The typical American picture of a family with 2.5 kids might not be as relevant as it once was: In 2023, there was an average of 1.94 children under 18 per family in the United States. This is a decrease from 2.33 children under 18 per family in 1960.

Familial structure in the United States

If there’s one thing the United States is known for, it’s diversity. Whether this is diversity in ethnicity, culture, or family structure, there is something for everyone in the U.S. Two-parent households in the U.S. are declining, and the number of families with no children are increasing. The number of families with children has stayed more or less constant since 2000.

Adoptions in the U.S.

Families in the U.S. don’t necessarily consist of parents and their own biological children. In 2021, around 35,940 children were adopted by married couples, and 13,307 children were adopted by single women.

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.

Percent of Children in Single-Parent Families is the percentage of children under age 18 who live with their own single parent, either in a family or subfamily. In this definition, single-parent families may include cohabiting couples and do not include children living with married stepparents. SOURCE: * U.S. Census Bureau, American Community Survey.

Percent of Children Living in Families Where No Parent Has Full-Time, Year-Round Employment is the share of all children under age 18 living in families where no parent has regular, full-time employment. For children living in single-parent families, this means that the resident parent did not work at least 35 hours per week, at least 50 weeks in the 12 months prior to the survey. For children living in married-couple families, this means that neither parent worked at least 35 hours per week, at least 50 weeks in the 12 months prior to the survey. Children living with neither parent also were listed as not having secure parental employment because those chil- dren are likely to be economically vulnerable. SOURCE: * U.S. Census Bureau, American Community Survey.

In 2023, women in households with an income below the poverty threshold had the highest birth rate in the United States, at 72 births per 1,000 women.

This dataset depicts the number of adopted children during the October 1, 2004 - September 30, 2005 time period. The numbers are categorized and broken down by state. The male and female figures are the percentage that each makes up of the total number of those adopted. This data was collected at: http://www.acf.hhs.gov/programs/cb/stats_research/afcars/statistics/gender_tbl1_2005.htm Access Date November 13, 2007.

Percent of Children in Poverty (income below $19,806 for a family of two adults and two children in 2005) is the percentage of children under age 18 who live in families with incomes below 100 percent of the U.S. poverty threshold, as defined by the U.S. Office of Management and Budget. The federal poverty definition consists of a series of thresholds based on family size and composition and is updated every year to account for inflation. In calendar year 2005, a family of two adults and two children fell in the poverty category if their annual income fell below $19,806. Poverty status is not determined for people living in group quarters, such as military barracks, prisons, and other institutional quarters, or for unrelated individuals under age 15 (such as foster children). The data are based on income received in the 12 months prior to the survey. SOURCE: * U.S. Census Bureau, American Community Survey.

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.

While the standard image of the nuclear family with two parents and 2.5 children has persisted in the American imagination, the number of births in the U.S. has steadily been decreasing since 1990, with about 3.6 million babies born in 2023. In 1990, this figure was 4.16 million. Birth and replacement rates A country’s birth rate is defined as the number of live births per 1,000 inhabitants, and it is this particularly important number that has been decreasing over the past few decades. The declining birth rate is not solely an American problem, with EU member states showing comparable rates to the U.S. Additionally, each country has what is called a “replacement rate.” The replacement rate is the rate of fertility needed to keep a population stable when compared with the death rate. In the U.S., the fertility rate needed to keep the population stable is around 2.1 children per woman, but this figure was at 1.67 in 2022. Falling birth rates Currently, there is much discussion as to what exactly is causing the birth rate to decrease in the United States. There seem to be several factors in play, including longer life expectancies, financial concerns (such as the economic crisis of 2008), and an increased focus on careers, all of which are causing people to wait longer to start a family. How international governments will handle falling populations remains to be seen, but what is clear is that the declining birth rate is a multifaceted problem without an easy solution.

This dataset explores what child care providers earn for 2005 and 2006. The BLS defines child care workers as those who attend to children at schools, businesses, private households, and child care institutions and perform a variety of tasks, such as dressing, feeding, bathing, and overseeing play. It is important to note that some family child care providers are excluded in the numbers because they are self-employed and report their income differently. The definition also excludes preschool teachers and teacher assistants. All data obtained from the 2005 and 2006 Occupational Employment Statistics Survey, Bureau of Labor Statistics, U. S. Department of Labor Compiled by the National Association of Child Care Resource and Referral Agencies.

Over the past 30 years, the birth rate in the United States has been steadily declining, and in 2023, there were 10.7 births per 1,000 of the population. In 1990, this figure stood at 16.7 births per 1,000 of the population. Demographics have an impact The average birth rate in the U.S. may be falling, but when broken down along ethnic and economic lines, a different picture is painted: Native Hawaiian and other Pacific Islander women saw the highest birth rate in 2022 among all ethnicities, and Asian women and white women both saw the lowest birth rate. Additionally, the higher the family income, the lower the birth rate; families making between 15,000 and 24,999 U.S. dollars annually had the highest birth rate of any income bracket in the States. Life expectancy at birth In addition to the declining birth rate in the U.S., the total life expectancy at birth has also reached its lowest value recently. Studies have shown that the life expectancy of both men and women in the United States has been declining over the last few years. Declines in life expectancy, like declines in birth rates, may indicate that there are social and economic factors negatively influencing the overall population health and well-being of the country.

This dataset displays data from the 2005 Census of Japan. It displays data on Private Households throughout prefectures in Japan. This dataset specifically deals with number of Private Households, Number of Private Household Members, and Average number of Members per Private Household. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.

Abstract

The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.

A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.

NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.

The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE

Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.

The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.

The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.

Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.

SAMPLE DESIGN

The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.

SAMPLE SELECTION IN RURAL AREAS

In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were

This dataset displays data from the 2005 Census of Japan. It displays data on Private Households throughout prefectures in Japan. This dataset specifically deals with number of Rented Households Issued Housing, Number of Rented Households Issued Housing Members, Average number of Members per Rented Households Issued Housing, Area of Floor Space per Household of Rented Households Issued Housing, and Area of Floor Space per Person of Rented Households Issued Housing. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.

This dataset displays data from the 2005 Census of Japan. It displays population by sex and households by type in the 47 prefectures in Japan. The data also breaks the data down by shi (cities) and gun(districts) within the prefecture. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.

This data explores the U.S. Department of Health and Human Services (DHHS) Administration for Children and Families Administration on Children, Youth and Families Children's Bureau Adoption of Children with Public Child Welfare Agency Involvement by State for Fiscal Years 1995 - 2006. For Fiscal Years 1995 - 1997, The data for FY 1995-FY 1997 were reported by States to set baselines for the Adoption Incentive Program. They came from a variety of sources including the Adoption and Foster Care Analysis and Reporting System (AFCARS), court records, file reviews and legacy information systems. For Fiscal Years 1998 - 2006, Unless otherwise noted, the data come from the AFCARS adoption database. Because AFCARS adoption data are being continuously updated and cleaned, the numbers reported here may differ from data reported elsewhere. In addition, data reported for the Adoption Incentive Program will differ from these data because adoptions reported for that program are identified through a different AFCARS data element and must qualify in other ways to be counted toward the award of incentive funds. Counts include adoptions reported as of 6/1/2005. Where appropriate, AFCARS data have been adjusted for duplication.

This dataset provides many demographic and social figures on topics such as health, education and family life for 2005. The data was accessed form the website for the National Institute of Statistics for Venezuela. The data are available yearly for the Federal Entities (states) of Venezuela. Values of -1 represent no data available.

This dataset is compiled from the Mexican Population and Household Census from 2005 (Conteo de Poblacion y Vivienda 2005). The data is at municipal level (of almost 2,000 municipalities) and is comprised of total population, population by age groups, population by sex, average age by sex and the male to female ratio. Where there were inconsistencies in municipality boundaries between the Mexican data and the available shapefile, the data have been combined in the appropriate fashion. The polygons that contain data from more than one municipality are labeled with all municipality names. Values of -1 represent no available data.

This dataset explores the time between tpr and finalization for fiscal year 2006 (from October 1, 2005 to September 30, 2006) from the Department of Health and Human Services - Administration for children and families - Children's Bureau.

This dataset displays data from the 2005 Census of Japan. It displays data on data on Institutional Households and Household Members throughout prefectures in Japan. This dataset specifically deals with Students in School Dormitories. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.