2010-2018. US Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. Median age is calculated based on single year of age. For population estimates methodology statements, see http://www.census.gov/popest/methodology/index.html.

United States US: Population: as % of Total: Aged 15-64 data was reported at 65.674 % in 2017. This records a decrease from the previous number of 65.940 % for 2016. United States US: Population: as % of Total: Aged 15-64 data is updated yearly, averaging 65.683 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 66.916 % in 2009 and a record low of 59.988 % in 1962. United States US: Population: as % of Total: Aged 15-64 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: Population and Urbanization Statistics. Total population between the ages 15 to 64 as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

United States US: Population: Total: Aged 0-14 data was reported at 61,603,617.000 Person in 2017. This records an increase from the previous number of 61,538,430.000 Person for 2016. United States US: Population: Total: Aged 0-14 data is updated yearly, averaging 57,943,651.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 62,401,154.000 Person in 2010 and a record low of 51,201,638.000 Person in 1983. United States US: Population: Total: Aged 0-14 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. Total population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum;

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

United States US: Population: as % of Total: Female: Aged 65 and Above data was reported at 16.925 % in 2017. This records an increase from the previous number of 16.550 % for 2016. United States US: Population: as % of Total: Female: Aged 65 and Above data is updated yearly, averaging 14.035 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 16.925 % in 2017 and a record low of 10.023 % in 1960. United States US: Population: as % of Total: Female: Aged 65 and Above 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. Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.5 degree grid resolution. This dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4) with the ISIMIP Histsoc gridded population data and the United Nations World Population Program (WPP) demographic modelling data. Demographic fractions are given for the time period covered by the UN WPP model (1950-2050) while demographic totals are given for the time period covered by the combination of GPWv4 and Histsoc (1950-2020) Method - demographic fractions Demographic breakdown of country population by grid cell is calculated by combining the GPWv4 demographic data given for 2010 with the yearly country breakdowns from the UN WPP. This combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP. This makes it possible to calculate exposure trends from 1980 to the present day. To combine the UN WPP demographics with the GPWv4 demographics, we calculate for each country the proportional change in fraction of demographic in each age band relative to 2010 as: (\delta_{year,\ country,age}^{\text{wpp}} = f_{year,\ country,age}^{\text{wpp}}/f_{2010,country,age}^{\text{wpp}}) Where: - (\delta_{year,\ country,age}^{\text{wpp}}) is the ratio of change in demographic for a given age and and country from the UN WPP dataset. - (f_{year,\ country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country, and year. - (f_{2010,country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country for the year 2020. The gridded demographic fraction is then calculated relative to the 2010 demographic data given by GPWv4. For each subset of cells corresponding to a given country c, the fraction of population in a given age band is calculated as: (f_{year,c,age}^{\text{gpw}} = \delta_{year,\ country,age}^{\text{wpp}}*f_{2010,c,\text{age}}^{\text{gpw}}) Where: - (f_{year,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for given year, for the grid cell c. - (f_{2010,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for 2010, for the grid cell c. The matching between grid cells and country codes is performed using the GPWv4 gridded country code lookup data and country name lookup table. The final dataset is assembled by combining the cells from all countries into a single gridded time series. This time series covers the whole period from 1950-2050, corresponding to the data available in the UN WPP model. Method - demographic totals Total population data from 1950 to 1999 is drawn from ISIMIP Histsoc, while data from 2000-2020 is drawn from GPWv4. These two gridded time series are simply joined at the cut-over date to give a single dataset covering 1950-2020. The total population per age band per cell is calculated by multiplying the population fractions by the population totals per grid cell. Note that as the total population data only covers until 2020, the time span covered by the demographic population totals data is 1950-2020 (not 1950-2050). Disclaimer This dataset is a hybrid of different datasets with independent methodologies. No guarantees are made about the spatial or temporal consistency across dataset boundaries. The dataset may contain outlier points (e.g single cells with demographic fractions >1). This dataset is produced on a 'best effort' basis and has been found to be broadly consistent with other approaches, but may contain inconsistencies which not been identified. {"references": ["UN. (2019). World Population Prospects 2019: Data Booklet. Retrieved from https://population.un.org/wpp/Publications/Files/WPP2019_DataBooklet.pdf", "NASA SEDAC, & CIESIN. (2016). Gridded Population of the World, Version 4 (GPWv4): Population Count. New York, New York, USA: Columbia University. Retrieved from http://dx.doi.org/10.7927/H4X63JVC", "ISIMIP. (2018). ISIMIP Project Design and Simulation Protocol. Retrieved from https://www.isimip.org/gettingstarted/input-data-bias-correction/details/31/"]}

"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."

The demographic indicators of the People’s Republic of China, Hong Kong, Macao, and Taiwan were compiled from (1) the World Bank United Nations (UN) Population Division, World Population Prospects: 2022 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) UN Statistical Division. Population and Vital Statistics Report (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Program. The dataset consists of descriptive demographic statistics of the People’s Republic of China, Hong Kong, Macao, and Taiwan and includes the following indicators: (1) total population, (2) population by broad age groups, (3) annual rate of population change, (4) crude birth rate and crude death rate, (5) annual number of births and deaths, (6) total fertility, (7) mortality under age 5, (8) life expectancy at birth by sex, (9) life expectancy at birth (both sexes combined), (10) annual natural change and net migration, (11) population by age and sex: 2101, (12) annual number of deaths per 1,000 population, and (13) annual number of deaths.

United States US: Population: Male: Ages 50-54: % of Male Population data was reported at 6.741 % in 2017. This records a decrease from the previous number of 6.885 % for 2016. United States US: Population: Male: Ages 50-54: % of Male Population data is updated yearly, averaging 5.415 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.196 % in 2011 and a record low of 4.426 % in 1986. United States US: Population: Male: Ages 50-54: % 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 50 to 54 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.; ;

United States US: Population: as % of Total: Male: Aged 0-14 data was reported at 19.532 % in 2017. This records a decrease from the previous number of 19.657 % for 2016. United States US: Population: as % of Total: Male: Aged 0-14 data is updated yearly, averaging 22.879 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 31.757 % in 1961 and a record low of 19.532 % in 2017. United States US: Population: as % of Total: Male: Aged 0-14 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 0 to 14 as a percentage of the total male population. Population is based on the de facto definition of population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network CIESIN in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and sex and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem.

For further details, please, read the Release Statement.

Release content

1. KEN_population_v1_0_gridded.tif
2. KEN_population_v1_0_agesex.zip
3. KEN_population_v1_0_mastergrid.tif

Recommended citations

Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. Census disaggregated gridded population estimates for Kenya (2021), version 1.0 University of Southampton. doi:10.5258/SOTON/WP00747

License

These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information.

The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org.

WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex and region with uncertainty quantiles based on Poisson replication of death counts.

30-lt_input.csv

Life table input data.

• `id`: unique row identifier
• `region_iso`: iso3166-2 region codes
• `sex`: Male, Female, Total
• `year`: iso year
• `age_start`: start of age group
• `age_width`: width of age group, Inf for age_start 100, otherwise 1
• `nweeks_year`: number of weeks in that year, 52 or 53
• `death_total`: number of deaths by any cause
• `population_py`: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)
• `death_total_nweeksmiss`: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)
• `death_total_minnageraw`: the minimum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_maxnageraw`: the maximum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_minopenageraw`: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_maxopenageraw`: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_source`: source of the all-cause death data
• `population_midyear`: midyear population (July 1st)
• `population_source`: source of the population count/exposure data
• `death_covid`: number of deaths due to covid
• `death_covid_date`: number of deaths due to covid as of
• `death_covid_nageraw`: the number of age groups in the covid input data
• `ex_wpp_estimate`: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year
• `ex_hmd_estimate`: life expectancy estimates from the Human Mortality Database
• `nmx_hmd_estimate`: death rate estimates from the Human Mortality Database
• `nmx_cntfc`: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

• source:
  • STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)
  • ONS for GB-EAW pre 2020
  • CDC for US pre 2020
• STMF:
  • harmonized to single ages via pclm
  • pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110
  • smoothing parameters estimated via BIC grid search seperately for every pclm iteration
  • last age group set to [110,111)
  • ages 100:110+ are then summed into 100+ to be consistent with mid-year population information
  • deaths in unknown weeks are considered; deaths in unknown ages are not considered
• ONS:
  • data already in single ages
  • ages 100:105+ are summed into 100+ to be consistent with mid-year population information
  • PCLM smoothing applied to for consistency reasons
• CDC:
  • The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

• source:
  • for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019
  • for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100
• mid-year population
  • mid-year population translated into exposures:
    • if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates
    • if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364\*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

• source: COVerAGE-DB (https://osf.io/mpwjq/)
• the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

• source:
  • World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019
  • Human Mortality Database (https://mortality.org/), single year and age tables

United States US: Population: Female: Ages 60-64: % of Female Population data was reported at 6.224 % in 2017. This records an increase from the previous number of 6.143 % for 2016. United States US: Population: Female: Ages 60-64: % of Female Population data is updated yearly, averaging 4.552 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 6.224 % in 2017 and a record low of 3.843 % in 1997. United States US: Population: Female: Ages 60-64: % of Female 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. Female population between the ages 60 to 64 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

The 2005 Armenia Demographic and Health Survey (2005 ADHS) is the second in a series of nationally representative sample surveys designed to provide information on population and health issues in Armenia. As in the 2000 ADHS, the primary goal of the 2005 survey was to develop a single integrated set of demographic and health data pertaining to the population of the Republic of Armenia. In addition to integrating measures of reproductive, child, and adult health, another feature of the 2005 ADHS survey is that the majority of data are presented at the marz (region) level.The 2005 ADHS was conducted by the National Statistical Service (NSS) and the MOH of the Republic of Armenia from September through December 2005. ORC Macro provided technical support for the survey through the MEASURE DHS project. MEASURE DHS is a worldwide project, sponsored by the United States Agency for International Development (USAID), with a mandate to assist countries in obtaining information on key population and health indicators. USAID/Armenia provided funding for the survey, while the United Nations Children’s Fund (UNICEF)/Armenia and the United Nations Population Fund (UNFPA)/Armenia supported the survey through in-kind contributions.The 2005 ADHS collected national- and regional-level data on fertility and contraceptive use, maternal and child health, adult health, and HIV/AIDS and other sexually transmitted diseases. The survey obtained detailed information on these issues from women of reproductive age and, on certain topics, from men as well. Data are presented by marz wherever sample size permits.The 2005 ADHS results are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health of and health services for the people of Armenia. The 2005 ADHS also contributes to the growing international database on demographic and health-related variables.

The HoA Refugee Database, produced by the Humanitarian Information Unit of the U.S. Department of State, is a compilation of the UN High Commission of Refugees (UNHCR) population and demographic data reports for refugee camp populations in the Horn of Africa Region. Dadaab Camp in Kenya and Dollo Ado camp of Ethiopia are the focus; there are seven sites within Dadaab: Dagahaley Camp, Hagadera Camp, Ifo Camp, Ifo 2 East Camp, Ifo 2 West Camp, and Camp Kambioos, and five sites within Dollo Ado: Bokolmanyo Camp, Melkadida Camp, Kobe Camp, Hilaweyn Camp, and Buramino Camp.

The HoA Refugee Database originated in July of 2011 and the current release is through December 2011. The HoA Refugee Database includes several demographic variables of populations within the refugee camps, including: individual population, household counts, gender, age and nationality. Geographic location, in the form of latitude and longitude coordinates, are provided for each of the camps.

United States US: Population: Male: Ages 75-79: % of Male Population data was reported at 2.399 % in 2017. This records an increase from the previous number of 2.355 % for 2016. United States US: Population: Male: Ages 75-79: % of Male Population data is updated yearly, averaging 1.984 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.399 % in 2017 and a record low of 1.514 % in 1960. United States US: Population: Male: Ages 75-79: % 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 75 to 79 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.; ;

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

United States US: Population: Female: Ages 5-9: % of Female Population data was reported at 6.176 % in 2017. This records a decrease from the previous number of 6.267 % for 2016. United States US: Population: Female: Ages 5-9: % of Female Population data is updated yearly, averaging 7.009 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 10.134 % in 1964 and a record low of 6.176 % in 2017. United States US: Population: Female: Ages 5-9: % of Female 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. Female population between the ages 5 to 9 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

United States US: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 28.799 % in 2017. This records a decrease from the previous number of 28.857 % for 2016. United States US: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 33.422 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 51.329 % in 1961 and a record low of 28.799 % in 2017. United States US: Age Dependency Ratio: % of Working-Age Population: Young 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: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

United States US: Population: Total: Aged 15-64 data was reported at 213,911,387.000 Person in 2017. This records an increase from the previous number of 213,254,816.000 Person for 2016. United States US: Population: Total: Aged 15-64 data is updated yearly, averaging 161,786,825.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 213,911,387.000 Person in 2017 and a record low of 108,740,728.000 Person in 1960. United States US: Population: Total: Aged 15-64 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. Total population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum;