In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

In the fiscal year of 2019, 25.14 percent of all active-duty enlisted women were employed as administrators. A further 14.79 percent of active-duty women were employed in the medical field, as compared to 5.75 percent of men.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks such as military installations in the MTDB for locating special features and to help enumerators during field operations. In 2012, the Census Bureau obtained the inventory and boundaries of most military installations from the U.S. Department of Defense (DOD) for Air Force, Army, Marine, and Navy installations and from the U.S. Department of Homeland Security (DHS) for Coast Guard installations. The military installation boundaries in this release represent the updates the Census Bureau made in 2012 in collaboration with DoD.

In 2019-2020, around 11.3 percent of those who had served in the U.S. military reported being diagnosed with some form of cancer. This statistic shows the percentage of those who have served/not served in the U.S. military who reported being told by a health professional that they had some form of cancer in 2019-2020.

In 2019, ** percent of adults in the United States thought that American military involvement in World War II was completely justified. On the other hand, only ***** percent of U.S. adults thought that American involvement in the Vietnam War was completely justified.

There were 449,344 active duty U.S. Army members in 2023. This amount represents a slight decrease in comparison to the number recorded in the previous year. Overall, there were 1.27 million active duty U.S. Department of Defense members, including officers and enlisted personnel in 2023.

The Military Bases dataset is as of May 21, 2019, and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The dataset depicts the authoritative boundaries of the most commonly known Department of Defense (DoD) sites, installations, ranges, and training areas in the United States and Territories. These sites encompass land which is federally owned or otherwise managed. This dataset was created from source data provided by the four Military Service Component headquarters and was compiled by the Defense Installation Spatial Data Infrastructure (DISDI) Program within the Office of the Deputy Under Secretary of Defense for Installations and Environment, Business Enterprise Integration Directorate. Sites were selected from the 2010 Base Structure Report (BSR), a summary of the DoD Real Property Inventory. This list does not necessarily represent a comprehensive collection of all Department of Defense facilities, and only those in the fifty United States and US Territories were considered for inclusion. For inventory purposes, installations are comprised of sites, where a site is defined as a specific geographic location of federally owned or managed land and is assigned to military installation. DoD installations are commonly referred to as a base, camp, post, station, yard, center, homeport facility for any ship, or other activity under the jurisdiction, custody, control of the DoD.

Acknowlegement

Original Data

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Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see the 2020 Island Areas Censuses Technical Documentation..Due to operational changes for military installation enumeration, the 2020 Census of Guam data tables reporting housing, social, and economic characteristics do not include housing units or populations living on Guam's U.S. military installations in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about operational changes and the impacts on Guam's data products, see the 2020 Island Areas Censuses Technical Documentation..Due to COVID-19 restrictions impacting data collection for the 2020 Census of Guam, data users should consider the following when using Guam's data products: 1) Data tables reporting social and economic characteristics do not include the group quarters population in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about data collection limitations and the impacts on Guam's data products, see the 2020 Island Areas Censuses Technical Documentation. 2) Cells in data tables will display the letter "N" when those data are not statistically reliable. A list of the geographic areas and data tables that will not have data displayed due to data quality concerns can be found in the 2020 Island Areas Censuses Technical Documentation. 3) The Census Bureau advises that data users consider high allocation rates while using the 2020 Census of Guam's available characteristics data. Allocation rates -- a measure of item nonresponse -- are higher than past censuses. Final counts can be adversely impacted when an item's allocation rate is high, and bias can be introduced if the characteristics of the nonrespondents differ from those reported by respondents. Allocation rates for Guam's key population and housing characteristics can be found in the 2020 Island Areas Censuses Technical Documentation. .Explanation of Symbols: 1.An "-" means the statistic could not be computed because there were an insufficient number of observations. 2. An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.3. An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.4. An "N" means data are not displayed for the selected geographic area due to concerns with statistical reliability or an insufficient number of cases.5. An "(X)" means not applicable..Source: U.S. Census Bureau, 2020 Census, Guam.

The U.S. Army remains the largest branch of the American military, with 449,344 active duty personnel in 2023. While the Army leads in numbers, the newly established Space Force had just 8,879 active duty members, highlighting the evolving nature of modern warfare and the increasing importance of space-based capabilities. Confidence in military remains high Despite fluctuations in force size, public trust in the U.S. military remains strong. In 2024, 61 percent of Americans expressed a great deal or quite a lot of confidence in the armed forces, a slight increase from the previous year. While a slightly higher share of Republicans have shown more confidence in the military, trust in the institution remains high across party lines. Global commitments The United States continues to invest heavily in its military capabilities, with defense spending reaching 916.02 billion U.S. dollars in 2023. This substantial budget supports not only domestic defense needs but also enables the U.S. to respond to global crises, as evidenced by the over 40 billion euros in military aid provided to Ukraine following Russia's invasion. The high level of spending, which translates to about 2,220 U.S. dollars per capita.

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The military simulation and virtual training market is expected to grow at a CAGR of 5% during the forecast period. Cost-effective virtual training, drivers.2, and drivers.3 are some of the significant factors fueling military simulation and virtual training market growth.

Cost-effective virtual training

To estimate the market size of military simulation and virtual training market, Technavio has tracked the recent trends and developments in the industry. The market size has been developed in terms of value by considering the following factors Vendor sales: It excludes all freelance tutoring services and discounts and rebates Revenues: Taken in local currencies, if not available in US dollars, for each country and vendor and then converted to US dollars using the yearly average currency exchange rate of 2019, the base year. This implies that the figures reflect industry trends, not distorted by fluctuations in international exchange rates. Exclusions: The report does not consider the effect of inflation and price fluctuation over the forecast period Currency: Unless explicitly mentioned, all revenues are represented in US dollars The market sizing has been built and validated using multiple demand-side and supply-side approaches for a detailed understanding of the military simulation and virtual training market. The specific market sizing approaches used for evaluating the military simulation and virtual training market are: Top down: Validated the market based on the contribution of military simulation and virtual training to the overall global education market Bottom up: Validated the market on the basis of the revenue and/or volume or market share of key education services companies providing military simulation and virtual training Combination: Using a combination of more than one approach described above and integrating the results in the data model Within the above-mentioned market sizing models, analysts have made assumptions and estimates listed below: Total enrollment/demand Average price of product/course/solution/subscription fees New installations For this report, we have also used the following macro data in modeling the market size for 2019 Population GDP growth Government spending on education Disposable income Based on the above data models, Technavio has estimated the total value for global military simulation and virtual training market as $12,545.33 billion in 2019.

This dataset tracks annual american indian student percentage from 2019 to 2023 for New Orleans Military & Maritime Academy vs. Louisiana and New Orleans Military & Maritime Academy School District

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The military simulation and virtual training market is expected to grow at a CAGR of 5% during the forecast period. Cost-effective virtual training, drivers.2, and drivers.3 are some of the significant factors fueling military simulation and virtual training market growth.

Cost-effective virtual training

To estimate the market size of military simulation and virtual training market, Technavio has tracked the recent trends and developments in the industry. The market size has been developed in terms of value by considering the following factors Vendor sales: It excludes all freelance tutoring services and discounts and rebates Revenues: Taken in local currencies, if not available in US dollars, for each country and vendor and then converted to US dollars using the yearly average currency exchange rate of 2019, the base year. This implies that the figures reflect industry trends, not distorted by fluctuations in international exchange rates. Exclusions: The report does not consider the effect of inflation and price fluctuation over the forecast period Currency: Unless explicitly mentioned, all revenues are represented in US dollars The market sizing has been built and validated using multiple demand-side and supply-side approaches for a detailed understanding of the military simulation and virtual training market. The specific market sizing approaches used for evaluating the military simulation and virtual training market are: Top down: Validated the market based on the contribution of military simulation and virtual training to the overall global education market Bottom up: Validated the market on the basis of the revenue and/or volume or market share of key education services companies providing military simulation and virtual training Combination: Using a combination of more than one approach described above and integrating the results in the data model Within the above-mentioned market sizing models, analysts have made assumptions and estimates listed below: Total enrollment/demand Average price of product/course/solution/subscription fees New installations For this report, we have also used the following macro data in modeling the market size for 2019 Population GDP growth Government spending on education Disposable income Based on the above data models, Technavio has estimated the total value for global military simulation and virtual training market as $12,545.33 billion in 2019.

The Military Health and Well-Being Project (MHWBP) is an online survey study conducted through Qualtrics Panels. United States military veterans were recruited from various online survey sites from May 2020 through June 2020. The purpose of the study was to collect information regarding psychosocial antecedents of health and wellness, including military identity, self-stigma, daily stress, combat exposure, purpose and value, substance use, traumatic brain injury, moral injury, suicide risk, social integration and contribution, and six of eight Substance Abuse and Mental Health Services Administration (SAMHSA) dimensions of wellness (social, emotional, spiritual, intellectual, physical, and environmental components for this study). Participant demographics were also collected, including age, race, gender, marital status, region of residence, duration of military service, employment status, current occupation, income, and housing status. Respondents must have been 18 years of age, veterans of the United States military post-Vietnam era, and residing in the United States. Data collection was funded by the North Carolina State University 2019 Non-Laboratory Research Scholarship Program.

Socio-demographic of the working age adult population, FY 2018–2019.

Demographics of the pediatric population, FY 2018–2019.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Workers include members of the Armed Forces and civilians who were at work last week..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2018 and later years are based on the 2017 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2018) were recoded to the 2017 Census industry codes. We recommend using caution when comparing data coded using 2017 Census industry codes with data coded using Census industry codes prior to data year 2018. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..2019 ACS data products include updates to several categories of the existing means of transportation question. For more information, see: Change to Means of Transportation..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..Occupation titles and their 4-digit codes are based on the Standard Occupational Classification (SOC). The Census occupation codes for 2018 and later years are based on the 2018 revision of the SOC. To allow for the creation of the multiyear tables, occupation data in the multiyear files (prior to data year 2018) were recoded to the 2018 Census occupation codes. We recommend using caution when comparing data coded using 2018 Census occupation codes with data coded using Census occupation codes prior to data year 2018. For more information on the Census occupation code changes, please visit our website at https://www.census.gov/topics/employment /industry-occupation/guidance/code-lists.ht...

United States Imports of military weapons, other than revolvers, pistols from Myanmar was US$46.52 Thousand during 2019, according to the United Nations COMTRADE database on international trade. United States Imports of military weapons, other than revolvers, pistols from Myanmar - data, historical chart and statistics - was last updated on November of 2025.

Mali Imports of military weapons, other than revolvers, pistols from United States was US$1.15 Million during 2019, according to the United Nations COMTRADE database on international trade. Mali Imports of military weapons, other than revolvers, pistols from United States - data, historical chart and statistics - was last updated on November of 2025.

In 2023, around 21.3 percent of active duty officers in the United States Navy were women. Additionally, approximately 19.4 percent of officers in the Space Force were women.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.