In 2023, about 17.7 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22.8 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over. A rapidly aging population In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce. The future population It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

In 2022, the state with the highest median age of its population was Maine at 45.1 years. Utah had the lowest median age at 32.1 years. View the distribution of the U.S. population by ethnicity here.

Additional information on the aging population in the United States

High birth rates during the so-called baby boom years that followed World War II followed by lower fertility and morality rates have left the United States with a serious challenge in the 21st Century. However, the issue of an aging population is certainly not an issue unique to the United States. The age distribution of the global population shows that other parts of the world face a similar issue.

Within the United States, the uneven distribution of populations aged 65 years and over among states offers both major challenges and potential solutions. On the one hand, federal action over the issue may be contentious as other states are set to harbor the costs of elderly care in states such as California and Florida. That said, domestic migration from comparably younger states may help to fill gaps in the workforce left by retirees in others.

Nonetheless, aging population issues are set to gain further prominence in the political and economic decisions made by policymakers regardless of the eventual distribution of America’s elderly. Analysis of the financial concerns of Americans by age shows many young people still decades from retirement hold strong concern over their eventual financial position.

Population 65+ by selected living arrangements. Estimates from US Census Bureau - American Community Survey 5-Year Estimates, 2014-2018.

In 2023, there were ********* adults aged 65 and older living in California, the most out of all U.S. states, followed by Florida with over *** million adults aged 65 and older. Both California and Florida have some of the highest resident population figures in the United States.

In 2023, about 17.7 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22.8 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over. A rapidly aging population In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce. The future population It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

We document that government spending multipliers depend on the population age structure. Using the variation in military spending and birth rates across U.S. states, we show that the local fiscal multiplier is 1.5 and increases with the population share of young people, implying multipliers of 1.1-1.9 in the inter-quartile range. A parsimonious life-cycle open-economy New Keynesian model with credit market imperfections and age-specific differences in labor supply and demand explains 87% of the relationship between local multipliers and demographics. The model implies that the U.S. population aging between 1980 and 2015 caused a 38% drop in national government spending multipliers.

This statistic depicts the age distribution in the United States from 2014 to 2024. In 2024, about 17.32 percent of the U.S. population fell into the 0-14 year category, 64.75 percent into the 15-64 age group and 17.93 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a sheet that has 2 maps and an inset map. The first map shows proportion of total population in 65 to 74 and 75 plus age groups for each Census Division in 1986. An inset map shows the same information for the area from Windsor to Quebec. The second map of Canada shows proportion under 15 by Census Division. Population pyramids of age / sex distributions for 1961 and 1986 shown for each province, territory and for Canada.

We quantify the role of population aging in the structural transformation process. Household-level data from the U.S. show that the fraction of expenditures devoted to services increases with household age. We use a shift-share decomposition and a quantitative model to show that U.S. population aging accounted for about a fifth of the observed increase in the service share in consumption between 1982 and 2016. The contribution of population aging to the rise in the service share is about the same size as the contribution of real income growth, and about half as large as that of changes in relative prices.

People in different subgroups age at different rates. Surveys containing biomarkers can be used to assess these subgroup differences. We illustrate this using hand-grip strength to produce an easily interpretable, physical-based measure that allows us to compare characteristic-based ages across educational subgroups in the United States. Hand-grip strength has been shown to be a good predictor of future mortality and morbidity, and therefore a useful indicator of population aging. Data from the Health and Retirement Survey (HRS) were used. Two education subgroups were distinguished, those with less than a high school diploma and those with more education. Regressions on hand-grip strength were run for each sex and race using age and education, their interactions and other covariates as independent variables. Ages of identical mean hand-grip strength across education groups were compared for people in the age range 60 to 80. The hand-grip strength of 65 year old white males with less education was the equivalent to that of 69.6 (68.2, 70.9) year old white men with more education, indicating that the more educated men had aged more slowly. This is a constant characteristic age, as defined in the Sanderson and Scherbov article “The characteristics approach to the measurement of population aging” published 2013 in Population and Development Review. Sixty-five year old white females with less education had the same average hand-grip strength as 69.4 (68.2, 70.7) year old white women with more education. African-American women at ages 60 and 65 with more education also aged more slowly than their less educated counterparts. African American men with more education aged at about the same rate as those with less education. This paper expands the toolkit of those interested in population aging by showing how survey data can be used to measure the differential extent of aging across subpopulations.

About this dataset

Context

The dataset tabulates the data for the Baltimore County, MD population pyramid, which represents the Baltimore 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Baltimore County, MD, is 28.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Baltimore County, MD, is 27.7.
• Total dependency ratio for Baltimore County, MD is 55.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Baltimore County, MD is 3.6.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Baltimore County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Baltimore County for the selected age group is shown in the following column.
• Population (Female): The female population in the Baltimore County for the selected age group is shown in the following column.
• Total Population: The total population of the Baltimore County for the selected age group is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Baltimore County Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the New York County, NY population pyramid, which represents the New York 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for New York County, NY, is 17.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for New York County, NY, is 25.3.
• Total dependency ratio for New York County, NY is 42.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for New York County, NY is 4.0.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the New York County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the New York County for the selected age group is shown in the following column.
• Population (Female): The female population in the New York County for the selected age group is shown in the following column.
• Total Population: The total population of the New York County for the selected age group is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for New York County Population by Age. You can refer the same here

This is a special extract of the 2000 Census 5-Percent Public Use Microdata Samples (PUMS) created by the National Archive of Computerized Data on Aging (NACDA). The file combines the individual 5-percent state files for all 50 states, the District of Columbia, and Puerto Rico as released by the United States Census Bureau into a single analysis file. The file contains information on all households that contain at least one person aged 65 years or more in residence as of the 2000 Census enumeration. The file contains individual records on all persons aged 65 and older living in households as well as individual records for all other members residing in each of these households. Consequently, this file can be used to examine both the characteristics of the elderly in the United States as well as the characteristics of individuals who co-reside with persons aged 65 and older as of the year 2000. All household variables from the household-specific "Household record" of the 2000 PUMS are appended to the end of each individual level record. This file is not a special product of the Census Bureau and is not a resample of the PUMS data specific to the elderly population. While it is comparable to the 1990 release CENSUS OF POPULATION AND HOUSING, 1990: UNITED STATES: PUBLIC USE MICRODATA SAMPLE: 3-PERCENT ELDERLY SAMPLE (ICPSR 6219), the sampling procedures and weights for the 2000 file reflect the methodology that applies to the 5-percent PUMS release CENSUS OF POPULATION AND HOUSING, 2000 UNITED STATES: PUBLIC USE MICRODATA SAMPLE: 5-PERCENT SAMPLE (ICPSR 13568). Person variables cover age, sex, relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, military service, mobility and personal care limitation, work limitation status, employment status, occupation, industry, class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absence from work, place of work, time of departure for work, travel time to work, means of transportation to work, total earnings, total income, wages and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividends, and net rental income. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage facilities, type of water source, type of heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, household language, number of persons in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage and property tax, condominium fees, mobile home costs, and cost of electricity, water, heating fuel, and flood/fire/hazard insurance. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR04204.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Age dependency ratio (% of working-age population) in United States was reported at 54.45 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Age dependency ratio (% of working-age population) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

The aging of the US population undoubtedly will be associated with macroeconomic changes. In particular, some combination of lower consumption growth and increased labor input will ultimately be required. But, the timing of these changes can have important effects on variables like the rate of return to capital and wages. If the adjustment to consumption is slow, which would be the case if budget deficits were allowed to rise significantly as the population ages, then aging is likely to be associated with an increase in the return to capital and a reduction in wages.

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

About this dataset

Context

The dataset tabulates the data for the Gulf Shores, AL population pyramid, which represents the Gulf Shores 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Gulf Shores, AL, is 13.8.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Gulf Shores, AL, is 40.0.
• Total dependency ratio for Gulf Shores, AL is 53.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Gulf Shores, AL is 2.5.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Gulf Shores population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Gulf Shores for the selected age group is shown in the following column.
• Population (Female): The female population in the Gulf Shores for the selected age group is shown in the following column.
• Total Population: The total population of the Gulf Shores for the selected age group is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Gulf Shores Population by Age. You can refer the same here

Graph and download economic data for Age Dependency Ratio: Older Dependents to Working-Age Population for the United States (SPPOPDPNDOLUSA) from 1960 to 2024 about 64 years +, working-age, ratio, population, and USA.

The number of Americans aged 65 and over with Alzheimer's disease is projected to more than double by 2060, reaching 13.8 million. This significant increase highlights the growing challenge of caring for an aging population, particularly those affected by dementia. As the prevalence of Alzheimer's rises, it will have far-reaching impacts on healthcare, families, and society as a whole. Aging population trends The surge in Alzheimer's cases is closely tied to broader demographic shifts in the United States. By 2050, it's estimated that 22 percent of the American population will be 65 years or older, up from 17.3 percent in 2022. This rapid aging of the population is expected to strain healthcare systems and change the nature of work and retirement. Challenges of aging in place As the number of older adults with Alzheimer's increases, there is a growing desire among seniors to age in their own homes. A 2024 survey found that three-quarters of adults aged 50 and older strongly or somewhat agreed they would like to remain in their current residence for as long as possible. This preference is even stronger among those 65 and older, with 80 percent expressing this desire. However, the ability to age in place may be compromised by declining physical capabilities, as only about one in five adults aged 72 and older reported being fully able to perform self-care and mobility activities in 2021.

In all OECD countries, populations aged 65 years and over have dramatically increased over the last 30 years, both in size and as a percentage of total population. As elderly people tend to be concentrated in few areas within each country, a small number of regions will have to face the social and economic challenges raised by aging population Share of National Elderly Population in the 10% Regions with the largest Elderly Population - 2004 or latest year available