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.

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.

In 2023, there were around 1.11 million active duty U.S. Armed Forces personnel stationed within the United States. In that year, there were 156,418 U.S. Armed Forces personnel stationed in California, the most of any state.

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.

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.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

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.

United States US: Armed Forces Personnel: % of Total Labour Force data was reported at 0.828 % in 2016. This records a decrease from the previous number of 0.838 % for 2015. United States US: Armed Forces Personnel: % of Total Labour Force data is updated yearly, averaging 0.995 % from Sep 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 1.704 % in 1990 and a record low of 0.828 % in 2016. United States US: Armed Forces Personnel: % of Total Labour Force 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: Defense and Official Development Assistance. Armed forces personnel are active duty military personnel, including paramilitary forces if the training, organization, equipment, and control suggest they may be used to support or replace regular military forces. Labor force comprises all people who meet the International Labour Organization's definition of the economically active population.; ; International Institute for Strategic Studies, The Military Balance.; Weighted average; Data for some countries are based on partial or uncertain data or rough estimates.

This scatter chart displays female population (people) against military expenditure (% of GDP) in the Americas. The data is about regions.

In 2023, 42.14 percent of U.S. men aged 75 years and over were veterans - the highest share of any age group or gender. In comparison, less than one percent of women aged 75 and over were veterans at that time.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

Throughout the 19th century, the share of military personnel employed by the United States government was below 0.2 percent of the total population in most years. There were noticeable spikes in enlistments and conscriptions during the American Civil War (1861-65), the First World War (1917-18*), and Second World War (1941-45*), as well as smaller increases during the Mexican-American War (1946-48) and the Spanish-American War (1898), but figures were generally much lower than the post-WWII era.

Following the Second World War, the United States abandoned many of its isolationist positions as it sought to become the world's leading superpower. This involved stationing millions of troops in overseas bases during the Cold War, in strategically important locations such as West Germany, Japan, and Taiwan. Additionally, involvement in conflicts such as the Korean War (1950-1953) and Vietnam War (1964-1973*) kept military employment high, usually between 1-2 percent until the 1970s. Figures remained just below the one percent mark until the 1990s, when the end of the Cold War and the growing influence of technology in conventional warfare saw a decrease in demand for many traditional combat roles. Despite U.S. involvement in a number of overseas conflicts in the 21st century, military personnel represented less than 0.5 percent of the total population in most years between 2000 and 2016.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for 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, 2015-2019 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 2015-2019 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:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

Free trade has gradually shifted the burden of military service onto the American South. While trade shocks generally lead to local increases in US Army enlistment, there are two different regional dynamics that concentrate this effect in the South. First, trade-related job losses are disproportionately concentrated in this region, where manufacturing jobs grad- ually migrated during the second half of the 20th century. Second, the South’s “military tradition,” a relatively youthful population, and weak labor unions, combine to translate trade shocks into larger spikes in Army enlistment than the rest of the country. This paper uses county-level data from 1996-2010 to demonstrate the importance of meso-level, regional factors for understanding the location of trade shocks, as well as how communities adjust to such economic dislocations. We find that trade-related job losses account for roughly 7 percent of the South’s over-representation in the Army during our period of study.

At the end of the fiscal year of 2024, it is estimated that there will be 15 Generals serving the United States Army, and a total of 354,948 enlisted personnel. Military personnel The military departments in the United States are: the U.S. Army, the U.S. Navy, the U.S. Air Force, the U.S. Marine Corps, and the U.S. Coast Guards. The President of the United States is the military’s overall head and forms the military policy with the U.S. Department of Defense. The U.S. military is one of the largest militaries in term of number of personnel.

The largest branch of the United States Armed Forces is the United States Army. The United States Army is responsible for land-based military operations. The active duty U.S. Army personnel number has decreased from 2010 to 2021. In 2010, there were 561,979 active duty U.S. Army members, as compared to 482,416 in 2021.

The number of active duty U.S. Navy personnel has decreased slowly over the past 20 years. In 2021, there were 343,223 active duty Navy members in the United States Navy. The United States Navy personnel are enlisted sailors, commissioned officers, and midshipmen. Sailors have to take part in Personnel Qualification Standards, to prove that they have mastered skills.

The United States Air Force is the aerial warfare service branch of the United States. The active duty U.S. Air Force personnel numbers also decreased between 1995 and 2015, although has started to increase slightly since 2015. The number decreased again in 2021, when the Air Force had 328,888 personnel.

Extent to which informed and ideas about the USA. Contacts withAmericans and trips to the United States. Topics: Knowledge of English; knowledge and reading Americannewspapers, books and films; concepts of respondent about the Americanschool system, family life, way of life, press, radio and television,agriculture, the political, cultural, religious life, the socialproblems, social services, the relationship employer-employee, theeconomy, industry and technology; judgement on Americans and reasonsfor a possible change in attitude to Americans; position on theinternational policy of the USA; trips of respondent to the USA;evaluation of the influence of a trip to the USA on one´s own attitudeto the USA; personal contacts with travelers to America; contacts withAmericans since the end of the war; knowledge of experiences with theGerman-American exchange program; adjustment of prejudices throughcontact with an ´Exchangee´; evaluation of employment with Americanemployers; personal difficulties of respondent; listening to thebroadcast ´Voice of America´; trips to the America House. Demography: age (classified); sex; marital status; religiousdenomination; school education; occupation; employment; householdincome; party preference; party membership; state; refugee status;present and past offices held. Interviewer rating: social class and willingness of respondent tocooperate; number of contact attempts; city size.

The 2020 Census Redistricting Summary File contains several hundred data fields spread over six different file segments. To facilitate access to more popular variables, the Tennessee State Data Center compiled a “QuickStat” reports detailing population, race/ethnicity and housing information. These fields are combined with geographic fields from the 2020 TIGER/Line Shapefiles for use with mapping software.Field names, descriptions and types selected from the two sources are detailed below.

      Field Name
      Alias
      Data Type
      Length


      OBJECTID

      Object ID



      Shape

      Geometry



      STATEFP
      State FIPS code
      Text
      2


      PLACEFP
      Place FIPS code
      Text
      5


      PLACENS
      Place GNIS code
      Text
      8


      GEOID
      Geographic identifier
      Text
      7


      NAME
      Name
      Text
      100


      NAMELSAD
      Legal/statistical area description
      Text
      100


      LSAD
      Legal/statistical area description code
      Text
      2


      CLASSFP
      FIPS class code
      Text
      2


      PCICBSA
      Metropolitan or micropolitan statistical area principal city indicator
      Text
      1


      PCINECTA
      New England city and town area principal city indicator
      Text
      1


      MTFCC
      MAF/TIGER feature class code
      Text
      5


      FUNCSTAT
      Functional status
      Text
      1


      ALAND
      Land area
      Long



      AWATER
      Water area
      Long



      INTPTLAT
      Latitude of the internal point
      Text
      11


      INTPTLON
      Longitude of the internal point
      Text
      12


      SUMLEV
      Summary Level
      Text
      3


      LOGRECNO
      Logical Record Number
      Long



      P0010001
      Total population
      Long



      P0010002
      Population of one race
      Long



      P0010003
      White alone
      Long



      P0010004
      Black or African American alone
      Long



      P0010005
      American Indian and Alaska Native alone
      Long



      P0010006
      Asian alone
      Long



      P0010007
      Native Hawaiian and Other Pacific Islander alone
      Long



      P0010008
      Some Other Race alone
      Long



      P0010009
      Population of two or more races:
      Long



      P0020002
      Hispanic or Latino
      Long



      P0020003
      Not Hispanic or Latino:
      Long



      P0020004
      Population of one race (Not Hispanic or Latino)
      Long



      P0020005
      White alone (Not Hispanic or Latino)
      Long



      P0020006
      Black or African American alone (Not Hispanic or Latino)
      Long



      P0020007
      American Indian and Alaska Native alone (Not Hispanic or Latino)
      Long



      P0020008
      Asian alone (Not Hispanic or Latino)
      Long



      P0020009
      Native Hawaiian and Other Pacific Islander alone (Not Hispanic or Latino)
      Long



      P0020010
      Some Other Race alone (Not Hispanic or Latino)
      Long



      P0020011
      Population of two or more races (Not Hispanic or Latino)
      Long



      P0030001
      Total population 18 years and over
      Long



      H0010001
      Total housing units
      Long



      H0010002
      Occupied housing units
      Long



      H0010003
      Vacant housing units
      Long



      P0050001
      Total population in group quarters
      Long



      P0050002
      Institutionalized population
      Long



      P0050003
      Correctional facilities for adults
      Long



      P0050004
      Juvenile facilities
      Long



      P0050005
      Nursing facilities/Skilled-nursing facilities
      Long



      P0050006
      Other institutional facilities
      Long



      P0050007
      Noninstitutionalized population
      Long



      P0050008
      College/University student housing
      Long



      P0050009
      Military quarters
      Long



      P0050010
      Other noninstitutional facilities
      Double



      Shape_Length

      Double



      Shape_Area

      Double

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.

Abstract (en): This data collection supplies standard monthly labor force data and also provides supplemental data on work experience, income, noncash benefits, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 15 years old and older. Additional data are available concerning weeks worked and hours per week worked, reason not working full time, total income and income components, and residence on March 1, 1990. This file also contains data covering nine noncash income sources: food stamps, school lunch programs, employer-provided group health insurance plans, employer-provided pension plans, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Information on demographic characteristics, such as age, sex, race, household relationship, and Spanish origin, are available for each person in the household enumerated. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.. Civilian noninstitutional population of the United States living in housing units and male members of the Armed Forces living in civilian housing units on military bases or in households not on military bases. A national probability sample was used in selecting housing units. About 57,000 housing units were contacted with an additional sample of 2,500 Spanish households added to the March survey sample. The sample was located in 729 sample areas comprising 1,973 counties and independent cities with coverage in every state and in the District of Columbia. The 300,012 cases in this hierarchical file include household-level, family-level, and person-level records. There are approximately 120 variables for the household records, approximately 65 variables for the family records, and approximately 350 variables for the person records. Data on employment and income refer to the preceding year, although demographic data refer to the time of the survey.

As of May 2025, China had the largest armed forces in the world by active duty military personnel, with about *********** active soldiers. India, the United States, North Korea, and Russia rounded out the top five largest armies. Difference between active and reserve personnel Active personnel, also known as active duty in the United States and active service in the United Kingdom, are those individuals whose full-time occupation is being part of a military force. Active duty contrasts with a military’s reserve force, which are individuals who have both a military role and a civilian career. The number of active duty forces in the U.S. is much larger than its reserve membership. What is the strongest army? The strength of a country’s armed forces is not only determined by how many personnel they maintain, but also the number and quality of their military equipment. For example, looking only at personnel does not factor in the overwhelmingly higher number of nuclear warheads owned by Russia and the United States compared to other countries. One way to answer this question is to look at the total amount of money each country spends on their military, as spending includes both personnel and technology. In terms of countries with the highest military spending, the United States leads the world with an annual budget almost ***** times larger than second-placed China.