2014 BDHS are to: • Provide information to meet the monitoring and evaluation needs of the health, population, and nutrition sector development program (HPNSDP) • Provide program managers and policy makers involved in the program with the information they need to plan and implement future interventions

The specific objectives of the 2014 BDHS were as follows: • To provide up-to-date data on demographic rates, particularly fertility and infant, and child mortality rates, at the national and divisional level • To measure the level of contraceptive use of currently married women • To provide data on maternal and child health, including antenatal care, assistance at delivery, postnatal care, newborn care, breastfeeding, immunizations, and prevalence and treatment of diarrhea and other diseases among children under age 5 • To assess the nutritional status of children (under age 5) and women by means of anthropometric measurements (weight and height), and to assess infant and child feeding practices • To provide data on knowledge and attitudes of women about sexually transmitted infections and HIV/AIDS • To measure key education indicators, including school attendance ratios • To provide community-level data on accessibility and availability of health and family planning services

Geographic coverage

National coverage The survey was designed to produce representative results for the country as a whole, for the urban and the rural areas separately, and for each of the seven administrative divisions.

Analysis unit

• Household
• Individual
• Children age 0-5
• Ever married Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample for the 2014 BDHS is nationally representative and covers the entire population residing in noninstitutional dwelling units in the country. The survey used a sampling frame from the list of enumeration areas (EAs) of the 2011 Population and Housing Census of the People's Republic of Bangladesh, provided by the Bangladesh Bureau of Statistics (BBS). The primary sampling unit (PSU) for the survey is an EA created to have an average of about 120 households.

Bangladesh is divided into seven administrative divisions: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. Each division is divided into zilas, and each zila into upazilas. Each urban area in an upazila is divided into wards, which are further subdivided into mohallas. A rural area in an upazila is divided into union parishads (UPs) and, within UPs, into mouzas. These divisions allow the country as a whole to be separated into rural and urban areas.

The survey is based on a two-stage stratified sample of households. In the first stage, 600 EAs were selected with probability proportional to the EA size, with 207 EAs in urban areas and 393 in rural areas. A complete household listing operation was then carried out in all of the selected EAs to provide a sampling frame for the second-stage selection of households. In the second stage of sampling, a systematic sample of 30 households on average was selected per EA to provide statistically reliable estimates of key demographic and health variables for the country as a whole, for urban and rural areas separately, and for each of the seven divisions. With this design, the survey selected 18,000 residential households, which were expected to result in completed interviews with about 18,000 ever-married women.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2014 BDHS used three types of questionnaires: a Household Questionnaire, a Woman’s Questionnaire, and a Community Questionnaire. The contents of the Household and Woman’s questionnaires were based on the MEASURE DHS Model Questionnaires. These model questionnaires were adapted for use in Bangladesh during a series of meetings with a Technical Working Group (TWG) that consisted of representatives from NIPORT, Mitra and Associates, International Center for Diarrheal Disease Research, Bangladesh (ICDDR,B), USAID/Bangladesh, and ICF International. Draft questionnaires were then circulated to other interested groups and were reviewed by the 2014 BDHS Technical Review Committee. 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 in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, current work status, birth registration, and individual possession of mobile phones. The main purpose of the Household Questionnaire was to identify women who were eligible for the individual interview. Information was collected about the dwelling unit, such as the source of water, type of toilet facilities, materials used to construct the floor, roof, and walls, ownership of various consumer goods, and availability of hand washing facilities. In addition, this questionnaire was used to record the height and weight measurements of ever-married women age 15-49 and children under age 6.

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

The Community Questionnaire was administered in each selected cluster during the household listing operation and included questions about the existence of development organizations in the community and the availability and accessibility of health services and other facilities. The Community Questionnaire was administered to a group of four to six key informants who were knowledgeable about socioeconomic conditions and the availability of health and family planning services/facilities in the cluster. Key informants included community leaders, teachers, government officials, social workers, religious leaders, traditional healers, and health care providers among others.

Cleaning operations

The completed 2014 BDHS questionnaires were periodically returned to Dhaka for data processing at Mitra and Associates. The data processing began shortly after fieldwork commenced. Data processing consisted of office editing, coding of open-ended questions, data entry, and editing of inconsistencies found by the computer program. Eight data entry operators and two data entry supervisors processed the data. Data processing commenced on July 24, 2014, and ended on November 20, 2014. The task was carried out using the Census and Survey Processing System (CSPro), a software jointly developed by the U.S. Census Bureau, ICF Macro, and Serpro S.A.

Response rate

Among a total of 17,989 selected households, 17,565 were found occupied. Interviews were successfully completed in 17,300, or 99 percent of households. A total of 18,245 ever-married women age 15-49 were identified in these households and 17,863 were interviewed, for a response rate of 98 percent. Response rates for households and eligible women are similar to those in the 2011 BDHS. The principal reason for nonresponse among women was their absence from home despite repeated visits to the household. The response rates do not vary notably by urban-rural residence.

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 2014 Bangladesh DHS (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 2014 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.

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 2014 BDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF International. These programs use the Taylor linearization method of

Abstract

Moldova's first Demographic and Health Survey (2005 MDHS) is a nationally representative sample survey of 7,440 women age 15-49 and 2,508 men age 15-59 selected from 400 sample points (clusters) throughout Moldova (excluding the Transnistria region). It is designed to provide data to monitor the population and health situation in Moldova; it includes several indicators which follow up on those from the 1997 Moldova Reproductive Health Survey (1997 MRHS) and the 2000 Multiple Indicator Cluster Survey (2000 MICS). The 2005 MDHS used a two-stage sample based on the 2004 Population and Housing Census and was designed to produce separate estimates for key indicators for each of the major regions in Moldova, including the North, Center, and South regions and Chisinau Municipality. Unlike the 1997 MRHS and the 2000 MICS surveys, the 2005 MDHS did not cover the region of Transnistria. Data collection took place over a two-month period, from June 13 to August 18, 2005.

The survey obtained detailed information on fertility levels, abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, adult health, and awareness and behavior regarding HIV infection and other sexually transmitted diseases. Hemoglobin testing was conducted on women and children to detect the presence of anemia. Additional features of the 2005 MDHS include the collection of information on international emigration, language preference for reading printed media, and domestic violence. The 2005 MDHS was carried out by the National Scientific and Applied Center for Preventive Medicine, hereafter called the National Center for Preventive Medicine (NCPM), of the Ministry of Health and Social Protection. ORC Macro provided technical assistance for the MDHS through the USAID-funded MEASURE DHS project. Local costs of the survey were also supported by USAID, with additional funds from the United Nations Children's Fund (UNICEF), the United Nations Population Fund (UNFPA), and in-kind contributions from the NCPM.

MAIN RESULTS

CHARACTERISTICS OF RESPONDENTS

Ethnicity and Religion. Most women and men in Moldova are of Moldovan ethnicity (77 percent and 76 percent, respectively), followed by Ukrainian (8-9 percent of women and men), Russian (6 percent of women and men), and Gagauzan (4-5 percent of women and men). Romanian and Bulgarian ethnicities account for 2 to 3 percent of women and men. The overwhelming majority of Moldovans, about 95 percent, report Orthodox Christianity as their religion.

Residence and Age. The majority of respondents, about 58 percent, live in rural areas. For both sexes, there are proportionally more respondents in age groups 15-19 and 45-49 (and also 45-54 for men), whereas the proportion of respondents in age groups 25-44 is relatively lower. This U-shaped age distribution reflects the aging baby boom cohort following World War II (the youngest of the baby boomers are now in their mid-40s), and their children who are now mostly in their teens and 20s. The smaller proportion of men and women in the middle age groups reflects the smaller cohorts following the baby boom generation and those preceding the generation of baby boomers' children. To some degree, it also reflects the disproportionately higher emigration of the working-age population.

Education. Women and men in Moldova are universally well educated, with virtually 100 percent having at least some secondary or higher education; 79 percent of women and 83 percent of men have only a secondary or secondary special education, and the remainder pursues a higher education. More women (21 percent) than men (16 percent) pursue higher education.

Language Preference. Among women, preferences for language of reading material are about equal for Moldovan (37 percent) and Russian (35 percent) languages. Among men, preference for Russian (39 percent) is higher than for Moldovan (25 percent). A substantial percentage of women and men prefer Moldovan and Russian equally (27 percent of women and 32 percent of men).

Living Conditions. Access to electricity is almost universal for households in Moldova. Ninety percent of the population has access to safe drinking water, with 86 percent in rural areas and 96 percent in urban areas. Seventy-seven percent of households in Moldova have adequate means of sanitary disposal, with 91 percent of households in urban areas and only 67 percent in rural areas.

Children's Living Arrangements. Compared with other countries in the region, Moldova has the highest proportion of children who do not live with their mother and/or father. Only about two-thirds (69 percent) of children under age 15 live with both parents. Fifteen percent live with just their mother although their father is alive, 5 percent live with just their father although their mother is alive, and 7 percent live with neither parent although they are both alive. Compared with living arrangements of children in 2000, the situation appears to have worsened.

FERTILITY

Fertility Levels and Trends. The total fertility rate (TFR) in Moldova is 1.7 births. This means that, on average, a woman in Moldova will give birth to 1.7 children by the end of her reproductive period. Overall, fertility rates have declined since independence in 1991. However, data indicate that fertility rates may have increased in recent years. For example, women of childbearing age have given birth to, on average, 1.4 children at the end of their childbearing years. This is slightly less than the total fertility rate (1.7), with the difference indicating that fertility in the past three years is slightly higher than the accumulation of births over the past 30 years.

Fertility Differentials. The TFR for rural areas (1.8 births) is higher than that for urban areas (1.5 births). Results show that this urban-rural difference in childbearing rates can be attributed almost exclusively to younger age groups.

CONTRACEPTION

Knowledge of Contraception. Knowledge of family planning is nearly universal, with 99 percent of all women age 15-49 knowing at least one modern method of family planning. Among all women, the male condom, IUD, pills, and withdrawal are the most widely known methods of family planning, with over 80 percent of all women saying they have heard of these methods. Female sterilization is known by two-thirds of women, while periodic abstinence (rhythm method) is recognized by almost six in ten women. Just over half of women have heard of the lactational amenorrhea method (LAM), while 40-50 percent of all women have heard of injectables, male sterilization, and foam/jelly. The least widely known methods are emergency contraception, diaphragm, and implants.

Use of Contraception. Sixty-eight percent of currently married women are using a family planning method to delay or stop childbearing. Most are using a modern method (44 percent of married women), while 24 percent use a traditional method of contraception. The IUD is the most widely used of the modern methods, being used by 25 percent of married women. The next most widely used method is withdrawal, used by 20 percent of married women. Male condoms are used by about 7 percent of women, especially younger women. Five percent of married women have been sterilized and 4 percent each are using the pill and periodic abstinence (rhythm method). The results show that Moldovan women are adopting family planning at lower parities (i.e., when they have fewer children) than in the past. Among younger women (age 20-24), almost half (49 percent) used contraception before having any children, compared with only 12 percent of women age 45-49.

MATERNAL HEALTH

Antenatal Care and Delivery Care. Among women with a birth in the five years preceding the survey, almost all reported seeing a health professional at least once for antenatal care during their last pregnancy; nine in ten reported 4 or more antenatal care visits. Seven in ten women had their first antenatal care visit in the first trimester. In addition, virtually all births were delivered by a health professional, in a health facility. Results also show that the vast majority of women have timely checkups after delivering; 89 percent of all women received a medical checkup within two days of the birth, and another 6 percent within six weeks.

CHILD HEALTH

Childhood Mortality. The infant mortality rate for the 5-year period preceding the survey is 13 deaths per 1,000 live births, meaning that about 1 in 76 infants dies before the first birthday. The under-five mortality rate is almost the same with 14 deaths per 1,000 births. The near parity of these rates indicates that most all early childhood deaths take place during the first year of life. Comparison with official estimates of IMRs suggests that this rate has been improving over the past decade.

NUTRITION

Breastfeeding Practices. Breastfeeding is nearly universal in Moldova: 97 percent of children are breastfed. However the duration of breast-feeding is not long, exclusive breastfeeding is not widely practiced, and bottle-feeding is not uncommon. In terms of the duration of breastfeeding, data show that by age 12-15 months, well over half of children (59 percent) are no longer being breastfed. By age 20-23 months, almost all children have been weaned.

Exclusive breastfeeding is not widely practiced and supplementary feeding begins early: 57 percent of breastfed children less than 4 months are exclusively breastfed, and 46 percent under six months are exclusively breastfeed. The remaining breastfed children also consume plain water, water-based liquids or juice, other milk in addition to breast milk, and complimentary foods. Bottle-feeding is fairly widespread in Moldova;

Abstract

The Cambodia Inter-Censal Population Survey, 2004 was designed not only to obtain the much-needed demographic data following the census, but also to serve as a means to train the staff of the NIS and Provincial Planning Offices in demographic data collection.

There are plans to produce in-depth studies on fertility, mortality, migration, literacy and education, labour force, housing and household amenities, and population projections based on the results of the survey.

The Cambodia Inter-Censal Population Survey 2004 (CIPS) is a nationally representative sample survey taken between two censuses, the 1998 census and the proposed 2008 census, in order to update information on population size and growth and other population characteristics as well as household facilities and amenities. Due to the national elections and administrative issues, the CIPS was undertaken in March 2004 instead of 2003, which would have been the five-year midpoint between the 1998 and 2008 censuses.

The conduct of the CIPS 2004 is an important step in the creation of a continuous flow of data that will allow Cambodia to prepare plans and programmes supported by a strong database.

The Cambodia Inter-Censal Population Survey 2004 was conducted with the objective of providing information on the following indicators: - Sex, age and marital status - Births and Deaths - Migration status - Literacy/Educational level - Economic characteristics - Housing and household amenities - Other population and household information

These fresh data will allow for calculations and reliable projections of: - Population size and growth - Fertility - Mortality - Migration

The survey was also intended to train the national staff in sampling, data collection, data processing, analysis and dissemination.

Geographic coverage

National

Analysis unit

Individual, Household

Universe

All Population and housing for all regular households in Cambodia excluding special settlements and institutional households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design for the CIPS 2004 is a three-stage stratified cluster sampling design, it is a probability sample selection of 100 percent of the Cambodian villages coverage areas, the survey covered only regular households and excludes special settlements and institutional households.

The CIPS 2004 was conducted in a nationwide representative sample of 21,000 households within selected 700 villages (primary sampling units) out of 13,886 villages in Cambodia. The 700 villages were selected from updated frame (list of villages for Cambodia).

The General Population Census 1998 databases of the National Institute of Statistics together with the new updated list of villages that were excluded in the general population census of 1998 was used as the sampling frame for the sampling design of the CIPS 2004.

The frame has the following identification particulars: 1- Province code 2- Province name 3- District code 4- District name 5- Commune code 6- Commune name 7- Village Code 8- Village name 9- Size of village (number of households) 10- Area code (1 = Urban, 2 = Rural)

A three-stage sample design has been used for the CIPS. In the first stage a sample of villages was selected. The villages were implicitly stratified into 45 strata (21 provinces each with rural/urban strata i.e. 42 strata plus 3 provinces each totally urban, i.e. 3 urban strata). The villages were selected using linear systematic sampling with probabilities proportionate to size (PPS). The size measure used for the selection was number of households in the village according to the 1998 Census with estimation for a few additional villages not in the 1998 census frame.

In the second stage one Census Enumeration Area was selected randomly (in the head office) in each selected PSU. At the beginning of the fieldwork all households in the EA were listed. A systematic sample of 30 non-vacant households was selected as the third stage of selection.

The listing of households in the EA would become cumbersome if there are many households in the EA. This might be the case when the enumeration area had grown substantially since the census. When the EA was large (population wise) the interviewer was instructed to split the EA into two or more approximately equal-sized segments and to select one segment randomly. All households in the selected segment were listed. Out of the 700 Sample PSUs, 598 were from the rural super stratum and the remaining 102 were from the urban super stratum. For more information on sampling for the survey the general report at national level may be referred to.

Note: All provincial headquarters were treated as urban. In the case of Sihanoukville, Kep and Pailin, the entire province was treated as urban. In Phnom Penh province, the four districts of Doun Penh, Chamkar Mon, 7 Makara and Tuol Kouk were classified as urban. All the remaining areas of the country were rural. Further, urban and rural areas are being reclassified in Cambodia. While these reclassifications have already been drafted, they have not yet been approved by the Royal Government of Cambodia. Upon endorsement and adoption, the new classifications will be used in future census/surveys.

Mode of data collection

Face-to-face [f2f]

Research instrument

The draft questionnaires for the CIPS 2004 were more or less on the 1998 General Census pattern. Some modifications, however, were made by adding new questions on

(i) Whether children aged 0-14 living with own mother (ii) Whether a person's mother is alive and (iii) Details of deaths in households in the last one year with focus on maternal mortality.

Questions mentioned at (i) and (ii) were intended respectively to estimate fertility (by application of own child method) and mortality (by application of orphan hood method). The questions to be included were carefully considered by a Working Group of Cambodia Inter-Censal Population Survey 2004, whose members were mostly from Ministries, NGOs and International Agencies. The Questionnaires were tested twice in the field (both urban and rural) by NIS staff in November 2003. The purpose of the pre-test was to have a full-dressed rehearsal of the whole process and particularly to test the questions in the field so as to make corrections in wording or definitions and to estimate the time taken for enumeration area mapping, house listing, sampling and enumeration of selected household. Based on the pre-test experience the questionnaires were modified and finalized.

Two types of questionnaires were used in the CIPS 2004: Form A House-list and Form B Household Questionnaire.

The Form A was used to collect information on buildings containing one or more households during the preliminary round preceding survey night (March 3, 2004). The information collected related to: construction material of wall, roof and floor, whether it is a wholly or partly residential building, number of households within the building, name and sex of head of household and number of persons usually living in the household.

The Form B, which has five parts, was used for survey enumeration in the period closely following the reference time.

In Part I, information on usual members of the selected household present on survey night, visitors present as well as usual members absent on survey night, was collected.

Part II was used to collect information on each usual member of the household and each visitor present on survey night. The information collected included: full name, relationship to household head, sex, age, natural mother, child aged 0-14 living with own mother, marital status, age at first marriage, mother tongue, religion, place of birth, previous residence, duration of stay, reason for migration, literacy, full time education and economic characteristics.

Part III was used to collect information on females of reproductive age (15-49) as well as children born to these women.

The information collected in part IV related to household conditions and facilities: main source of light, main cooking fuel used, whether toilet facility is available, main source of drinking water and number of living rooms occupied by household.

Part V was used to record the following information in respect of deaths in the household within the last one year:- name of deceased, sex, relationship to head of household, age at death, whether the death has been registered with the civil authorities or not, the cause of death and maternal mortality information.

Cleaning operations

The completed records (Forms A, Form B, Form I, Form II, Map, and other Forms) were systematically collected from the provinces by NIS Survey Coordinators on the due date and submitted to the team receptionist at NIS. NIS Survey Coordinators formed into three teams of two persons were trained during March 7-10 to receive and arrange the completed forms and maps for processing after due checking form the field. Control forms were prescribed by DUC to record every form without any omission. These records were carefully checked, registered and stored in the record room. Editing and coding of the questionnaires were done manually, after which the questionnaires were submitted to the computer section for further processing. The instruction for editing and coding were revised and expanded. Training on editing and coding was conducted for senior staff, who in turn had to train other editors and coders.

The purpose of the editing process was to remove matters of obvious inconsistency, incorrectness and incompleteness, and to improve the quality of data collected. Coding had to be done very carefully in

Abstract

The Survey Assessment of Vietnamese Youth (SAVY) undertaken in late 2003 was a collaboration of the Ministry of Health, General Statistics Office with technical and financial support from the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF).

This is the first nationwide baseline survey of youth ever undertaken in Viet Nam. It mainly aims to collect data on various aspects of youth life in order to inform policy and programmes in the adolescent and youth health and development area.

SAVY reveals a positive picture of Vietnamese youth as they face both challenges and opportunities in a changing economic and social environment. Compared with young people in other Asian countries, Vietnamese youth display relatively less risky behaviour, are supported by protective factors and are optimistic and eager to build a prosperous country. However, this survey does reveal that some young people will encounter considerable challenges in their transition to adulthood, unless provided with support. It is important that parents, the community and the government, with the support of international agencies and young people, work together to ensure the healthy development of young people in Viet Nam.

The survey involved 7,584 youth aged 14-25 years from 42 provinces across the country, from the smallest rural hamlet to the largest cities. Using a household sample, youth were invited to a central location to complete both a face-to-face interview and a self-administered anonymous survey which contained sensitive questions young people could answer in private. What results is the most extensive understanding of the social life, attitudes and aspirations of young Vietnamese people today.

Survey Objectives - Provide information that can best inform future initiatives to promote the healthy development of youth across the country; - Inform policy and program development in the Adolescent and Youth Health area in the immediate future; and - Provide baseline data about Vietnamese youth to identify trends and patterns in the coming years.

Survey Content The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinion of young people ware actively solicited to ensure quality and relevance. The specific information collected through the questionnaire includes: Personal demographics Schooling, education Vocational training, Work and employment Puberty: knowledge and behaviors about reproductive health Dating and friendships HIV/AIDS Injury, illness and physical health Attitudes, perceptions and behaviors Social factors and emotional wellbeing Mass media Future aspirations

Survey Implementation SAVY is a collaborative effort between many agencies and young people. It is the result of extensive investment and parnership building between the Vietnamese Government through the Ministry of Health, the General Statistics Office, and United Nations agencies, notably The World Health Organisation and the United Nations Children's Fund. Several other organizations, from a variety of sectors, also contributed to the endeavor, notably the Ministry of Education and Training (MoET), the Central Youth Union (YU) and the Vietnam Women's Union (VWU). In order to ensure that the survey was methodologically sound, the East- West Centrer (Honolulu, Hawaii) provided intensive technical assisstance.

Survey Results Results from the surveys, including national reports, and micro level datasets. The dataset was formatted by *.sav (SPSS) and *.dta (STATA) More information and electronic files of SAVY, visit : http://www.moh.gov.vn/SKSS/Savy_htm/savy.htm

Geographic coverage

National

Analysis unit

Youth aged 14-25 years

Universe

The survey covered all youths aged 14-25 years resident in the household. The SAVY sample did not include Vietnamese youth not living with their families nor those living in military barracks, social protection centers, dormitories, re-education centers and drug treatment centers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The SAVY sample is a national representative sample of youth (persons ages 14-25 years) living in households across the eight economic regions of Viet Nam. THe sample was drawn from the sub-sample of 45,000 households in the 2002 Viet Nam Living Standards Survey (VLSS 2002), within a multi-staged and stratified design. The youth in the SAVY sample design are sufficient to represent the nation as a whole, as well as the urban and rural separely. The largest cities (Hanoi and Ho Chi Minh) were over sampled in order to provide for increased statistical power in that segment of the total population of youth.

Forty-two out of 61 provinces were selected for the SAVY sample, using the probability proportional to size (PPS) method to maintain representativeness . At the next stage of sampling, enumeration areas (EAs) in each province were selected. In those EAs sampled, all youth aged 14 through 25 were identified (i.e, those born between 1978 and 1989) males and females, married and non married from the 20 households that had been selected for the VLSS2002. The youth cohort represents all youth, but not those living in special arrangements, such as barracks, re-education centers, social protection centers, factories and dormitories.

The 61 provinces in the VLSS 2002 sample included 2.250 EAS, and the 42 provinces selected for SAVY included 1643 EAs. From these, a total of 446 EAs were selected for the SAVY sample. These EAs contained 8920 households corresponding to a population of 40,140 (about 4.5 persons per household). Since youth aged 14-25 account for 24.5% of the total population (the figure in the 1999 census), the anticipated number of youth in the SAVY sample was approximately 9,835. If the mobilization rate (percentage of eligible youth actually interviewed) was 90% then the number of youth interviewed woul be estimated to be about 8,850. In the actual SAVY field experiece, the mobilization rate was 85% and the number of completed interviews was 7,584.

The sample is therefore representative, and provides sufficient cases for analysis at the national level within urban and rural sectors at the national level, by gender at the nation level, and for each of the regions. Further detail on the sampling methodology is provided in the Appendix of the Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinions of young people were actively solicited to ensure quality and relevance. This process also helped to define the methodology and implications for fieldwork planning.

A number of stakeholders’ agencies, including research institutes, were involved in the development of the questionnaire. This process ensured broad participation and ownership of the questionnaire and the survey.

The questionnaire design took place in two stages. In the first stage, experienced researchers, and others interested in the survey as stakeholders, were convened to a workshop by the MoH. Potential topics, and the possible phrasing of questions using the questionnaire bank from previous studies in the region as reference, were fully discussed. Since some of the topics were deemed to be more sensitive than others, it was recommended that the questionnaire should be organized into two parts, one for an interview and the other for self-completion. On the basis of that workshop, a draft questionnaire was created for review by the workshop members and numerous others in stakeholder agencies, as well as by young people through a series of consultations.

Eight focus group discussions were conducted in Hanoi and HCMC, with around 60 young people of different ages in the 14-25 range who were either married or unmarried and either attending or not attending school. Participants gave detailed feedback about the terminology, the ways in which questions were posed and the sequencing of the questions, as well as which specific questions or issues they would prefer to respond to on their own, rather than with an interviewer. This process resulted in the rephrasing of a number of questions and changes to the self-completed section.

Preliminary training was conducted for field-testing of the questionnaire. Participants came from the GSO Office in Tuyen Quang, Hue and HCMC, representing the north, south and central regions of Viet Nam. A group of 50 young males and females, either married or unmarried and either attending or not attending school, participated in the interviewers’ practice session. In the debriefing discussions, these young people expressed their feelings about the interviews, the questions asked, what they liked and did not like about the process, seating arrangements, ideas of what topics/issues they thought might still be missing in the draft questionnaire, and what they thought would be needed to make good interviewers. Field testing with around 180 young people from six communes in these three provinces then took place.

The second stage involved further vetting of questionnaire sections and was coordinated by the GSO. The review meeting following the field trips recommended the need for another field testing exercise, particularly because little experience had been gained from testing with urban young people and interviewing ethnic minority young people through interpreters. Following the second round of field-testing in Hanoi and Yen Bai, the feedback was incorporated to finalise the questionnaire for the interviewers training. At the training, further revision and refinement of

教育：农村：其他在06-01-2021达0.000%，相较于06-01-2020的0.000%保持不变。教育：农村：其他数据按年更新，06-01-2020至06-01-2021期间平均值为0.000%，共2份观测结果。该数据的历史最高值出现于06-01-2021，达0.000%，而历史最低值则出现于06-01-2021，为0.000%。CEIC提供的教育：农村：其他数据处于定期更新的状态，数据来源于National Institute of Statistics，数据归类于全球数据库的柬埔寨 – Table KH.G014: Education Statistics。

教育：农村：初中完成在06-01-2021达8.600%，相较于06-01-2020的8.600%保持不变。教育：农村：初中完成数据按年更新，06-01-2020至06-01-2021期间平均值为8.600%，共2份观测结果。该数据的历史最高值出现于06-01-2021，达8.600%，而历史最低值则出现于06-01-2021，为8.600%。CEIC提供的教育：农村：初中完成数据处于定期更新的状态，数据来源于National Institute of Statistics，数据归类于全球数据库的柬埔寨 – Table KH.G014: Education Statistics。

Abstract

The 2022 Bangladesh Demographic and Health Survey (2022 BDHS) is the ninth national survey to report on the demographic and health conditions of women and their families in Bangladesh. The survey was conducted under the authority of the National Institute of Population Research and Training (NIPORT), Medical Education and Family Welfare Division, Ministry of Health and Family Welfare (MOHFW), Government of Bangladesh.

The primary objective of the 2022 BDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the BDHS collected information on: • Fertility and childhood mortality levels • Fertility preferences • Awareness, approval, and use of family planning methods • Maternal and child health, including breastfeeding practices • Nutrition levels • Newborn care

The information collected through the 2022 BDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the population of Bangladesh. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Bangladesh.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2022 BDHS is the Integrated Multi-Purpose Sampling Master Sample, selected from a complete list of enumeration areas (EAs) covering the whole country. It was prepared by the Bangladesh Bureau of Statistics (BBS) for the 2011 population census of the People’s Republic of Bangladesh. The sampling frame contains information on EA location, type of residence (city corporation, other than city corporation, or rural), and the estimated number of residential households. A sketch map that delineates geographic boundaries is available for each EA.

Bangladesh contains eight administrative divisions: Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Each division is divided into zilas and each zila into upazilas. Each urban area in an upazila is divided into wards, which are further subdivided into mohallas. A rural area in an upazila is divided into union parishads (UPs) and, within UPs, into mouzas. These administrative divisions allow the country to be separated into rural and urban areas.

The survey is based on a two-stage stratified sample of households. In the first stage, 675 EAs (237 in urban areas and 438 in rural areas) were selected with probability proportional to EA size. The BBS drew the sample in the first stage following specifications provided by ICF. A complete household listing operation was then carried out by Mitra and Associates in all selected EAs to provide a sampling frame for the second-stage selection of households.

In the second stage of sampling, a systematic sample of an average of 45 households per EA was selected to provide statistically reliable estimates of key demographic and health variables for urban and rural areas separately and for each of the eight divisions in Bangladesh.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four types of questionnaires were used for the 2022 BDHS: the Household Questionnaire, the Woman’s Questionnaire (completed by ever-married women age 15–49), the Biomarker Questionnaire, and two verbal autopsy questionnaires. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect population and health issues relevant to Bangladesh. In addition, a selfadministered Fieldworker Questionnaire collected information about the survey’s fieldworkers. The questionnaires were adapted for use in Bangladesh after a series of meetings with a Technical Working Group (TWG). The questionnaires were developed in English and then translated to and printed in Bangla.

Cleaning operations

The survey data were collected using tablet PCs running Windows 10.1 and Census and Survey Processing System (CSPro) software, jointly developed by the United States Census Bureau, ICF, and Serpro S.A. The Bangla language questionnaire was used for collecting data via computer-assisted personal interviewing (CAPI). The CAPI program accepted only valid responses, automatically performed checks on ranges of values, skipped to the appropriate question based on the responses given, and checked the consistency of the data collected. Answers to the survey questions were entered into the PC tablets by each interviewer. Supervisors downloaded interview data to their computer, checked the data for completeness, and monitored fieldwork progress

Each day, after completion of interviews, field supervisors submitted data to the servers. Data were sent to the central office via the internet or other modes of telecommunication allowing electronic transfer of files. The data processing manager monitored the quality of the data received and downloaded completed files into the system. ICF provided the CSPro software for data processing and offered technical assistance in preparation of the data editing programs. Secondary editing was conducted simultaneously with data collection. All technical support for data processing and use of PC tablets was provided by ICF.

Abstract

The Tajik Living Standards Survey (TLSS) was conducted jointly by the State Statistical Agency and the Center for Strategic Studies under the Office of the President in collaboration with the sponsors, the United Nations Development Programme (UNDP) and the World Bank (WB). International technical assistance was provided by a team from the London School of Economics (LSE). The purpose of the survey is to provide quantitative data at the individual, household and community level that will facilitate purposeful policy design on issues of welfare and living standards of the population of the Republic of Tajikistan in 1999.

Geographic coverage

National coverage. The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

The country is divided into 4 oblasts, or regions; Leninabad in the northwest of the country, Khatlon in the southwest, Rayons of Republican Subordination (RRS) in the middle and to the west of the country, and Gorno-Badakhshan Autonomous Oblast (GBAO) in the east. The capital, Dushanbe, in the RRS oblast, is a separately administrated area. Oblasts are divided into rayons (districts). Rayons are further subdivided into Mahallas (committees) in urban areas, and Jamoats (villages) in rural areas.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

In common with standard LSMS practice a two-stage sample was used. In the first stage 125 primary sample units (PSU) were selected with the probability of selection within strata being proportional to size. At the second stage, 16 households were selected within each PSU, with each household in the area having the same probability of being chosen. [Note: In addition to the main sample, the TLSS also included a secondary sample of 15 extra PSU (containing 400 households) in Dangara and Varzob. Data in the oversampled areas were collected for the sole purpose of providing baseline data for the World Bank Health Project in these areas. The sampling for these additional units was carried out separately after the main sampling procedure in order to allow for their exclusion in nationally representative analysis.] The twostage procedure has the advantage that it provides a self-weighted sample. It also simplified the fieldwork operation as a one-field team could be assigned to cover a number of PSU.

A critical problem in the sample selection with Tajikistan was the absence of an up to date national sample frame from which to select the PSU. As a result lists of the towns, rayons and jamoats (villages) within rayons were prepared manually. Current data on population size according to village and town registers was then supplied to the regional offices of Goskomstat and conveyed to the center. This allowed the construction of a sample frame of enumeration units by sample size from which to draw the PSU.

This procedure worked well in establishing a sample frame for the rural population. However administrative units in some of the larger towns and in the cities of Dushanbe, Khojand and Kurgan-Tubbe were too large and had to be sub-divided into smaller enumeration units. Fortuitously the survey team was able to make use of information available as a result of the mapping exercise carried out earlier in the year as preparation for the 2000 Census in order to subdivide these larger areas into enumeration units of roughly similar size.

The survey team was also able to use the household listings prepared for the Census for the second stage of the sampling in urban areas. In rural areas the selection of households was made using the village registers – a complete listing of all households in the village which is (purported to be) regularly updated by the local administration. When selecting the target households a few extra households (4 in addition to the 16) were also randomly selected and were to be used if replacements were needed. In actuality non-response and refusals from households were very rare and use of replacement households was low. There was never the case that the refusal rate was so high that there were not enough households on the reserve list and this enabled a full sample of 2000 randomly selected households to be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was based on the standard LSMS for the CIS countries, and adapted and abridged for Tajikistan. In particular the health section was extended to allow for more in depth information to be collected and a section on food security was also added. The employment section was reduced and excludes information on searching for employment.

The questionnaires were translated into Tajik, Russian and Uzbek.

The TLSS consists of three parts: a household questionnaire, a community level questionnaire and a price questionnaire.

Household questionnaire: the Household questionnaire is comprised of 10 sections covering both household and individual aspects.

Community/Population point Questionnaire: the Community level or Population Point Questionnaire consists of 8 sections. The community level questionnaire provides information on differences in demographic and economic infrastructure. Open-ended questions in the questionnaire were not coded and hence information on the responses to these qualitative questions is not provided in the data sets.

Summary of Section contents

The brief descriptions below provide a summary of the information found in each section. The descriptions are by no means exhaustive of the information covered by the survey and users of the survey need to refer to each particular section of the questionnaire for a complete picture of the information gathered.

Household information/roster This includes individual level information of all individuals in the household. It establishes who belongs to the household at the time of the interview. Information on gender, age, relation to household head and marital status are included. In the question relating to family status, question 7, “Nekared” means married where nekar is the Islamic (arabic) term for marriage contract. Under Islamic law a man may marry more than once (up-to four wives at any one time). Although during the Soviet period it was illegal to be married to more than one woman this practice did go on. There may be households where the household head is not present but the wife is married or nekared, or in the same household a respondent may answer married and another nekared to the household head.

Dwelling This section includes information covering the type of dwelling, availability of utilities and water supply as well as questions pertaining to dwelling expenses, rents, and the payment of utilities and other household expenses. Information is at the household level.

Education This section includes all individuals aged 7 years and older and looks at educational attainment of individuals and reasons for not continuing education for those who are not currently studying. Questions related to educational expenditures at the household level are also covered. Schooling in Tajikistan is compulsory for grades (classes) 1-9. Primary level education refers to grades 1 - 4 for children aged 7 to 11 years old. General secondary level education refers to grades 5-9, corresponding to the age group 12-16 year olds. Post-compulsory schooling can be divided into three types of school: - Upper secondary education covers the grades 10 and 11. - Vocational and Technical schools can start after grade 9 and last around 4 years. These schools can also start after grade 11 and then last only two years. Technical institutions provide medical and technical (e.g. engineering) education as well as in the field of the arts while vocational schools provide training for employment in specialized occupation. - Tertiary or University education can be entered after completing all 11 grades. - Kindergarten schools offer pre-compulsory education for children aged 3 – 6 years old and information on this type of schooling is not covered in this section.

Health This section examines individual health status and the nature of any illness over the recent months. Additional questions relate to more detailed information on the use of health care services and hospitals, including expenses incurred due to ill health. Section 4B includes a few terms, abbreviations and acronyms that need further clarification. A feldscher is an assistant to a physician. Mediniski dom or FAPs are clinics staffed by physical assistants and/or midwifes and a SUB is a local clinic. CRH is a local hospital while an oblast hospital is a regional hospital based in the oblast administrative centre, and the Repub. Hospital is a national hospital based in the capital, Dushanbe. The latter two are both public hospitals.

Employment This section covers individuals aged 11 years and over. The first part of this section looks at the different activities in which individuals are involved in order to determine if a person is engaged in an income generating activity. Those who are engaged in such activities are required to answer questions in Part B. This part relates to the nature of the work and the organization the individual is attached to as well as questions relating to income, cash income and in-kind payments. There are also a few questions relating to additional income generating activities in addition to the main activity. Part C examines employment

Abstract

The 2011 Bangladesh Demographic and Health Survey (BDHS) is the sixth DHS undertaken in Bangladesh, following those implemented in 1993-94, 1996-97, 1999-2000, 2004, and 2007. The main objectives of the 2011 BDHS are to: • Provide information to meet the monitoring and evaluation needs of health and family planning programs, and • Provide program managers and policy makers involved in these programs with the information they need to plan and implement future interventions.

The specific objectives of the 2011 BDHS were as follows: • To provide up-to-date data on demographic rates, particularly fertility and infant mortality rates, at the national and subnational level; • To analyze the direct and indirect factors that determine the level of and trends in fertility and mortality; • To measure the level of contraceptive use of currently married women; • To provide data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS; • To assess the nutritional status of children (under age 5), women, and men by means of anthropometric measurements (weight and height), and to assess infant and child feeding practices; • To provide data on maternal and child health, including antenatal care, assistance at delivery, breastfeeding, immunizations, and prevalence and treatment of diarrhea and other diseases among children under age 5; • To measure biomarkers, such as hemoglobin level for women and children, and blood pressure, and blood glucose for women and men 35 years and older; • To measure key education indicators, including school attendance ratios and primary school grade repetition and dropout rates; • To provide information on the causes of death among children under age 5; • To provide community-level data on accessibility and availability of health and family planning services; • To measure food security.

The 2011 BDHS was conducted under the authority of the National Institute of Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare. The survey was implemented by Mitra and Associates, a Bangladeshi research firm located in Dhaka. ICF International of Calverton, Maryland, USA, provided technical assistance to the project as part of its international Demographic and Health Surveys program (MEASURE DHS). Financial support was provided by the U.S. Agency for International Development (USAID).

Geographic coverage

National

Analysis unit

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

Universe

The 2011 BDHS covers the entire population residing in noninstitutional dwelling units in the country.

Kind of data

Sample survey data

Sampling procedure

Sample Design The sample for the 2011 BDHS is nationally representative and covers the entire population residing in noninstitutional dwelling units in the country. The survey used as a sampling frame the list of enumeration areas (EAs) prepared for the 2011 Population and Housing Census, provided by the Bangladesh Bureau of Statistics (BBS). The primary sampling unit (PSU) for the survey is an EA that was created to have an average of about 120 households.

Bangladesh has seven administrative divisions: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. Each division is subdivided into zilas, and each zila into upazilas. Each urban area in an upazila is divided into wards, and into mohallas within a ward. A rural area in the upazila is divided into union parishads (UP) and mouzas within a UP. These divisions allow the country as a whole to be easily separated into rural and urban areas.

The survey is based on a two-stage stratified sample of households. In the first stage, 600 EAs were selected with probability proportional to the EA size, with 207 clusters in urban areas and 393 in 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. In the second stage of sampling, a systematic sample of 30 households on average was selected per EA to provide statistically reliable estimates of key demographic and health variables for the country as a whole, for urban and rural areas separately, and for each of the seven divisions. With this design, the survey selected 18,000 residential households, which were expected to result in completed interviews with about 18,000 ever-married women. In addition, in a subsample of one-third of the households, all evermarried men age 15-54 were selected and interviewed for the male survey. In this subsample, a group of eligible members were selected to participate in testing of the biomarker component, including blood pressure measurements, anemia, blood glucose testing, and height and weight measurements.

Note: See Appendix A (in final survey report) for the details of the sample design.

Sampling deviation

The 2007 BDHS sampled all ever-married women age 10-49. The number of eligible women age 10-49 was 11,234, of whom 11,051 were interviewed for a response rate of 98.4 percent. However, there were very few ever-married women age 10-14 (55 unweighted cases or less than one percent). These women have been removed from the data set and weights recalculated for the 15-49 age group. The tables in the survey report discuss only women age 15-49.

Mode of data collection

Face-to-face

Research instrument

The 2011 BDHS used five types of questionnaires: a Household Questionnaire, a Woman’s Questionnaire, a Man’s Questionnaire, a Community Questionnaire, and two Verbal Autopsy Questionnaires to collect data on causes of death among children under age 5. The contents of the household and individual questionnaires were based on the MEASURE DHS model questionnaires. These model questionnaires were adapted for use in Bangladesh during a series of meetings with a Technical Working Group (TWG) that consisted of representatives from NIPORT, Mitra and Associates, International Centre for Diarrheal Diseases and Control, Bangladesh (ICDDR,B), USAID/Bangladesh, and MEASURE DHS. Draft questionnaires were then circulated to other interested groups and were reviewed by the 2011 BDHS Technical Review Committee. The questionnaires were developed in English and then translated and printed into Bangla.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, information was collected about the dwelling unit, such as the source of water, type of toilet facilities, materials used to construct the floors and walls, and ownership of various consumer goods. The Household Questionnaire was also used to record for eligible individuals: • Height and weight measurements • Anemia test results • Measurements of blood pressure and blood glucose

The Woman’s Questionnaire was used to collect information from ever-married women age 12-49. Women were asked questions on the following topics: • Background characteristics (e.g., age, education, religion, and media exposure) • Reproductive history • Use and source of family planning methods • Antenatal, delivery, postnatal, and newborn care • Breastfeeding and infant feeding practices • Child immunizations and childhood illnesses • Marriage • Fertility preferences • Husband’s background and respondent’s work • Awareness of AIDS and other sexually transmitted infections • Food security

The Man’s Questionnaire was used to collect information from ever-married men age 15-54. Men were asked questions on the following topics: • Background characteristics (including respondent’s work) • Marriage • Fertility preferences • Participation in reproductive health care • Awareness of AIDS and other sexually transmitted infections

The Community Questionnaire was administered in each selected cluster during the household listing operation. Data were collected by administering the Community Questionnaire to a group of four to six community leaders who were knowledgeable about socioeconomic conditions and the availability of health and family planning services/facilities, in or near the sample area (cluster). Community leaders included such persons as government officials, social workers, teachers, religious leaders, traditional healers, and health care providers.

The Community Questionnaire collected information about the existence of development organizations in the community and the availability and accessibility of health services and other facilities. During the household listing operation, the geographic coordinates and altitude of each cluster were also recorded. The information obtained in these questionnaires was also used to verify information gathered in the Woman’s and Man’s Questionnaires on the types of facilities accessed and health services personnel seen.

The Verbal Autopsy Questionnaires were developed based on the work done by an expert group led by the WHO, consisting of researchers, data users, and other stakeholders under the sponsorship of the Health Metrics Network (HMN). The verbal autopsy tools are intended to serve the various needs of the users of mortality information. Two questionnaires were used to collect information related to the causes of death among young children; the first questionnaire collected data on neonatal deaths (deaths at 0-28 days), and the