This graph shows the Percentage of households led by a female householder with no spouse present with own children under 18 years living in the household in the U.S. in 2021, by state. In 2021, about 4.24 percent of Californian households were single mother households with at least one child.
Additional information on single mother households and poverty in the United States
For most single mothers a constant battle persists between finding the time and energy to raise their children and the demands of working to supply an income to house and feed their families. The pressures of a single income and the high costs of childcare mean that the risk of poverty for these families is a tragic reality. Comparison of the overall United States poverty rate since 1990 with that of the poverty rate for families with a female householder shows that poverty is much more prevalent in the latter. In 2021, while the overall rate was at 11.6 percent, the rate of poverty for single mother families was 23 percent. Moreover, the degree of fluctuation tends to be lower for single female household families, suggesting the rate of poverty for these groups is less affected by economic conditions.
The sharp rise in the number of children living with a single mother or single father in the United States from 1970 to 2022 suggests more must be done to ensure that families in such situations are able to avoid poverty. Moreover, attention should also be placed on overall racial income inequality given the higher rate of poverty for Hispanic single mother families than their white or Asian counterparts.
The layer was derived and compiled from the U.S. Census Bureau’s 2012 – 2016 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table S1101 HOUSEHOLDS AND FAMILIES, 2012 – 2016 ACS 5-Year Estimates
Effective Date: December 2017
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each
December. Vintage used for 2020 Census
planning purposes by Broward County.
Since 1960, the U.S. Department of Agriculture has provided estimates of expenditures on children from birth through age 17. This technical report presents the most recent estimates for married- couple and single-parent families using data from the 2011-15 Consumer Expenditure Survey (all data presented in 2015 dollars). Data and methods used in calculating annual child-rearing expenses are described. Estimates are provided for married-couple and single-parent families with two children for major components of the budget by age of child, family income, and region of residence. For the overall United States, annual child-rearing expense estimates ranged between $12,350 and $13,900 for a child in a two-child, married-couple family in the middle-income group. Adjustment factors for households with less than or greater than two children are also provided. Expenses vary considerably by household income level, region, and composition, emphasizing that a single estimate may not be applicable to all families. Results of this study may be of use in developing State child support and foster care guidelines, as well as public health and family-centered educational programs. i
Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
A national sample survey dataset covering a wide variety of issues on American family life beginning in 1987-88 and at two subsequent timepoints1992-93 and 2001-03. Topics covered included detailed household composition, family background, adult family transitions, couple interactions, parent-child interactions, education and work, health, economic and psychological well-being, and family attitudes. The first wave interviewed 13,017 respondents, including a main cross-section sample of 9,643 persons aged 19 and over plus an oversample of minorities and households containing single-parent families, step-families, recently married couples, and cohabiting couples. In each household, a randomly selected adult was interviewed. In addition, a shorter, self-administered questionnaire was filled out by the spouse or cohabiting partner of the primary respondent. Interviews averaged about 100 minutes, although interview length varied considerably with the complexity of the respondent''s family history. In 1992-94, an in-person interview was conducted of all surviving members of the original sample, the current spouse or cohabiting partner, and with the baseline spouse or partner in cases where the relationship had ended. Telephone interviews were conducted with focal children who were aged 5-12 and 13-18 at baseline. Short proxy interviews were conducted with a surviving spouse or other relative in cases where the original respondent died or was too ill to interview. A telephone interview was conducted with one randomly selected parent of the main respondent. In 2001-03, telephone interviews were conducted with: Surviving members of the original respondents who had a focal child age 5 or over at baseline; the baseline spouse/partner of these original respondents, whether or not the couple was still together; the focal children who were in the household and aged 5-18 at baselinemost of whom were interviewed at wave 2; and all other original respondents age 45 or older in 2000, and their baseline spouse/partner. Oversamples: Blacks, 9.2%; Mexican-Americans, 2.4%; Puerto Ricans, 0.7% * Dates of Study: 1987-2003 * Study Features: Longitudinal, Minority Oversampling * Sample Size (original respondents): ** Wave I (1987-88): 13,017 ** Wave II (1992-93): 10,007 ** Wave III (2001-03): 8,990 Links: * Wave I (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06041 * Wave II (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06906 * Wave III (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00171
The 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 House Districts for New Mexico as posted on the Census Bureau website for 2006.
Subcounty-level family type estimates for family households, including presence of children in family households, single-parent households, and families with female or male householders without a spouse or partner present. Estimates are accompanied by margins of error, coefficients of variation, and percentages. Geometry source: 2020 Census. Attribute source: 2019-2023 American Community Survey 5-year estimates, table B11003. Date of last data update: 2024-01-04 This is official RLIS data. Contact Person: Joe Gordon joe.gordon@oregonmetro.gov 503-797-1587 RLIS Metadata Viewer: https://gis.oregonmetro.gov/rlis-metadata/#/details/3828 RLIS Terms of Use: https://rlisdiscovery.oregonmetro.gov/pages/terms-of-use
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 zip code 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.ApplicationsTargeted Interventions: Facilitates the development of targeted interventions to address the needs of vulnerable populations within specific zip codes.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability at the zip code level.Research: Provides a rich dataset for academic and applied research in socio-economic and demographic studies at a granular zip code level.Community Planning: Supports the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities within specific zip code areas.Note: Due to limitations in the data environment, 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, 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.
This dataset includes live births, birth rates, and fertility rates by race of mother in the United States since 1960.
Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.
SOURCES
NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).
REFERENCES
National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.
Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.
National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.
Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.
Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.
Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.
The study examined to the extent to which the parents of unmarried teenagers under 18 are informed that their daughters are attending a family planning clinic or abortion facility,how parents have been informed, and how notification requirements would effect the behavior of those teenagers whose parents do not know. The data are based on an Alan Guttmacher Institute survey of 1,241 young women seeking contraceptive services from 53 family planning clinics and another 1,170 seeking abortion services. The present data set contains data only for the teenagers seeking contraceptive services. Data were collected during the period of October, 1979 to March, 1980. Each respondent was asked whether or not her parents knew about her clinic visit for contraceptive services and, if her parents did not know, what ahe would have done (with respect to contraceptive and aexual behavior, and utilization of clinic services) if their notification had been required by the clinic. The study was also designed to determine what proportion of teenagers whose parents knew they were getting birth control services had told them voluntarily, what propor tion had told them because the clinic required them to do so, and whether or not the teenager talked about ways of preventing pregnancy with their parents. The survey asked each respondent if she had ever used the pill, IUD, or diaphragm and what birth control method she intended to obtain from the clinic. The 30 respondents who chose nonprescription methods are not included in this dataset. Finally, the women were asked with whom they lived: teenagers who did not answer that they were living with their husbands were assumed to be unmarried.
This dataset includes teen birth rates for females by age group, race, and Hispanic origin in the United States since 1960. Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison. National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf). SOURCES NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.
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This graph shows the Percentage of households led by a female householder with no spouse present with own children under 18 years living in the household in the U.S. in 2021, by state. In 2021, about 4.24 percent of Californian households were single mother households with at least one child.
Additional information on single mother households and poverty in the United States
For most single mothers a constant battle persists between finding the time and energy to raise their children and the demands of working to supply an income to house and feed their families. The pressures of a single income and the high costs of childcare mean that the risk of poverty for these families is a tragic reality. Comparison of the overall United States poverty rate since 1990 with that of the poverty rate for families with a female householder shows that poverty is much more prevalent in the latter. In 2021, while the overall rate was at 11.6 percent, the rate of poverty for single mother families was 23 percent. Moreover, the degree of fluctuation tends to be lower for single female household families, suggesting the rate of poverty for these groups is less affected by economic conditions.
The sharp rise in the number of children living with a single mother or single father in the United States from 1970 to 2022 suggests more must be done to ensure that families in such situations are able to avoid poverty. Moreover, attention should also be placed on overall racial income inequality given the higher rate of poverty for Hispanic single mother families than their white or Asian counterparts.