Professional organizations in STEM (science, technology, engineering, and mathematics) can use demographic data to quantify recruitment and retention (R&R) of underrepresented groups within their memberships. However, variation in the types of demographic data collected can influence the targeting and perceived impacts of R&R efforts - e.g., giving false signals of R&R for some groups. We obtained demographic surveys from 73 U.S.-affiliated STEM organizations, collectively representing 712,000 members and conference-attendees. We found large differences in the demographic categories surveyed (e.g., disability status, sexual orientation) and the available response options. These discrepancies indicate a lack of consensus regarding the demographic groups that should be recognized and, for groups that are omitted from surveys, an inability of organizations to prioritize and evaluate R&R initiatives. Aligning inclusive demographic surveys across organizations will provide baseline data that can be used to target and evaluate R&R initiatives to better serve underrepresented groups throughout STEM. Methods We surveyed 164 STEM organizations (73 responses, rate = 44.5%) between December 2020 and July 2021 with the goal of understanding what demographic data each organization collects from its constituents (i.e., members and conference-attendees) and how the data are used. Organizations were sourced from a list of professional societies affiliated with the American Association for the Advancement of Science, AAAS, (n = 156) or from social media (n = 8). The survey was sent to the elected leadership and management firms for each organization, and follow-up reminders were sent after one month. The responding organizations represented a wide range of fields: 31 life science organizations (157,000 constituents), 5 mathematics organizations (93,000 constituents), 16 physical science organizations (207,000 constituents), 7 technology organizations (124,000 constituents), and 14 multi-disciplinary organizations spanning multiple branches of STEM (131,000 constituents). A list of the responding organizations is available in the Supplementary Materials. Based on the AAAS-affiliated recruitment of the organizations and the similar distribution of constituencies across STEM fields, we conclude that the responding organizations are a representative cross-section of the most prominent STEM organizations in the U.S. Each organization was asked about the demographic information they collect from their constituents, the response rates to their surveys, and how the data were used. Survey description The following questions are written as presented to the participating organizations. Question 1: What is the name of your STEM organization? Question 2: Does your organization collect demographic data from your membership and/or meeting attendees? Question 3: When was your organization’s most recent demographic survey (approximate year)? Question 4: We would like to know the categories of demographic information collected by your organization. You may answer this question by either uploading a blank copy of your organization’s survey (linked provided in online version of this survey) OR by completing a short series of questions. Question 5: On the most recent demographic survey or questionnaire, what categories of information were collected? (Please select all that apply)

Disability status Gender identity (e.g., male, female, non-binary) Marital/Family status Racial and ethnic group Religion Sex Sexual orientation Veteran status Other (please provide)

Question 6: For each of the categories selected in Question 5, what options were provided for survey participants to select? Question 7: Did the most recent demographic survey provide a statement about data privacy and confidentiality? If yes, please provide the statement. Question 8: Did the most recent demographic survey provide a statement about intended data use? If yes, please provide the statement. Question 9: Who maintains the demographic data collected by your organization? (e.g., contracted third party, organization executives) Question 10: How has your organization used members’ demographic data in the last five years? Examples: monitoring temporal changes in demographic diversity, publishing diversity data products, planning conferences, contributing to third-party researchers. Question 11: What is the size of your organization (number of members or number of attendees at recent meetings)? Question 12: What was the response rate (%) for your organization’s most recent demographic survey? *Organizations were also able to upload a copy of their demographics survey instead of responding to Questions 5-8. If so, the uploaded survey was used (by the study authors) to evaluate Questions 5-8.

Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated

Demographic information about the online survey respondents (%, n = 314) regarding: gender; age; country of residence; position in the trade; and how they encountered the surveySurvey sample demographics.

Abstract

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

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

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

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

The questionnaires were developed in Turkish and translated into English.

Cleaning operations

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

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

Response rate

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

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the TDHS-2013 to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

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

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

Public perception regarding diagnostic sample types as well as personal experiences can influence willingness to test. As such, public preferences for specific sample type(s) should be used to inform diagnostic and surveillance testing programs to improve public health response efforts. To understand where preferences lie, we conducted an international survey regarding the sample types used for SARS-CoV-2 tests. A Qualtrics survey regarding SARS-CoV-2 testing preferences was distributed via social media and email. The survey collected preferences regarding sample methods and key demographic data. Python was used to analyze survey responses. From March 30th to June 15th, 2022, 2,094 responses were collected from 125 countries. Participants were 55% female and predominantly aged 25–34 years (27%). Education and employment were skewed: 51% had graduate degrees, 26% had bachelor’s degrees, 27% were scientists/researchers, and 29% were healthcare workers. By rank sum analysis, the most preferred sample type globally was the oral swab, followed by saliva, with parents/guardians preferring saliva-based testing for children. Respondents indicated a higher degree of trust in PCR testing (84%) vs. rapid antigen testing (36%). Preferences for self- or healthcare worker-collected sampling varied across regions. This international survey identified a preference for oral swabs and saliva when testing for SARS-CoV-2. Notably, respondents indicated that if they could be assured that all sample types performed equally, then saliva was preferred. Overall, survey responses reflected the region-specific testing experiences during the COVID-19. Public preferences should be considered when designing future response efforts to increase utilization, with oral sample types (either swabs or saliva) providing a practical option for large-scale, accessible diagnostic testing.

Abstract

The 2015-16 Armenia Demographic and Health Survey (2015-16 ADHS) is the fourth in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the objective of the 2015-16 ADHS is to provide current and reliable information on fertility and abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, domestic violence against women, child discipline, awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking, tuberculosis, and anemia. The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.

The 2015-16 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve the health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2015-16 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000, 2005, and 2010 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2015-16 ADHS also provides comparable data for longterm trend analysis because the 2000, 2005, 2010, and 2015-16 surveys were implemented by the same organization and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to produce representative estimates of key indicators at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.

The sampling frame used for the 2015-16 ADHS is the Armenia Population and Housing Census, which was conducted in Armenia in 2011 (APHC 2011). The sampling frame is a complete list of enumeration areas (EAs) covering the whole country, a total number of 11,571 EAs, provided by the National Statistical Service (NSS) of Armenia, the implementing agency for the 2015-16 ADHS. This EA frame was created from the census data base by summarizing the households down to EA level. A representative probability sample of 8,749 households was selected for the 2015-16 ADHS sample. The sample was selected in two stages. In the first stage, 313 clusters (192 in urban areas and 121 in rural areas) were selected from a list of EAs in the sampling frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey. Appendix A provides additional information on the sample design of the 2015-16 Armenia DHS. Because of the approximately equal sample size in each marz, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used for the 2015-16 ADHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Armenia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Armenian. They were pretested in September-October 2015.

Cleaning operations

The processing of the 2015-16 ADHS data began shortly after fieldwork commenced. All completed questionnaires were edited immediately by field editors while still in the field and checked by the supervisors before being dispatched to the data processing center at the NSS central office in Yerevan. These completed questionnaires were edited and entered by 15 data processing personnel specially trained for this task. All data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data was an advantage because the senior ADHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in June 2016.

Response rate

A total of 8,749 households were selected in the sample, of which 8,205 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 7,893, yielding a household response rate of 96 percent. The household response rate in urban areas (96 percent) was nearly the same as in rural areas (97 percent).

In these households, a total of 6,251 eligible women were identified; interviews were completed with 6,116 of these women, yielding a response rate of 98 percent. In one-half of the households, a total of 2,856 eligible men were identified, and interviews were completed with 2,755 of these men, yielding a response rate of 97 percent. Among men, response rates are slightly lower in urban areas (96 percent) than in rural areas (97 percent), whereas rates for women are the same in urban and in rural areas (98 percent).

The 2015-16 ADHS achieved a slightly higher response rate for households than the 2010 ADHS (NSS 2012). The increase is only notable for urban households (96 percent in 2015-16 compared with 94 percent in 2010). Response rates in all other categories are very close to what they were in 2010.

Sampling error estimates

SAS computer software were used to calculate sampling errors for the 2015-16 ADHS. The programs used the Taylor linearization method of variance estimation for means or proportions and the Jackknife repeated replication method 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 B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children based on the NCHS/CDC/WHO International Reference Population - Vaccinations by background characteristics for children age 18-29 months

See details of the data quality tables in Appendix C of the survey final report.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

Descriptive statistics for the demographic variables of the full survey sample.

Abstract

The SHDS is a national sample survey designed to provide information on population, birth spacing, reproductive health, nutrition, maternal and child health, child survival, HIV/AIDS and sexually transmitted infections (STIs), in Somalia.. The main objective of the SHDS was to provide evidence on the health and demographic characteristics of the Somali population that will guide the development of programmes and formulation of effective policies. This information would also help monitor and evaluate national, sub-national and sector development plans, including the Sustainable Development Goals (SDGs), both by the government and development partners. The target population for SHDS was the women between 15 and 49 years of age, and the children less than the age of 5 years

Geographic coverage

The SHDS 2020 was a nationally representative household survey.

Analysis unit

The unit analysis of this survey are households, women aged 15-49 and children aged 0-5

Universe

This sample survey covered Women aged 15-49 and Children aged 0-5 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample for the SHDS was designed to provide estimates of key indicators for the country as a whole, for each of the eighteen pre-war geographical regions, which are the country's first-level administrative divisions, as well as separately for urban, rural and nomadic areas. With the exception of Banadir region, which is considered fully urban, each region was stratified into urban, rural and nomadic areas, yielding a total of 55 sampling strata. All three strata of Lower Shabelle and Middle Juba regions, as well as the rural and nomadic strata of Bay region, were completely excluded from the survey due to security reasons. A final total of 47 sampling strata formed the sampling frame. Through the use of up-to-date, high-resolution satellite imagery, as well as on-the-ground knowledge of staff from the respective ministries of planning, all dwelling structures were digitized in urban and rural areas. Enumeration Areas (EAs) were formed onscreen through a spatial count of dwelling structures in a Geographic Information System (GIS) software. Thereafter, a sample ground verification of the digitized structures was carried out for large urban and rural areas and necessary adjustments made to the frame.

Each EA created had a minimum of 50 and a maximum of 149 dwelling structures. A total of 10,525 EAs were digitized: 7,488 in urban areas and 3,037 in rural areas. However, because of security and accessibility constraints, not all digitized areas were included in the final sampling frame-9,136 EAs (7,308 in urban and 1,828 in rural) formed the final frame. The nomadic frame comprised an updated list of temporary nomadic settlements (TNS) obtained from the nomadic link workers who are tied to these settlements. A total of 2,521 TNS formed the SHDS nomadic sampling frame. The SHDS followed a three-stage stratified cluster sample design in urban and rural strata with a probability proportional to size, for the sampling of Primary Sampling Units (PSU) and Secondary Sampling Units (SSU) (respectively at the first and second stage), and systematic sampling of households at the third stage. For the nomadic stratum, a two-stage stratified cluster sample design was applied with a probability proportional to size for sampling of PSUs at the first stage and systematic sampling of households at the second stage. To ensure that the survey precision is comparable across regions, PSUs were allocated equally to all regions with slight adjustments in two regions. Within each stratum, a sample of 35 EAs was selected independently, with probability proportional to the number of digitized dwelling structures. In this first stage, a total of 1,433 EAs were allocated (to urban - 770 EAs, rural - 488 EAs, and nomadic - 175 EAs) representing about 16 percent of the total frame of EAs. In the urban and rural selected EAs, all households were listed and information on births and deaths was recorded through the maternal mortality questionnaire. The data collected in this first phase was cleaned and a summary of households listed per EA formed the sampling frames for the second phase. In the second stage, 10 EAs were sampled out of the possible 35 that were listed, using probability proportional to the number of households. All households in each of these 10 EAs were serialized based on their location in the EA and 30 of these households sampled for the survey. The serialization was done to ensure distribution of the households interviewed for the survey in the EA sampled. A total of 220 EAs and 150 EAs were allocated to urban and rural strata respectively, while in the third stage, an average of 30 households were selected from the listed households in every EA to yield a total of 16,360 households from 538 EAs covered (220 EAs in urban, 147 EAs in rural and 171 EAs in nomadic) out of the sampled 545 EAs. In nomadic areas, a sample of 10 EAs (in this case TNS) were selected from each nomadic stratum, with probability proportional to the number of estimated households. A complete listing of households was carried out in the selected TNS followed by the selection of 30 households for the main survey interview. In those TNS with less than 30 households, all households were interviewed for the main survey. All eligible ever-married women aged 12 to 49 and never-married women aged 15 to 49 were interviewed in the selected households, while the household questionnaire was administered to all households selected. The maternal mortality questionnaire was administered to all households in each sampled TNS.

Mode of data collection

Face-to-face [f2f]

Response rate

A total of 16,360 households were selected for the sample, of which 15,870 were occupied. Of the occupied households, 15,826 were successfully interviewed, yielding a response rate of 99.7 percent. The SHDS 2020 interviewed 16,486 women-11,876 ever-married women and 4,610 never-married women.

Sampling error estimates

Sampling errors are important data quality parameters which give measure of the precision of the survey estimates. They aid in determining the statistical reliability of survey 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 Somaliland Health and Demographic Survey ( SHDS 2020) to minimise 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 SHDS 2020 is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. 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% of all possible samples of identical size and design. If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the SHDS 2020 sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The variance approximation procedure that account for the complex sample design used R program was estimated sampling errors in SHDS which is Taylor series linearization. The non-linear estimates are approximated by linear ones for estimating variance. The linear approximation is derived by taking the first-order Tylor series approximation. Standard variance estimation methods for linear statistics are then used to estimate the variance of the linearized estimator. The Taylor linearisation method treats any linear statistic such as a percentage or mean as a ratio estimate, r = y/x, where y represents the total sample value for variable y and x represents the total number of cases in the group or subgroup under consideration

Data appraisal

• Household age distribution
• Age distribution of eligible and interviewed women
• Pregnancy- related mortality trends Note: See detailed data quality tables in APPENDIX C of the report.

Abstract

The 2022 Socio-Demographic and Economic Survey is a nationally representative household survey designed to provide information on population, migration, education, labour and employment, fertility, disability, household, and housing characteristics. The key objectives of the survey are:

-to generate essential key indicators as inputs in the preparation of national plans and programs for the well-being of the population -to monitor the progress of development programs as stipulated in the Sustainable Development Goals (SDGs), Medium Term Development Plans, Vision 2050 and other national policies/plans and priorities.

Geographic coverage

National coverage. 43 strata and 22 provinces were covered.

Analysis unit

Household and Individual.

Kind of data

Sample survey data [ssd]

Sampling procedure

-Used a stratified, two-stage cluster sampling method, with a third stage in very large sample census units (CU, enumeration areas selected within the sample CUs).

-Produced 43 strata, 22 provinces by urban/rural (National Capital District has only urban areas).

-Allocation was done proportionately according to size (in terms of the number of households).

-Thus, 335 CUs / clusters were selected in the first- stage while a fixed number of 15 households per cluster were selected at the second stage resulting to a total sample size of 5,025 households.

Sampling deviation

Coverage: 95.8% (14 out of 335 clusters not accessed) due to security issues (tribal fights/lawlessness), and election related misconceptions.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was generated using the World Bank's software Survey Solutions. It contains a set of 47 questions covering several modules such as Employment, Fertility, Housing, Disability, Education. The questionnaire is provided in English in the External Resources section in this documentation.

Cleaning operations

-Checking of data submitted from field, identifying unique / valid households and removing invalid or duplicate households, coding of responses, consistency checks -Tabulations - generating tables for data analysis and generation of key indicators

Abstract

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

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

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

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

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

Geographic coverage

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

Analysis unit

• Household
• Women age 15-49

Universe

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

Kind of data

Sample survey data

Sampling procedure

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

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

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

Mode of data collection

Face-to-face

Research instrument

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

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

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

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

Cleaning operations

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

Response rate

The results of the household and individual

Abstract

A National Census of Population and Housing could not be ventured due to the disturbances in the Northern and eastern Provinces. Hence the Dept of Census and Statistics has decided to conduct an island-wide large scale demographic survey (excluding the Northern and Eastern Provinces) during the year 1994 to satisfy the urgent needs of the data users, with a view to furnish estimates at Divisional Secretariat, District, Provincial and National levels.

Geographic coverage

National coverage (excluding Northern and Eastern Provinces)

Analysis unit

Housing Unit

A housing unit has been defined as a place of residence:

1. which is separate from other places of residence, ie where there are walls or partitions separating it so that the persons occupying it can live separately from other persons in the building or in the locality and 2. which has independent access.

Living Quarters other than housing units

Building or a group of buildings where a number of persons (generally not related to one another) reside under the supervision of a central authority, eg convents, school, hostels, police barracks, boarding houses etc

Non Housing unit

Every building or part of a building which is not a place of residence and does not form part of a housing unit is regarded as a non-housing unit.

Household

A household may be (a) a one person Household or (b) a multi-person household

A one person household is one where a person lives by himself and makes separate provision for his food (either cooking it himself or purchasing it)

A multi person household is a group of two or more persons live together and have a common arrangement for cooking and partaking of food (in short, living and eating together). The household includes not only members of the family but also others who live with the family and share meals with them such as relatives boarders servants. The members of a household could be unrelated.

In the case of lodgers living with a household and having their own arrangements for meals, each lodger should be treated as a separate household. But boarders who share meals with the household should be treated as members of the household.

a housing unit may consist of one or more households.

Universe

The population living in housing units alone were selected for the survey. Institutional population such as those who are living in barracks, hostels etc has not been encompassed. Accordingly, the estimates reflect a coverage confined to the institutional population who were accounted for 2.3% of the entire population in Sri Lanka in 1981 which could be considerably higher at present. Nontheless the household definition has been modified to incorporate all the households without an upper limit for boarders and lodgers. Therefore the data user should note this distinction of population when comparing with other data.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 92,180 housing units distributed in the island barring Northern and Eastern Provinces was picked for this survey. Stratification was done at sectoral level and all the Divisional Secretary areas were taken as domains. A minimal samples of 300 housing units were selected from each DSD in order to give estimates at these levels. Percentage of Urban housing units in the country was 13% and the balance 87% represented the Rural housing units. When allocating the total sample into these two sectors however Urban (MC UC sector) was over sampled because this sector is more heterogeneous in terms of the characteristics, which were to be collected through this survey. As such at national level 21360 housing units (23%) were allocated to Urban sector and 70820 housing units (77%) were allocated to Rural sector.

A stratified two stage sample design was used with GN Division or part of the GN Division as primary sampling unit (PSU) and housing unit as the secondary sampling unit (SSU) in the rural sector. Rural sector covers about 219 DS Divisions. 3541 PSU's were selected from this sector and 20 housing units selected from each selected PSU.

Urban sector covered all the Municipal Councils and urban Councils in the island (excl North and east). A stratified three stage sample design was adopted with PPS selection of Wards and subsequent selection of a part of Ward as PSU and the housing unit as the final sampling unit were done. About 40% of the wards in each MC/UC was selected as PPS with replacement. Thereafter SSU's were selected from each selected ward. Finally 40 housing unit's were selected from each selected PSU. The Urban Sector represents 10 MCs and 32 UC's in 42 Divisional Secretariat Divisions.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is similar to which is usually administered in the Census of Population and Housing with few exceptions. Housing questions were filled only in the schedule of the main household of the housing unit. The information as collected in the Housing Section (H1-H.13) has been processed in order to tabulate the housing data.

Cleaning operations

Standard Data editing process of DPD/DCS

Response rate

Estimates given in the publication - Demographic Survey 1994 Sri Lanka - Feb 1996 - are subject to standard sampling errors due to enumeration of only selected housing units representing the population. An account of non sampling error is also not readily available for reference.

an adjustment for non-response and coverage errors have been done while inflating the data.

Abstract

The Government of the Republic of Zambia conducted the 2024 Zambia Demographic and Health Survey (2024 ZDHS). The survey was implemented by the Zambia Statistics Agency (ZamStats) in partnership with the Ministry of Health (MoH), the University Teaching Hospital Virology Laboratory (UTH-VL), the National Health Research and Training Institute (NHRTI) formerly the Tropical Diseases Research Centre (TDRC), and the Department of Demography, Population Sciences, Monitoring and Evaluation at the University of Zambia (UNZA).

The primary objective of the 2024 ZDHS is to provide up-to-date estimates of basic demographic and health indicators as well as indicators related to the Sustainable Development Goals (SDGs). Specifically, the ZDHS collected information on: - Fertility levels, fertility preferences, and contraceptive use - Maternal health, including antenatal and delivery care and maternal mortality - Child mortality and child heath, including childhood diseases and vaccination coverage - Nutritional status of children under age 5 and women age 15–49 (via weight and height measurements) - Anemia prevalence among children age 6–59 months and women age 15–49 - Availability of, access to, and use of insecticide-treated nets (ITNs) - Awareness of HIV and behavioral risk factors - HIV prevalence among men age 15–59, women age 15–49, and children age 2–14 - Gender-based violence

The information collected through the 2024 ZDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Zambia’s population.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, 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 2024 ZDHS was based on the 2022 Census of Population and Housing of the Republic of Zambia (2022 CPH), conducted by the Zambia Statistics Agency. Zambia is administratively divided into 10 provinces, with each province subdivided into districts, each district into constituencies, and each constituency into wards. There are in total 116 districts, 156 constituencies, and 1,858 wards. In addition to these administrative units, during the 2022 CPH each ward was subdivided into enumeration areas (EA) that served as counting units for the population census. There are in total 36,770 EAs. EAs are classified into two types, urban EAs and rural EAs. Among the 36,770 EAs, 13,273 are urban and 23,497 are rural. Each EA has two measures of size, the size of the population and the number of households in the EA. The average EA size is 111 households; urban EAs are larger on average than rural EAs (143 households and 93 households, respectively).

The 2024 ZDHS sample was stratified and selected in two stages. The first stage involved selecting sample points (clusters) consisting of EAs. Each province was stratified into urban and rural areas, yielding 20 sampling strata in total. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected. The second stage involved systematic sampling of households. A household listing exercise was undertaken in all of the selected clusters. During the listing, an average of 111 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels. All women age 15–49 and men age 15–59 who were either permanent residents of the selected households or were visitors who stayed in the households the night before the survey were eligible to be interviewed.

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

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used for the 2024 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Zambia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers. The Household, Man’s, and Woman’s Questionnaires were administered in eight major languages: English, Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga.

Cleaning operations

The survey data were collected using tablet computers running the Android operating system and Census and Survey Processing System (CSPro) software, jointly developed by the United States Census Bureau, ICF, and Serpro S.A.

The CAPI programme was used for data collection. The programme 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 tablets by each interviewer. Supervisors downloaded interview data from interviewers’ tablets to their tablet via Bluetooth, checked the data for completeness, and monitored fieldwork progress. Each day, after completion of interviews, field supervisors submitted data to the central server. Data were sent to the central office via secure internet data transfer. The data processing monitors monitored the quality of the data received and downloaded completed data files for completed clusters into the system. ICF provided the CSPro software for data processing and offered technical assistance in the preparation of the data capture, data management, and data editing programmes. Secondary editing was conducted simultaneously with data collection and was completed following data collection on 28 August 2024. Technical support for data processing was provided by ICF.

Response rate

A total of 13,625 households were selected for the ZDHS sample, of which 12,877 were found to be occupied. Of the occupied households, 12,808 were successfully interviewed, yielding a response rate of almost 100%. In the interviewed households, 14,362 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 13,951 women, yielding a response rate of 97%. Also, 13,424 men age 15–59 in the interviewed households were identified as eligible for individual interviews and 12,585 were successfully interviewed, yielding a response rate of 94%.

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 2024 Zambia Demographic and Health Survey (2024 ZDHS) 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 2024 ZMDHS is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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 and minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2024 ZMDHS sample was the result of a multistage stratified cluster design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF International. These programmes use the Taylor linearization method to estimate variances for survey estimates that are means, medians, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility rates and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Age displacement at

Abstract

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

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

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

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

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

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

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

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

Sampling deviation

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

Mode of data collection

Face-to-face

Research instrument

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

The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview. In addition, information was collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.

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

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

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

Cleaning operations

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

Response rate

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

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

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions

Abstract

To improve the situation the PCBS has decided to undertake a fairly large demographic survey The main purpose of this survey is to provide basic demographic estimates at both the national and district level filling important gaps in existing statistics and reducing uncertainties surrounding the utility of available data Specifically, the survey provides detailed data on the following topics Population structure Female fertility Fertility preference Infant and child mortality Maternal and adult mortality Internal and international migration Marriage Family and household composition Educational attainmentHousing conditions

Geographic coverage

The target population consists of all Palestinian households that usually reside in the West Bank and Gaza Strip

Analysis unit

individual/ Household

Universe

The target population in this sample survey comprises all households living in West Bank and Gaza Strip excluding institutional population and nomads

Kind of data

Sample survey data [ssd]

Sampling procedure

A sampling strategy comprises two main elements: a sample design describing the scheme by which the sample of survey units is selected, and the estimators by which survey results can be computed from sample data. The two elements are usually closely interrelated, and determine the quality or reliability of survey estimates. In this section both elements will be described briefly. A more detailed description is provided in a separate working paper (Abu Hassan and Tamsfoss 1995).

The sample design adopted is a stratified three stage design for selection of households to be surveyed. At the first stage a sample of localities was selected. The sample localities have been subdivided into cells of approximately equal size, and a number of cells were selected randomly from each of the sample localities at the second stage. At the third and final stage, a sample of households was selected from the sample cells. For all the demographic variables included in the survey, records were taken for all members of the sample household.

Although a two-stage design would have been preferable, the present, more complex one is partly an outcome of limited availability of data on which sample designing usually is based, specifically data on the population size of various small area units, e.g. cells. The sample designing was undertaken in parallel with the updating of maps for the localities in the West Bank and Gaza Strip during the winter and spring 1995 - another ongoing PCBS project. Due to the limited time available, the design had to be completed before a complete set of updated locality maps was ready, implying the small area information needed was available for only a limited number of localities. However, the map updating was coordinated with the sample designing in such a way that once the first stage sample of localities was selected, mapping of these localities was given highest priority, thus offering an opportunity to subdivide sample localities into cells with a known measure of (population) size.

The present design is based on listings of localities provided by Barghouti and Daibas (1993) for the West Bank, and Abdeen and Abu-Libdeh (1993) for the Gaza Strip. Even though the population figures are rough estimates as per 1992-93, produced mainly by questioning local administration informants (e.g. Mukhtars) about the number of families in the locality, or projected estimates, they appear to be fairly well attuned with other sources (e.g. Benvenisti and Khayat 1988). Furthermore, the listings applied as a frame comprise more localities than previous ones, and should thus be more complete. However, the coverage may still be less than - although close to - 100% in terms of areas.

The first stage comprises the assigning of localities (as listed by Barghouti and Daibas 1993; Abdeen and Abu Libdeh 1993) to be the Primary Sampling Units (PSUs), the stratification of the PSUs, and the selection of sample PSUs from each stratum. The stratification is a subdivision of the PSUs according to district, administrative status of the locality, and estimated population (households) size. The PSUs were selected independently for each stratum, and with probability proportionate to estimated population size. In the Gaza Strip all localities were selected. The same applies to the district capitals, municipal localities and refugee camps in the West Bank, except in two strata in A Ramallah district. Whenever all PSUs in a stratum are selected, the design is a two stage one, and each single PSU is to be regarded as a separate substratum. The two stage design also applies for several of the small villages (single cell localities). As a matter of fact, the major parts of the sample is selected in two stages only, contributing favorably to smaller sampling error as compared to a strict three stage design.

The second stage subdivision of sample PSUs into cells (or Secondary Sampling Units - SSUs) was done on maps indicating location of buildings and a rough estimate of the number of dwelling in each building. Thus, for each sample PSU or locality as a whole, there are two size measures available; the estimated number of households, and the roughly estimated number of dwelling units. Although these sets of measures proved to be positively correlated, they departed significantly in most cases. However, for the cells, the number of dwelling units were the only measure of size available. Therefore, when selecting the sample cells from each sample PSU with probability proportionate to size, the size in terms of dwelling units had to be applied, i.e. a conceptually different size measure than the one applied at the first stage of selection (households).

For each sample cell the population has been listed by enumeration of buildings (map reference), and dwelling units. It should be noted that the number of dwelling units in each building was assessed by listers from outside no thorough inquiries were made as to whether they were inhabited or not. It was thus expected that errors would occur rather frequently - a problem which is to be evaluated separately on the basis of data collected during the survey. The listing of dwelling units constitutes the Sampling Frame from which the household sample was selected at a third stage by systematic sampling.

The planned sample size was 15,000 households. However, due to the sampling frame imperfections which were envisaged (several non-eligible units included), oversampling was carried out at a rate of approximately 30%, i.e. the gross sample selected at the outset comprised around 20,000 dwelling units.

The sampling design and sample allocation yield a household sample with varying inclusion probabilities. In order to have unbiased results, it is thus recommended that all estimates are based on weighed observations, the weights being the inverse of the respective inclusion probabilities.

All households in a cell have the same probability of being selected, however varying from cell to cell. It should be noted that non-eligible dwelling units (i.e. units which are not inhabited by households) have been removed from the sample. This does not affect the inclusion probabilities or the weights . The actual values of the weights are in the range 0.3 to 3.0. However, 80 % of the weights are in the range 0.7 to 1.4. Only a very few (small) cells are near the extremes.

Since the sampling design is a complex multi-stage one, variance must be calculated with other methods than those applicable to simple random sampling. In order to carry out the calculations, the software CENVAR (US Bureau of the Census 1993) has been used.

Mode of data collection

Face-to-face [f2f]

Research instrument

e Demographic Survey questionnaire consists of seven main parts Control Sheet which includes items related to quality control sample identification interview schedule and interview results Household Roster which includes questions related to the demographic and socio-economic characteristics of persons Household Mortality Schedule which includes questions related to deaths in the household during the past 24 months. Housing Schedule which includes questions on housing and housing conditions Relatives Abroad Schedule which includes questions on the number and the demographic characteristics of close relatives residing abroad Women's Schedule which includes questions mainly related to ever married women age 14-54 years Birth History which includes questions related to the characteristics of all births occurring to ever married women eligible for interview Answers to the first five parts of the questionnaires were obtained by interviewing the household head or any adult member of the household in cases where the head was not present during enumeration The last two sections of the questionnaire were completed by interviewing all eligible women The questionnaire was worded in colloquial Arabic Questions were written in full on the questionnaire and strict instructions were given to interviewers to read all questions verbatim during the interviews

Cleaning operations

A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks logical check range checks consisting checks and cross-validation Weekly thorough checks on the overall consistency of the data files and sample allocation were also performed after data entry Questionnaire containing field-related errors were sent back to the field for corrections EPI-INFO Version 6.02 supported with NAFITHA-Version 4.00 (Arabization program) was used

The American Community Survey: Public Use Microdata Sample: Artist Extract, 2018-2022 can be downloaded from the IPUMS USA website. The extract captures information on the number of artists, by occupation, demographic group, and other individual characteristics. To explore social, housing, and economic characteristics within the arts sector, the 2018-2022 ACS 5-year sample can narrowed down to only respondents in arts-related occupations (identified by the variable name: OCC): 1300 Architects, Except Naval 2600 Artists and Related Workers 2630 Designers 2700 Actors 2710 Producers and Directors 2740 Dancers and Choreographers 2750 Musicians, Singers, and Related Workers 2760 Entertainers and Performers, Sports and Related Workers, All Other 2700 Announcers 2850 Writers and Authors 2910 Photographers 2920 Television, Video, and Motion Picture Camera Operators and Editors Users can also visit the IPUMS USA website to analyze the 2018-2022 ACS 5-year sample online in the IPUMS SDA system. About the American Community Survey (ACS): The ACS is an ongoing statistical survey that samples a small percentage of the population every year -- giving communities the information they need to plan investments and services. The 5-year public use microdata sample (PUMS) for 2018-2022 is a subset of the 2015-2019 American Community Survey (ACS) and Puerto Rico Community Survey (PRCS) samples. It contains the same sample as the combined PUMS 1-year files for 2018, 2019, 2020, 2021, and 2022. The 2018-2022 ACS 5-year PUMS contains five years of data for housing units (HUs) and the population from households and the group quarters (GQ) population. The GQ population, housing units and population from households are all weighted to agree with the ACS counts, which are an average over the five year period. The ACS sample is selected from all counties across the nation and all municipios in Puerto Rico. The 5-year dataset is a 5-in-100 national random sample of the population, comprising all households and individuals from the 1% American Community Survey (ACS) samples for 2018, 2019, 2020, 2021, and 2022, identifiable by year. It includes persons in group quarters and is weighted. The smallest identifiable geographic unit is the PUMA, which contains at least 100,000 persons and does not cross state boundaries. However, the updating of some geography variables has been delayed due to the usage of two different census definitions (2010 and 2020) of PUMA across the five years in the sample. Regarding data quality issues caused by the COVID-19 pandemic, the Census Bureau revised its methodology for weighting households in the 2017-2020 5-year sample, resulting in larger coefficients of variation for some key estimates. Users should proceed with caution when using the 2020 1-year ACS PUMS file and should not compare it to other ACS years in the multi-year data samples. Please see ACS and COVID-19: Guidance for Using the PUMS with Experimental Weights for more information. Additionally, data collection errors occurred in certain years, notably in 2016, 2017, and 2019, affecting specific variables in particular counties. These errors should be considered when analyzing the data. Users should read the FAQ on the multi-year data.

Abstract

The 2009 Kiribati Demographic and Health Survey was the first survey in phase two of Pacific DHS Project with funding support from ADB. The primary objective of this survey was to provide up-to-date information for policy-makers, planners, researchers and programme managers, for use in planning, implementing, monitoring and evaluating population and health programmes within the country. The survey was intended to provide key estimates of Kiribati’s demographic and health situation.

The main objective of the 2009 Kiribati Demographic and Health Survey (2009 KDHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, the use of maternal and child healthcare services, and knowledge of HIV and AIDS. Specific objectives are to:

• collect data (at the national level) that will allow the calculation of key demographic rates;
• analyse the direct and indirect factors that determine the level and trends of fertility;
• measure the level of contraceptive knowledge and practice among women and men by method, urban–rural residence and region;
• collect high-quality data on family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5 years, and maternity care indicators (including antenatal visits, assistance at delivery, and postnatal care);
• collect data on infant and child mortality;
• obtain data on child feeding practices, including breastfeeding, and collect ‘observation’ information to use in assessing the nutritional status of women and children;
• collect data on knowledge and attitudes of women and men about sexually transmitted infections (STIs), HIV and AIDS, and evaluate patterns of recent behaviour regarding condom use; and
• collect data on knowledge and attitudes of women and men about tuberculosis.

Geographic coverage

National coverage.

Analysis unit

• Household,
• Individual.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary focus of the 2009 Kiribati Demographic Health Survey (DHS) was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole, for the urban area and rural areas (separately) - urban is South Tarawa and urban settlement on Kiritimati Island while the rest of Kiribati is defined as rural areas. The survey used the sampling frame provided by the list of census enumeration areas, with population and household information coming from the 2005 Kiribati Population and Housing Census.

The survey was designed to obtain completed interviews of 2,193 women aged 15-49. In addition, males aged 15-59 in every second household were interviewed. To take non-response into account, 1,480 households countrywide were selected: 640 in the urban area and 840 in rural areas.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were administered during the 2009 Kiribati Demographic Health Survey (KDHS): a Household questionnaire, a Women’s questionnaire and a Men’s questionnaire. These were adapted to reflect population and health issues relevant to Kiribati, and were presented at a series of meetings with various stakeholders, including government ministries and agencies, NGOs and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organised by Kiribati National Statistics Office (KNSO) in March 2009 in Tarawa. Survey questionnaires were then translated into the local language (I-Kiribati) and pretested from 7–19 August 2009.

The Household questionnaire was used to list all the usual members and visitors in selected households, and to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education and relationship to the head of the household. For children under age 18 years, the survival status of their parents was ascertained. The Household questionnaire also collected information on characteristics of each household’s dwelling unit, such as source of drinking water, type of toilet facility, material used for the floor, and ownership of various durable goods.

The Women’s questionnaire collected information from all women aged 15–49 about: - education, residential history and media exposure; - pregnancy history and childhood mortality; - knowledge and use of family planning methods; - fertility preferences; - antenatal, delivery and postnatal care; - breastfeeding and infant feeding practices; - immunisation and childhood illnesses; - marriage and sexual activity; - their own work and their husband’s background characteristics; and - awareness and behaviour regarding HIV and other STIs.

The Men’s questionnaire was administered to all men aged 15–49 living in every second household. It collected much of the same information as the women’s questionnaire, but was shorter because it did not contain questions about reproductive history or maternal and child health or nutrition.

Cleaning operations

Processing the 2009 Kiribati Demographic Health Survey (KDHS) results began three weeks after the start of fieldwork. Completed questionnaires were returned periodically from the field to the Kiribati National Statistics Office (KNSO) data processing center in South Tarawa, where the data were entered and edited by seven data processing personnel specially trained for this task. Data processing personnel were supervised by KNSO staff. Data entry and editing of questionnaires was completed by 30 March 30 2010. CSPRo was used for data processing.

Response rate

In total, 1,477 households were selected for the sample, of which 1,451 were found to be occupied during data collection. Of these existing households, 1,422 were successfully interviewed, giving a household response rate of 98%.

In households, 2,193 women were identified as being eligible for the individual interview. Interviews were completed with 1,978 women, yielding a response rate of 90%. Of the 1,337 eligible men identified in the selected sub-sample of households, 85% were successfully interviewed. Response rates were higher in rural areas than in the urban area, with the rural–urban difference in response rates being the greatest among eligible men.

Sampling error estimates

The sample of respondents selected in the 2009 Kiribati Demographic Health Survey (KDHS) 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 errors are the errors that result from taking a sample of the covered population through a particular sample design. Non-sampling errors are systematic errors that would be present even if the entire population was covered (e.g. response errors, coding and data entry errors, etc.).

For the entire covered population and for large subgroups, the KDHS sample is generally sufficiently large to provide reliable estimates. For such populations the sampling error is small and less important than the non-sampling error. However, for small subgroups, sampling errors become very important in providing an objective measure of reliability of the data.

Sampling errors will be displayed for total, urban and rural and each sample domain only. No other panels should be included in the sampling error table. The choice of variables for which sampling error computations will be done depends on the priority given to specific variables. However, it is recommended that sampling errors be calculated for at least the following variables, which was not case with Kiribati given the smallness of the sample compared to other countries in the Pacific.

Sampling errors are 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% of all possible samples of identical size and design.

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2009 KDHS sample was the result of a multistage stratified design, and, consequently, it is necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2009 KDHS is the Integrated Sample Survey Analysis (ISSA) Sampling Error Module. This module uses the Taylor linearisation method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

In addition to the standard error, ISSA

Abstract

The 1997 Jordan Population and Family Health Survey (JPFHS) is a national sample survey carried out by the Department of Statistics (DOS) as part of its National Household Surveys Program (NHSP). The JPFHS was specifically aimed at providing information on fertility, family planning, and infant and child mortality. Information was also gathered on breastfeeding, on maternal and child health care and nutritional status, and on the characteristics of households and household members. The survey will provide policymakers and planners with important information for use in formulating informed programs and policies on reproductive behavior and health.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

The 1997 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, for urban and rural areas, for the three regions (each composed of a group of governorates), and for the three major governorates, Amman, Irbid, and Zarqa.

The 1997 JPFHS sample is a subsample of the master sample that was designed using the frame obtained from the 1994 Population and Housing Census. A two-stage sampling procedure was employed. First, primary sampling units (PSUs) were selected with probability proportional to the number of housing units in the PSU. A total of 300 PSUs were selected at this stage. In the second stage, in each selected PSU, occupied housing units were selected with probability inversely proportional to the number of housing units in the PSU. This design maintains a self-weighted sampling fraction within each governorate.

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings and housing units were updated, listed and documented, along with the name of the owner/tenant of the unit or household and the name of the household head. These activities took place between January 7 and February 28, 1997.

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

Mode of data collection

Face-to-face

Research instrument

The 1997 JPFHS used two questionnaires, one for the household interview and the other for eligible women. Both questionnaires were developed in English and then translated into Arabic. The household questionnaire was used to list all members of the sampled households, including usual residents as well as visitors. For each member of the household, basic demographic and social characteristics were recorded and women eligible for the individual interview were identified. The individual questionnaire was developed utilizing the experience gained from previous surveys, in particular the 1983 and 1990 Jordan Fertility and Family Health Surveys (JFFHS).

The 1997 JPFHS individual questionnaire consists of 10 sections: - Respondent’s background - Marriage - Reproduction (birth history) - Contraception - Pregnancy, breastfeeding, health and immunization - Fertility preferences - Husband’s background, woman’s work and residence - Knowledge of AIDS - Maternal mortality - Height and weight of children and mothers.

Cleaning operations

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

Data entry started after a week of office data processing. The process of data entry, editing, and cleaning was done by means of the ISSA (Integrated System for Survey Analysis) program DHS has developed especially for such surveys. The ISSA program allows data to be edited while being entered. Data entry was completed on November 14, 1997. A data processing specialist from Macro made a trip to Jordan in November and December 1997 to identify problems in data entry, editing, and cleaning, and to work on tabulations for both the preliminary and final report.

Response rate

A total of 7,924 occupied housing units were selected for the survey; from among those, 7,592 households were found. Of the occupied households, 7,335 (97 percent) were successfully interviewed. In those households, 5,765 eligible women were identified, and complete interviews were obtained with 5,548 of them (96 percent of all eligible women). Thus, the overall response rate of the 1997 JPFHS was 93 percent. The principal reason for nonresponse among the women was the failure of interviewers to find them at home despite repeated callbacks.

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

Sampling error estimates

The estimates from a sample survey are subject to two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing (such as failure to locate and interview the correct household, misunderstanding questions either by the interviewer or the respondent, and data entry errors). Although during the implementation of the 1997 JPFHS numerous efforts were made to minimize this type of error, nonsampling errors are not only impossible to avoid but also difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The respondents selected in the 1997 JPFHS constitute only one of many samples that could have been selected from the same population, given the same design and expected size. Each of those samples would have yielded results differing somewhat from the results of the sample actually selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, since the 1997 JDHS-II sample resulted from a multistage stratified design, formulae of higher complexity had to be used. The computer software used to calculate sampling errors for the 1997 JDHS-II was the ISSA Sampling Error Module, which uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics, such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

Data appraisal

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

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

Abstract

The Cambodia Demographic and Health Survey 2000 (CDHS) is the first nationally representative survey ever conducted in Cambodia on population and health issues. The primary objective of the survey is to provide the Ministry of Health, Ministry of Planning (MoP), and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, health expenditures, women’s status, domestic violence, and knowledge and behavior regarding AIDS and other sexually transmitted infections (STIs). This information contributes to policy decisions, planning, monitoring, and program evaluation for the development of Cambodia, at both national- and local-government levels.

The long-term objectives of the survey are to technically strengthen the capacity both of the Ministry of Health and the National Institute of Statistics (NIS) of MoP for planning, conducting, and analyzing the results of further surveys.

The CDHS 2000 survey was conducted by the National Institute of Statistics of the Ministry of Planning, and the Ministry of Health. The CDHS executive committee and technical committee were established to oversee all technical aspects of implementation. They consisted of representatives from the Ministry of Health, the Ministry of Planning, the National Institute of Statistics, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), and the U.S. Agency for International Development (USAID). ORC Macro provided technical assistance including sampling design, survey methodology, interviewer training, and data analysis through the MEASURE DHS+ project. Funding for the survey came from UNFPA, UNICEF, and USAID.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The CDHS survey called for a nationally representative sample of 15,300 women between the ages of 15 and 49. Survey estimates are produced for 12 individual provinces (Banteay Mean Chey, Kampong Cham, Kampong Chhnang, Kampong Spueu, Kampong Thum, Kandal, Kaoh Kong, Phnom Penh, Prey Veaeng, Pousat, Svay Rieng, and Takaev) and for the following 5 groups of provinces: - Bat Dambang and Krong Pailin - Kampot, Krong Preah Sihanouk, and Krong Kaeb - Kracheh, Preah Vihear, and Stueng Traeng - Mondol Kiri and Rotanak Kiri - Otdar Mean Chey and Siem Reab.

The master sample developed in 1998 by the National Institute of Statistics served as the sampling frame for the CDHS survey. The master sample is based on the 1998 Cambodia General Population Census and consists of 600 villages selected with probability proportional to the number of households within the village. Villages are listed with the total population count and the number of enumeration areas (EAs), households, and segments. Enumeration areas were created during the cartography conducted in preparation for the 1998 census. A segment in a village corresponds to a block of about ten households. Segments were created only for villages retained in the master sample and maps showing their boundaries were also available for all of them.

The sample for the CDHS survey is a stratified sample selected in three stages. As for the master sample, stratification was achieved by separating every reporting domain into urban and rural areas. The sample was selected independently in every stratum.

The master sample contains a small number of villages for some of the provinces. For this reason, additional villages were directly selected from the census frame in order to reach the required sample size in these provinces. In the first stage, 471 villages were selected with probability proportional to the number of households in the village. Of these 471 villages, 63 were directly selected from the 1998 census frame. In the second stage, 5 or fewer segments were retained from each of the villages selected from the master sample, while 1 EA was retained from each of the 63 villages directly selected from the 1998 census frame. Each of these EAs consists of several segments.

A household listing was carried out in all selected segments and EAs, and the resulting lists of households served as the sampling frame for the selection of households in the third stage. All women 15-49 were interviewed in selected households.

In addition, a subsample of 50 percent of households was selected for data collection of anthropometry. Anemia testing was implemented in 25 percent of the sample. Only the women identified in the households with anemia testing were eligible for the section related to women's status. In this subsample of households, only one woman was selected in each household to be interviewed on domestic violence.

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

Mode of data collection

Face-to-face

Research instrument

Two types of questionnaires were used in the CDHS 2000 survey: the Household Questionnaire and the Women’s questionnaire. The contents of these questionnaires were based on the international MEASURE DHS+ model. They were modified according to the situation in Cambodia and were designed to provide information needed by health and family planning program managers and policymakers, mainly the Ministry of Health, the Ministry of Planning, and other relevant institutions and organizations. The agencies involved in developing these questionnaires were the National Institute of Public Health/MoH, the National Institute of Statistics/MoP, UNFPA, UNICEF, USAID, WHO, Hellen Keller International, Marie Stopes International, the Ministry of Women’s Affairs, Project Against Domestic Violence, and the Demographic and Health Surveys (DHS) project of ORC Macro. The questionnaires were developed in English and then translated into Khmer. Back translation of the questionnaires, from Khmer to English, was also conducted.

The Household Questionnaire enumerated all the usual members and visitors of the selected households and collected information on the socioeconomic status of the households. The first part of the questionnaire collected information on the relationship of the persons to the head of household and items such as residence, sex, age, marital status, and level of education. This information was used to identify women who were eligible for the individual interview. The Household Questionnaire also contained information on the prevalence of accidents, physical impairment, illness, and health expenditures. Information was also collected on the dwelling units, including source of water, type of toilet facilities, fuels used for cooking, materials used for the house’s floor and roof, and ownership of a variety of consumer goods. In addition, during the household survey, anthropometry and anemia testing were carried out to determine nutritional status among children less than five years old and women age 15-49.

The Women’s Questionnaire collected information from all women age 15-49 on the following topics:-• Respondent’s background characteristics - Reproduction - Contraceptin (knowledge and use of family planning) - Pregnancy, antenatal care, delivery, and postnatal care - Infant feeding practices, child immunization, and health - Marriage and sexual activity - Fertility preference - Husband’s background characteristics and women’s work - Knowledge of HIV/AIDS and other sexually transmitted infections - Maternal mortality and adult mortality - Women’s status - Domestic violence (household relations module).

Response rate

A total of 12,810 households were selected in the sample, of which 12,475 were occupied at the time the fieldwork was carried out. Of the 12,475 occupied households, 12,236 were successfully interviewed, resulting in a household response rate of 98.1 percent. The main reason for the noninterviewed households was that those households no longer existed in the sampled clusters at the time of the interview.

A total of 15,558 women in these households were identified as women eligible to be interviewed. Questionnaires were then completed for 15,351 of those women, which represented a response rate of 98.7 percent. The principal reason for nonresponse among eligible women was a failure to find them at home despite repeated visits to their household.

Note: See summarized response rates by residence (urban/rural) in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: 1) nonsampling errors, and 2) sampling errors. Nonsampling errors are the results of 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 2000 Cambodia Demographic and Health Survey (CDHS) 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 2000 Cambodia Demographic and Health Survey 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.

This data collection is comprised of responses from the March and April installments of the 2008 Current Population Survey (CPS). Both the March and April surveys used two sets of questions, the basic CPS and a separate supplement for each month.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the March supplement, known as the Annual Social and Economic (ASEC) supplement. The ASEC provides supplemental data on work experience, income, noncash benefits, and migration. Comprehensive work experience information was given on the employment status, occupation, and industry of persons 15 years old and older. Additional data for persons 15 years old and older are available concerning weeks worked and hours per week worked, reason not working full time, total income and income components, and place of residence on March 1, 2007. The March supplement also contains data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Questions covering training and assistance received under welfare reform programs, such as job readiness training, child care services, or job skill training were also asked in the March supplement.The April supplement, sponsored by the Department of Health and Human Services, queried respondents on the economic situation of persons and families for the previous year. Moreover, all household members 15 years of age and older that are a biological parent of children in the household that have an absent parent were asked detailed questions about child support and alimony. Information regarding child support was collected to determine the size and distribution of the population with children affected by divorce or separation, or other relationship status change. Moreover, the data were collected to better understand the characteristics of persons requiring child support, and to help develop and maintain programs designed to assist in obtaining child support. These data highlight alimony and child support arrangements made at the time of separation or divorce, amount of payments actually received, and value and type of any property settlement.The April supplement data were matched to March supplement data for households that were in the sample in both March and April 2008. In March 2008, there were 4,522 household members eligible, of which 1,431 required imputation of child support data. When matching the March 2008 and April 2008 data sets, there were 170 eligible people on the March file that did not match to people on the April file. Child support data for these 170 people were imputed. The remaining 1,261 imputed cases were due to nonresponse to the child support questions. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the preceding year, although other demographic data refer to the time at which the survey was administered.