In 2022, there were about 4.15 million Black families in the United States with a single mother. This is an increase from 1990 levels, when there were about 3.4 million Black families with a single mother.

Single parenthood

The typical family is comprised of two parents and at least one child. However, that is not the case in every single situation. A single parent is someone who has a child but no spouse or partner. Single parenthood occurs for different reasons, including divorce, death, abandonment, or single-person adoption. Historically, single parenthood was common due to mortality rates due to war, diseases, and maternal mortality. However, divorce was not as common back then, depending on the culture.

Single parent wellbeing

In countries where social welfare programs are not strong, single parents tend to suffer more financially, emotionally, and mentally. In the United States, most single parents are mothers. The struggles that single parents face are greater than those in two parent households. The number of families with a single mother in the United States has increased since 1990, but the poverty rate of black families with a single mother has significantly decreased since that same year. In comparison, the poverty rate of Asian families with a single mother, and the percentage of white, non-Hispanic families with a single mother who live below the poverty level in the United States have both been fluctuating since 2002.

Single-parent Families reports the percent of families with children that are headed by a single parent, per race/ethnicity of the householder. Dimensions Year;Measure.Type;Variable Full Description Children are all persons under the age of 18 years, living in families, and related as children by birth, marriage, or adoption to the householder. Children living with married step-parents are not included. Single-parent families may include unmarried couples. This data originates from the American Community Survey (ACS) 5-Year estimates, table B11003. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. At this time only state-level annual data are available on CTdata.org. Town-level data aggregated from the five-year datasets (considered to be more accurate for geographic areas that are the size of a county or smaller) can be produced using Census tables currently available on the Census website.

In 2023, there were about 1.18 million Black families with a single father living in the United States. This is an increase from 1990, when there were 472,000 Black families with a single father in the U.S.

This statistic shows the number of children living with single divorced parents in the United States in 2020, by race. In 2020, ****** Asian children lived with their divorced single father.

In 2023, there were about 15.09 million children living with a single mother in the United States, and about 3.05 million children living with a single father. The number of children living with a single mother is down from its peak in 2012, and the number of children living with a single father is down from its peak in 2005.

Marriage and divorce in the United States

Despite popular opinion in the United States that “half of all marriages end in divorce,” the divorce rate in the U.S. has fallen significantly since 1992. The marriage rate, which has also been decreasing since the 1990s, was still higher than the divorce rate in 2021. Half of all marriages may not end in divorce, but it does seem that fewer people are choosing to get married in the first place.

New family structures

In addition to a falling marriage rate, fewer people in the U.S. have children under the age of 18 living in the house in comparison to 1970. Over the past decade, the share of families with children under 18, whether that be married couples or single parents, has stayed mostly steady, although the number of births in the U.S. has also fallen.

In 2023, there were about 6.65 million white, non-Hispanic families with a single mother living in the United States. This is a slight increase from 1990, when there were 6.4 million white families with a single mother living in the U.S.

This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines.

The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee.

Units of Response: United States and Territories, CCDF Family Recipients, CCDF Children Recipients

Type of Data: Administrative

Tribal Data: No

Periodicity: Annual

Demographic Indicators: Ethnicity;Household Income;Household Size;Race

SORN: Not Applicable

Data Use Agreement: Not Applicable

Data Use Agreement Location: https://www.icpsr.umich.edu/rpxlogin

Granularity: Family;Individual

Spatial: United States

Geocoding: Tribe

The data on relationship to householder were derived from answers to Question 2 in the 2015 American Community Survey (ACS), which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs.

The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multi-generational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.

Household – A household includes all the people who occupy a housing unit. (People not living in households are classified as living in group quarters.) 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 separately from any other people in the building and which have direct access from the outside of 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 people who share living arrangements.

Average Household Size – A measure obtained by dividing the number of people in households by the number of households. In cases where people in households are cross-classified by race or Hispanic origin, people in the household are classified by the race or Hispanic origin of the householder rather than the race or Hispanic origin of each individual.

Average household size is rounded to the nearest hundredth.

Comparability – The relationship categories for the most part can be compared to previous ACS years and to similar data collected in the decennial census, CPS, and SIPP. With the change in 2008 from “In-law” to the two categories of “Parent-in-law” and “Son-in-law or daughter-in-law,” caution should be exercised when comparing data on in-laws from previous years. “In-law” encompassed any type of in-law such as sister-in-law. Combining “Parent-in-law” and “son-in-law or daughter-in-law” does not represent all “in-laws” in 2008.

The same can be said of comparing the three categories of “biological” “step,” and “adopted” child in 2008 to “Child” in previous years. Before 2008, respondents may have considered anyone under 18 as “child” and chosen that category. The ACS includes “foster child” as a category. However, the 2010 Census did not contain this category, and “foster children” were included in the “Other nonrelative” category. Therefore, comparison of “foster child” cannot be made to the 2010 Census. Beginning in 2013, the “spouse” category includes same-sex spouses.

The purpose of this study was to determine the role that extended families play in supporting African American single mothers. The sample consists of 320 African American single mothers and 126 of their "significant others." All mothers were over 20 years old, worked outside the home, and had children under the age of 18 living at home. Significant others were defined as the person who was most supportive of the respondent; half of these were relatives. The mothers completed a questionnaire inquiring about families of origin and families of procreation as well as the following topics: mobility patterns, significant life events, interactions with family and friends, concerns of single mothers, sources of stress, role conflicts and coping strategies, help-seeking and help-exchange patterns, utilization of services, and race-related attitudes. The questionnaire also assessed mental health and included scales about general well-being, anxiety, self-esteem, degree of control, role satisfaction, and life satisfaction. The questionnaire completed by the significant others included many of the same questions as well as questions about the relationship with the mother. The Murray Research Archive holds both numeric file data, and original record paper data from the mothers and the significant others.

The 1901 Census of Canada was the fourth Census conducted . The Canadian Families Project has a broad mandate. Their re-investigation of family in Canada includes the study of discourses of family; class, ethnicity and region as they relate to family; the history of single parenthood and fragmented families; fertility decline; language, education and family; religion and family; family and community in rural Canada; the social geography of urban families; family income and standards of living. Basic to the work of the Project is the study of families in the past. The Project begins by creating a large database of information from the 1901 census of Canada. The database will include all information from Schedules 1 and 2 of the census for five percent of individuals and families in the whole of Canada (as it existed in 1901). Schedule 1 contains the nominal returns - the enumeration of the population by name. Schedule 2 is a continuation of Schedule 1 and it gives information of buildings and lands held by persons enumerated in Schedule 1. The 5 percent sample will include information on approximately 268,500 persons. (Summary derived from User Guide)

This paper examines the association between the Great Recession and real assets among families with young children. Real assets such as homes and cars are key indicators of economic well-being that may be especially valuable to low-income families. Using longitudinal data from the Fragile Families and Child Wellbeing Study (N = 4,898), we investigate the association between the city unemployment rate and home and car ownership and how the relationship varies by family structure (married, cohabiting, and single parents) and by race/ethnicity (White, Black, and Hispanic mothers). Using mother fixed-effects models, we find that a one percentage point increase in the unemployment rate is associated with a -0.5 percentage point decline in the probability of home ownership and a -0.7 percentage point decline in the probability of car ownership. We also find that the recession was associated with lower levels of home ownership for cohabiting families and for Hispanic families, as well as lower car ownership among single mothers and among Black mothers, whereas no change was observed among married families or White households. Considering that homes and cars are the most important assets among middle and low-income households in the U.S., these results suggest that the rise in the unemployment rate during the Great Recession may have increased household asset inequality across family structures and race/ethnicities, limiting economic mobility, and exacerbating the cycle of poverty.

This statistic shows the percentage of women who were the primary breadwinner in the household that were single mothers in the United States in 2014, by race. Among black women who were the primary income provider to the household, **** percent were single mothers in 2014.

There are just under **** million single parent families in the United Kingdom as of 2024, compared with *** million in 1996.

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsPolicy Development: Helps policymakers develop targeted interventions to address the needs of vulnerable populations.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability.Research: Provides a robust foundation for academic and applied research in socio-economic and demographic studies.Community Planning: Aids in the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities.Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2013-2017 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2013-2017 ACSEP_PCIEP_PCIPer capita income estimate, 2013-2017 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2013-2017 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2013-2017 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2013-2017 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2013-2017 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2013-2017 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

The Priority Neighborhoods dataset is a part of the City of Oakland Department of Transportation's (OakDOT's) Geographic Equity Toolbox. The Priority Neighborhoods GIS dataset relies upon demographic data from the American Community Survey (ACS). This dataset assigns each census tract in Oakland a numerical priority value and a quantile from lowest and highest, as determined by the following seven weighted demographic factors (with weights in brackets "[XX%]"): • People of Color [25%] • Low-income Households (<50% of Area Median Income for a 4-person household) [25%] • People with Disability [10%] • Seniors 65 Years and Over [10%] • Single Parent Families [10%] • Severely Rent-Burdened Households [10%] • Low Educational Attainment (less than a bachelor's degree) [10%]

This dataset was last updated in October 2024 with data from the 2022 5-year (i.e., averaged from 2018 through 2022) American Community Survey (ACS). The ACS is managed by the United States Census Bureau; learn more about the ACS at: https://www.census.gov/programs-surveys/acs.

See the online map and read the methodology at: https://www.oaklandca.gov/resources/oakdot-geographic-equity-toolbox. This dataset is maintained by the OakDOT Race and Equity Team; learn more about the team at: https://www.oaklandca.gov/topics/oakdot-race-and-equity-team.

Field Descriptions: • TRACT: Census Tract Number • QUINTILE: Priority Quintile (calculated) • PLAN_AREA: OakDOT Planning Area • POPULATION: Population (average from 2018 through 2022) • PCT_POC: Percent People of Color • PCT_INC: Percent Low Income • PCT_SRB: Percent Severely Rent-Burdened • PCT_PWD: People with a Disability • PCT_SENIOR: Percent Seniors • PCT_SPH: Percent Single Parent Households • PCT_EDU: Percent Low Educational Attainment • RAT_POC: Ratio of People of Color (compared to Citywide average) • RAT_INC: Ratio of Low Income (compared to Citywide average) • RAT_SRB: Ratio of Severely Rent-Burdened (compared to Citywide average) • RAT_PWD: Ratio of People with a Disability (compared to Citywide average) • RAT_SENIOR: Ratio of Seniors (compared to Citywide average) • RAT_SPH: Ratio of Single Parent Households (compared to Citywide average) • RAT_EDU: Ratio of Low Educational Attainment (compared to Citywide average) • RAT_SCORE: Priority Ratio (compared to Citywide average) • ALAND: Land Area in square feet

City of Oakland, Department of Transportation (OakDOT) 250 Frank H. Ogawa Plaza, Suite 4314 | Oakland, CA 94612

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themesEach tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively. In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United StatesNote: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2015-2019 ACSEP_PCIEP_PCIPer capita income estimate, 2015-2019 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2015-2019 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2015-2019 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2015-2019 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2015-2019 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computerThis table provides a mapping between the CSV variable names and the shapefile variable names, along with a brief description of each variable.

The data this week comes from the National Database of Childcare Prices.

Data Dictionary

childcare_costs.csv

variable	class	description
county_fips_code	double	Four- or five-digit number that uniquely identifies the county in a state. The first two digits (for five-digit numbers) or 1 digit (for four-digit numbers) refer to the FIPS code of the state to which the county belongs.
study_year	double	Year the data collection began for the market rate survey and in which ACS data is representative of, or the study publication date.
unr_16	double	Unemployment rate of the population aged 16 years old or older.
funr_16	double	Unemployment rate of the female population aged 16 years old or older.
munr_16	double	Unemployment rate of the male population aged 16 years old or older.
unr_20to64	double	Unemployment rate of the population aged 20 to 64 years old.
funr_20to64	double	Unemployment rate of the female population aged 20 to 64 years old.
munr_20to64	double	Unemployment rate of the male population aged 20 to 64 years old.
flfpr_20to64	double	Labor force participation rate of the female population aged 20 to 64 years old.
flfpr_20to64_under6	double	Labor force participation rate of the female population aged 20 to 64 years old who have children under 6 years old.
flfpr_20to64_6to17	double	Labor force participation rate of the female population aged 20 to 64 years old who have children between 6 and 17 years old.
flfpr_20to64_under6_6to17	double	Labor force participation rate of the female population aged 20 to 64 years old who have children under 6 years old and between 6 and 17 years old.
mlfpr_20to64	double	Labor force participation rate of the male population aged 20 to 64 years old.
pr_f	double	Poverty rate for families.
pr_p	double	Poverty rate for individuals.
mhi_2018	double	Median household income expressed in 2018 dollars.
me_2018	double	Median earnings expressed in 2018 dollars for the population aged 16 years old or older.
fme_2018	double	Median earnings for females expressed in 2018 dollars for the population aged 16 years old or older.
mme_2018	double	Median earnings for males expressed in 2018 dollars for the population aged 16 years old or older.
total_pop	double	Count of the total population.
one_race	double	Percent of population that identifies as being one race.
one_race_w	double	Percent of population that identifies as being one race and being only White or Caucasian.
one_race_b	double	Percent of population that identifies as being one race and being only Black or African American.
one_race_i	double	Percent of population that identifies as being one race and being only American Indian or Alaska Native.
one_race_a	double	Percent of population that identifies as being one race and being only Asian.
one_race_h	double	Percent of population that identifies as being one race and being only Native Hawaiian or Pacific Islander.
one_race_other	double	Percent of population that identifies as being one race and being a different race not previously mentioned.
two_races	double	Percent of population that identifies as being two or more races.
hispanic	double	Percent of population that identifies as being Hispanic or Latino regardless of race.
households	double	Number of households.
h_under6_both_work	double	Number of households with children under 6 years old with two parents that are both working.
h_under6_f_work	double	Number of households with children under 6 years old with two parents with only the father working.
h_under6_m_work	double	Number of households with children under 6 years old with two parents with only the mother working.
h_under6_single_m	double	Number of households with children under 6 years old with a single mother.
h_6to17_both_work	double	Number of households with children between 6 and 17 years old with two parents that are both working.
h_6to17_fwork	double	Number of households with children between 6 and 17 years old with two parents with only the father working.
h_6to17_mwork	double	Number of households with children between 6 and 17 year...

Abstract copyright UK Data Service and data collection copyright owner.

To collect data on family history through census probes in 1850 and 1880.
Main Topics:

Variables
Household composition: whether single or multiple family dwelling, total number of residents, total number of children of the head of household (age and sex is given for each child), number of parents or parents-in-law of the head of household residing in household, number of other related adults (i.e. over 14 years of age) in household, number of other related children (i.e. 14 or less years of age) in household, number of boarders or roomers in household and finally number of children listed as employed.
The following data are given for head of household; sex, age, race (10 categories), occupation (12 occupational cohorts), birthplace (i.e. US state or other country). Information also includes: birthplace of head of household's parents, residence (i.e. same household, another household), age, race and occupation of head of household's spouse, and birthplaces of spouse's parents.
Geographical information: county in which household resided, township, village or city in which household resided (together with 1850 population figure for each) and type of locale (9 categories - e.g. 'rural - less than 250', 'city of 2,500 - 4,999 persons' etc.).

The goal of this study was to test specific hypotheses illustrating the relationships among serious victimization experiences, the mental health effects of victimization, substance abuse/use, and delinquent behavior in adolescents. The study assessed familial and nonfamilial types of violence. It was designed as a telephone survey of American youth aged 12-17 living in United States households and residing with a parent or guardian. One parent or guardian in each household was interviewed briefly to establish rapport, secure permission to interview the targeted adolescent, and to ensure the collection of comparative data to examine potential nonresponse bias from households without adolescent participation. All interviews with both parents and adolescents were conducted using Computer-Assisted Telephone Interviewing (CATI) technology. From the surveys of parents and adolescents, the principal investigators created one data file by attaching the data from the parents to the records of their respective adolescents. Adolescents were asked whether violence and drug abuse were problems in their schools and communities and what types of violence they had personally witnessed. They were also asked about other stressful events in their lives, such as the loss of a family member, divorce, unemployment, moving to a new home or school, serious illness or injury, and natural disaster. Questions regarding history of sexual assault, physical assault, and harsh physical discipline elicited a description of the event and perpetrator, extent of injuries, age at abuse, whether alcohol or drugs were involved, and who was informed of the incident. Information was also gathered on the delinquent behavior of respondents and their friends, including destruction of property, assault, theft, sexual assault, and gang activity. Other questions covered history of personal and family substance use and mental health indicators, such as major depression, post-traumatic stress disorders, weight changes, sleeping disorders, and problems concentrating. Demographic information was gathered from the adolescents on age, race, gender, number of people living in household, and grade in school. Parents were asked whether they were concerned about violent crime, affordable child care, drug abuse, educational quality, gangs, and the safety of their children at school. In addition, they were questioned about their own victimization experiences and whether they discussed personal safety issues with their children. Parents also supplied demographic information on gender, marital status, number of children, employment status, education, race, and income.