Around *** million families in the United States had three or more children under 18 living in the household in 2023. In that same year, about ***** million households had no children under 18 living in the household.

Family Preservation Services (FPR) are services provided to the child and the family where the caregiver retains legal custody. This chart counts unique children served during fiscal year in Family Preservation Services (FPR) with a count of those removed. Children served in Family Preservation Services stay in their own home during services. NOTE: Family Preservation Services is under the umbrella of Family Based Safety Services (FBSS).

Abstract

The 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 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, fertility preferences, as well as maternal and child health and nutrition that can be used by program managers and policy makers to evaluate and improve existing programs. In addition, 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 crossnational studies.

The content of the 2002 JPFHS was significantly expanded from the 1997 survey to include additional questions on women’s status, reproductive health, and family planning. In addition, all women age 15-49 and children less than five years of age were tested for anemia.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

The estimates from a sample survey are affected by two types of errors: 1) nonsampling errors and 2) sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2002 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 2002 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2002 JPFHS sample is the result of a multistage stratified design and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2002 JPFHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Mode of data collection

Face-to-face

Research instrument

The 2002 JPFHS used two questionnaires – namely, the Household Questionnaire and the Individual Questionnaire. Both questionnaires were developed in English and translated into Arabic. The Household Questionnaire was used to list all usual members of the sampled households and to obtain information on each member’s age, sex, educational attainment, relationship to the head of 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. The Household Questionnaire was also used to identify women who are eligible for the individual interview: ever-married women age 15-49. In addition, all women age 15-49 and children under five years living in the household were measured to determine nutritional status and tested for anemia.

The household and women’s questionnaires were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990 and 1997 Jordan Population and Family Health Surveys. For each evermarried woman age 15 to 49, information on the following topics was collected:

1. Respondent’s background
2. Birth history
3. Knowledge and practice of family planning
4. Maternal care, breastfeeding, immunization, and health of children under five years of age
5. Marriage
6. Fertility preferences
7. Husband’s background and respondent’s employment
8. Knowledge of AIDS and STIs

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

Cleaning operations

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

Data entry and verification started after one week of office data processing. The process of data entry, including one hundred percent re-entry, 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 the end of October 2002. A data processing specialist from ORC Macro made a trip to Jordan in October and November 2002 to follow up data editing and cleaning and to work on the tabulation of results for the survey preliminary report. The tabulations for the present final report were completed in December 2002.

Response rate

A total of 7,968 households were selected for the survey from the sampling frame; among those selected households, 7,907 households were found. Of those households, 7,825 (99 percent) were successfully interviewed. In those households, 6,151 eligible women were identified, and complete interviews were obtained with 6,006 of them (98 percent of all eligible women). The overall response rate was 97 percent.

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: 1) nonsampling errors and 2) sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2002 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 2002 JPFHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2002 JPFHS sample is the result of a multistage stratified design and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2002 JPFHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: See detailed

Family Income: Couples: Without Children data was reported at 499,986,489.000 DKK th in 2017. This records an increase from the previous number of 482,309,570.000 DKK th for 2016. Family Income: Couples: Without Children data is updated yearly, averaging 392,679,981.500 DKK th from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 499,986,489.000 DKK th in 2017 and a record low of 302,221,773.000 DKK th in 2000. Family Income: Couples: Without Children data remains active status in CEIC and is reported by Statistics Denmark. The data is categorized under Global Database’s Denmark – Table DK.H009: Income Statistics: Family Income.

Statistical tool designed to measure, in a quantifiable way, the progress made by FACS each year in achieving the following objectives:

• Improving the lives of children and young people

• Supporting people with a disability to realise their potential

• Breaking disadvantage with social housing assistance

• Participation in social and economic life

• Reducing domestic and family violence

• Working with Aboriginal people and communities

Number of persons in low income, low income rate and average gap ratio by economic family type, annual.

The marital and family labor force statistics (FM) database from the Current Population Survey reflects data published each year in the news release, Employment Characteristics of Families. At the present time, only data for persons are available in the FM database. Person data include employment status by marital status and presence and age of own children. For example, the FM database includes the labor force participation rate of mothers with children under age 6 (series FMUP1378865).

IFHEADS01 - Family Units. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Family Units...

This service shows the median after-tax income of lone parent families in 2015 for Canada by 2016 census division. The data is from the data table Household Income Statistics (3) and Household Type Including Census Family Structure (11) for Private Households of Canada, Provinces and Territories, Census Divisions and Census Subdivisions, 2016 Census - 100% Data, Statistics Canada Catalogue no. 98-400-X2016099. This data pertains to households with one lone-parent census family without other persons in the household. In the context of census families, total income refers to receipts from certain sources of all of its family members, before income taxes and deductions, during a specified reference period. After-tax income refers to total income less income taxes of the statistical unit during a specified reference period. The median income of a specified group is the amount that divides the income distribution of that group into two halves. For additional information refer to the 2016 Census Dictionary for 'Total income', 'After-tax income' and 'Census family'. For additional information refer to the 2016 Census Dictionary for 'Total income', 'After-tax income' and 'Census family'. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

In 2024, the total number of families in Canada increased by 0.2 million families (+1.87 percent) compared to 2023. Therefore, the total number in Canada reached a peak in 2024 with 10.93 million families. Notably, the total number continuously increased over the last years.

Families of tax filers; Census families with capital gains by family type (final T1 Family File; T1FF).

Georgia GE: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data was reported at 52.800 % in 2010. This records an increase from the previous number of 41.800 % for 2005. Georgia GE: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data is updated yearly, averaging 41.800 % from Dec 2000 (Median) to 2010, with 3 observations. The data reached an all-time high of 52.800 % in 2010 and a record low of 30.800 % in 2000. Georgia GE: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Health Statistics. Demand for family planning satisfied by modern methods refers to the percentage of married women ages 15-49 years whose need for family planning is satisfied with modern methods.; ; Demographic and Health Surveys (DHS).; Weighted Average;

This study investigated the scope of efforts to involve parents in family planning progress for teenagers. The study data come from a 1981 national survey of 351 Title X recipients conducted by the Family Planning council of Southeastern Pennsylvania, Inc. Total cases: 351; total variables: 102.

The National Survey of Family Growth (NSFG) is designed and administered by the National Center for Health Statistics (NCHS), an agency of the U.S. Department of Health and Human Services, in collaboration with several other federal agencies (see Acknowledgements). Since the NSFG began in 1973, there have been eight data release files. The purpose of the survey is to produce national estimates of:

-Factors affecting pregnancy, including sexual activity, contraceptive use, and infertility;
-The medical care associated with contraception, infertility, and childbirth;
-Factors affecting marriage, divorce, cohabitation, and adoption;
-Adoption and caring for nonbioogical children
-Father involvement behaviors, and
-Men's and women's attitudes about sex, childbearing, and marriage.

The survey contains key religion variables that may relate to these topics. The survey results are used by the U.S. Department of Health and Human Services and other research and policy organizations to plan health services and health education programs, and to do statistical studies on the topics listed above.

For the 2011-2013 NSFG, statistical design, interviewing, and data processing have been conducted by the University of Michigan's Institute for Social Research (ISR), under a contract with the National Center for Health Statistics (NCHS), in collaboration with the NCHS NSFG. William Mosher served as Project Officer and Joyce Abma as Alternate Project Officer for the 2011-2013 data collection.

The 2006-2010 NSFG survey represents a shift from periodic surveys to continuous interviewing, with interviews being conducted 48 weeks of every year for four years. This public use data file contains all interviews conducted from June 2006-June 2010. In-person interviews were conducted with 12,279 women 15-44 years of age and 10,403 men 15-44 years of age for a total sample size of 22,682.

The Monthly Child Care Services Data Report - Families Served by ZIP Code data set includes demographic data of parents and families of children receiving Child Care and Development Fund (CCDF) assistance. The Administration for Children and Families (ACF) Office of Child Care (OCC) collects data regarding the children and families served through the Child Care and Development Fund (CCDF) as well as the types of child care settings and facilities providing services. Each quarterly data set contains data aggregated by ZIP code for each month of the quarter. Counts less than 5 are masked with an asterisk (*) to protect the confidentiality of individuals in this report.

Monthly statistics for pages viewed by visitors to the Queensland Government website—Parents and families franchise. Source: Google Analytics

Median One Parent Family Payment Rate