In 2022, the median age for the first wedding among women in the United States stood at 28.6 years. For men, the median age was 30.5 years. The median age of Americans at their first wedding has been steadily increasing for both men and women since 1998.

This statistic contains data on the estimated median age of Americans at their first wedding in the United States in 2021, by race and origin. In 2021, the median age for the first wedding among Asian women stood at 28.8 years.

Age at First Marriage in America

The Effect of Population Density

By Andy Kriebel [source]

About this dataset

This dataset contains information on the median age at first marriage for women in the United States. The data is broken down by county, and includes information on population density, FIPS code, and county type

How to use the dataset

This dataset contains information on the age at first marriage for women in the United States. The data is broken down by state, county, and year. To use this dataset, you can choose to either download the entire dataset or select specific states, counties, and years of interest. If you select specific states, counties, and years of interest, be sure to filter the data accordingly

Research Ideas

To find out which states have the oldest or youngest median ages at first marriage. To understand how population density may affect the median age at first marriage. To compare the median age at first marriage across different types of counties

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Median Age at First Marriage .csv | Column name | Description | |:---------------------------------|:---------------------------------------------------------------------------| | FIPS | The Federal Information Processing Standard code for each county. (String) | | Name | The name of the county. (String) | | Type | The type of county. (String) | | TimeFrame | The timeframe of the data. (String) | | Median Age | The median age at first marriage for women in the county. (Float) | | Population Density per Sq Mi | The population density of the county. (Float) |

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel.

81 percent of the Silent generation were married between the age of 23 and 38. This is true for only 44 percent of Millennials.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2012-2016 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2012-2016 American Community Survey 5-Year Estimates

Men and women in Japan are getting married increasingly later than previous generations. In 2024, the average age of women who married for the first time was about **** years, while men were on average **** years old when they first got married. Social integration of women The rising age at first marriage was partly explained by a common theory that holds the growing number of “parasite singles” accountable for the trend. The term refers to young working people aged between 28 and 40 years who decide to keep living comfortably in their parents' homes to save money. An alternative explanation is the more active participation of Japanese women in society. Increasingly more women in Japan obtain higher education degrees and focus on their career paths. With a rising income, they are financially less dependent, and marriage is no longer essential to afford the life they pursue. Delayed family planning The overall number of newly registered marriages has also declined in the past decade. The reported number of marriages was around ******* in 2024, representing the second consecutive year below *******. These developments concerning marriages have also impacted the mean age of childbearing, which has risen considerably since the *****.

United States Marriage Statistics

Marriage rates by gender, age group, and year in the United States (2005-2017)

By Throwback Thursday [source]

About this dataset

This dataset, titled United States Marriage Status 2005-2017, provides detailed information on marriage rates and population estimates in the United States. The data is sourced from the U.S. Census Bureau's American Community Survey 1-Year Estimates.

The dataset includes several key attributes that offer insights into different aspects of marriage status. These attributes include Year, Gender, Age Group, Metric, Estimated Percent, and Estimated Population.

The Year attribute represents the year in which the data was collected, spanning from 2005 to 2017. It allows for analysis of trends and changes in marriage rates over time.

The Gender attribute categorizes the population groups based on their gender. This information helps explore any variations or differences between male and female populations in terms of marital status.

Age Group attribute classifies individuals into specific age categories within the population. By segmenting the data based on age groups, it becomes possible to analyze how different age demographics contribute to overall marriage rates.

Metric serves as a descriptor for specific measurements or indicators being reported within this dataset. This attribute provides further context for understanding different aspects related to marriage status and its calculation methods.

Estimated Percent denotes the estimated percentage of a particular population group falling into a specific category related to marital status. It offers valuable insights into relative proportions within each demographic group.

Estimated Population showcases estimated count figures representing various subgroups' populations classified by gender, age groupings, and metric categories specified previously. These estimates allow researchers to explore potential correlations between population sizes and marriage rates across various segments of society over time period covered by this dataset.

Overall, this comprehensive United States Marriage Status dataset provides a valuable resource for analyzing trends in marriage rates while considering gender demographics, age distributions within these populations along with respective metrics indicating changes occurring over time periods marked since 2005 until 2017 (date-range excluding exact dates provided). By exploring relationships among these factors using reliable census data available through American Community Survey 1-Year Estimates, researchers can gain deep understanding of marriage status dynamics in the United States

How to use the dataset

• Understand the Columns:

  • Year: This column represents the year in which the data was collected. It provides a timeline for analyzing marriage trends over time.
  • Gender: This column categorizes individuals based on their gender, providing insights into marriage rates and patterns specific to each gender.
  • Age Group: This column categorizes individuals based on their age group. It allows for a detailed analysis of marriage rates and statistics among different age groups.
  • Metric: This column specifies the type of data or measurement being reported, providing clarity on what aspect of marriage is being analyzed.
  • Estimated Percent: This column represents the estimated percentage of individuals within a population group falling into a particular category. It quantifies marriage rates as percentages.
  • Estimated Population: This column provides an estimation of the total population count within a specific category, offering insights into the size and distribution of different population groups.

• Analyzing Trends: Use this dataset to analyze trends in US marriage statistics by leveraging various combinations of columns:

  • Gender vs Metric: Compare different metrics (e.g., number of marriages, divorce rate) between genders, allowing for an understanding of any gender-specific variations in marital trends.
  • Year vs Metric: Study changes in various metrics over time (e.g., changes in average age at first marriage), identifying trends and potential shifts in societal attitudes towards marriage.
  • Age Group vs Metric/Gender/Year: Examine how different age groups contribute to overall marital statistics (e.g., comparing divorce rates among different age groups or analyzing changes over time within specific age cohorts).

• Interpreting Results: When analyzing this dataset's results, keep these factors in mind:

  • Size Differences: Ensure you factor in the estimated population count for eac...

In 2022, there were 67.85 million married men and 68.45 million married women living in the United States. This is compared to 3.7 million widowed men and 11.48 million widowed women.

Marriage in the United States

Nevada had the highest marriage rate in the United States in 2021, followed by Hawaii and Montana. This can be attributed to marriage accessibility in the state. Las Vegas weddings are known for being quick, easy, and inexpensive chapel weddings. In comparison to the cheap weddings available in Las Vegas, the average expenditure for a wedding in the United States was the highest in New Jersey, clocking in at 51,000 U.S. dollars.

Same-sex marriage

The number of Americans who think that same-sex marriage should be recognized by law has more than doubled since 1996, while the number of Americans who think it should not be valid has decreased. It was not until June 26, 2015 that the United States Supreme Court legalized same-sex marriage in all 50 states. Before then, it was up to the states to decide if they allowed same-sex marriage. States in the Southeast are the most opposed to same-sex marriage, whereas the strongest support comes from Northern coastal states.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

This dataset provides valuable insights into the work and household characteristics of married individuals in the United States. With 753 observations representing individuals, the dataset offers a comprehensive view of various factors that influence work patterns and family dynamics.

Details

These data seem to have come from the same source as carData::Mroz, though each data set has variables not in the other. The variables that are shared have different names. On 2019-11-04 Bruno Rodrigues explained that Ecdat::Mroz['work'] had the two labels incorrectly swapped, and wooldridge::mroz['inlf'] was correct; wooldridge matches carData::Mroz['lfp'].

Source

Mroz, T. (1987) “The sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions”, Econometrica, 55, 765-799. 1976 Panel Study of Income Dynamics.

References

Greene, W.H. (2003) Econometric Analysis, Prentice Hall, https://archive.org/details/econometricanaly0000gree_f4x3, Table F4.1.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .ACS Technical Documentation..). The effect of nonsampling error is not represented in these tables..While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available....

The Wedding Services industry provides a wide variety of wedding day services, apparel retailers and venues. Evolving social norms and medical advancements, which enable women to safely give birth later in life, have caused the marriage rate to decline in recent decades. Extended periods of cohabitation before marriage and family planning have increasingly become normal among young couples. As a result, the industry has contended with declining revenue over the past five years. Despite fewer couples getting married, increasing per capita disposable income has enabled those seeking to spend more on their big day, limiting revenue declines. Nonetheless, as couples postponed or downsized their weddings during the COVID-19 pandemic, industry revenue dropped significantly in 2020 alone. Consequently, industry revenue fell at a CAGR of 4.1% to $70.3 billion over the past five years, including a decrease of 0.6% in 2023 alone.Despite rising wedding budgets, which translated to higher revenue, heightened competition has hindered revenue per operator. Over the past five years, the barriers to entry for operators in this industry have decreased as more couples can find vendors through the internet. Online marketing and social media have increased visibility for wedding services and lowered marketing budgets, making it easier for new companies to enter the industry. But, coronavirus-related pressures forced many of these new entrants out of the industry. Also, limited demand because of the declining marriage rate has led to lower revenue per operator somewhat deterring new entrants.Moving forward, industry demand will continue to be pressured by the marriage rate, which will further decline over the next five years. Even so, continued pent-up demand from previously postponed weddings will support industry revenue. During the outlook period, rising consumer confidence indicates that individuals will be more willing to take on nonessential expenditures and incur high wedding costs. Also, the increasing average age of marriage and the length of engagements will give couples more time to plan and save money for their ceremonies. Overall, industry revenue will rise at a CAGR of 0.2% to $71.1 billion over the next five years.

This study was in response to Grant Number HHS-2020-ACF-OZA-ZB-1817 from the Office of Family Assistance (OFA) within the Administration for Children and Families (ACF, U.S. Department of Health and Human Services (HHS). Study enrollment began on April 1, 2021, and continued through March 1, 2024. The sample size for the study was 1,403. The goal of the descriptive evaluation was to assess the extent to which participation in the program was associated with improved parenting, co-parenting, and financial attitudes and behaviors among program participants. The aim of the AVANCE-Houston FRAMEWorks program was to promote healthy family relationships and economic stability, particularly in areas with a high number of single-family households, high poverty rates, low educational attainment, and high incidences of domestic violence. We believe this report can inform practitioners in the HMRF field and beyond about innovative approaches that help adults from predominately low-income households build the skills necessary to engage in healthy relationships and economic behaviors. Primary research questions for this study are as follows: a) How did parenting attitude outcomes change from program enrollment to program completion? b) How did parenting behavior outcomes change from program enrollment to one year after enrollment? c) How did partner relationship attitude outcomes change from program enrollment to program completion? d) How did partner relationship behavior outcomes change from program enrollment to one year after enrollment? e) How did employment attitude outcomes change from program enrollment to one year after enrollment? f) How did financial readiness behavior outcomes change from program enrollment to one year after enrollment? Secondary research questions for this study are as follows: g) How did participant outcomes above change from program enrollment to program completion or one year after enrollment when delivering the SSHF curriculum with a virtual format compared to an in-person format? h) How did participant outcomes above change from program enrollment to program completion or one year after enrollment when delivering the SSHF curriculum in English-language compared to Spanish-language? Implementation study research questions are as follows: a) To what extent is the SSHF curriculum received by program participants? b) What were the unplanned adaptations to key intervention components? Participants in the study resided in the greater Houston, TX area. At 76%, the majority of AVANCE FRAMEWorks participants received the program virtually. The average age of participants was 40 years, and almost three-fourths reported that they were in a relationship. The average age of their youngest child was just above eight years of age. Most (75%) participants were female. The majority of participants (64%) indicated they were Hispanic, with exactly 50% reporting their race as White and 26% as Black or African American. About 44% of participants reported having full-time employment, and 35% reported being either unemployed or a stay-at-home parent/homemaker at the time of survey completion. Paired t-tests were conducted on continuous constructs using timepoint 1 (nFORM Entrance, OLLE Pre) and timepoint 2 (nFORM Exit, OLLE Post, OLLE Follow-Up) data. For categorical variables—such as yes/no questions about having a checking or savings account or a resume—McNemar’s chi-square tests were used to compare pre- to post-test differences in proportions. Statistical significance was set at p<0.05, and no adjustments for multiple comparisons were made. Tests were reported in terms of p-values. Results were significant and positive for participants’ partner relationships, financial readiness, and employment outlook. We did not find a significant association with the parenting attitudes outcome, measured from baseline to post-program, or parenting behaviors outcome, measured from baseline to one-year post-enrollment. When analyzing virtual and in-person subgroups, we found the same positive results in the group of participants who received the program virtually compared to the overall results. We also found similar results for participants who received the program in person; however, there was not a significant association with employment outlook. We found high rates of program retention, with 95% of participants reaching the required number of curriculum hours on average.

This dataset comes from a longitudinal study of a random sample of 232 coupled partners (464 individuals) in heterosexual, dating, romantic relationships. All participants were never-married, dating someone of the opposite sex, and between the ages of 19 to 35. Due to the random sample, the ethnicity and SES of the participants was reflective of the population of Austin, Texas, USA which was where the sample was drawn. The average age was approximately 23. The sample was 69% White, 7.5% African-American, 16.4% Hispanic or Latino, and 5.8% Asian or Pacific Islander. See attached demographic fact sheet for more information. We collected data once per month for nine months as well as a brief 5-year follow-up. During one of the phases, we also conducted a daily diary over 9 days. Data were collected with face-to-face interviews with each partner separately. Phase 1 was a 2-3 hour interview. Phase 2 consisted of interviews lasting 15-30 minutes once per month for seven months. Phase 3 was a 2-3 hour interview that replicated Phase 1. Phase 4 was 5-year follow-up on breakup, marriage, and cohabitation. The project also includes a full version of a commitment graphing procedure described in the referenced Ogolsky, Surra, and Monk, 2016 citation. The study was approved by the University of Illinois IRB #17875

This statistic shows the average income of married and unmarried men in the United States in 2016, by age. In that year, 45-year-old married men had an average income of **** thousand U.S. dollars, compared to 45-year-old unmarried men, who had an average income of **** thousand U.S. dollars.

The highest share of home buyers in the United States in 2024 across all age groups were married couples. Married couples made up at least ** percent of home buyers in all age groups that year, except for homebuyers aged between 18 and 25 years old.

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.

Niger has the highest child marriage rate in the world among girls. According to the most recent data, in this West African country, more than three-fourths of girls aged under 18 were married, with nearly 30 percent of them being younger than 15 years old. The Central African Republic, Chad, and Mali followed behind with rates ranging from 61 to 54 percent. This issue is globally spread, particularly in African countries. In many of these countries, the legal age to get married is lower for females than for males. In Niger and Chad, for instance, the legal age is 15 years for females and 18 for males. In Guinea, instead, the legal age for marriage is 17 for females and 18 for males. Child marriage is often related to poverty, with poor families choosing to marry away their girls, both to earn money as a wedding gift and as this means fewer mouths to feed.