Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the United States population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.
Key observations
The largest age group in United States was for the group of age 30 to 34 years years with a population of 22.71 million (6.86%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in United States was the 80 to 84 years years with a population of 6.25 million (1.89%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 United States 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: Population: Male: Ages 80 and Above: % of Male Population data was reported at 2.993 % in 2017. This records an increase from the previous number of 2.928 % for 2016. United States US: Population: Male: Ages 80 and Above: % of Male Population data is updated yearly, averaging 1.869 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.993 % in 2017 and a record low of 1.142 % in 1960. United States US: Population: Male: Ages 80 and Above: % of Male 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: Population and Urbanization Statistics. Male population between the ages 80 and above as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Live Oak population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Live Oak. The dataset can be utilized to understand the population distribution of Live Oak by age. For example, using this dataset, we can identify the largest age group in Live Oak.
Key observations
The largest age group in Live Oak, FL was for the group of age 20 to 24 years years with a population of 782 (11.33%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Live Oak, FL was the 80 to 84 years years with a population of 89 (1.29%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
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 Live Oak Population by Age. You can refer the same here
This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).
Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.
There's a story behind every dataset and here's your opportunity to share yours.
This dataset collects characteristics of the population in each region (age distribution, unemployment rate, immigration percent and primary economic sector) and cross it with the votes per each political part.
It has 52 fields:
1) Code [String]: Region code of the different Spanish areas. There are 8126 different regions, but the dataset only contains 8119, because some sources were incomplete.
2) RegionName [String]: Name of the region.
3) Population [Int]: Amount of people living in that area (1st January 2015)
4) TotalCensus [Int]: Number of people over 18 years old, which means that can vote.
5) TotalVotes [Int]: Number of total votes.
6) AbstentionPtge [Float]: Percent of the people that have not votes in the election. (TotalCensus-TotalVotes)/TotalCensus*100 %
7) BlankVotesPtge [Float]: Percent of votes that were blank. Calculated as follows: BlankVotes/TotalVotes*100 %
8) NullVotesPtge [Float]: Percent of votes that were null. Calculated as follows: NullVotes/TotalVotes*100 %
9) PP_Ptge [Float]: Percent of the votes given to the political party called “Partido Popular”. (PP_Votes)/TotalVotes*100 %
10) PSOE_Ptge [Float]: Percent of the votes given to the political party called “Partido Socialista Obrero Español” (PSOE_Votes)/TotalVotes*100 %
11) Podemos_Ptge [Float]: Percent of the votes given to the political party called “Podemos” (Podemos_Votes)/TotalVotes*100 %
12) Ciudadanos_Ptge [Float]: Percent of the votes given to the political party called “Ciudadanos” (Ciudadanos_Votes)/TotalVotes*100 %
13) Others_Ptge [Float]: Percent of the votes given to the others political parties (∑▒MinoritaryVotes)/TotalVotes*100 %
14) Age_0-4_Ptge [Float]: Percent of the populations which age is between 0 and 4 years old. It is calculated as follows: (Number of people in (0-4))/TotalPopulation*100 %
15) Age_5-9_Ptge [Float]: Percent of the populations which age is between 5 and 9 year old.
16) Age_10-14_Ptge [Float]: Percent of the populations which age is between 10 and 14 years old
17) Age_15-19_Ptge [Float]: Percent of the populations which age is between 15 and 19 years old
18) Age_20-24_Ptge [Float]: Percent of the populations which age is between 20 and 24 years old
19) Age_25-29_Ptge [Float]: Percent of the populations which age is between 25 and 29 years old
20) Age_30-34_Ptge [Float]: Percent of the populations which age is between 30 and 34 years old
21) Age_35-39_Ptge [Float]: Percent of the populations which age is between 35 and 39 years old
22) Age_40-44_Ptge [Float]: Percent of the populations which age is between 40 and 44 years old
23) Age_45-49_Ptge [Float]: Percent of the populations which age is between 45 and 49 years old
24) Age_50-54_Ptge [Float]: Percent of the populations which age is between 50 and 54 years old
25) Age_55-59_Ptge [Float]: Percent of the populations which age is between 55 and 59 years old
26) Age_60-64_Ptge [Float]: Percent of the populations which age is between 60 and 64 years old
27) Age_65-69_Ptge [Float]: Percent of the populations which age is between 65 and 69 years old
28) Age_70-74_Ptge [Float]: Percent of the populations which age is between 70 and 74 years old
29) Age_75-79_Ptge [Float]: Percent of the populations which age is between 75 and 79 year old
30) Age_80-84_Ptge [Float]: Percent of the populations which age is between 80 and 84 years old
31) Age_85-89_Ptge [Float]: Percent of the populations which age is between 85 and 89 year old
32) Age_90-94_Ptge [Float]: Percent of the populations which age is between 90 and 94 years old
33) Age_95-99_Ptge [Float]: Percent of the populations which age is between 95 and 99 years old
34) Age_100+_Ptge [Float]: Percent of the populations which is older than 100 years old.
35) ManPopulationPtge [Float]: Percentage of masculine population in a region. Calculated as follows: ManPopulation/TotalPopulation*100
36) WomanPopulationPtge [Float]: Percentage of masculine population in a region. Calculated as follows: WomanPopulation/TotalPopulation*100
37) SpanishPtge [Float]: Percentage of people with spanish nationality in a region. Calculated as follows: NativeSpanishPopulation/TotalPopulation*100
38) ForeignersPtge [Float]: Percentage of foreign people in a region. Calculated as follows: ForeignPopulation/TotalPopulation*100
39) SameComAutonPtge [Float]: Percentage of people who live in the same autonomic community (same province) that was born. Calculated as follows: SameComAutonPopulation/TotalPopulation*100
40) SameComAutonDiffProvPtge [Float]: Percentage of people who live in the same autonomic community (different province) that was born. Calculated as follows: SameComAutonDiffProvPopulation/TotalPopulation*100
41) DifComAutonPtge [Float]: Percentage of people who live in different autonomic community that was born. Calculated as follows: SameComAutonDiffProvPopulation/TotalPopulation*100
42) UnemployLess25_Ptge [Float]: Percent of unemployed people that are under 25 years and older than 18. It is calculated over the total amount of unemployment. (UnemploymentLess25_Man+ UnemploymentLess25_Woman)/TotalUnemployment*100
43) Unemploy25_40_Ptge [Float]: Percent of unemployed people that are 25-40 years over the total amount of unemployment. (Unemployment(25-40)_Man+ Unemployment(25-40)_Woman )/TotalUnemployment*100
44) UnemployMore40_Ptge [Float]: Percent of unemployed people that are older that 40 and younger than 69 years over the total amount of unemployment. (Unemployment(40-69)_Man+Unemployment(40-69)_Woman)/TotalUnemployment*100
45) UnemployLess25_population_Ptge [Float]: Percent of unemployed people younger than 25 and older than 18, over the total population of the region. Note that the percent is calculated over the total population and not over the total active population. (UnemploymentLess25_Man+ UnemploymentLess25_Woman)/TotalPopulation*100
46) Unemploy25_40_population_Ptge [Float]: Percent of unemployed people (25-40) years old, over the total population of the region. Note that the percent is calculated over the total population and not over the total active population. (Unemployment(25-40)_Man+ Unemployment(25-40)_Woman )/TotalPopulation*100
47) UnemployMore40_population_Ptge [Float]: Percent of unemployed people (40-69) years old, over the total population of the region. Note that the percent is calculated over the total population and not over the total active population. (UnemploymentLess25_Man+ UnemploymentLess25_Woman)/TotalPopulation*100
48) AgricultureUnemploymentPtge [Float]: Percent of unemployment in the agriculture sector relative to the total amount of unemployment. PeopleUnemployedInAgriculture/TotalUnemployment*100
49) IndustryUnemploymentPtge [Float]: Percent of unemployment in the industry sector relative to the total amount of unemployment. PeopleUnemployedInIndustry/TotalUnemployment*100
50) ConstructionUnemploymentPtge [Float]: Percent of unemployment in the construction sector relative to the total amount of unemployment. PeopleUnemployedInConstruction/TotalUnemployment*100
51) ServicesUnemploymentPtge [Float]: Percent of unemployment in the services sector relative to the total amount of unemployment. PeopleUnemployedInServices/TotalUnemployment*100
52) NotJobBeforeUnemploymentPtge [Float]: Percent of unemployment of people that didn’t have an employ before, over the total amount of unemployment. PeopleUnemployedWithoutEmployBefore/TotalUnemployment*100
References:
[1] Unemployment: www.datos.gob.es/es/catalogo/e00142804-paro-registrado-por-municipios
[2] Age distribution per region Relation between Spanish and foreigners Relation between woman and man Relation between people born in the same area or different areas of Spain http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&file=pcaxis&path=%2Ft20%2Fe245%2Fp05%2F%2Fa2015
[3] Congress elections result of Spanish election (June 2016) http://www.infoelectoral.interior.es/min/areaDescarga.html?method=inicio
Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Annual data on death registrations by single year of age for the UK (1974 onwards) and England and Wales (1963 onwards).
Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis. The data provided here show the counts of the population in nursing homes and/or residences for senior citizens by broad age groups (0 to 79 years and 80 years and over) and sex, from the 2016 Census. Nursing homes and/or residences for senior citizens are facilities for elderly residents that provide accommodations with health care services or personal support or assisted living care. Health care services include professional health monitoring and skilled nursing care and supervision 24 hours a day, 7 days a week, for people who are not independent in most activities of daily living. Support or assisted living care services include meals, housekeeping, laundry, medication supervision, assistance in bathing or dressing, etc., for people who are independent in most activities of daily living. Included are nursing homes, residences for senior citizens, and facilities that are a mix of both a nursing home and a residence for senior citizens. Excluded are facilities licensed as hospitals, and facilities that do not provide any services (which are considered private dwellings).
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWMhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWM
This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.
As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.
Teens and social media
As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.
As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.
As of April 2024, Bahrain was the country with the highest Instagram audience reach with 95.6 percent. Kazakhstan also had a high Instagram audience penetration rate, with 90.8 percent of the population using the social network. In the United Arab Emirates, Turkey, and Brunei, the photo-sharing platform was used by more than 85 percent of each country's population.
As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.
Instagram’s Global Audience
As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
Who is winning over the generations?
Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.
As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.
The population share with mobile internet access in North America was forecast to increase between 2024 and 2029 by in total 2.9 percentage points. This overall increase does not happen continuously, notably not in 2028 and 2029. The mobile internet penetration is estimated to amount to 84.21 percent in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the population share with mobile internet access in countries like Caribbean and Europe.
The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Australia & Oceania and Asia.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the New Hope population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for New Hope. The dataset can be utilized to understand the population distribution of New Hope by age. For example, using this dataset, we can identify the largest age group in New Hope.
Key observations
The largest age group in New Hope, AL was for the group of age 10 to 14 years years with a population of 352 (12.16%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in New Hope, AL was the 75 to 79 years years with a population of 19 (0.66%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
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 New Hope 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 United States population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.
Key observations
The largest age group in United States was for the group of age 30 to 34 years years with a population of 22.71 million (6.86%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in United States was the 80 to 84 years years with a population of 6.25 million (1.89%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 United States Population by Age. You can refer the same here