In 2022, approximately ***** million young people between the ages of 15 to 19 years old lived in the United States. This was a slight increase from the previous year, when ***** million young people aged 15 to 19 lived in the U.S.
In 2022, around 20.3 percent of teenagers between ages 16 and 19 were employees while enrolled at school in the United States. This is an increase from the previous year, when 19.4 percent of teenagers were working while in school.
This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year.
DEFINITIONS
Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate. Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state. Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model.
NOTES
Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5).
Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used.
Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4).
The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that 1-α≤P({C│y})=∫p{θ │y}dθ, where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6).
County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7).
This statistic shows the development of the number of young people between the ages of 14 to 24 in the United States from 2000 to 2010. In 2010, approximately 47 million young people from that age group lived in the U.S.
According to a 2023 survey, 97 percent of teenagers in the United States between 15 and 17 years had smartphone access at home. The percentage of younger respondents owning a smartphone was lower, 92 percent. Overall, 94 percent of the surveyed teens stated owning a smartphone device.
As of October 2023, Facebook usage by teens aged 15 to 17 years in the United States was ** percent. Social network usage was slightly lower among the younger age group. According to the survey, ** percent of U.S. teens used Facebook overall.
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United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population data was reported at 15.630 % in 2012. This records a decrease from the previous number of 16.200 % for 2011. United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population data is updated yearly, averaging 16.590 % from Dec 2009 (Median) to 2012, with 4 observations. The data reached an all-time high of 17.330 % in 2010 and a record low of 15.630 % in 2012. United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population 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: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;
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United States US: Adolescents Out of School: % of Lower Secondary School Age data was reported at 0.949 % in 2015. This records a decrease from the previous number of 1.855 % for 2014. United States US: Adolescents Out of School: % of Lower Secondary School Age data is updated yearly, averaging 0.949 % from Dec 1987 (Median) to 2015, with 11 observations. The data reached an all-time high of 6.755 % in 1987 and a record low of 0.010 % in 1994. United States US: Adolescents Out of School: % of Lower Secondary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).
This dataset includes teen birth rates for females by age group, race, and Hispanic origin in the United States since 1960. Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison. National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf). SOURCES NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.
A 2023 survey found that half of the teenagers in the United States between 15 and 17 years used the internet almost constantly. The share of teens between 13 and 14 years going online frequently was lower, 40 percent. Overall, 46 percent of U.S. teens surveyed said they used the internet almost continuously.
In 1990, there were around *** teen pregnancies among teens aged 18 to 19 years per 1,000 women in the United States. This rate had decreased to about ** per 1,000 by the year 2020. This statistic depicts the U.S. pregnancy rate among teenagers from 1973 to 2020, by age group.
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Teenagers are the 2nd largest group of people affected by social media addiction. Teens ages 13 to 18 years old spend a significant amount of their free time on social media with an average of 3 hours a day.
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The average for 2021 based on 12 countries was 98.27 percent. The highest value was in Costa Rica: 99.53 percent and the lowest value was in Puerto Rico: 92.4 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.
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Context
The dataset tabulates the data for the Fayette County, AL population pyramid, which represents the Fayette County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Fayette County Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the Cranbury Township, New Jersey population pyramid, which represents the Cranbury township population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Cranbury township Population by Age. You can refer the same here
description:
This data set contains mean teen birth rates by year for each county and state in the United States.
Hierarchical Bayesian space-time models were used to generate hierarchical Bayes estimates of county teen birth rates for each year during 2003 2015. These annual county-level estimates borrow strength across counties and years to generate stable estimates of teen birth rates where data are sparse due to small population size. The population estimates were extracted from the files containing inter-censal and post-censal bridged race population estimates provided by the National Center for Health Statistics. For each year, the July population estimates were used with the exception of the year of the decennial census, 2010, for which the April estimates were used.
; abstract:This data set contains mean teen birth rates by year for each county and state in the United States.
Hierarchical Bayesian space-time models were used to generate hierarchical Bayes estimates of county teen birth rates for each year during 2003 2015. These annual county-level estimates borrow strength across counties and years to generate stable estimates of teen birth rates where data are sparse due to small population size. The population estimates were extracted from the files containing inter-censal and post-censal bridged race population estimates provided by the National Center for Health Statistics. For each year, the July population estimates were used with the exception of the year of the decennial census, 2010, for which the April estimates were used.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Gen Z and Millennials are the biggest social media users of all age groups.
As of April 2024, 55 percent of older teenagers aged between 15 and 18 years in the United States reported to use generative artificial intelligence (AI) for school assignments. Homework help was also the top motivating factor for younger U.S. teens aged 13 and 14 years to use gen AI tools, as 49 percent of them reported doing so. Approximately 20 percent of all U.S. teens reported having used generative AI to create content as a joke, or to tease another person.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the Petersburg, AK population pyramid, which represents the Petersburg population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Petersburg Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data was reported at 1.159 % in 2014. This records an increase from the previous number of 1.100 % for 2013. United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data is updated yearly, averaging 1.159 % from Dec 1987 (Median) to 2014, with 7 observations. The data reached an all-time high of 5.578 % in 1987 and a record low of 0.421 % in 1993. United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).
In 2022, approximately ***** million young people between the ages of 15 to 19 years old lived in the United States. This was a slight increase from the previous year, when ***** million young people aged 15 to 19 lived in the U.S.