Facebook
TwitterAround *** 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.
Facebook
TwitterThis dataset includes the following variables: client county; number, percentage, average, and age of clients served, number and percentage of adolescent client served, number and percentage of male clients served , and clients served by race and ethnicity (Latino, White, African American, Asian and Pacific Islander, Other (including Native American); and clients served by primary language (Spanish, English, Other).
Facebook
Twitterhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.null/customlicense?persistentId=doi:10.15139/S3/WZSQYBhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.null/customlicense?persistentId=doi:10.15139/S3/WZSQYB
Demographics Child and Family
Facebook
TwitterNumber of persons in low income, low income rate and average gap ratio by economic family type, annual.
Facebook
TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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).
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in United States. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in United States. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in United States, householders within the 45 to 64 years age group have the highest median household income at $94,847, followed by those in the 25 to 44 years age group with an income of $87,575. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $57,108. Notably, householders within the under 25 years age group, had the lowest median household income at $43,534.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for United States median household income by age. You can refer the same here
Facebook
TwitterNA, not applicableDemographics and clinical presentations of affected family members.
Facebook
TwitterFamily Income and Benefits data with margins of error for Alaskan Communities/Places and aggregation at Borough/CDA and State level for recent 5-year American Community Survey (ACS) intervals. The 5-year interval data sets are published approximately 1/2 a period later than the End Year listed - for instance the interval ending in 2019 is published in mid-2021.Source: US Census Bureau, American Community SurveyThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: US Census ACS Income PublicationsUSE CONSTRAINTS: The Alaska Department of Commerce, Community, and Economic Development (DCCED) provides the data in this application as a service to the public. DCCED makes no warranty, representation, or guarantee as to the content, accuracy, timeliness, or completeness of any of the data provided on this site. DCCED shall not be liable to the user for damages of any kind arising out of the use of data or information provided. DCCED is not the authoritative source for American Community Survey data, and any data or information provided by DCCED is provided "as is". Data or information provided by DCCED shall be used and relied upon only at the user's sole risk.For information about the American Community Survey, click here.
Facebook
TwitterThe 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.
National
Sample survey data
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.
Face-to-face
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:
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.
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.
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.
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
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Facebook
TwitterThis report presents the latest statistics on type and volume of cases that are received and processed through the family court system of England and Wales in the first quarter of 2019 (January to March).
The material contained within this publication was formerly contained in Court Statistics Quarterly, a publication combining Civil, Family and Criminal court statistics.
To note: Family Court Statistics Quarterly currently includes the gender and age breakdown of Lasting Power of Attorney applications with data up to December 2016. This data can be found in table 25 and in the csv folder. We are unable to update these files due to data limitations. We propose that this table and csv should be removed from future publications. Please contact familycourt.statistics@justice.gov.uk by 31st July 2019 if you have any comment on this proposal.
Facebook
Twitter‘Family Food’ is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the ‘Family Food Module of the Living Costs and Food Survey’.
Next update: see the statistics release calendar.
Defra statistics: family food
Email mailto:familyfood@defra.gov.uk">familyfood@defra.gov.uk
<p class="govuk-body">You can also contact us via Twitter: <a href="https://x.com/DefraStats" class="govuk-link">https://x.com/DefraStats</a></p>
Facebook
TwitterWe are currently conducting a user consultation on these statistics. If you are interested in offering your views on this publication and future developments, the survey can be found https://www.smartsurvey.co.uk/s/73DHX0/">here.
This consultation will run until 17th December 2020.
This report presents the latest statistics on type and volume of cases that are received and processed through the family court system of England and Wales in the second quarter of 2020 (April to June).
The material contained within this publication was formerly contained in Court Statistics Quarterly, a publication combining Civil, Family and Criminal court statistics.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
ABSTRACT This study aimed to evaluate the demographic and healthcare situation of dogs and cats owned by families assisted by the Family Health Strategy (FHS), from Santa Maria/RS, Brazil. This research was a cross-sectional and population-based study developed by applying a questionnaire to residents in the 16 FHS areas of the city. This was the first study addressing pet animal conditions in the FHS area. A total of 414 households were studied, and 88.5% of them had pets (dogs and/or cats), with an average of 2.2 dogs and 0.8 cats per household. Only 18.4% (228/1.241) of the animals were sterilized (dogs, 15.1% [135/891]; cats, 26.7% [93/348]). When considering the number of dogs, households with one resident had fewer dogs than households with two or more residents (p=0.006). The level of education and family income were not associated with the number of animals (p>0.001). However, higher levels of education and family income were associated with the sterilization of dogs, veterinary monitoring, vaccination, and treatment of ectoparasites in dogs and cats (p
Facebook
Twitterhttps://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms
This archive includes all data compiled in the course of a systematic review on the association between family demographic processes and in-work poverty that represents the empirical material used in the paper Polizzi, Struffolino, Van Winkle. 2020. "Family Demographic Processes and In-Work Poverty: A Systematic Review." SocArXiv: https://doi.org/10.31235/osf.io/zncaq
The systematic review aims at locating empirical results on these associations within a common grid to summarize the findings with respect to five family demographic processes: parental home leaving, cohabitation, parenthood and subsequent births, union formation, and union dissolution. We concentrate on empirical studies on in-work poverty in OECD and EU-28 countries without any restriction on the year of publication.
In the first part of the systematic review, we provide a quantitative review of results from a comparative pool of cross-sectional analyses. In the second part of the systematic review, we perform a narrative review of the literature that pays special attention to recent research implementing a longitudinal design with household panel data and to alternative operationalizations of pivotal variables.
The methods report provides detailed information on all files included in the archive.
Facebook
TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
Facebook
TwitterThis report presents the latest statistics on type and volume of cases that are received and processed through the family court system of England and Wales in the third quarter of 2019 (July to September).
The material contained within this publication was formerly contained in Court Statistics Quarterly, a publication combining Civil, Family and Criminal court statistics.
Consultation on Probate statistics:
Currently data on grants of representation issued at published in Tables 25 and 26, including a split by registry type (Principal and District registries). To make sure that our statistics are responding to user needs, we are consulting on the following points and would welcome your views:
To participate in this consultation, please send your comments to familycourt.statistics@justice.gov.uk by Friday 17th January 2020.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Tinley Park. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Tinley Park population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 79.25% of the total residents in Tinley Park. Notably, the median household income for White households is $104,972. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $142,500. This reveals that, while Whites may be the most numerous in Tinley Park, Two or More Races households experience greater economic prosperity in terms of median household income.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Tinley Park median household income by race. You can refer the same here
Facebook
Twitterhttps://datacatalog.worldbank.org/public-licenses?fragment=externalhttps://datacatalog.worldbank.org/public-licenses?fragment=external
The 2023 Jordan Population and Family Health Survey (JPFHS) is the eighth Population and Family Health Survey conducted in Jordan, following those conducted in 1990, 1997, 2002, 2007, 2009, 2012, and 2017–18. It was implemented by the Department of Statistics (DoS) at the request of the Ministry of Health (MoH).
The primary objective of the 2023 JPFHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the 2023 JPFHS:
• Collected data at the national level that allowed calculation of key demographic indicators
• Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality
• Measured contraceptive knowledge and practice
• Collected data on key aspects of family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery
• 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 haemoglobin testing with eligible children age 6–59 months and women age 15–49 to gather information on the prevalence of anaemia
• Collected data on women’s and men’s knowledge and attitudes regarding sexually transmitted infections and HIV/AIDS
• Obtained data on women’s experience of emotional, physical, and sexual violence
• Gathered data on disability among household members
The information collected through the 2023 JPFHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Jordan.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Jordan JO: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data was reported at 58.000 % in 2012. This records an increase from the previous number of 57.900 % for 2009. Jordan JO: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data is updated yearly, averaging 57.950 % from Dec 1990 (Median) to 2012, with 6 observations. The data reached an all-time high of 59.100 % in 2007 and a record low of 40.400 % in 1990. Jordan JO: 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 Jordan – Table JO.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;
Facebook
TwitterAround *** 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.