The number of non-family households in the United States has been on the rise. In 2022, there were about ***** million non-family households in the U.S., up from about **** million in 1990.

Non-family households are defined as either a householder living alone or where the householder shares a home with those to whom they are not related.

Over the past five years, the profile of the American household has been changing. Between 2014 and 2019, the number of households of married Millennials without children has risen by ten percent, while the number of households of Millennials with children has decreased by seven percent. The largest change occurred in households of people over the age of 75. The number of households in this age group increased by 49 percent for married people with children, 46 percent for people living with non-family members, and 41 percent for single parents.

The purpose of this project is to study the early development of a group of children who are at risk regarding later successful adjustment and for whom we have little information: children living in rural, largely poor communities. A birth cohort of 800 children in three rural counties of North Carolina and 600 children in three rural counties of Pennsylvania were studied over the first 3 years of life. A multidisciplinary team investigated multiple levels of influences affecting the early development of these children. The research emphases of the component research projects include the following: Project I: Temperament: Emphasizes the development of child-related factors and how they predict preschool social-emotional and cognitive competence Project II: School Readiness: Emphasizes the pathways to and precursors of school readiness Project III: Family Process: Emphasizes how family processes mediate or moderate the effects of rural poverty on children Project IV: Work and Family: Emphasizes the impact of parents' occupational conditions on parenting, and, in turn, children's social, cognitive, emotional and linguistic development Project V: Ethnography: Emphasizes two components: an in-depth contextual appraisal of community characteristics a family ethnography with 72 families developmentally ahead of the cohort above to provide input to design and measurement This project used a cumulative risk model to examine the relation between social risk and children's executive functioning, language development and behavioral competence at 36 months. Using both the Family Process Model of development and the Family Investment Model of development, observed parenting was examined over time in relation to child functioning at 36 months. Different aspects of observed parenting were examined as mediators/moderators of risk in predicting child outcomes. Results suggested that cumulative risk was important in predicting all three major domains of child outcomes and that positive and negative parenting and maternal language complexity were mediators of these relations. Maternal positive parenting was found to be a buffer for the most risky families in predicting behavioral competence. In a final model using both family process and investment measures, there was evidence of mediation but with little evidence of the specificity of parenting for particular outcomes. Results demonstrate the importance of cumulative risk and parenting in understanding child competence in rural poverty and the implications for possible intervention strategies that might be effective in maximizing the early development of these children.

This collection contains data obtained from families of wage earners or salaried workers in industrial locales scattered throughout the United States. The purpose of the survey was to estimate the cost of living of a "typical" American family. The completed questionnaires contain information about income sources and family expenditures including specific quantities and costs of food, housing, clothing, fuel, furniture, and miscellaneous household items for the calendar year. Demographic characteristics recorded for each household member include relationship to head, age, sex, occupation, weeks spent in the household and employed, wage rate, and total earnings.

The 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.

The US Family Budget Dataset provides insights into the cost of living in different US counties based on the Family Budget Calculator by the Economic Policy Institute (EPI).

This dataset offers community-specific estimates for ten family types, including one or two adults with zero to four children, in all 1877 counties and metro areas across the United States.

Interesting Task Ideas:

1. See how family budgets compare to the federal poverty line and the Supplemental Poverty Measure in different counties.
2. Look into the money challenges faced by different types of families using the budgets provided.
3. Find out which counties have the most affordable places to live, food, transportation, healthcare, childcare, and other things people need.
4. Explore how the average income of families relates to the overall cost of living in different counties.
5. Investigate how family size affects the estimated budget and find counties where bigger families have higher costs.
6. Create visuals showing how the cost of living varies across different states and big cities.
7. Check whether specific counties are affordable for families of different sizes and types.
8. Use the dataset to compare living standards and economic security in different US counties.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

Checkout my other datasets

Employment-to-Population Ratio for USA

Productivity and Hourly Compensation

130K Kindle Books

900K TMDb Movies

USA Unemployment Rates by Demographics & Race

Photo by Alev Takil on Unsplash

This dataset contains two tables on the percent of household overcrowding (> 1.0 persons per room) and severe overcrowding (> 1.5 persons per room) for California, its regions, counties, and cities/towns. Data is from the U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) and U.S. Census American Community Survey (ACS). The table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity: Healthy Communities Data and Indicators Project of the Office of Health Equity. Residential crowding has been linked to an increased risk of infection from communicable diseases, a higher prevalence of respiratory ailments, and greater vulnerability to homelessness among the poor. Residential crowding reflects demographic and socioeconomic conditions. Older-adult immigrant and recent immigrant communities, families with low income and renter-occupied households are more likely to experience household crowding. A form of residential overcrowding known as "doubling up"—co-residence with family members or friends for economic reasons—is the most commonly reported prior living situation for families and individuals before the onset of homelessness. More information about the data table and a data dictionary can be found in the About/Attachments section.The household crowding table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf
The format of the household overcrowding tables is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

Graph and download economic data for New Privately Owned Housing Completions in the United States, Total One-Family Units (COMP1FQ) from Q1 1987 to Q1 2025 about privately owned, 1-unit structures, family, new, housing, and USA.

United States Housing Affordability Index: Median Family Income data was reported at 77,021.000 USD in Oct 2018. This records an increase from the previous number of 76,754.000 USD for Sep 2018. United States Housing Affordability Index: Median Family Income data is updated monthly, averaging 53,251.500 USD from Jan 1989 (Median) to Oct 2018, with 358 observations. The data reached an all-time high of 77,021.000 USD in Oct 2018 and a record low of 33,287.000 USD in Jan 1989. United States Housing Affordability Index: Median Family Income data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB018: Housing Affordability Index.

The Future of Families and Child Wellbeing Study (FFCWS, formerly known as the Fragile Families and Child Wellbeing Study) follows a cohort of nearly 5,000 children born in large, U.S. cities between 1998 and 2000. The study oversampled births to unmarried couples; and, when weighted, the data are representative of births in large U.S. cities at the turn of the century. The FFCWS was originally designed to address four questions of great interest to researchers and policy makers: What are the conditions and capabilities of unmarried parents, especially fathers? What is the nature of the relationships between unmarried parents? How do children born into these families fare? How do policies and environmental conditions affect families and children? The FFCWS consists of interviews with mothers, fathers, and/or primary caregivers at birth and again when children are ages 1, 3, 5, 9, 15, and 22. The parent interviews collected information on attitudes, relationships, parenting behavior, demographic characteristics, health (mental and physical), economic and employment status, neighborhood characteristics, and program participation. Beginning at age 9, children were interviewed directly (either during the home visit or on the telephone). The direct child interviews collected data on family relationships, home routines, schools, peers, and physical and mental health, as well as health behaviors. A collaborative study of the FFCWS, the In-Home Longitudinal Study of Pre-School Aged Children (In-Home Study) collected data from a subset of the FFCWS Core respondents at the Year 3 and 5 follow-ups to ask how parental resources in the form of parental presence or absence, time, and money influence children under the age of 5. The In-Home Study collected information on a variety of domains of the child's environment, including: the physical environment (quality of housing, nutrition and food security, health care, adequacy of clothing and supervision) and parenting (parental discipline, parental attachment, and cognitive stimulation). In addition, the In-Home Study also collected information on several important child outcomes, including anthropometrics, child behaviors, and cognitive ability. This information was collected through interviews with the child's primary caregiver, and direct observation of the child's home environment and the child's interactions with his or her caregiver. Similar activities were conducted during the Year 9 follow-up. At the Year 15 follow-up, a condensed set of home visit activities were conducted with a subsample of approximately 1,000 teens. Teens who participated in the In-Home Study were also invited to participate in a Sleep Study and were asked to wear an accelerometer on their non-dominant wrist for seven consecutive days to track their sleep (Sleep Actigraphy Data) and that day's behaviors and mood (Daily Sleep Actigraphy and Diary Survey Data). An additional collaborative study collected data from the child care provider (Year 3) and teacher (Years 9 and 15) through mail-based surveys. Saliva samples were collected at Year 9 and 15 (Biomarker file and Polygenic Scores). The Study of Adolescent Neural Development (SAND) COVID Study began data collection in May 2020 following the onset of the COVID-19 pandemic. It included online surveys with the young adult and their primary caregiver. The FFCWS began its seventh wave of data collection in October 2020, around the focal child's 22nd birthday. Data collection and interviews continued through January 2024. The Year 22 wave included a young adult (YA) survey with the original focal child and a primary caregiver (PCG) survey. Data were also collected on the children of the original focal child (referred to as Generation 3, or G3). Documentation for these files is available on the FFCWS website located here. For details of updates made to the FFCWS data files, please see the project's Data Alerts page. Data collection for the Future of Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations.

Graph and download economic data for New Privately-Owned Housing Units Completed: Single-Family Units in the Northeast Census Region (COMPUNE1USA) from Jan 1985 to May 2025 about Northeast Census Region, 1-unit structures, family, new, private, housing, and USA.

The layer was compiled from the U.S. Census Bureau’s 2018 Planning Database (PDB), a database that assembles a range of housing, demographic, socioeconomic, and census operational data. The data is from the 2012 – 2016 American Community Survey 5-Year Estimates. The purpose of the data is for 2020 Census planning purposes.

Source: 2018 PDB, U.S. Census Bureau

Effective Date: June 2018

Last Update: January 2020

Update Cycle: Generally, annually as needed. 2018 PDB is vintage used for 2020 Census planning purposes by Nation and County.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Live Oak, FL, 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 Live Oak, FL 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 Live Oak households based on income levels.

Key observations

• For Family Households: In Live Oak, the majority of family households, representing 17.09%, earn $60,000 to $74,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $40,000 to $44,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Live Oak, the majority of non-family households, accounting for 32.57%, have income $35,000 to $39,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $40,000 to $44,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Live Oak, FL (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Live Oak, FL
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Live Oak, FL
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Live Oak, FL

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Live Oak median household income. You can refer the same here

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.

U.S. Housing Starts - One-Family Units Floor Area: 26 years of historical data from 1999 to 2025.

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.

The layer was compiled from the U.S. Census Bureau’s 2018 Planning Database (PDB), a database that assembles a range of housing, demographic, socioeconomic, and census operational data. The data is from the 2012 – 2016 American Community Survey 5-Year Estimates. The purpose of the data is for 2020 Census planning purposes.

Source: 2018 PDB, U.S. Census Bureau

Effective Date: June 2018

Last Update: January 2020

Update Cycle: Generally, annually as needed. 2018 PDB is vintage used for 2020 Census planning purposes by Nation and County.

Housing Starts Multi Family in the United States decreased to 316 Thousand units in May from 454 Thousand units in April of 2025. This dataset includes a chart with historical data for the United States Housing Starts Multi Family.

United States Housing Market Index: sa: Single Family Detached: Present data was reported at 67.000 NA in Nov 2018. This records a decrease from the previous number of 74.000 NA for Oct 2018. United States Housing Market Index: sa: Single Family Detached: Present data is updated monthly, averaging 59.000 NA from Jan 1985 (Median) to Nov 2018, with 407 observations. The data reached an all-time high of 86.000 NA in Dec 1998 and a record low of 6.000 NA in Jan 2009. United States Housing Market Index: sa: Single Family Detached: Present data remains active status in CEIC and is reported by National Association of Home Builders. The data is categorized under Global Database’s United States – Table US.EB013: Housing Market Index.

In 2022, about 40.26 percent of all family households in the United States had their own children under age 18 living in the household. This is compared to the approximate 50.62 percent of female led households with their own children.