The average American family in 2023 consisted of 3.15 persons. Families in the United States According to the U.S. Census Bureau, a family is a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered as members of one family. As of 2023, the U.S. Census Bureau counted about 84.33 million families in the United States. The average family consisted of 3.15 persons in 2021, down from 3.7 in the 1960s. This is reflected in the decrease of children in family households overall. In 1970, about 56 percent of all family households had children under the age of 18 living in the household. This percentage declined to about 40 percent in 2020. The average size of a family household varies greatly from state to state. The largest average families can be found in Utah, California, and Hawaii, while the smallest families can be found in Wisconsin, Vermont and Maine.

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.

In 2021, the average size of families in Utah was 3.51 people, the largest out of any state. California, Hawaii, Texas, and Alaska rounded out the top five states with the largest average family size in that year. Nationwide, the average family size was 3.15 people.

In 2023, about 39.47 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 48.5 percent of female-led households with their own children under 18.

United States US: Fertility Rate: Total: Births per Woman data was reported at 1.800 Ratio in 2016. This records a decrease from the previous number of 1.843 Ratio for 2015. United States US: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 2.002 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 3.654 Ratio in 1960 and a record low of 1.738 Ratio in 1976. United States US: Fertility Rate: Total: Births per Woman data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average; Relevance to gender indicator: it can indicate the status of women within households and a woman’s decision about the number and spacing of children.

Graph and download economic data for Total Families with Children under 18 Years Old with Married Couple (FMLWCUMC) from 1950 to 2024 about married, 18 years +, family, child, household survey, and USA.

In 2022, about 60 percent of Hispanic origin children lived with two married parents in the United States. On the other hand, about 4.3 percent of Hispanic origin children in the country lived with their father only.

The graph illustrates the number of babies born in the United States from 1995 to 2025. The x-axis represents the years, labeled from '95 to '25, while the y-axis shows the annual number of births. Over this 30-year period, birth numbers peaked at 4,316,233 in 2007 and reached a low of 3,596,017 in 2023. The data reveals relatively stable birth rates from 1995 to 2010, with slight fluctuations, followed by a gradual decline starting around 2017. The information is presented in a line graph format, effectively highlighting the long-term downward trend in U.S. birth numbers over the specified timeframe.

In 2024, 34.59 percent of all households in the United States were two person households. In 1970, this figure was at 28.92 percent. Single households Single mother households are usually the most common households with children under 18 years old found in the United States. As of 2021, the District of Columbia and North Dakota had the highest share of single-person households in the United States. Household size in the United States has decreased over the past century, due to customs and traditions changing. Families are typically more nuclear, whereas in the past, multigenerational households were more common. Furthermore, fertility rates have also decreased, meaning that women do not have as many children as they used to. Average households in Utah Out of all states in the U.S., Utah was reported to have the largest average household size. This predominately Mormon state has about three million inhabitants. The Church of the Latter-Day Saints, or Mormonism, plays a large role in Utah, and can contribute to the high birth rate and household size in Utah. The Church of Latter-Day Saints promotes having many children and tight-knit families. Furthermore, Utah has a relatively young population, due to Mormons typically marrying and starting large families younger than those in other states.

In 2021, the birth rate in the United States was highest in families that had under 10,000 U.S. dollars in income per year, at 62.75 births per 1,000 women. As the income scale increases, the birth rate decreases, with families making 200,000 U.S. dollars or more per year having the second-lowest birth rate, at 47.57 births per 1,000 women. Income and the birth rate Income and high birth rates are strongly linked, not just in the United States, but around the world. Women in lower income brackets tend to have higher birth rates across the board. There are many factors at play in birth rates, such as the education level of the mother, ethnicity of the mother, and even where someone lives. The fertility rate in the United States The fertility rate in the United States has declined in recent years, and it seems that more and more women are waiting longer to begin having children. Studies have shown that the average age of the mother at the birth of their first child in the United States was 27.4 years old, although this figure varies for different ethnic origins.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In the United States in 1800, the average woman of childbearing age would have seven children over the course of their lifetime. As factors such as technology, hygiene, medicine and education improved, women were having fewer children than before, reaching just two children per woman in 1940. This changed quite dramatically in the aftermath of the Second World War, rising sharply to over 3.5 children per woman in 1960 (children born between 1946 and 1964 are nowadays known as the 'Baby Boomer' generation, and they make up roughly twenty percent of todays US population). Due to the end of the baby boom and increased access to contraception, fertility reached it's lowest point in the US in 1980, where it was just 1.77. It did however rise to over two children per woman between 1995 and 2010, although it is expected to drop again by 2020, to just 1.78.

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACS

The Head Start Family and Child Experiences Survey (FACES) is a periodic, ongoing longitudinal study of program performance. Successive nationally representative samples of Head Start children, their families, classrooms, and programs provide descriptive information on the population of children and families served; staff qualifications, credentials, and opinions; Head Start classroom practices and quality measures; and child and family outcomes. FACES includes a battery of child assessments across multiple developmental domains (cognitive, social, emotional, and physical).

For nearly a decade, the Office of Head Start, the Administration for Children and Families, other federal agencies, local programs, and the public have depended on FACES for valid and reliable national information on (1) the skills and abilities of Head Start children, (2) how Head Start children's skills and abilities compare with preschool children nationally, (3) Head Start children's readiness for and subsequent performance in kindergarten, and (4) the characteristics of the children's home and classroom environments. The FACES study is designed to enable researchers to answer a wide range of research questions that are crucial for aiding program managers and policymakers. Some of the questions that are central to FACES include:

1. What are the demographic characteristics of the population of children and families served by Head Start? How has the population served by Head Start changed?
2. What are the experiences of families and children in the Head Start program? How have they changed?
3. What are the cognitive and social skills of Head Start children at the beginning and end of their first year in the program? Has Head Start program performance improved over time?
4. Do the gains in cognitive and social skills that Head Start children achieve carry over into kindergarten? Do larger gains (or greater declines in problem behavior) translate into higher achievement at the end of kindergarten?
5. What are the qualifications of Head Start teachers in terms of education, experience, and credentials? Are average teacher education levels rising in Head Start?
6. What is the observed quality of Head Start classrooms as early learning environments, including the level and range of teaching and interactions, provisions for learning, emotional and instructional support, and classroom organization? How has quality changed over time? What program- and classroom-level factors are related to observed classroom quality? How is observed quality related to children's outcomes and developmental gains?

FACES also supports analyses of subgroups of interest, such as children with disabilities, dual language learners, and children who are performing above or below average on standardized assessments. Its design changes in response to emerging policy and research questions. For example, in response to the growing concern about childhood obesity, measures of children's height and weight were introduced in FACES 2006.

Measures for FACES 2006 were selected to balance the need to support comparisons to previous cohorts of FACES (particularly with respect to program performance measures) against the need to update the measurement battery and address emerging policy issues and benefits from progress in the assessment field. Many of the measures used in FACES 2006 were included in previous cohorts and they are presented below by the five major measurement sources in FACES: (1) child direct assessments; (2) parent interviews; (3) teacher interviews and survey; (4) classroom observations; and (5) program director, center director, and education coordinator interviews.

1. The child direct assessments included the major components of school readiness. They included a language screener, the Peabody Picture Vocabulary Test, Fourth Edition/Test de Vocabulario de Imagines Peabody, subtests from the Woodcock-Johnson Tests of Achievement Third Edition/Bateria III Woodcock-Munoz (letter word identification, applied problems, spelling, and word attack), a measure of early math literacy based on items from the Early Childhood Longitudinal Study, Birth and Kindergarten Cohorts math assessments (geometry, patterns, and measurement), story and print concepts, and physical measurements (height and

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show family types by Atlanta City Council Districts in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Families_e

# Family households, 2017

Families_m

# Family households, 2017 (MOE)

MarriedCouple_e

# Married-couple families, 2017

MarriedCouple_m

# Married-couple families, 2017 (MOE)

pMarriedCouple_e

% Married-couple families, 2017

pMarriedCouple_m

% Married-couple families, 2017 (MOE)

MarriedOwnChild_e

# Married-couple families with own child, 2017

MarriedOwnChild_m

# Married-couple families with own child, 2017 (MOE)

pMarriedOwnChild_e

% Married-couple families with own child, 2017

pMarriedOwnChild_m

% Married-couple families with own child, 2017 (MOE)

MaleNoWife_e

# Male-headed families, no wife present, 2017

MaleNoWife_m

# Male-headed families, no wife present, 2017 (MOE)

pMaleNoWife_e

% Male-headed families, no wife present, 2017

pMaleNoWife_m

% Male-headed families, no wife present, 2017 (MOE)

MaleNoWifeOwnChild_e

# Male-headed families, no wife present with own child under 18 years, 2017

MaleNoWifeOwnChild_m

# Male-headed families, no wife present with own child under 18 years, 2017 (MOE)

pMaleNoWifeOwnChild_e

% Male-headed families, no wife present with own child under 18 years, 2017

pMaleNoWifeOwnChild_m

% Male-headed families, no wife present with own child under 18 years, 2017 (MOE)

FemaleNoHusband_e

# Female-headed families, no husband present, 2017

FemaleNoHusband_m

# Female-headed families, no husband present, 2017 (MOE)

pFemaleNoHusband_e

% Female-headed families, no husband present, 2017

pFemaleNoHusband_m

% Female-headed families, no husband present, 2017 (MOE)

FemaleNoHusbOwnChild_e

# Female-headed families, no husband present with own child under 18 years, 2017

FemaleNoHusbOwnChild_m

# Female-headed families, no husband present with own child under 18 years, 2017 (MOE)

pFemaleNoHusbOwnChild_e

% Female-headed families, no husband present with own child under 18 years, 2017

pFemaleNoHusbOwnChild_m

% Female-headed families, no husband present with own child under 18 years, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

The difference between mean Egyptian and mean American composite scores in each subtest of Bayley Scales.

Abstract

The Trinidad and Tobago DHS survey--a national-level self-weighting random sample survey--was funded by the United States Agency for International Development (US/AID) and executed by the Family Planning Association of Trinidad and Tobago (FPATT). Technical assisstance was provided by the Demographic and Health Surveys Program at the Institute for Resource Development (IRD), a subsidiary of Westinghouse located in Columbia, Maryland.

The sampling frame for the TTDHS was the Continuous Sample Survey of Population (CSSP), an ongoing survey conducted by the Central Statistical Office based on the 1980 Population and Housing Census.

The TTDHS used a household schedule to collect information on residents of selected households, and to identify women eligible for the individual questionnaire. The individual questionnaire was based on DHS's Model "A" Questionnaire for High Contraceptive Prevalence countries, which was modified for use in Trinidad and Tobago. It covered four main areas: (1) background information on the respondent, her partner and marital status, (2) fertility and fertility preferences, (3) contraception, and (4) the health of children.

The short term objective of the Trinidad and Tobago Demographic and Health Survey (TTDHS) is to collect and analyse data on the demographic characteristics of women in the reproductive years, and the health status of their young children. Policymakers and programme managers in public and private agencies will be able to utilize the data in designing and administering programmes.

The long term objective of the project is to enhance the ability of organisations involved in the TTDHS to undertake surveys of excellent technical quality.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1988 TTDHS is defined as the universe of all women age 15-49.

Kind of data

Sample survey data

Sampling procedure

The sample for the TTDHS was based on the Continuous Sample Survey of Population (CSSP), used by the Central Statistical Office since 1968, and redesigned on the basis of the 1980 Population and Housing Census. The country is divided into 14 domains of study, comprising a total of 1,638 enumeration districts (EDs). Results from the 1980 Census indicated that some EDs were too large (more than 300 households) and some too small (fewer than 30 households) to be appropriate primary sampling units (PSUs) for the TFDHS. Therefore, the largest units were further subdivided, and the smaller units combined with contiguous ones for the CSSP sample.

The CSSP sample is selected in two stages. In the first, PSUs are systematically selected, with probability proportional to size (size equals the number of households in the PSU). Following an operation to list all households in each selected PSU, individual households are selected, with probability of selection inversely proportional to the PSU's size.

The CSSP grand sample, which provides an overall sampling fraction of one household in forty (1/40) has been divided into 9 sub-samples, each with an overall sampling fraction of one in three-hundred sixty (1/360). Each CSSP survey round, conducted quarterly, uses three of the nine sub-samples, with an overall sampling fraction of one in one-hundred twenty (1/120).

The DHS sample was taken from the CSSP sample selected for the January-March 1987 quarter. The main objectives of the DHS sample were: - a self-weighting sample of households, - a sample take in each selected PSU of about 25 women aged 15-49, and - a total of 4,000 completed interviews with women aged 15-49.

To achieve this sample size, 5,000 households were selected. This figure assumes an average of one eligible woman per household, and 294,400 eligible women nationwide, giving an overall sampling fraction of one in sixty (1/60). It also allows for 10 percent non-response at both the household and the individual interview level, commensurate with CSO experience in similar recent surveys. In total, 178 PSUs were selected throughout Trinidad and Tobago.

Mode of data collection

Face-to-face

Research instrument

The individual questionnaire was based on DHS's Model "A" Questionnaire for High Contraceptive Prevalence countries, which was modified for use in Trinidad and Tobago. It covered four main areas: (1) background information on the respondent, her partner and marital status, (2) fertility and fertility preferences, (3) contraception, and (4) the health of children.

The DHS model "A" questionnaire was adapted for use in Trinidad and Tobago, and pretested during February 1987. Thirteen pretest interviewers were trained for two weeks by FPATI', CSO, and IRD staff, and carded out two days of interviews. The questionnaire was further modified based on pretest results and interviewer comments.

Cleaning operations

The data processing staff consisted of a chief editor, 3 data entry clerks, and a control clerk who logged in questionnaires when they reached the office. All data entry staff completed the main interviewer training, in addition to data processing instruction by IRD staff. Data entry, editing, and tabulations were performed on microcomputers using the Integrated System for Survey Analysis (ISSA) programme, developed by IRD. The system performed range, skip, and consistency checks upon data entry, so that relatively little machine or manual editing was required. The chief editor was responsible for supervising data entry, and for resolving inconsistencies in the questionnaires detected during secondary machine editing.

Response rate

4,122 households were successfully interviewed, out of the 4,799 selected for the sample. The household response rate was 94 percent. This represents households for which the interview was successfully completed out of 4,371 households for which an interview could have been conducted. This latter group includes households not interviewed due to the absence of a competent respondent, refusal, or the interviewer not finding the selected household. Among the 677 selected households which were not interviewed, 604 were missed because of contact difficulties: addresses not found, houses vacant, or those in which the occupants were not at home during repeated visits. Fewer than one percent of households refused to be interviewed.

The household questionnaires identified 4,196 women eligible for the individual questionnaire. This figure represents a yield of one eligible woman per household, which was the average expected. Questionnaires were completed for 3,806 women. The response rate at the individual level was 92 percent, which represents the proportion of interviews successfully completed out of the total number of women identified by the household schedule. The overall response rate, the product of response rates at the household and individual levels is 87 percent.

Contact was not made with 199 eligible women, either because the respondent was not at home during any of three visits by the interviewer, or was temporarily away from the household. Sixty-eight cases were missed due to "Other" reasons, and 83 women refused to be interviewed.

The response rates for the urban and rural areas were similar. In the urban areas, the overall response rate was 86 percent, compared with 88 percent for the rural areas.

Sampling error estimates

Sampling errors, on the other hand, can be evaluated statistically. The sample of women selected in the 'IIDHS is only one of many samples of the same size that could have been drawn from the population using the same design. Each sample would have yielded slightly different results from the sample actually selected. The variability observed among all possible samples constitutes sampling error, which can be estimated from survey results (though not measured exact/y).

Sampling error is usually measured in terms of the "standard error" (SE) of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic across all possible samples of equal size and design. The standard error can be used to calculate confidence intervals within which one can be reasonably sure the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples of identical size and design will fall within a range of plus or minus two times the standard error of that statistic.

If simple random sampling had been used to select women for the TTDHS, it would have been possible to use straightforward formulas for calculating sampling errors. However, the TTDHS sample design used two stages and clusters of households, and it was necessary to use more complex formulas. Therefore, the computer package CLUSTERS, developed for the World Fertility Survey, was used to compute sampling errors.

In addition to the standard errors, CLUSTERS computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design, and the standard error that would result if a simple random sample had been used. A DEFT value of 1 indicates that the sample design is as efficient as a simple random sample; a value greater than 1 indicates that the increase in the sampling error is due to the use of a more complex and less statistically efficient design.

Sampling errors are presented in Table B.1 of the Final Report for 35 variables considered to be of primary interest. Results are presented for the whole

The Head Start Family and Child Experiences Survey (FACES) has been a source of information on the Head Start program and the children and families it serves. The 2019 Head Start Family and Child Experiences Survey, or FACES 2019, is the seventh in a series of national studies of Head Start, with earlier studies conducted in 1997, 2000, 2003, 2006, 2009, and 2014. It includes nationally representative samples of Head Start programs and centers, classrooms, and children and their families during the 2019-2020 program year. Data from surveys of Head Start program and center directors and classroom teachers provide descriptive information about program policies and practices, classroom activities, and the background of Head Start staff. These data compromise the Classroom Study. A sample of these programs also provides data from parent surveys, teacher child reports, and direct child assessments as part of the Classroom + Child Outcomes Study. FACES 2019 is designed to help policymakers address current policy questions and to support programs and practitioners working with Head Start families. According to the study design, FACES would have assessed children's readiness for school, surveyed parents, and asked teachers to provide information on children in both fall 2019 and spring 2020. In response to the COVID-19 (for coronavirus disease 2019) pandemic, however, FACES 2019 cancelled the first piece--the in-person data collection of child assessments in spring 2020. In-person classroom observations as part of the Classroom Study were also cancelled in spring 2020. FACES is designed so that researchers can answer a wide range of research questions that are crucial for aiding program directors and policymakers. FACES 2019 data may be used to describe (1) the quality and characteristics of Head Start programs, teachers, and classrooms; (2) the changes or trends in the quality and characteristics of the classrooms, programs, and staff over time; (3) the school readiness skills and family characteristics of the children who participate in Head Start; (4) the factors or characteristics that predict differences in classroom quality; (5) the changes or trends in the children's outcomes and family characteristics over time; and (6) the factors or characteristics at multiple levels that predict differences in the children's outcomes. The study also supports research questions related to subgroups of interest, such as children with identified disabilities and children who are dual-language learners (DLLs), as well as policy issues that emerge during the study. The study addresses changes in children's outcomes and experiences as well as changes in the characteristics of Head Start classrooms over time and across the rounds of FACES. Some of the questions that are central to FACES include: What are the characteristics of Head Start programs, including structural characteristics and program policies and practices? What are the characteristics and observed quality of Head Start classrooms? What are the characteristics and qualifications of Head Start teachers and management staff? Are the characteristics of programs, classrooms, and staff changing over time? What are the demographic characteristics and home environments of children and families who participate in Head Start? Are family demographic characteristics and aspects of home environments changing over time? How do families make early care and education decisions? What are the experiences of families and children in Head Start? What are the average school readiness skills and developmental outcomes of the population of Head Start children in fall and spring of the Head Start year? What gains do children make during a year of Head Start? Are children's school readiness skills (average skills or average gains in skills) improving over time? Does classroom quality vary by characteristics of classrooms, teachers, or programs? What characteristics of programs, teachers, or classrooms are associated with aspects of classroom quality? Do the school readiness skills of children in fall and spring and their gains in skills vary by child, family, program, and classroom characteristics? What is the association between observed classroom quality and children's school readiness skills? Between child and family characteristics and children's school readiness skills? The User Guide provides d

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.