Readers of The Guardian were more likely to be women, with nearly 15 million monthly female readers in the United Kingdom from April 2019 to March 2020. Readership of The Guardian proved to be more popular among older adults than younger ones. Throughout the period observed, approximately 18.5 million individuals over 35 years old read The Guardian, either on print or online.

Reach for The Sun

The tabloid newspaper The Sun saw the highest reach on 2019, with The Guardian as the sixth highest. Compared to other online news brands in the UK, BBC News online was by far the most popular, followed by the Mail online. The Guardian online was the third most popular online news brand as of February 2019.

Accessing the news online

More and more people access news online these days, with the main way of accessing online news? via smartphone. A 2019 survey revealed that half of users prefer smartphones to access news online.

Abstract

The 2023 Tajikistan Demographic and Health Survey (TjDHS) is the third Demographic and Health Survey conducted in Tajikistan. The primary objective of the 2023 TjDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility and contraceptive use, maternal and child health and nutrition, childhood mortality, domestic violence against women, child discipline, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2023 TjDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Tajikistan.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2023 TjDHS is the 2020 Tajikistan Population and Housing Census (TPHC), conducted by Tajstat. Administratively, Tajikistan is divided into five administrative regions: Dushanbe City, Districts of Republican Subordination (DRS), Sughd, Khatlon, and Gorno-Badakhshan Autonomous Oblast (GBAO). Each region is subdivided into urban and rural areas. The country is divided into 68 cities and rayons (districts) distributed over the country’s regions. Each city or rayon (district) is further divided into census divisions, which are subdivided into instruction areas. Each instruction area is divided into enumeration areas (EAs).

The 2023 TjDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were drawn with a probability proportional to their size within each sampling stratum. A total of 370 clusters were selected, 166 in urban areas and 204 in rural areas. The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 22 households per cluster were selected through an equal probability systematic selection process, for a total sample size of approximately 8,140 households.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Hemoglobin testing was performed in each household among eligible women age 15-49 who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anemia in each household. Height and weight information was collected from eligible women age 15-49 and children age 0-59 months in all households. Also, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence.

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

Three questionnaires were used in the 2023 TjDHS: the Household Questionnaire, the Woman’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 Tajikistan. Suggestions were 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 Russian and Tajik.

Cleaning operations

The 2023 TjDHS used a Windows-based system. All electronic data files were transferred via a secure SyncCloud server to the Tajstat central office in Dushanbe, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by five IT specialists/secondary editors who took part in the main fieldwork training, the training of trainers, and a refresher secondary editing training session; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in December 2023 and completed in February 2024.

Response rate

A total of 8,140 households were selected for the TjDHS sample, of which 8,070 were found to be occupied. Of the occupied households, 8,035 were successfully interviewed, yielding a response rate of over 99%. In the interviewed households, 9,930 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 9,879 women, yielding a response rate of over 99%.

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 2023 Tajikistan Demographic and Health Survey (2023 TjDHS) 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 2023 TjDHS 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 2023 TjDHS sample was the result of a multistage stratified cluster design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age displacement at age 14/15 - Age displacement at age 49/50 - Pregnancy outcomes by years preceding the survey - Completeness of reporting - Standardization exercise results from anthropometry training - Height and weight data completeness and quality for children - Height measurements from random subsample of measured children - Interference in height and weight measurements of children - Interference in height and weight measurements of women - Heaping in anthropometric measurements for children (digit preference) - Observation of handwashing facility - School attendance by single year of age - Vaccination cards photographed - Prevalence of anemia in children based on 2011 WHO guidelines - Prevalence of anemia in women based on 2011 WHO guidelines - Population pyramid - Five-year mortality rates See details of the data quality tables in Appendix C of the final report.

Content

Police Killings

This directory contains the data behind the story Where Police Have Killed Americans In 2015.

We linked entries from the Guardian's database on police killings to census data from the American Community Survey. The Guardian data was downloaded on June 2, 2015. More information about its database is available here.

Census data was calculated at the tract level from the 2015 5-year American Community Survey using the tables S0601 (demographics), S1901 (tract-level income and poverty), S1701 (employment and education) and DP03 (county-level income). Census tracts were determined by geocoding addresses to latitude/longitude using the Bing Maps and Google Maps APIs and then overlaying points onto 2014 census tracts. GEOIDs are census-standard and should be easily joinable to other ACS tables -- let us know if you find anything interesting.

Field descriptions:

Note regarding income calculations:

All income fields are in inflation-adjusted 2013 dollars.

comp_income is simply tract-level median household income as a share of county-level median household income.

county_bucket provides where the tract's median household income falls in the distribution (by quintile) of all tracts in the county. (1 indicates a tract falls in the poorest 20% of tracts within the county.) Distribution is not weighted by population.

nat_bucket is the same but for all U.S. counties.

Context

This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using GitHub's API and Kaggle's API.

This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

The print and digital reach of the Daily Star and Daily Star Sunday in the United Kingdom from April 2019 to March 2020 was higher among women than men, with over 5.7 million women a month reached by the Daily Star or its website on average. Reach was also significantly higher amongst older consumers, with roughly 9.7 million in the over 35 years age group accessing the Daily Star each month.

Overall positive growth

During the same year, tabloid newspaper The Sun and The Sun on Sunday had the highest reach of all newspapers in the United Kingdom (UK), roughly five times that of the Daily Star and its Sunday publication. Despite this, monthly reach of the Daily Star has been on the rise since 2012, hitting its peak in the period between April 2018 and March 2019. Between July 2017 and December 2019, its cumulative reach was higher than any recorded during the previous years. As the print industry digitalizes, the Daily Star and many other newspapers have adapted by launching online platforms which in conjunction with print editions have helped maintain and even grow their reader base.

The Guardian leading the UK newspaper industry

As of 2019, the most popular newspapers in the UK according to consumers’ opinions were Metro, The Guardian, The Times, and The Sunday Times. The Guardian saw the least decrease in circulation growth among tabloid newspapers in 2019, a year where all newspapers suffered an overall decline. The Daily Star Sunday was impacted the most, with a 16.2 percent drop in circulation.

Abstract

The 2010-2011 Zimbabwe Demographic and Health Survey (2010-11 ZDHS) is one of a series of surveys undertaken by the Zimbabwe National Statistics Agency (ZIMSTAT) as part of the Zimbabwe National Household Survey Capability Programme (ZNHSCP) and the worldwide MEASURE DHS programme.

The 2010-11 ZDHS is a follow-on to the 1988, 1994, 1999, and 2005-06 ZDHS surveys and provides updated estimates of basic demographic and health indicators covered in these earlier surveys. Data on malaria prevention and treatment, domestic violence, anaemia, and HIV/AIDS were also collected in the 2010-11 ZDHS. In contrast to the earlier surveys, the 2010-11 ZDHS was carried out using electronic personal digital assistants (PDAs) rather than paper questionnaires for recording responses during interviews.

The primary objective of the 2010-11 ZDHS is to provide up-to-date information on fertility levels, nuptiality, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of mothers and young children, early childhood mortality and maternal mortality, maternal and child health, and knowledge and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs).

Geographic coverage

The sample for the 2010-11 ZDHS was designed to provide population and health indicator estimates at the national and provincial levels. The sample design allows for specific indicators, such as contraceptive use, to be calculated for each of Zimbabwe's 10 provinces (Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Matabeleland North, Matabeleland South, Midlands, Masvingo, Harare, and Bulawayo).

Analysis unit

Household, individual, adult woman, adult male,

Kind of data

Sample survey data

Sampling procedure

The sample for the 2010-11 ZDHS was designed to provide population and health indicator estimates at the national and provincial levels. The sample design allows for specific indicators, such as contraceptive use, to be calculated for each of Zimbabwe’s 10 provinces (Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Matabeleland North, Matabeleland South, Midlands, Masvingo, Harare, and Bulawayo). The sampling frame used for the 2010-11 ZDHS was the 2002 Population Census.

Administratively, each province in Zimbabwe is divided into districts and each district into smaller administrative units called wards. During the 2002 Population Census, each of the wards was subdivided into enumeration areas (EAs). The 2010-11 ZDHS sample was selected using a stratified, two-stage cluster design, and EAs were the sampling units for the first stage. Overall, the sample included 406 EAs, 169 in urban areas and 237 in rural areas.

Households were the units for the second stage of sampling. A complete listing of households was carried out in each of the 406 selected EAs in July and August 2010. Maps were drawn for each of the clusters, and all private households were listed. The listing excluded institutional living facilities (e.g., army barracks, hospitals, police camps, and boarding schools). A representative sample of 10,828 households was selected for the 2010-11 ZDHS.

All women age 15-49 and all men age 15-54 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. Anaemia testing was performed in each household among eligible women and men who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anaemia. Also, among eligible women and men who consented, blood samples were collected for laboratory testing of HIV in each household. In addition, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used for the 2010-11 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed for the MEASURE DHS project to reflect population and health issues relevant to Zimbabwe. Relevant issues were identified at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organizations (NGOs), and international donors. Also, more than 30 individuals representing 19 separate stakeholders attended a questionnaire design meeting on 8-9 February 2010. In addition to English, the questionnaires were translated into two major languages, Shona and Ndebele.

The Household Questionnaire was used to list all of the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on age and sex obtained in the Household Questionnaire were used to identify women and men who were eligible for an individual interview. Additionally, the Household Questionnaire collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership and use of mosquito nets (to assess the coverage of malaria prevention programmes).

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

The Man’s Questionnaire was administered to all men age 15-54 in each household in the 2010-11 ZDHS sample. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

In this survey, instead of using paper questionnaires, interviewers used personal digital assistants to record responses during interviews.

Cleaning operations

In this survey, instead of using paper questionnaires, interviewers used personal digital assistants to record responses during interviews. The PDAs were equipped with Bluetooth technology to enable remote electronic transfer of files (e.g., transfer of assignment sheets from team supervisors to interviewers and transfer of completed questionnaires from interviewers to supervisors). The PDA data collection system was developed by the MEASURE DHS project using the mobile version of CSPro. CSPro is software developed jointly by the U.S. Census Bureau, the MEASURE DHS project, and Serpro S.A.

All electronic data files for the ZDHS were returned to the ZIMSTAT central office in Harare, where they were stored on a password-protected computer. The data processing operation included secondary editing, which involved resolution of computer-identified inconsistencies and coding of open-ended questions. Two members of the data processing staff processed the data. Data editing was accomplished using CSPro software. Office editing and data processing were initiated in October 2010 and completed in May 2011.

Response rate

A total of 10,828 households were selected for the sample, of which 10,166 were found to be occupied during the survey fieldwork. The shortfall was largely due to members of some households being away for an extended period of time and to structures that were found to be vacant at the time of the interview. Of the 10,166 existing households, 9,756 were successfully interviewed, yielding a household response rate of 96 percent. A total of 9,831 eligible women were identified in the interviewed households, and 9,171 of these women were interviewed, yielding a response rate of 93 percent. Of the 8,723 eligible men identified, 7,480 were successfully interviewed (86 percent response rate). The principal reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the households. The lower response rate among men than among women was due to the more frequent and longer absences of men from the households. Nevertheless, the response rates for both women and men were higher in the 2010-11 ZDHS than in the 2005-06 ZDHS (in which response rates were 90 percent for women and 82 percent for men).

Sampling error estimates

Sampling errors for the 2010-11 ZDHS are calculated for selected variables considered to be of primary interest.

Abstract

The 2004 Nigeria DHS EdData Survey (NDES) was a nationally representative sample survey covering 4,268 households, 3,987 parent/guardians, 81 independent children age 13-16, and 9,695 children age 4-16. The primary objective of the 2004 NDES is to provide upto date household-based information on education among children of primary and secondary school age in order to inform the development, monitoring, and evaluation of education programmes in Nigeria. The survey focuses on the factors influencing household decisions about children’s school attendance. In addition, information is available on school attendance, costs of schooling (monetary and non-monetary) and parent/guardian attitudes about schooling. The 2004 NDES was the first education survey of its kind in Nigeria, and was linked to the 2003 Nigeria Demographic and Health Survey (DHS). The survey report (available under External Resources) presents information on adult educational attainment, children’s characteristics and rates of school attendance, absenteeism among primary school pupils and secondary school students, household expenditures on schooling and other contributions to schooling, and parent/guardian perceptions of schooling, among other topics.

The sample size for both the 2003 Nigeria DHS survey and the 2004 NDES was sufficiently large to provide estimates for indicators at the national level, by urban-rural residence, and at the regional level for most indicators. Twelve survey teams trained by the National Population Commission (NPC), in collaboration with the Federal Ministry of Education (FMOE), conducted the survey from February to July 2004.

Geographic coverage

National Coverage

Analysis unit

Individuals Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2004 NDES is based on the sampling frame for the 2003 Nigeria DHS survey, which was designed to provide estimates of health and demographic indicators for the country as a whole, urban and rural areas, and six geo-political zones (hereafter referred to as regions). This discussion will first address the sample design for the 2003 Nigeria DHS survey, then the subsequent design for the 2004 NDES.

The 2003 Nigeria DHS sample points (clusters) were systematically selected from a list of enumeration areas (EAs) defined in the 1991 Population Census. A total of 365 clusters was drawn from the census sample frame. After selecting the 365 clusters, the NPC trained teams to conduct the comprehensive listing of households and to update maps in the selected clusters. Following the listing operation, households to be included in the 2003 Nigeria DHS survey were selected, with the number of households selected per cluster being inversely proportional to the size of the cluster. In the 2003 Nigeria DHS sampling frame, the number of households by region was disproportional to population size, in order to have adequate numbers of cases for reporting by region. For both the 2003 Nigeria DHS survey and the 2004 NDES, the sample was constructed to allow for separate estimates for key indicators in each of the six geo-political regions in Nigeria (North Central, North East, North West, South East, South South, and South West), with the result that the sample is not selfweighting at the national level.

Of the 365 clusters selected for the 2003 Nigeria DHS survey, 362 were successfully sampled. For the 2004 NDES, all of the 362 clusters completed for the 2003 Nigeria DHS survey were selected, and within those clusters, all households with children in the eligible child age range (4-16) were selected, comprising 4,563 households with one or more children age 4-16. Of these 362 clusters, 360 clusters were successfully completed for the 2004 NDES.

Sampling deviation

Of the 4,563 potential households selected, the 2004 NDES fieldwork teams successfully interviewed 4,268 households. The main reason that potential households were not interviewed was that the household had moved.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used for the 2004 NDES: 1. The Household Questionnaire 2. The Parent/Guardian Questionnaire 3. The Eligible Child Questionnaire 4. The Independent Child Questionnaire These are all available under Appendix D of the Survey Report available under External Resources.

The Household questionnaire listed all of the people who were members of the household at the time the household was surveyed during the 2003 Nigeria DHS survey. The three purposes of the 2004 NDES Household Questionnaire were to: - Confirm that the household was the same household surveyed by the 2003 Nigeria DHS survey; - Identify which children were eligible (qualified) to be covered by the Eligible Child Questionnaire and those eligible to have anthropometric and literacy/numeracy data collected about them; and - Identify a parent or guardian as the respondent for each eligible child. Children who were age 4-16 at the time of the 2003 Nigeria DHS survey were eligible to be covered by the Eligible Child Questionnaire. Children age 4-9 at the time of the 2003 Nigeria DHS survey had their height and weight measured, and children age 4-12 were given a literacy/numeracy test.

The Parent/Guardian Questionnaire collected background information on each parent/guardian respondent and on general education issues. Information was collected on the parent/guardian’s age, education, literacy, and religion. Questions were asked about the walking time and distance to the nearest primary and secondary schools, as well as household support of and participation in school activities. Parent/guardians were also asked about their views on school quality, the benefits and disadvantages of schooling, and reproductive health and HIV/AIDS education. In addition, information was collected on each primary school attended by the children for whom the parent/guardian responded, including the school type, location, and the reason for selection of that school.

The Eligible Child Questionnaire collected different kinds of information about each eligible child age 4-16, depending on the child’s schooling status. While the subject of the Eligible Child Questionnaire was the individual child and his/her schooling, the respondent for the questionnaire was the child’s parent/guardian, as the purpose of the questionnaire was to collect information on issues from the parent/guardian’s perspective. Data were collected on the following topics, according to a child’s schooling status: • Schooling background and participation during the 2003-2004 school year (attended school during the 2003-2004 school year, dropped out of school, or never attended school) • Frequency of and reasons for pupil absenteeism, household expenditures on schooling, and other costs of schooling (for children who attended school during the 2002-2003 school year) • Reasons for dropping out of school (for children who had dropped out of school) • Reasons for not attending school during the 2003-2004 school year (for children who had never attended school) • Children’s eating patterns

The Independent Child Questionnaire was used to interview directly a small percentage of the children age 13-16 in the selected households, rather than collecting information from a parent/guardian respondent. Independent children included those age 13-16 who were the head of the household, or the spouse of the head, or the son-in-law or daughter-in-law of the household head. Because these children did not have a parent/guardian who could answer questions about their schooling decisions, these children were interviewed directly. The same information was collected from these children themselves that otherwise would have been collected in the Eligible Child Questionnaire, and in terms of analysis, the data were grouped with data on other children in the eligible child age range.

The questionnaires were translated from English into three local languages—Hausa, Igbo, and Yoruba. Pretest training and fieldwork took place from 22 September to 4 October, 2003. For this exercise, six interviewers were trained (two per local language). The questionnaires were tested in Awka and Nibo (in Anambra State), Ibadan (in Oyo State), and Kano (in Kano State) in all languages, including English.

Cleaning operations

All questionnaires for the NDES were returned to the NPC headquarters in Abuja for data processing. Data processing consisted of office editing, the coding of open-ended questions, data entry, verification, and correcting of the computer-identified errors. A team of two data entry supervisors, a questionnaire administrator, three office editors, and ten data entry clerks processed the data. Data entry and editing started in late February, using the computer package CSPro (Census and Survey Processing System), which was specifically designed to process data from large-scale household surveys of this type. Data tables were produced using CSPro.

Response rate

A total of 4,354 households were occupied, of which 4,268 were successfully interviewed, for an overall response rate of 98 percent. The household response rate was similar in urban and rural areas. In the interviewed households, 9,695 children were found and Eligible Child Questionnaires were completed for all of these children. In addition, 90 independent children were identified and interviews were completed with 81 of them, producing a response rate of 90 percent.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1)

This dataset contains student achievement data for two Portuguese high schools. The data was collected using school reports and questionnaires, and includes student grades, demographics, social, parent, and school-related features.

Two datasets are provided regarding performance in two distinct subjects: Mathematics and Portuguese language. I have cleaned the original datasets so that they are easier to read and use.

Attributes for both student_math_cleaned.csv (Math course) and student_portuguese_cleaned.csv (Portuguese language course) datasets:

1. school - student's school (binary: "GP" - Gabriel Pereira or "MS" - Mousinho da Silveira)
2. sex - student's sex (binary: "F" - female or "M" - male)
3. age - student's age (numeric: from 15 to 22)
4. address_type - student's home address type (binary: "Urban" or "Rural")
5. family_size - family size (binary: "Less or equal to 3" or "Greater than 3")
6. parent_status - parent's cohabitation status (binary: "Living together" or "Apart")
7. mother_education - mother's education (ordinal: "none", "primary education (4th grade)", "5th to 9th grade", "secondary education" or "higher education")
8. father_education - father's education (ordinal: "none", "primary education (4th grade)", "5th to 9th grade", "secondary education" or "higher education")
9. mother_job - mother's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
10. father_job - father's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
11. reason - reason to choose this school (nominal: close to "home", school "reputation", "course" preference or "other")
12. guardian - student's guardian (nominal: "mother", "father" or "other")
13. travel_time - home to school travel time (ordinal: "<15 min.", "15 to 30 min.", "30 min. to 1 hour", or 4 - ">1 hour")
14. study_time - weekly study time (ordinal: 1 - "<2 hours", "2 to 5 hours", "5 to 10 hours", or ">10 hours")
15. class_failures - number of past class failures (numeric: n if 1<=n<3, else 4)
16. school_support - extra educational support (binary: yes or no)
17. family_support - family educational support (binary: yes or no)
18. extra_paid_classes - extra paid classes within the course subject (Math or Portuguese) (binary: yes or no)
19. activities - extra-curricular activities (binary: yes or no)
20. nursery - attended nursery school (binary: yes or no)
21. higher_ed - wants to take higher education (binary: yes or no)
22. internet - Internet access at home (binary: yes or no)
23. romantic_relationship - with a romantic relationship (binary: yes or no)
24. family_relationship - quality of family relationships (numeric: from 1 - very bad to 5 - excellent)
25. free_time - free time after school (numeric: from 1 - very low to 5 - very high)
26. social - going out with friends (numeric: from 1 - very low to 5 - very high)
27. weekday_alcohol - workday alcohol consumption (numeric: from 1 - very low to 5 - very high)
28. weekend_alcohol - weekend alcohol consumption (numeric: from 1 - very low to 5 - very high)
29. health - current health status (numeric: from 1 - very bad to 5 - very good)
30. absences - number of school absences (numeric: from 0 to 93)

These grades are related with the course subject, Math or Portuguese:

1. grade_1 - first period grade (numeric: from 0 to 20)
2. grade_2 - second period grade (numeric: from 0 to 20)
3. final_grade - final grade (numeric: from 0 to 20, output target)

Important note: the target attribute final_grade has a strong correlation with attributes grade_2 and grade_1. This occurs because final_grade is the final year grade (issued at the 3rd period), while grade_1 and grade_2 correspond to the 1st and 2nd period grades. It is more difficult to predict final_grade without grade_2 and grade_1, but these predictions will be much more useful.

Additional note: there are 382 students that belong to both datasets, though the ID's do not match. These students can be identified by searching for identical attributes that characterize each student.

Please include this citation if you plan to use this database: P. Cortez and A. Silva. Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12, Porto, Portugal, April, 2008, EUROSIS, ISBN 978-9077381-39-7.

Dogs are relinquished to animal shelters for animal-related or guardian-related reasons. Understanding what drives relinquishment patterns is essential for informing intervention opportunities to keep animals with their guardians. Whereas, overall reasons for relinquishment in a given shelter system have been well explored, analysis of human and animal predictors of relinquishing for a specific reason has not been previously attempted. We used characteristics of relinquishment including year, population of the relinquishing guardian's region, health status of the dog, breed, age group, weight, and sex to predict reasons for dog relinquishment to British Columbia (BC) Society for the Prevention of Cruelty to Animals (SPCA) shelters across BC between 2008 and 2019 (n = 32,081). Relinquishment trends for puppies and adult dogs were also viewed and described. From 2008–2019, the proportion of dogs relinquished relative to total intake remained consistent (range: 31–35%). Primary reasons reported by guardians were having too many dogs (19%), housing issues (17%), personal issues (15%), financial issues (10%), dog behavior (10%), and guardian health (8%). Over years, an increasing proportion of dogs were relinquished for the reason “too many” (OR = 1.16, 95% CI, 1.10–1.23, p < 0.001) and “behavior” (OR = 1.34, 95% CI, 1.26–1.43, p < 0.001), while a decreasing proportion were relinquished due to financial problems (OR = 0.94, 95% CI, 0.88–1.00, p = 0.047). Being a puppy, mixed breed, small, and from a small or medium population center predicted the reason “too many.” Being a senior, Healthy, or from a medium or large population center predicted the reason “housing issues.” Being a non-puppy, Healthy dog in a large population center predicted the reason “personal issues.” Being a puppy, non-Healthy, female, and from a large population center predicted the reason “financial issues.” Being a larger young adult or adult and Healthy predicted the reason “dog behavior.” Being an adult or senior small dog from a small population center predicted the reason “guardian health.” Particularly promising region-specific intervention opportunities include efforts to prevent too many animals in small population centers, improvement of pet-inclusive housing in large population centers, and providing animal care support in large population centers. Accessible veterinary services, including low-cost or subsidized care, likely benefit dog retention across BC.

Comparison between observed behaviors at the time of vaccine injection using the Face, Legs, Activity, Cry, and Consolability (FLACC) scale, as evaluated by a third party and the guardian.

Abstract

The 2019-20 Gambia Demographic and Health Survey (GDHS) was implemented by The Gambia Bureau of Statistics (GBoS) in collaboration with the Ministry of Health (MoH). Data collection took place from 21 November 2019 to 30 March 2020. SURVEY OBJECTIVES The primary objective of the 2019-20 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2019-20 GDHS: - collected data on fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; gender; nutrition; awareness about HIV/AIDS; self-reported sexually transmitted infections (STIs); and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) - obtained information on the availability of, access to, and use of mosquito nets as part of the National Malaria Control Programme - gathered information on other health issues such as injections, tobacco use, hypertension, diabetes, and health insurance - collected data on women’s empowerment, domestic violence, fistula, and female genital mutilation/cutting - tested household salt for the presence of iodine - obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15-49 ? conducted anaemia testing of women age 15-49 and children age 6-59 months - conducted malaria testing of children age 6-59 months

The information collected through the 2019-20 GDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.

Geographic coverage

Results from this sample are representative at the national, urban, and rural levels and at the Local Government Areas (LGA) levels.

Analysis unit

Household Woman Man Children

Universe

the survey covered all household members, All women age 15-49, in half of the selected households men age 15-59 wee eligible, all children aged 0-59 months

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019-20 GDHS was based on an updated version of the 2013 Gambia Population and Housing Census (2013 GPHC) conducted by GBoS. The census counts were updated in 2015-16 based on district-level projected counts from the 2015-16 Integrated Household Survey (IHS). Administratively, The Gambia is divided into eight Local Government Areas (LGAs). Each LGA is subdivided into districts and each district is subdivided into settlements. A settlement, a group of small settlements, or a part of a large settlement can form an enumeration area (EA). These units allow the country to be easily separated into small geographical area units, each with an urban or rural designation. There are 48 districts, 120 wards, and 4,098 EAs in The Gambia; the EAs have an average size of 68 households.

The sample for the 2019-20 GDHS was a stratified sample selected in two stages. In the first stage, EAs were selected with a probability proportional to their size within each sampling stratum. A total of 281 EAs were selected.

In the second stage, the households were systematically sampled. A household listing operation was undertaken in all of the selected clusters. The resulting lists of households served as the sampling frame from which a fixed number of 25 households were systematically selected per cluster, resulting in a total sample size of 7,025 selected households. Results from this sample are representative at the national, urban, and rural levels and at the LGA levels.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Additionally, in half of the selected households, men age 15-59 were eligible to be interviewed. In the households selected for male interviews, biomarker tests were also performed. Haemoglobin testing for anaemia was done in each of these households among eligible women age 18-49 and young emancipated women age 15-17 who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months and young non-emancipated women age 15-17 were also tested for anaemia in each household. In addition, with parental consent, children age 6-59 months were eligible for malaria testing using a rapid diagnostic test (RDT). Height and weight measurements were conducted on children age 0-59 months and women age 15-49. Finally, one eligible woman in each household from which the male sample was drawn was randomly selected to be asked questions about domestic violence.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019-20 GDHS: 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 questionnaires, were adapted to reflect the population and health issues relevant to The Gambia. Suggestions were solicited from various stakeholders representing government ministries, departments, and agencies; nongovernmental organisations; and international donors. All questionnaires were written in English, and interviewers translated the questions into the appropriate local language to carry out the interview.

The Household Questionnaire listed all members of and visitors to the selected households. Basic demographic information was collected on each person listed, including age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members were used to identify women and men eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s housing unit, such as source of water; type of toilet facilities; materials used for flooring, external walls, and roofing; ownership of various household goods; access to and use of mosquito nets; and the iodine content in household salt.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: - Background characteristics (including age, education, and media exposure) - Reproduction and child mortality - Contraception - Antenatal, delivery, and postnatal care - Vaccinations and childhood illnesses - Maternal and child health and nutrition - Marriage, sexual activity, and fistula - Fertility preferences - Women’s work and husbands’ background characteristics - Knowledge, awareness, and behaviour regarding HIV/AIDS and other STIs - Other health issues (e.g., injections, smoking, and health insurance) - Noncommunicable diseases (e.g., hypertension and diabetes) - Female genital mutilation/cutting - Adult and maternal mortality - Domestic violence

The Man’s Questionnaire was used to collect information from all eligible men age 15-59 in half of the sampled households. These men were asked questions on: - Background characteristics - Reproduction - Contraception - Marriage and sexual activity - Fertility preferences - Employment and gender roles - HIV/AIDS - Other health issues (e.g., injections, smoking, female genital mutilation/cutting, hypertension, diabetes, and health insurance)

The Biomarker Questionnaire was used to record the results of the anthropometric measurements and haemoglobin and malaria testing.

The Fieldworker Questionnaire served as a tool for conducting analyses of data quality. Fieldworkers filled out a two-page self-administered questionnaire on their general background characteristics after the main training and before fieldworkers entered the field. No personal identifiers were attached to the GDHS fieldworkers’ data file.

Cleaning operations

All electronic data files were transferred via the Internet File Streaming System (IFSS) to the GBoS central office. The IFSS automatically encrypts the data and sends the data to a server, and the server in turn downloads the data to the data processing supervisor’s password-protected computer in the central office. The data processing operation included secondary editing, which required resolution of computeridentified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and three secondary editors who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in November 2019 and completed in May 2020.

Response rate

All 6,985 households in the selected housing units were eligible for the survey, of which 6,736 were occupied. Of the occupied households, 6,549 were successfully interviewed, yielding a response rate of 97%. Among the households successfully interviewed, 1,948 interviews were completed in 2019 and 4,601 in 2020.

In the interviewed households, 12,481 women age 15-49 were identified for individual interviews; interviews were completed with 11,865 women, yielding a response rate of 95%, a 4 percentage point increase from the 2013 GDHS. Among men, 5,337 were eligible for individual interviews, and 4,636 completed an

Description: The guardian data of the SABSSM 2008 study covers information from the parents or care givers of children 2 - 11 years on matters ranging from biographical information of the child and parent/guardian, the child's home environment, care and protection, sources of information on HIV and AIDS, media impact and the health status of the child. The data set contains 243 variables and 4318 cases. Abstract: South Africa continues to have the largest number of people living with HIV/AIDS in the World. This study intends to understand the determinants that lead South Africans to be vulnerable and susceptible to HIV. This is the third in a series of household surveys conducted by Human Sciences Research Council (HSRC), that allow for tracking of HIV and associated determinants over time using a slightly same methodology used in 2002 and 2005 survey, making it the third national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 survey included individuals of all ages living in South Africa, including infants younger than 2 years of age. The interval of three years since 2002 allows for an exploration of shifts over time against a complex of demographic and other variables, as well as allowing for investigation of the new areas. The survey provides the first nationally representative HIV incidence estimates. The study key objectives were to: determine the prevalence of HIV infection in South Africa; examine the incidence of HIV infection in South Africa; assess the relationship between behavioural factors and HIV infection in South Africa; describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002-2008; investigate the link between social, values, and cultural determinants and HIV infection in South Africa; assess the type and frequency of exposure to major national behavioural change communication programmes and assess their relationship to HIV prevention, AIDS treatment, care, and support; describe male circumcision practices in South Africa and assess its acceptability as a method of HIV prevention; collect data on the health conditions of South Africans; and contribute to the analysis of the impact of HIV/AIDS on society. In the 13440 valid households or visiting points, 10856 agreed to participate in the survey, 23369 individuals (no more than 4 per household, including infants under 2 years) were eligible to be interviewed, and 20826 individuals completed the interview. Of the 23369 eligible individuals, 15031 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. the household response rate was 80.8%, the individual response rate was 89.1% and the overall response rate for HIV testing was 64.3%. Clinical measurements Face-to-face interview Focus group Observation South African population of all individuals from urban formal, urban informal, rural formal (farms), rural informal (tribal area) settlements. As in previous surveys, a multi-stage disproportionate, stratified sampling approach was used. A total of 1 000 census enumeration areas (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create a new updated Master Sample as a basis for sampling visiting points/households. The selection of EAs was stratified by province and locality type. Locality types were identified as urban formal, urban informal, rural formal (including commercial farms), and rural informal. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate; that means, over-sampling or over-allocation of EAs was done, for example, in areas that were dominated by Indian, coloured or white race groups to ensure that the minimum required sample size in those smaller race groups was obtained. The Master Sample was designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. A maximum of four visits were made to each VP to optimise response. Fieldworkers enumerated household members, using a random number generator to select the respondent and then preceded with the interview. All people in the households, resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups: under 2 years, 2-14 years, 15-24 years and 25+ years. These individuals constituted the USUs of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 15 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 15 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 15 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. The VP questionnaire was administered by the fieldworker, and in follow-up, participant selection was made by the supervisor. Participants aged 12 years and older who consented were all interviewed and also asked to provide dried blood spots (DBS) specimens for HIV testing. In case of 0-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children. The sample size estimate for the 2008 survey was guided by the (1) requirement for measuring change over time in order to detect a change in HIV prevalence of 5 percentage points in each of the main reporting domains, namely gender, age-group, race, locality type, and province (5% level of significance, 80% power, two-sided test), and (2) the requirement of an acceptable precision of estimates per reporting domain; that is, to be able to estimate HIV prevalence in each of the main reporting domains with a precision level of less than 4%, which is equivalent to the expected width of the 95% confidence interval (z-score at the 95% level for two-sided test). A design effect of 2 was assumed. Overall, a total of 20826 interviewed participants composed of 4981 children (0-14 years), 5344 youths (15-24 years) and 10501 adults (25+ years) were interviewed. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). More females (68.9%) than males (62.02%) were tested for HIV. The 25+ years age group was the most compliant (68.8%), and 2-14 years the least (58.9%). The highest testing response rate was found in urban informal settlements (72.5%) and the lowest in urban formal areas (62.8%).

Abstract

The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) was undertaken by the National Bureau of Statistics (NBS) and the Office of Chief Government Statistician (OCGS), Zanzibar, in collaboration with the Ministry of Health, Community Development, Gender, Elderly, and Children on the Tanzania Mainland and the Ministry of Health, Zanzibar.

The primary objective of the 2015-16 TDHS-MIS is to provide up-to-date estimates of basic demographic and health indicators. This survey collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, malaria, and other health-related issues. In addition, the 2015-16 TDHS-MIS provided estimates of anaemia prevalence among children age 6-59 months and women age 15-49 years, estimates of malaria prevalence among children age 6-59 months, and estimates of iodine concentration in household salt and women’s urine.

The information collected through the 2015-16 TDHS-MIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies to improve the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

Households Women 15-49 years Men 15-49 years Children 6-59 months

Universe

the survey covered all household members and visitors, all women 15-49 years, all men 15-49 years in one third houshold's sample and all children 0-59 months

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the 2015-16 TDHS-MIS was done in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the 30 regions (25 regions from Tanzania Mainland and 5 regions from Zanzibar). The first stage involved selecting sample points (clusters), consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census. A total of 608 clusters were selected.

In the second stage, a systematic selection of households was involved. A complete households listing was carried out for all 608 selected clusters prior to the fieldwork. From the list, 22 households were then systematically selected from each cluster, yielding a representative probability sample of 13,376 households for the 2015-16 TDHS-MIS. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the MoHCDGEC. Grouping the regions into zones allowed a relatively large number of people in the denominator and a reduced sampling error. Note that the zones, defined below, differ slightly from the zones used in previous DHS surveys. Therefore, comparisons across the zones and from survey to survey should be made with caution. The zones are as follows: Western zone: Tabora, Kigoma Northern zone: Kilimanjaro, Tanga, Arusha Central zone: Dodoma, Singida, Manyara Southern Highlands zone: Iringa, Njombe, Ruvuma Southern zone: Lindi, Mtwara South West Highlands zone: Mbeya, Rukwa, Katavi Lake zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga Eastern zone: Dar es Salaam, Pwani, Morogoro Zanzibar: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba

All women age 15-49 who were either usual residents or visitors in the household on the night before the survey were included in the 2015-16 TDHS-MIS and were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey. In all households, with the parent’s or guardian’s consent, children age 6-59 months were tested for anaemia and malaria. All interviewed women were tested for anaemia. In the households selected for interviews with men, interviewed women were asked to provide a urine sample and a sample of household salt for laboratory testing to detect the presence of iodine.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used for the 2015-16 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were based on the DHS Program’s standard Demographic and Health Survey (DHS) questionnaires. They were adapted to reflect the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries, departments, and agencies; non-governmental organizations; and development partners. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Kiswahili.

Cleaning operations

In the 2015-16 TDHS-MIS the first data entry was done concurrently with data collection in the field. After the paper questionnaires were completed, edited, and checked by both the field editor and the supervisor, the data was entered into a tablet equipped with a data entry programme. This was done by the editor. Completed questionnaires were then sent to NBS headquarters, where they were entered for the second time and edited by data processing personnel who were given special training for this task. ICF International provided technical assistance during the entire data processing period.

Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of good performance and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100% double entry to minimise keying errors, and data editing, were completed on March 21, 2016. Data cleaning and finalization were completed on April 22, 2016.

Response rate

A total of 13,360 households were selected for the survey, of which 12,767 were occupied. Of the occupied households, 12,563 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 13,634 eligible women were identified for individual interviews; interviews were completed with 13,266 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,822 eligible men were identified and 3,514 were successfully interviewed, yielding a response rate of 92%. There is little variation in household response rates between rural and urban residences.

Abstract

The 2014 Lesotho Demographic and Health Survey (LDHS) was implemented by the Lesotho Ministry of Health (MOH). Data collection took place from 22 September to 7 December 2014. The primary objective of the 2014 LDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health issues such as smoking, knowledge of breast cancer, and male circumcision. In addition, the 2014 LDHS provides estimates of anaemia prevalence among children age 6-59 months and adults, and gives estimates of hypertension, HIV prevalence and HIV incidence among adults. The 2014 LDHS is a follow-up to the 2004 and 2009 LDHS surveys.

The information collected through the LDHS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

Households Women Men Children

Universe

The Lesotho DHS 2014 covered all household members, all women 15-49 years, all children aged 0-59 months and all men aged 15-59 years in the half of households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2014 LDHS is an updated frame from the 2006 Lesotho Population and Housing Census (PHC) provided by the Lesotho Bureau of Statistics (BOS). The sampling frame excluded nomadic and institutional populations such as persons in hotels, barracks, and prisons.

The 2014 LDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as in urban and rural areas, four ecological zones,1 and each of Lesotho’s 10 districts.2 The first stage involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2006 PHC. A total of 400 clusters were selected, 118 in urban areas and 282 in rural areas.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs in July 2014, and households to be included in the survey were randomly selected from these lists. About 25 households were selected from each sample point, for a total sample size of 9,942 households. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the households, all men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In the subsample of households selected for the male survey, blood pressure measurements and anaemia testing were performed among eligible women and men who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anaemia. In the same subsample of households, blood specimens were collected for laboratory testing of HIV from eligible women and men who consented; height and weight were measured for eligible women, men, and children age 0-59 months; and mid-upper-arm circumference (MUAC) measurements were collected for children age 6-59 months.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Three questionnaires were used for the 2014 LDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s 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 Lesotho. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Sesotho.

Cleaning operations

All electronic data files for the 2014 LDHS were transferred via IFSS to the MOH central office in Maseru, where they were stored on a password-protected computer. The data processing operation included secondary editing, which involved resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by one person who took part in the main fieldwork training. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in October 2014 and completed in February 2015.

Response rate

A total of 9,942 households were selected for the sample, of which 9,543 were occupied. Of the occupied households, 9,402 were successfully interviewed, yielding a response rate of 99%. This compares favourably to the 2009 LDHS response rate (98%).

In the interviewed households, 6,818 eligible women were identified for individual interviews; interviews were completed with 6,621 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,133 eligible men were identified and 2,931 were successfully interviewed, yielding a response rate of 94%. The lower response rate for men was likely due to their more frequent and longer absences from the household.

The response rates for both women and men were slightly lower in the 2014 LDHS than in the 2009 LDHS (in which response rates were 98% for women and 95% for men). Strikingly, however, the numbers of eligible women and men identified in households in the 2014 LDHS were substantially lower than in the 2009 LDHS. Whereas there was an average of 0.83 eligible women and 0.72 eligible men per household in the 2009 LDHS, the corresponding averages in 2014 were 0.73 and 0.67 (data not shown).

The reason for the difference in the average number of eligible women and men between the 2009 and 2014 LDHS surveys is unknown. Possibilities range from a demographic shift in the population of Lesotho to data quality issues such as age displacement or omission of household members (or a combination of both).

Abstract

The principal aim of the 2002 Malawi DHS EdData Survey (MDES) is to provide upto-date information on education among children of primary school age (age 6-13). The survey focuses on factors influencing household decisions about children's school attendance. These data supplement the data collected by the Ministry of Education, Science, and Technology by focusing on attendance rather than enrolment and exploring the costs of schooling (monetary and non-monetary) and parent/guardian attitudes about schooling.The survey provides data on topics such as the age of children's first school attendance and dropout; the reasons for overage first-time enrolment in school, never enrolling in school, and dropout; the frequency of and reasons for pupil absenteeism; household expenditures on schooling and other contributions to schooling; distances and travel times to schools; and parent/guardian perceptions of school quality and the benefits and disadvantages of schooling.

The 2002 MDES was designed to supplement education data sources and to provide data to assist policy-makers in evaluating education programmes in the country. In broad terms, the 2002 MDES aims to: • Provide baseline data on key education indicators • Assist in the evaluation of Malawi's education programmes • Advance survey methodology in Malawi and contribute to national and international databases.

In more specific terms, the 2002 MDES was designed to: • Provide data on the schooling status of Malawian children of primary school age and on factors influencing whether children ever enrol in school and why pupils drop out of school • Quantify household expenditures on children's schooling and examine differential patterns of expenditure by various background characteristics • Measure parent/guardian attitudes about schoolin - including their perceptions of the quality of schooling and of the effects of Free Primary Education, to provide an understanding of attitudes that shape parents' and guardians. willingness to send their children to school • Measure the frequency of pupil absenteeism and the reasons for missing school in order to suggest approaches to maximise pupil attendance.

Geographic coverage

National

Analysis unit

Households Individuals

Universe

The principal aim of the 2002 Malawi DHS EdData Survey (MDES) is to provide up-to-date information on education among children of primary school age (age 6-13)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2002 MDES was based on the sampling frame for the 2000 MDHS, which was designed to provide estimates of health and demographic indicators. The discussion in this section first addresses the sample design for the 2000 Malawi DHS, then the subsequent design for the 2002 MDES.

The 2000 Malawi DHS was designed to provide estimates at the national and regional levels and for urban and rural areas. It was also designed to provide estimates of some health and demographic indicators at the sub-regional level in 11 districts.

The 2000 Malawi DHS sample points (clusters) were systematically sampled from a list of enumeration areas (EAs) defined in the 1998 Malawi Census of Population and Housing. A total of 560 clusters were drawn from the census sample frame: 449 in rural areas and 111 in urban areas. After selecting the 560 clusters, the NSO trained teams to conduct the comprehensive listing of households and to update maps in the selected clusters. Nine listing teams conducted a comprehensive listing of households and updated maps in the selected clusters, from April through May 2000. This exercise provided a basis for second-stage sampling for the 2000 Malawi DHS-and later, for the 2002 MDES.

After the listing operation, households to be included in the 2000 Malawi DHS were selected; the number of households selected per cluster was inversely proportional to the size of the cluster. In the Malawi DHS sampling frame, as in the 2002 MDES sampling frame, the number of EAs selected in each district was not proportional to the total population; rather, urban areas were oversampled in order to generate unbiased urban estimates.

As part of the 2002 MDES pre-test, a verification exercise was conducted in one urban and two rural enumeration areas around Zomba to estimate what percentage of households identified at the time of the 2000 household listing would be found during the 2002 MDES fieldwork. During this verification exercise-using structure numbers that were written on buildings during the household listing, and the name of the household head at the time of the listing exercise-92 percent of the urban and 95 percent of the rural households were located. These results suggested that the household listing conducted in 2000 as part of the Malawi DHS remained usable for purposes of the 2002 MDES.

While structures and households were still identifiable, in many instances, the household head (and sometimes the entire household) had changed between 2000 and 2002. In 52 percent of the households in the urban area and 15 percent of the households in the rural areas, the name of the household head was different in 2002 than in 2000. In other words, household composition had changed for over half of the households in the urban area and for one-seventh of the households in the rural areas, supporting the decision not to try to link information from the 2000 Malawi DHS and 2002 MDES at the household level.

For the 2002 MDES, 129 EAs-111 in rural areas and 18 in urban areas-were selected from the 560 EAs in the 2000 Malawi DHS sample.The 2002 MDES was designed to provide estimates at the national and regional levels and for urban and rural areas.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2002 MDES: the Household Questionnaire, the Parent/Guardian Questionnaire, and the Eligible Child Questionnaire.

The three purposes of the MDES Household Questionnaire were to 1) list all household members and visitors to the household, 2) identify which children were eligible (qualified) to be covered by the Eligible Child Questionnaire, and 3) identify a parent or guardian as the respondent for each eligible child. Children age 6-14 were eligible to be covered by the Eligible Child Questionnaire.

The Parent/Guardian Questionnaire collected background information on each parent/guardian respondent and on general education issues. Information was collected on the parent/guardian’s age, education, literacy, and religion. Questions were asked about the walking time and distance to the nearest primary and secondary schools, and about household participation in school activities. Information was also collected on each primary school attended by the children for whom the parent/guardian responded, including the school type and location, the reason for selection of that school, and perceived school quality.

The Eligible Child Questionnaire collected different kinds of information about each eligible child, depending on the child’s schooling status. While the subject of the Eligible Child Questionnaire was the eligible child and his/her schooling, the respondent for the questionnaire was the child’s parent/guardian, as the purpose of the questionnaire was to collect information on issues from the parent/guardian’s perspective. Data were collected on the following topics, according to a child’s schooling status:

• Schooling background and participation during the current school year (attended school during the 2002 school year, dropped out of school, or never attended school) • Frequency of and reasons for pupil absenteeism, household expenditures on schooling, other costs of schooling (for children who attended school during the 2001 school year) • Reasons for dropping out of school (for children who have dropped out of school) • Reasons for not attending school during the 2002 school year (for children who have never attended school) • Children’s eating patterns

In April, the questionnaires were pre-tested in Chichewa in and around Zomba. A total of 108 households were interviewed and 120 Parent/Guardian Questionnaires and 367 Eligible Child Questionnaires were completed. Based on the results of the pre-test, minor changes in the pre-test survey questionnaires were made before the main survey fieldwork was conducted.

Response rate

A total of 3,866 households were selected, of which 3,325 were occupied. Of the 3,325 occupied households, 3,290 were interviewed successfully, yielding a household response rate of 99 percent. In the interviewed households, 2,048 parents/guardians were identified to be interviewed. Completed interviews were conducted with all of these parents/guardians, yielding a response rate of 100 percent. Since the parent/guardians responded to the questions for their children and the children for whom they were responsible, the Eligible Child Questionnaire response rate reflects the percentage of eligible children for whom data were collected. A total of 3,755 eligible children were identified and data were collected on 3,752 of these children, yielding a response rate of nearly 100 percent.

Abstract

This first Child Activity Survey (CAS) rectifies the absence of statistical information on working children and their activities in Belize. It follows Belize's commitment to international instruments concerning child labour, such as the UN Convention on the Rights of the Child (CRC) and International Labour Organization (ILO) Conventions, and concern by the Government of Belize at educational indicators of inadequate rates of school enrolment, participation and completion.

The CAS was conducted by the Central Statistical Office in April-May 2001 (postponed from October 2000 due to Hurricane Keith) and aims to provide national information to assist the Government in identifying appropriate responses. Such responses may include policies and programmes to ensure protective measures to minimize the negative consequences of child labour as well as supportive measures to encourage and enable improved education participation by Belizean young people.

The data from the CAS will also be used for: • In-depth analysis and research, for example, in-depth analysis of child labour and education in Belize; • Decision-making and planning, for example, designing protective measures; • Formulation and implementation of policies, programmes and projects, for example, implementing protective measures to minimise the negative consequences of child labour and protection of working children in the short-term and the eventual elimination of the practice in the long-run; and • Monitoring and refining these policies and programmes.

Geographic coverage

National

Analysis unit

Children aged 5-17 years

Universe

The survey covered all de jure children (usual residents) aged between 5-17 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Administratively, Belize is divided into six districts, namely Corozal and Orange Walk in the north, Belize to the east, Cayo to the west and Stann Creek and Toledo in the south. Each of these districts has distinct urban and rural demarcation. Overall, about 52% of the households in the country are located in the rural areas. Two districts, namely Cayo (which contains the capital Belmopan City), and Belize (which contains the largest urban centre, Belize City), account for almost half the households in the country (CSO, 2001 a).

For the purpose of the Population and Housing Census, each district is sub-divided into smaller Enumeration Districts (EDs). Each ED has an average size of 144 households (Census 2000). For the sampling design of the CAS, available data from both the 1991 and 2000 Censuses were utilised (Tables 2-3 and 2-4). During the time of the preparation of the sample design, the Census 2000 data were not yet computerised and the only available data for 2000 were for household by district and ED and for population by sex, district and ED.

The survey comprised a two-stage design with the selection of EDs being the first stage: the selection of EDs being proportional to the size of EDs, that is, the number of households at the time of the Census 2000. The second stage was the random selection of a cluster of households from within selected EDs. Each district was treated as a stratum in its own right. However, in each case the selected ED and cluster were such that

f = f1 x f2 where f1 is the probability of selecting an ED, f2 is the probability of selecting a cluster, and f is the probability of selecting a household.

To randomly select the 6,058 households, it was necessary to first obtain a distribution of the population 5 to 17 years by district, based on the 1991 Census (Table 2-3). From the data it was also possible to obtain the average number of persons 5 to 17 years per household by district. The 1991 Census also provided data on household income, which were used for ordering EDs within districts prior to selection.

Data on the number of households in each ED were available from the 2000 Population and Housing Census (Table 2-4). These data, together with data on the average number of persons 5 to 17 years per household from the 1991 Census, were used to allocate the number of households to be selected from each district and the urban and rural areas within each district.

Using an average cluster size of 30 households, which gives approximately 200 clusters to yield the 6,058 households and about the same number of EDs, each district was assigned a number of clusters based on the number of households obtained from the Census 2000. After examining the available income data, a monthly household income of BZ$5002 was used as the criterion for ordering the EDs before selection. The EDs were ranked by proportion of households earning less than BZ$500 per month from the highest to the lowest proportion. This was done within each urban and rural area within each district. Within each district, a number of EDs were systematically selected. The selection interval was determined by the number of households in the district and the number of clusters assigned to the district.

After selecting these EDs, one cluster was then selected from each ED. Dividing the number of households by 30 and rounding off as necessary gave the number of clusters assigned to an ED. However, the sum of clusters from the EDs did not exceed the number of clusters assigned to the district. Because the number of households in an ED was not exactly divisible by 30 and the number of clusters assigned to an ED must be an integer, meant that the cluster sizes varied from 27 to 35 households with an average of about 30 households. For example, an ED with 128 households would have been assigned four clusters, each with an average size of 32 households.

Based on the average number of persons aged 5 to 17 years per household from the 1991 Census data, it was estimated that the number of persons aged 5 to 17 years to be interviewed from the sample would be just over 10,000 (the actual number interviewed for the survey was 7,870 children.). An estimated 20% to 25% employment rate for children 5 to 17 years old should have yielded 2,000 to 2,500 employed persons in the sample (the results from the survey showed 896 employed children). Selection of the sample was made at the CSO using the households from the 2000 Population and Housing Census as the sample frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire used for the CAS was designed to gather detailed information specifically on children aged between 5 and 17 years inclusive, and basic demographic information for the parent or guardian of the child and, in the absence of the parent or guardian, a responsible adult over 17 years (Figure 2-1). According to the Convention on the Rights of the Child (CRC), a child is any person under the age of 18 years; hence the upper age limit for the target population is 17 years. Given that the compulsory school age in Belize is 5 to 14 years, five years was used as the lower age limit. All children 5 to 17 years in the households selected were interviewed.

The questionnaire (refer to Figure 2-1 and Annex III) was divided into 11 sections: Section I: Housing Section II: Migration status of households Section III: All children 5-17 years old living away from this household Section IV: Respondent characteristics Section V: Characteristics of the child 5-17 years old Section VI: Migration status of the child Section VII: Usual economic activity of the child Section VIII: Non economic activity and complete idleness Section IX: Health and safety aspects of child who has worked at any time in the past Section X: Perception of parent or guardian of the child Section XI: For the child 5 to 17 years old.

Unlike Section XI, the respondent for Sections I to X was the parent or guardian (or responsible adult, in the absence of the parent or guardian) of any of the children 5 to 17 years old in the household. The person who answered Sections I to X expressed his or her views and knowledge about the housing and household characteristics and provided information on each child 5 to 17 years old who was a member of the household. For every additional child, interviews were repeated for Sections V to XI.

Most respondents (84.3%) for Sections I to X were the parent or guardian of the child. The grandparent (6.5%), the brother or sister (3.9%) and other relative (3.7%) were the other most likely respondents. Interestingly, 0.5% of children had their spouse or partner answering as the responsible adult in their household. Note that if the child’s spouse or partner was under 18 years, the spouse or partner was still considered a child.

Each child 5 to 17 years old responded to Section XI. Screening questions were included in this section of the questionnaire to help determine if the child interviewed was economically active, not economically active or idle, and then specific questions were asked depending upon the working status of the child.

More than 70% of the children interviewed were accompanied either by the parent or guardian or another member of the household. The rest of the children were alone when they were interviewed. A total of 44 children (0.6% of all children in the sample) did not answer Section XI but had information on them in Sections I to X.

Cleaning operations

The interviewers first checked the questionnaires before submitting them to the field supervisors, who then did a second check of the questionnaires. The field supervisor then submitted the questionnaires to the editor/coders, who then edited and coded the questionnaires. The district supervisors and personnel from the main office did random editing of questionnaires. After the questionnaires were both

Logistic regression outputs summarizing associations between knowledge adequacy and selected demographic variables.

Demographic profile of participants who were interviewed.

Socio-Demographic and clinical characteristics of HIV infected children and their family/ guardian who visited UoGSRH ART clinic, Gondar, Northwest Ethiopia, 2020 (N = 255).