The Multilinks project explores how demographic changes shape intergenerational solidarity, well-being and social integration. The project examines a) multiple linkages in families (e.g. transfers up and down family lineages, interdependencies between older and younger family members); b) multiple linkages across time (measures at different points in time, at different points in the individual and family life course); c) multiple linkages between, on the one hand, national and regional contexts (e.g. policy regimes, economic circumstances, normative climate, religiosity) and, on the other hand, individual behaviour, well-being and values.



The conceptual approach builds on three key premises. First, ageing affects all age groups: the young, the middle-aged and the old. Second, there are critical interdependencies between family generations as well as between men and women. Third, we must recognize and distinguish analytical levels: the individual, the dyad (parent-child, partners), family, region, historical generation and country.



The database aims to map how the state, in form of public policies and legal norms, defines and regulates intergenerational obligations within the family. What is the contribution of public authorities to support and secure financial and care needs for the young and the elderly in the family? In what ways the state assumes that intergenerational responsibilities are a family matter? In order to answer these questions the database includes a dual intergenerational perspective: upwards generations; from children to parents; and downwards; from parents to children. It looks across a variety of social policies and also includes legal obligations to support. It entails over 70 indicators on social policy rights, legal obligations to support, and care service usage. It offers a structured access to the public support for families with children and for elderly people within 30 European countries for 2004 and 2009.





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The research project MULTILINKS (How demographic changes shape intergenerational solidarity, well-being, and social integration: A Multilinks framework) existed from 2009 to 2011. It has received funding from the European Union's Seventh Framework Programme (FP7/2007-2011) under grant agreement n° 217523.



After the end of the project the results were made available as a web application and as individual datasets together with the documentation files by the WZB (http://multilinks-database.wzb.eu). Since 2020, this website no longer exists. The single datasets and reports are available here unchanged.



However, the web application, together with the documents, is still available through the "Gender & Generations Programme (GGP)" and the French Institute for Demographic Research (INED). There you will find further information, additional descriptive variables and full possibilities to explore and navigate through the database. For more details see: https://www.ggp-i.org/data/multilinks-database/

Abstract

The Jordan Population and Family Health Survey (JPFHS) is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 2012 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, and fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policymakers to evaluate and improve existing programs. The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 2012 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and for the two special domains: the Badia areas and people living in refugee camps. To facilitate comparisons with previous surveys, the sample was also designed to produce estimates for the three regions (North, Central, and South). The grouping of the governorates into regions is as follows: the North consists of Irbid, Jarash, Ajloun, and Mafraq governorates; the Central region consists of Amman, Madaba, Balqa, and Zarqa governorates; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba governorates.

The 2012 JPFHS sample was selected from the 2004 Jordan Population and Housing Census sampling frame. The frame excludes the population living in remote areas (most of whom are nomads), as well as those living in collective housing units such as hotels, hospitals, work camps, prisons, and the like. For the 2004 census, the country was subdivided into convenient area units called census blocks. For the purposes of the household surveys, the census blocks were regrouped to form a general statistical unit of moderate size (30 households or more), called a "cluster", which is widely used in surveys as a primary sampling unit (PSU).

Stratification was achieved by first separating each governorate into urban and rural areas and then, within each urban and rural area, by Badia areas, refugee camps, and other. A two-stage sampling procedure was employed. In the first stage, 806 clusters were selected with probability proportional to the cluster size, that is, the number of residential households counted in the 2004 census. A household listing operation was then carried out in all of the selected clusters, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the second stage of selection, a fixed number of 20 households was selected in each cluster with an equal probability systematic selection. A subsample of two-thirds of the selected households was identified for anthropometry measurements.

Refer to Appendix A in the final report (Jordan Population and Family Health Survey 2012) for details of sampling weights calculation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 JPFHS used two questionnaires, namely the Household Questionnaire and the Woman’s Questionnaire (see Appendix D). The Household Questionnaire was used to list all usual members of the sampled households, and visitors who slept in the household the night before the interview, and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of the household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. Moreover, the questionnaire included questions about child discipline. The Household Questionnaire was also used to identify women who were eligible for the individual interview (ever-married women age 15-49 years). In addition, all women age 15-49 and children under age 5 living in the subsample of households were eligible for height and weight measurement and anemia testing.

The Woman’s Questionnaire was administered to ever-married women age 15-49 and collected information on the following topics: • Respondent’s background characteristics • Birth history • Knowledge, attitudes, and practice of family planning and exposure to family planning messages • Maternal health (antenatal, delivery, and postnatal care) • Immunization and health of children under age 5 • Breastfeeding and infant feeding practices • Marriage and husband’s background characteristics • Fertility preferences • Respondent’s employment • Knowledge of AIDS and sexually transmitted infections (STIs) • Other health issues specific to women • Early childhood development • Domestic violence

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

The Household and Woman’s Questionnaires were based on the model questionnaires developed by the MEASURE DHS program. Additions and modifications to the model questionnaires were made in order to provide detailed information specific to Jordan. The questionnaires were then translated into Arabic.

Anthropometric data were collected during the 2012 JPFHS in a subsample of two-thirds of the selected households in each cluster. All women age 15-49 and children age 0-4 in these households were measured for height using Shorr height boards and for weight using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children in the field to measure their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Cleaning operations

Fieldwork and data processing activities overlapped. Data processing began two weeks after the start of the fieldwork. After field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman, where they were registered and stored. Special teams were formed to carry out office editing and coding of the openended questions.

Data entry and verification started after two weeks of office data processing. The process of data entry, including 100 percent reentry, editing, and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by early January 2013. A data processing specialist from ICF International made a trip to Jordan in February 2013 to follow up on data editing and cleaning and to work on the tabulation of results for the survey preliminary report, which was published in March 2013. The tabulations for this report were completed in April 2013.

Response rate

In all, 16,120 households were selected for the survey and, of these, 15,722 were found to be occupied households. Of these households, 15,190 (97 percent) were successfully interviewed.

In the households interviewed, 11,673 ever-married women age 15-49 were identified and interviews were completed with 11,352 women, or 97 percent of all eligible women.

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 2012 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012 JPFHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 JPFHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer

The Scanian Economic Demographic Database (SEDD) is based on family reconstitutions for nine rural parishes (Ekeby, Frillestad, Halmstad, Hässlunda, Hög, Kågeröd, Kävlinge, Sireköpinge and Stenestad) and one city (Helsingborg) in Scania, the southernmost county of Sweden, in which information in church records on births, deaths and marriages are linked together to form families. The database is the result of project collaborations between the Centre for Economic Demography (CED) and the Regional Archives in Lund. The co-operation has produced both an event database, in which all basic source material is registered, and an applied research database. The event database is accessible through the Regional Archives in Lund.

The description that follows primarily relates to the research database which contains information on five parishes (Halmstad, Hög, Kågeröd, Kävlinge and Sireköpinge). From the late 19th century onwards, one of the rural parishes was transformed from a minor rural village to a small industrial town (Kävlinge), while the others preserved their rural characters.

At its present stage, the research database includes data for 104 000 individuals from 1646 up to 1968, to which data from central registers for the period up to 2011 has been added. Data for the city of Landskrona are presently digitized. The database contains a variety of information on individual as well as household/family level and each individual in the database is under observation from birth/ in-migration and throughout the life span/ until an out-migration occurs. The fact that the database covers almost four centuries and that it combines economic and demographic data in one database has made it unique by Swedish comparisons.

Demographic variables include:

Births
Deaths
Cause of death
Marriages
In-migration
Out-migration
Birth-order

Socioeconomic and health variables include:

Occupation
Land holdings (farm size etc.)
Type of residence (farm, croft, cottage etc.)
Property ownership (freehold, crown, noble)
Income
Height
Health at birth
Health at mustering

Household variables include:

House-hold size
Typology of house-hold members (servants, nuclear family, lodgers etc.)

Purpose:

The purpose of the Scanian Economic Demographic Database (SEDD) is to function as a research infrastructure for economic as well as demographic research.

This data collection contains the first four waves of the Iowa Youth and Families Project (IYFP), conducted in 1989, 1990, 1991, and 1992. The Iowa Youth and Families Project was developed from an initial sample of 451 7th graders from two-parent families in rural Iowa. The study was merged with the Iowa Single Parent Project (ISPP) to form the Iowa Family Transitions Project in 1994, when the target youth were seniors in high school. Survey data were collected from the target child (7th grader), a sibling within four years of age of the target child, and both parents. Field interviewers visited families at their homes on several occasions to administer questionnaires and videotape interaction tasks including family discussion tasks, family problem-solving tasks, sibling interaction tasks, and marital interaction tasks. The Household Data files contain information about the family's financial situation, involvement in farming, and demographic information about household members. The Parent and the Child Survey Data files contain responses to survey questions about the quality and stability of family relationships, emotional, physical, and behavioral problems of individual family members, parent-child conflict, family problem-solving skills, social and financial support from outside the home, traumatic life experiences, alcohol, drug, and tobacco use, and opinions on topics such as abortion, parenting, and gender roles. In addition, the Child Survey Data files include responses collected from the target child and his or her sibling in the study about experiences with puberty, dating, sexual activity, and risk-taking behavior. The Problem-Solving Data files contain survey data collected from respondents about the family interactions tasks. The Observational Data files contain the interviewers' observations collected during these tasks. Demographic variables include sex, age, employment status, occupation, income, home ownership, religious preference, frequency of religious attendance, as well as the ages and sex of all household members and their relationship to the head of household. Demographic information collected on the parents also includes their birth order within their family, the ages and political philosophy of their parents, the sex, age, education level, and occupation of their siblings, and the country of origin of their ancestors.

This collection, the second wave of a panel survey, provides household-level retrospective and current data for Peninsular Malaysian women and their husbands and covers traditional topics of demographic research such as fertility, nuptiality, migration, and mortality as well as social and economic factors affecting family decision-making. The overall purpose of the data collection was to study household behavior in diverse settings during a period of rapid demographic and socioeconomic change. Eight survey instruments were used in this study. The tracking instrument, MFLS-2, was used for all households where an interview was attempted, and recorded information such as disposition of survey and questionnaires, number of eligibles, and respondent identifiers. The MF20 instrument, Household Members, was administered to all Panel sample households that were located. It solicited information on the status of the household members and included items such as location, marital status, education, and birthdate. The MF21 form, Household Roster, was used on all households interviewed in the survey. This form collected demographic information on current and very recent household members. The MF22 form, Female Life History, surveyed the Panel women and their selected daughters and daughters-in-law, and the New Sample women. Information collected by this form included pregnancy history and related events, marital, work, and migration histories, family background, and education. The MF23 form, Male Life History, collected data from husbands of the Panel women, selected sons and sons-in-law, and husbands of New Sample women. Data on marital, work, and migration histories, education, and family background were recorded. The MF24 form, Senior Life History, was administered to selected persons aged 50 or more and contained questions on marriages, children living elsewhere, literacy, work experience, migration history, health, and family background. The MF25 form, Household Economy, collected data on household economy from all households interviewed in this wave. Forms MF26 and MF27 were used to generate community-level data subfiles for this collection. Part 97 (MF26DIST--District-Level Data) contains one record for each of the 78 districts of Peninsular Malaysia. This file provides information (most of which pertains to 1988, but some of which dates back to 1970) on health services (e.g., number of hospitals, health centers, and doctors), family planning services (e.g., number of family planning clinics, contraceptive use), birth, death, and fertility rates, number of primary and secondary schools, ethnic distributions, and industrial and occupational distributions. Part 98 (MF26EB--Community-Level Data) contains one record for each of the 398 Enumeration Blocks selected for MFLS-2 and the 52 Primary Sampling Units used in MFLS-1. This file gives the current status of family planning services, general health services, schools, water and sanitation, housing costs, agriculture, transportation, population, urban/rural status, and government programs. Part 99 (MF27COMM--Community-Level Data) offers data for the same units as Part 98 and contains similar information, along with retrospective data on family planning services, health services, schools, and water treatment. Merged files (Parts 106-112) that contain one record per respondent were created by ICPSR using the variables CASE SPLIT PERSON for MF22, MF23, MF24, and MF25 on the New and Senior samples and the Panel and Children samples.

Child and caregiver characteristics by PEARLS screening format.

Product contains one data file (.csv format) for each year from 2006-2022. Records provide information about family demographics, dwelling characteristics, home value, income, years in residence & detailed geographic identifiers. Note: These data files are large (9-14GB each) and cannot be delivered through the Borealis platform. Please contact the Map and Data Library to arrange access: https://mdl.library.utoronto.ca/about/contact-form.

description: Most indicators throughout Vital Signs are created by acquiring and analyzing data collected from governmental agencies for some public administration purpose, such as 311 calls or housing inspections. However, data from the United States Bureau of the Census remains the best source for demographic and socioeconomic indicators for neighborhoods. The Census Bureau collects a wide variety of information through administration of both the decennial Census and the annual American Community Survey (ACS).; abstract: Most indicators throughout Vital Signs are created by acquiring and analyzing data collected from governmental agencies for some public administration purpose, such as 311 calls or housing inspections. However, data from the United States Bureau of the Census remains the best source for demographic and socioeconomic indicators for neighborhoods. The Census Bureau collects a wide variety of information through administration of both the decennial Census and the annual American Community Survey (ACS).

Wrigley, Schofield, Oeppen and Davies' 'English Population History from Family Reconstitution 1580-1837' (1997) was important both for its scope and its methodology. It was based on data from 26 family reconstitutions carefully selected to represent 250 years of English demographic history (UKDA-SN-853082). These data remain relevant for new research questions, such as studying the intergenerational inheritance of fertility and mortality. To expand their availability the family reconstitutions have been transcribed to Intermediate Data Structure (IDS) and an episode file for fertility analysis in this data collection.
These files were used for fertility analysis in George Alter, Gill Newton, and Jim Oeppen, "Re-introducing the Cambridge Group Family Reconstitutions," Historical Life Course Studies (in review). The contents and structure of IDS files are described in Alter, G., & Mandemakers, K. (2014). "The Intermediate Data Structure (IDS) for Longitudinal Historical Microdata, version 4". Historical Life Course Studies, 1, 1-26.

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

1971 census data at the census tract level (short form).

Previous research has suggested that owners’ attitude to their family dogs may contribute to a variety of behaviour problems in the dog, and authors assume that dogs with separation-related disorder (SRD) attach differently to the owner than typical dogs do. Our previous research suggested that these dogs may have an insecure attachment style. In the present study we have investigated whether owners’ attachment style, personality traits and the personality of the dog influence the occurrence of SRD in the dog. In an internet-based survey 1508 (1185 German and 323 Hungarian) dog-owners filled in five questionnaires: Demographic questions, Separation Behaviour Questionnaire (to determine SRD), Human and Dog Big Five Inventory and Adult Attachment Scale. We found that with owners’ higher score on attachment avoidance the occurrence of SRD in the dog increases. Dogs scoring higher on the neuroticism scale were more prone to develop SRD. Our results suggest that owners’ attachment avoidance may facilitate the development of SRD in dogs. We assume that avoidant owners are less responsive to the dog’s needs and do not provide a secure base for the dog when needed. As a result dogs form an insecure attachment and may develop SRD. However, there may be alternative explanations of our findings that we also discuss.

1971 data at the enumeration area level on census families, demography, households, and housing.

Wald tests, standardized effect sizes (r) and their 95% CI are given. Note that in case of German data gender (b = -0.75±0.240, p = 0.002) and age of owner (b = -0.01±0.007, p = 0.074) were also in the model.Parameter estimates (±se) from binomial GLMs for the human personality.

Abstract

The Jerusalem Household Social Survey 2005 is one of the most important statistical activities that have been conducted by PCBS. It is the most detailed and comprehensive statistical activity that PCBS has conducted in Jerusalem. The main objective of the Jerusalem household social survey, 2005 is to provide basic information about: Demographic and social characteristics for the Palestinian society in Jerusalem governorate including age-sex structure, Illiteracy rate, enrollment and drop-out rates by background characteristics, Labor force status, unemployment rate, occupation, economic activity, employment status, place of work and wage levels, Housing and housing conditions, Living levels and impact of Israeli measures on nutrition behavior during Al-Aqsa intifada, Criminal offence, its victims, and injuries caused.

Geographic coverage

Social survey data covering the province of Jerusalem only, the type locality (urban, rural, refugee camps) and Governorate

Analysis unit

households, Individual

Universe

The target population was all Palestinian households living in Jerusalem Governorate.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Sample Frame Were estimated sample size of Jerusalem by 3,300 family, including 2,240 families in the region J1, and 1,060 families in the region of J2 has been the establishment of Sample Frame to Jerusalem (J2) of the General Census of Population and Housing, and Establishment, which was carried out by the PCBS at the end of 1997, was create Sample Frame to Jerusalem (J1) of project data that has been exclusively in 2004. And the frame is a list of counting areas, and these areas are used as units an initial preview (PSUs) in the first stage of the process of selecting the sample. Stratified cluster random sample of regular two phases: Phase I: was selected a stratified random sample of enumeration areas from Jerusalem (J1) and Jerusalem (J2). The number of enumeration areas that have been chosen counting area 123 divided into two regions: 70 the count of Jerusalem (J1), 53 the count of Jerusalem (J2). Phase II: A random sample was withdrawn systematically with size of 20 families from each enumeration area that was selected in the first stage of the Jerusalem J2, and 32 families from each enumeration area that was selected in the first stage of the Jerusalem J1.

Mode of data collection

Face-to-face [f2f]

Research instrument

A survey questionnaire the main tool for gathering information, so do not need to check the technical specifications for the phase of field work, as required to achieve the requirements of data processing and analysis, has been designed form the survey after examining the experience of other countries on the subject of social surveys, covering the form as much as possible the most important social indicators as recommended by the United Nations, taking into account the specificity of the Palestinian community in this aspect.

Cleaning operations

Phase included a set of data processing Activities and operations that have been made to the Forms to prepare her for the analysis phase, This phase included the following operations: Before the introduction of audit data: at this stage was Check all the forms using the instructions To check to make sure the field of logical data and re- Incomplete, including a second field. Data Entry: The data entry Central to the central headquarters in Al-Bireh, was organized The data entry process using the BLAISE Program Where the form has been programmed through this program. Was marked by the program that was developed in the Device properties and features the following: The possibility of dealing with an exact copy of the form The computer screen. The ability to conduct all tests and possibilities Possible and logical sequence of data in the form. Maintain a minimum of errors Portal Digital data or errors of field work. Ease of use and deal with the software and data (User-Friendly). The possibility of converting the data to the other formula can be Use and analysis of the statistical systems Analysis such as SPSS.

Response rate

during the field work we visit 3,300 family in Jerusalem Governorate, 2,240 in Area J1 and1,060 in Area J2 where the final results of the interviews were as follows: The number of families who were interviewed (2,485) in Jerusalem Governorate, complete questioner 75.3% (1,773) in J1 79.2% (712) in J2 67.2%

Sampling error estimates

Data were collected in a manner that the survey sample and not Balhsr destruction, so she is exposed to two main types of errors. The first sampling errors (statistical errors), and the second non-statistical errors. It is intended that sampling errors of the errors resulting from sample design, so it is easy to measure, the contrast has been calculated and the effect of sample design.

The non-statistical errors are possible to occur in every stage of project implementation, through data collection, inserting, and mistakes can be summarized by the non-response, and response errors (surveyed), and the mistakes of the interview (the researcher) and data-entry errors. To avoid errors and reduce the impact it has made significant efforts through the training of researchers extensive training, and the presence of a group of experts in the concepts and terminology, medical / health, and training on how to conduct interviews, and the things that must be followed during the interview, and the things that should be avoided.

Have been trained on the data entry program entry, program, and were examined in order to see the picture of the situation and reduce any problems, there was constant contact between supervisors and checkers through ongoing visits and periodic meetings. In addition, has been drafting a set of circulars and instructions reminder to the team. Also been circulated answers to questions and problems faced by the researchers during the field work.

As for office work have been trained crew to check the special forms and field detection of errors, which greatly reduces the rates of errors that can occur during field work. In order to reduce the proportion of errors that can occur during entry form to the computer, the software is designed to entry so as not to allow any errors Tnasagah can get during the process of input and contains many of the conditions Logical, where they were loading the program the input of many tests on private answers each question in addition to the relations between the different questions and testing the other logical. This process has led to the disclosure of most of the errors that are not found in previous phases of work, where they were correct all errors that have been discovered.

Data were evaluated according to the following areas: 1. Definition of family members and how to register. 2. Demographic characteristics that have a relationship on Christmas. 3. Breakdown of the profession and activity.

Methods of assessment vary according to the data subject in this survey include the following: 1. Occurrences of missing values and Answers "other" and "Do not know" and examine inconsistencies between different sections or between the date of birth and other sections. Add to examine the internal consistency of the data as part of a logical data and completeness. 2. Compared to survey data with the results of surveys of the relationship and by the Central Bureau of Statistics Palestinian implementation.

Can be summarized as sources of some non-statistical errors that have emerged during the implementation of the survey including the following: Inability to meet the data in some cases the forms because of the lack of a home or be in the housing unit does not exist or are uninhabited and there are families not able to provide some data or refused to do so. Some families did not take the form subject very seriously affecting the quality of the data provided. Errors resulting from the method of asking the question by the researcher in the field. Category understand the question and answer based on his understanding of it. The inability of the technical team overseeing the project from the field visit on a regular basis for all duty stations in order to see the workflow and meet researchers and directing them, especially in the area J1. There was difficulty in reaching the families because of the construction of the wall, especially in the Ram Area and also in the area of Bir Nabala where the switch was a full count area due to additional incompleteness caused by the absence of the families in the region because of the separation wall. It was not easy to follow and adjust the time researchers because of the prevailing security conditions.

1971 census data at the census agglomeration/census metropolitan area level (long form).

Abstract

The 2009 MDHS was designed to provide data to monitor the population and health situation in Maldives. Specifically, the MDHS collected information on fertility levels and preferences, marriage, sexual activity, knowledge and use of family planning methods, breastfeeding practices, nutrition status of women and young children, childhood mortality, maternal and child health, and awareness and behaviour regarding AIDS and other sexually transmitted infections. At the household level, the survey collected information on domains of physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the impact of the tsunami of 2004, health expenditures, and care and support for physical activity of adults age 65 and older. At the individual level, the survey assessed additional features of blood pressure, diabetes, heart attack, and stroke.

Geographic coverage

National

Analysis unit

• Households
• Children age under 5
• Women age 15-49
• Men age 15-64

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The population of the republic of Maldives is distributed on 195 inhabited islands among a total of 202 inhabited islands; seven islands have no residents (MPND, 2008). Each inhabited island is an administrative unit with an island office that handles island-based affairs. The islands are regrouped to form atolls, a higher-level administrative unit with an atoll office and an atoll chief. There are 20 atolls in total in the republic. The capital city of Malé and the two surrounding islands, Villingili and Hulhumale, form a special atoll. The 21 atolls are regrouped to form six geographic regions according to their location. Malé atoll alone forms a region. In Maldives, there is no urbanrural designation for residential households within an atoll. All residential households in the 20 atolls outside of Malé are considered rural; all residential households in Malé are considered urban.

The 2009 Maldives DHS is based on a probability sample of 7,515 households. The sample was designed to produce representative data on households, women, and children for the country as a whole, for urban and rural areas, for the six geographical regions, and for each of the atolls of the country. The male and youth surveys were designed to produce representative results for the country as a whole, for urban and rural areas, and for each of the six geographical regions.

The 2006 Maldives Population and Housing Census provided the sampling frame for the 2009 MDHS. The MDHS sample was a stratified multistage sample selected in two stages from the census frame. In the first stage, 270 census blocks were selected using a systematic selection, with probability proportional to the number of residential households residing in the block. Stratification was achieved by treating each of the 21 atolls as a sampling stratum. Samples were selected independently in each stratum according to an appropriate allocation.

In the second stage of sampling, residential households were selected in each of the selected census blocks. Household selection involved an equal probability systematic selection of a fixed number of households: 28 households per block. Households were selected from the household listings created in the census, but to allow all households an opportunity to be included in the sample, listings were sent to island offices for updating prior to making household selections for the MDHS.

All ever-married women age 15-49 in the total sample of MDHS households, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In half of the households selected for the ever-married sample of women, all ever-married men age 15-64, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In the same half of households selected for the ever-married sample of men, never-married women and nevermarried men age 15-24, who were either usual residents of the household or visitors present in the household on the night before the survey, were also eligible to be interviewed. The MDHS was for the most part limited to Maldivian citizens; non-Maldivians were included in the survey only if they were the spouse, son, or daughter of a Maldivian.

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

Mode of data collection

Face-to-face

Research instrument

Four questionnaires were used for the 2009 MDHS: the Household Questionnaire, the Women’s Questionnaire, the Men’s Questionnaire, and the Youth Questionnaire. The contents of the Household, Women’s, and Men’s questionnaires were based on model questionnaires developed by the MEASURE DHS programme. The DHS model questionnaires were modified to reflect concerns pertinent to the Maldives in the areas of population, women and children’s health, family planning, and others. Questionnaires were translated from English into Dhivehi.

The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Basic information was collected on the characteristics of each person listed, including their age, sex, education, and relationship to the head of the household. The Household Questionnaire was also designed to collect information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, water shortage, materials used for the floor and roof of the house, and ownership of various durable goods. In addition, height and weight measurements of ever-married women age 15-49 and children age 6-59 months were recorded in the Household Questionnaire to assess their nutritional status.

Topics added to the Household Questionnaire to reflect issues relevant in the Maldives include physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the tsunami of 2004, health expenditures, and care and support for physical activities of adults age 65 and older.

The Women’s Questionnaire was used to collect information from ever-married women age 15-49. These women were asked questions on the following topics: - Background characteristics (education, media exposure, etc.) - Reproductive history - Knowledge and use of family planning methods - Fertility preferences - Antenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant and child feeding practices - Childhood mortality - Awareness and behaviour about AIDS and other sexually transmitted infections (STIs) - Knowledge of blood pressure, diabetes, heart attack, and stroke

The Men’s Questionnaire was administered to all ever-married men age 15-64 living in every second household in the MDHS sample. The Men’s Questionnaire collected much of the same information as the Women’s Questionnaire, but it was shorter because it did not contain questions on reproduction, maternal and child health, and nutrition.

The Youth Questionnaire was administered to all never-married women and men age 15-24 living in every second household in the MDHS sample (the same one-half selected for the Men’s survey). The Youth Questionnaire focuses on priorities of the MOHF that pertain to young adults: reproductive health, knowledge and attitudes about HIV/AIDS, sexual activity, and tobacco, alcohol, and drug use.

Response rate

A total of 7,515 households were selected in the sample, of which 7,137 were found to be occupied at the time of data collection. The difference between the number of households selected and the number occupied usually occurs because some structures are found to be vacant or non-existent. The number of occupied households successfully interviewed was 6,443, yielding a household response rate of 90 percent.

In the households interviewed in the survey, a total of 8,362 ever-married women were identified as eligible for the individual interview; interviews were completed with 7,131 women, yielding a female response rate of 85 percent. In the one-half sub-sample of MDHS households, a total of 3,224 evermarried men age 15-64 were identified as eligible for the individual interview; interviews were completed with 1,727 men, yielding a male response rate of 54 percent. In the same sub-sample of households, a total of 3,205 never-married women and men age 15-24 (youth) were identified as eligible for individual interview; interviews were completed with 2,240 youth, yielding a youth response rate of 70 percent. The response rate was higher for female youth (80 percent) than male youth (61 percent).

The urban household response rate of 83 percent is lower than the 92 percent response rate among rural households. The same is true for individual interviews with ever-married respondents; response rates are somewhat lower among urban women (79 percent) and men (47 percent) than among their rural counterparts (87 percent and 55 percent, respectively). The difference in response rates between urban and rural youth is negligible.

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling

BackgroundFamily caregiver’s role can be involving patients with heart failure (HF) in each behavior of self-care such as treatment adherence, and healthy eating, which will \ultimately lead to disease control. This study aimed to investigate family caregivers’ contributions to self-care behaviors among patients with heart failure in Oman.MethodsA descriptive cross-sectional design was used. A convenience sample of 136 family caregivers of patients with HF has completed the family caregivers’ demographics characteristics sheet and the Caregiver Contribution to Self-Care of HF Index2 (CC-SCHFI 2).ResultsCaregivers demonstrated low levels of contribution to patients’ self-care. The mean and (standard deviation) of caregivers’ contribution to maintenance tasks, patients’ ability to perceive symptoms, and to patients’ ability to manage self-care tasks scored 64.12 (SD = 15.70), 66.78 (SD = 14.72).and 52.26 (SD = 15.98) respectively. Education, exercise, and quality of social support were found to have a statistically significant association with caregivers’ contribution to self-care maintenance at a p–value of 0.004, 0.004, 0.004 respectively. While gender, education, marital status, exercise, and quality of social support had statistically significant association with caregivers’ contribution to self-care perception at a p-value of 0.003, 0.002, 0.006,

The Comprehensive Child Development Program (CCDP) was implemented as a result of the Comprehensive Child Development Act (Public Law [PL] 100-297), originally enacted by Congress in 1988 in an effort to increase the educational potential of young children from low-income families and to decrease the likelihood that they would be caught in the cycle of poverty. The CCDP was designed to provide intensive, comprehensive, integrated, and continuous support services for children from low-income families from birth, or before, through their entrance into elementary school, to enhance their intellectual, social, emotional, and physical development. Additionally, the CCDP was designed to offer support services for parents and other household family members to enhance their life management skills and economic self-sufficiency. The Comprehensive Child Development Act also mandated that programs collect data on the individuals and geographic areas served, including the types of services provided, the estimated costs of providing comprehensive services, the types and nature of conditions and needs identified and met, and other information that may be required.

Thus, there are two components of the CCDP data collection: the Evaluation of the Comprehensive Child Development Program and the Comprehensive Child Development Program Management Information System (MIS). The families in the MIS included all CCDP families in the CCDP evaluation and all families who replaced CCDP families that dropped out of the study any time during the demonstration. More than 4,000 families participated in the CCDP study. Those that were selected were randomly assigned to either an experimental or control group.

The CCDP evaluation data are taken from parental self-report and child assessments and consist of 25 data files that can be grouped into several broad categories. Some of the data files are longitudinal in nature, that is, there are multiple observations (e.g., interviews and tests) for each family or child. Other files, however, are at the family or child level, and they contain data describing outcomes at the end of the study. The categories covered in the CCDP evaluation data files include:

For research and monitoring purposes, the CCDP mandated that all contacts and services must be recorded and entered into the management information system (MIS). The MIS was designed to monitor the nature and number of services received by families participating in each of the CCDP projects. The MIS contains both qualitative and quantitative data for CCDP families at all of the 24 project sites. MIS data is composed of 23 data collection forms spanning 4 broad categories: (1) CCDP grantee administration, (2) CCDP program descriptions, (3) CCDP family characteristics and service plans, and (4) CCDP services utilization. MIS data include information about CCDP family goals, service utilization, and program and staff characteristics.

The CCDP MIS was the primary source of the quantitative data used in the CCDP evaluation. Supplemental MIS verification data was a secondary source of qualitative information. The CCDP also collected qualitative data in the form of ethnographer reports that provide information about program characteristics, operations, implementation, service delivery, program attrition, diversity among families, and family satisfaction. Sixteen ethnographer reports were produced for each of the 24 project sites.

Wald tests, standardized effect sizes (r) and their 95% CI are given. Note that in case of German data gender (b = -0.869±0.247, p