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TwitterThe average American household consisted of 2.51 people in 2023.
Households in the U.S.
As shown in the statistic, the number of people per household has decreased over the past decades.
The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”
The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.
Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.
In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.
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Graph and download economic data for Total Families with Children under 18 Years Old (TTLFMCU) from 1950 to 2024 about 18 years +, family, child, household survey, and USA.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents a breakdown of households across various income brackets in United States, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for United States reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of United States households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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. You can refer the same here
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TwitterThe 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2006 Second Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. This shapefile represents the current State Senate Districts for New Mexico as posted on the Census Bureau website for 2006.
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TwitterIn 2024, around **** percent of households in Japan were estimated to be single households. The share of married couple households with unmarried children has gradually declined over the past decades, reaching **** percent in the same year.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Labour Force Survey (LFS) estimates including measures of uncertainty of the number of households by types of household and families, for regions of England and also Scotland and Wales.
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TwitterThis dataset contains Iowa households with and without children under 18 years old by household type for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B11005. Household type includes Total Households, Family - All Types, Family - Married Couple, Family - All Single Householders, Family - Male Householder - No Wife Present, Family - Female Householder - No Husband Present, Nonfamily - All Types, Nonfamily - Male Householder, Nonfamily - Female Householder, Total Households w/Minors, and Total Households w/o Minors. A family household is a household maintained by a householder who is in a family. A family group is defined as any two or more people residing together, and related by birth, marriage, or adoption. Householder refers to the person (or one of the people) in whose name the housing unit is owned or rented (maintained) or, if there is no such person, any adult member, excluding roomers, boarders, or paid employees. If the house is owned or rented jointly by a married couple, the householder may be either the husband or the wife.
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Graph and download economic data for Households and Nonprofit Organizations; One-to-Four-Family Residential Mortgages; Liability, Level (HMLBSHNO) from Q4 1945 to Q2 2025 about balance sheet, nonprofit organizations, mortgage, liabilities, households, housing, and USA.
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Context
The dataset presents a breakdown of households across various income brackets in Henry, SD, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Henry, SD reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Henry households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 Henry median household income. You can refer the same here
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Contains projections of the number of households, families and living arrangement types for 2011-2036. The projections are not intended as predictions or forecasts, but are illustrations of growth and change in the population that would occur if the assumptions about future living arrangements of Australia's population were to prevail over the projection period. Three assumption series are referred to, which are informed by data from the past four Censuses - series I (no change in living arrangement propensity), series II (historical trend gradually plateauing) and series III (historical trend continuing). These projections are not forecasts or predictions. Non-demographic factors such as economic conditions may affect future household and family formation, but have not been explicitly taken into account in these projections.
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We examine whether complex cross-household structures of post-separation families are associated with higher risk-taking behavior in adolescence (substance use, bullying, early sexual onset) and whether the proportion, and thus statistical normality, of complex family types in a certain country is a potential moderator of this association. Drawing on representative data from 42 countries and regions from the Health Behavior in School-aged Children (HBSC) study in 2001, 2006, and 2010 (N = 506,977), we provide detailed analyses on adolescent risk behavior even for very rare family types, thereby accounting for the complex cross-household structure present in many post-separation families. We combine logistic and count regression models to analyze risk incidence and intensity. Controlling for relevant child and family characteristics, our results reveal a gradient along which adolescent risk-taking increases with family complexity: The incidence and intensity of risk-taking among adolescents is lowest in two-biological-parent and highest in two-household families with stepparents in both households. The association decreases with a higher proportion of the respective family type in a country. However, the differences between family types, other than the two-biological parent family, are not as pronounced as expected.
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TwitterTIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.
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Context
The dataset presents a breakdown of households across various income brackets in Wildwood, MO, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Wildwood, MO reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Wildwood households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 Wildwood median household income. You can refer the same here
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TwitterBetween 2010 and 2025, the average number of household members in Italy decreased. In 2010, Italian households had about 2.41 individuals, whereas the average number of members was 2.2 in 2025.
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TwitterOpen Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
Source: U.S. Census Bureau; American Community Survey, 2019-2023 American Community Survey 5-Year Estimates, Table DP03; generated by CCRPC staff; using data.census.gov; https://data.census.gov/cedsci/; (6 March 2025).
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TwitterThese family food datasets contain more detailed information than the ‘Family Food’ report and mainly provide statistics from 2001 onwards. The UK household purchases and the UK household expenditure spreadsheets include statistics from 1974 onwards. These spreadsheets are updated annually when a new edition of the ‘Family Food’ report is published.
The ‘purchases’ spreadsheets give the average quantity of food and drink purchased per person per week for each food and drink category. The ‘nutrient intake’ spreadsheets give the average nutrient intake (e.g. energy, carbohydrates, protein, fat, fibre, minerals and vitamins) from food and drink per person per day. The ‘expenditure’ spreadsheets give the average amount spent in pence per person per week on each type of food and drink. Several different breakdowns are provided in addition to the UK averages including figures by region, income, household composition and characteristics of the household reference person.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Dependent children living in multi-generational family households and overcrowding of multi-generational family households.
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License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Solon, OH, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Solon, OH reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Solon households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 Solon median household income. You can refer the same here
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License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Grays Harbor County, WA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Grays Harbor County, WA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Grays Harbor County households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 Grays Harbor County median household income. You can refer the same here
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Graph and download economic data for New One Family Homes for Sale in the United States (HNFSEPUSSA) from Jan 1963 to Aug 2025 about 1-unit structures, family, new, sales, housing, and USA.
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TwitterThe average American household consisted of 2.51 people in 2023.
Households in the U.S.
As shown in the statistic, the number of people per household has decreased over the past decades.
The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”
The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.
Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.
In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.