Historical chart and dataset showing U.S. military size by year from 1985 to 2020.

Content

Lists the military spending, GDP, and population estimate for the US each year from 1960 to 2020.

Acknowledgements

Banner image source: https://unsplash.com/photos/BQgAYwERXhs

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.

The 2012 US Army Anthropometric Survey (ANSUR II) was executed by the Natick Soldier Research, Development and Engineering Center (NSRDEC) from October 2010 to April 2012 and is comprised of personnel representing the total US Army force to include the US Army Active Duty, Reserves, and National Guard. The data was made publicly available in 2017. In addition to the anthropometric and demographic data described below, the ANSUR II database also consists of 3D whole body, foot, and head scans of Soldier participants. These 3D data are not publicly available out of respect for the privacy of ANSUR II participants. The data from this survey are used for a wide range of equipment design, sizing, and tariffing applications within the military and has many potential commercial, industrial, and academic applications.These data have replaced ANSUR I as the most comprehensive publicly accessible dataset on body size and shape. The ANSUR II dataset includes 93 measurements from over 6,000 adult US military personnel, comprising 4,082 men (ANSUR_II_MALE_Public.csv) and 1,986 women (ANSUR_II_FEMALE_Public.csv).

The ANSUR II working databases contain 93 anthropometric measurements which were directly measured, and 15 demographic/administrative variables.

Much more information about the data collection methodology and content of the ANSUR II Working Databases may be found in the following Technical Reports, available from theDefense Technical Information Center (www.dtic.mil) through:

a. 2010-2012 Anthropometric Survey of U.S. Army Personnel: Methods and Summary
Statistics. (NATICK/TR-15/007)
b. Measurer’s Handbook: US Army and Marine Corps Anthropometric Surveys,
2010-2011 (NATICK/TR-11/017)

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

Context

According to The Oregonian hundreds of National Guard armories across the U.S. may have been contaminated with lead from indoor firing ranges. It was reported that areas populated by children under 7 years of age should have less than 40 micrograms of lead per square foot.

Content

The Oregonian collected over 23,000 pages of public records following a Freedom Of Information Act request. The dataset covers armory inspections conducted since 2012 and may facilitate investigation of lead contamination in the U.S.

Acknowledgements

The data assembly process is described by Melissa Lewis here.

Inspiration

This dataset can be used to conduct research in the realm of public health. It will be especially useful if 1) you know about health effects of exposure to lead in relatively short terms periods; 2) you are able to find relevant health data to conduct a study on lead poisoning.

The Defense Logistics Agency (DLA) has the Department of Defense mission of disposing of obsolete/unneeded excess property turned in by U.S. military units around the world. The type of property turned in ranges from military-specific equipment and vehicles to generic office furniture, computers, medical items and shop equipment. DLA Disposition Services, one of DLA’s major subordinate commands, disposes of this property in a variety of ways, including reutilization/transfer to other military components or federal agencies, donating through programs like computers for schools, destruction for scrap metal and resale to the general public.

In the National Defense Authorization Act for fiscal years 1990 and 1991, Congress authorized the transfer of excess DoD property to federal, state and local law enforcement agencies. Congress later passed the NDAA for fiscal year 1997, which allows law enforcement agencies to acquire property for bona fide law enforcement purposes – particularly those associated with counter-drug and counter-terrorism activities. The program has been named in the press and elsewhere as the “1033 Program,” which refers to the numbered section of the 1997 NDAA that granted permanent authority to the Secretary of Defense to transfer defense material to federal, state and local law enforcement agencies.

The Law Enforcement Support Office, located at DLA Disposition Services Headquarters in Battle Creek, Michigan, is responsible for the management of the LESO/1033 Program and continues to make improvements for efficiency, cost effectiveness, transparency and inventory control.

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

AbstractObjective: To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. Methods: A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. Results: The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. Conclusion: The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions. Usage notesPrev of MS in the US-E-Appendix-Feb-19-2018

Context

While attempting to create an interactive map of the Vietnam War, I compiled a list of the war time campaigns performed by the U.S. Military. Contains the operation name, the start and end date, also in which Province(s) in Vietnam where it occurred.

Content

Using a list provided by National Archives Catalogue, I referenced the Library of Congress records for the campaigns provided. I have no doubt that more operations need to be included to be a comprehensive list, but a start.

https://catalog.archives.gov/id/10643608 - original list http://id.loc.gov/authorities/subjects/sh85143280.html - As reference

Inspiration

I hope this sheds more light on to choices America has made and continue to make.

To evaluate the incidence, refractive error (RE) association, and distribution of atraumatic rhegmatogenous retinal detachment (RRD) in U.S. military service members (SMs). This study used data from the Military Health System (MHS) M2 database to identify active U.S. military and National Guard SMs diagnosed with RRD from 2017 to 2022. The RE in diopters (D) was manually extracted from available medical charts for 518 eyes. The annual incidence rate of RRD was calculated overall and evaluated in terms of age, gender, and RE. A multivariate Poisson regression model was used to estimate the relative risk (RR) for RRD with RE. From 2017 to 2022, 1,537 SMs were diagnosed with RRD and 1,243,189 were diagnosed with RE. One thousand two hundred seventy-five SMs had both diagnoses: RRD and RE. The overall incidence rate of RRD over the 6-year study was 16.3 per 100,000 people (16.4 and 15.9 for males and females, respectively). In all study groups, the incidence of RRD increased with age. SMs with RE had an overall 25-fold increased risk for RRD compared to SMs without RE. RE was present in 83.0% of cases of RRD. Myopia accounted for 93.3% of cases for eyes with detailed refractive data. The incidence of RRD in U.S. SMs is comparable to other studies and is similar among male and female SMs. RE is present in most cases of RRD in SMs, with the most common type being low to moderate amounts of myopia.

NOTE: As of 12/17/2024, this dataset is no longer updated. Please use ASPR Treatments Locator.

This dataset displays pharmacies, clinics, and other locations with safe and effective COVID-19 medications. These medications require a prescription from a healthcare provider. Some locations, known as Test to Treat sites, give you the option to get tested, get assessed by a healthcare provider, and receive treatment – all in one visit. COVID-19 medications may be available at additional locations that are not shown in this dataset.

The locations displayed have either self-attested they have inventory of Paxlovid (nirmatrelvir packaged with ritonavir), Lagevrio (molnupiravir), or Veklury (Remdesivir) within at least the last two months and/or reported participation in the Paxlovid Patient Assistance Program. Sites that have not reported in the last two weeks display a notification, "Inventory has not been reported in the last 2 weeks. Please contact the provider to make sure the product is available." Outpatient COVID-19 medications may be available at additional locations not listed on this website.

All therapeutics identified in the locator not approved by the FDA must be used in alignment with the terms of the respective product’s Emergency Use Authorization. Visit COVID-19 Treatments and Therapeutics for more information on all treatment options.

This website identifies sites that have commercially purchased inventory of COVID-19 treatments and, in some cases, may identify sites that have remaining, no-cost U.S. government distributed supply. Some sites may charge for services not covered by insurance. Some sites may offer telehealth services. This website is intended for informational purposes only and does not serve as an endorsement or recommendation for use of any of the locations listed on the sites.

Clarification for DoD Facilities: Those individuals eligible for care in an MTF include Active Duty Service Members (ADSMs), covered beneficiaries enrolled in TRICARE Prime or Select, including TRICARE Reserve Select (TRS), TRICARE Retired Reserve (TRR) and TRICARE Young Adult (TYA) participants, TRICARE for Life beneficiaries, and individuals otherwise entitled by law to MTF care (e.g., regular retired members and their dependents who are not enrolled in TRICARE but who are otherwise eligible for MTF space-available care, certain foreign military members and their families registered in DEERS, and others).

The USACE SACS Population and Infrastructure Exposure Index combines the normalized score of each Infrastructure and Population Index, and then re-normalizes these values across the study area.

The SACS Infrastructure Exposure Index was created by spatially joining 52 infrastructure datasets from DHS’s HIFLD database and Military Installation Ranges and Training Areas from the DOD OSD to census tracts across the study area. The infrastructure elements were assigned a weighting value consistent with the NACCS Tier 1 Methodology (URL). The weighted infrastructure element values were then aggregated by count within each census tract, and then divided by the census tract area to generate an infrastructure density value. This infrastructure density value was then enumerated and ranked across all census tracts, and normalized to 0 to 1 using these rankings. The census tract feature dataset was then converted to a grid using these normalized values for aggregation with other SACS datasets.

The SACS Population Exposure Index depicts the 2015 Census – American Community Survey data as population density. This population density is calculated as persons per square mile, per census tract. The census tracts depicted are within the USACE South Atlantic Coastal Study boundaries with an inland extent of NOAA’s Category 5 Maximum of Maximum Storm Surge Hazard Layer. The index ranks all census tracts within the SACS study area on a percentile index by population density. These data are represented on a normalized scale of 0 to 1, with 1 being the most densely populated census tract in the study area, and zero being the least densely populated census tract. The census tract feature dataset was then converted to a grid using these normalized values for aggregation with other SACS datasets.

References: DHS HIFLD https://gii.dhs.gov/hifld/

DOD OSD https://www.acq.osd.mil/dodsc/fast41_gisdatasets.html

US Census https://www.census.gov/

NACCS (appendix C, page 107) https://www.nad.usace.army.mil/Portals/40/docs/NACCS/NACCS_Appendix_C.pdfThis Tier 1 dataset is available for download here:Tier 1 Risk Assessment Download

Annual Population Estimates for the United States; States; Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Related Statistical Areas; Counties; and Subcounty Places; and for Puerto Rico and Its Municipios: April 1, 2010 to July 1, 2018 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through May. // Note: 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. // The Office of Management and Budget's statistical area delineations for metropolitan, micropolitan, and combined statistical areas, as well as metropolitan divisions, are those issued by that agency in July 2015. // The 2010 Census did not ascertain the military status of the household population. Therefore, variables for the 2010 Census civilian, civilian noninstitutionalized, and resident population plus Armed Forces overseas populations cannot be derived and are not available on this file. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., Vintage 2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

Abstract

The Freedom in the World 1972-2010 dataset, produced by a US based organisation, Freedom House, contains data on political rights and civil liberties for countries. Numerical ratings of between 1 and 7 are allocated to each country or territory, with 1 representing the most free and 7 the least free. The status designation of Free, Partly Free, or Not Free, which is determined by the combination of the political rights and civil liberties ratings, indicates the general state of freedom in a country or territory.

The total number of points awarded to the political rights and civil liberties checklists determines the political rights and civil liberties ratings for each country in the Freedom House dataset. Each point total corresponds to a rating of 1 through 7, with 1 representing the highest and 7 the lowest level of freedom. Each pair of political rights and civil liberties ratings is averaged to determine an overall status of "Free," "Partly Free," or "Not Free." Those whose ratings average 1.0 to 2.5 are considered Free, 3.0 to 5.0 Partly Free, and 5.5 to 7.0 Not Free . The designations of Free, Partly Free, and Not Free each cover a broad third of the available raw points. Therefore, countries and territories within any one category, especially those at either end of the category, can have quite different human rights situations. In order to see the distinctions within each category, a country or territory's political rights and civil liberties ratings should be examined. For example, countries at the lowest end of the Free category (2 in political rights and 3 in civil liberties, or 3 in political rights and 2 in civil liberties) differ from those at the upper end of the Free group (1 for both political rights and civil liberties). Also, a designation of Free does not mean that a country enjoys perfect freedom or lacks serious problems, only that it enjoys comparably more freedom than Partly Free or Not Free (or some other Free) countries.

General Characteristics of Each Political Rights and Civil Liberties Rating: Political Rights Rating of 1 -- Countries and territories that receive a rating of 1 for political rights come closest to ensuring the freedoms embodied in the checklist questions, beginning with free and fair elections. Those who are elected rule, there are competitive parties or other political groupings, and the opposition plays an important role and has actual power. Minority groups have reasonable self-government or can participate in the government through informal consensus. Rating of 2 -- Countries and territories rated 2 in political rights are less free than those rated 1. Such factors as political corruption, violence, political discrimination against minorities, and foreign or military influence on politics may be present and weaken the quality of freedom. Ratings of 3, 4, 5 -- The same conditions that undermine freedom in countries and territories with a rating of 2 may also weaken political rights in those with a rating of 3, 4, or 5. Other damaging elements can include civil war, heavy military involvement in politics, lingering royal power, unfair elections, and one-party dominance. However, states and territories in these categories may still enjoy some elements of political rights, including the freedom to organize quasi-political groups, reasonably free referendums, or other significant means of popular influence on government. Rating of 6 -- Countries and territories with political rights rated 6 have systems ruled by military juntas, one-party dictatorships, religious hierarchies, or autocrats. These regimes may allow only a minimal manifestation of political rights, such as some degree of representation or autonomy for minorities. A few states are traditional monarchies that mitigate their relative lack of political rights through the use of consultation with their subjects, tolerance of political discussion, and acceptance of public petitions. Rating of 7 -- For countries and territories with a rating of 7, political rights are absent or virtually nonexistent as a result of the extremely oppressive nature of the regime or severe oppression in combination with civil war. States and territories in this group may also be marked by extreme violence or warlord rule that dominates political power in the absence of an authoritative, functioning central government. Civil Liberties Rating of 1 -- Countries and territories that receive a rating of 1 come closest to ensuring the freedoms expressed in the civil liberties checklist, including freedom of expression, assembly, association, education, and religion. They are distinguished by an established and generally equitable system of rule of law. Countries and territories with this rating enjoy free economic activity and tend to strive for equality of opportunity. Rating of 2 -- States and territories with a rating of 2 have deficiencies in a few aspects of civil liberties, but are still relatively free. Ratings of 3, 4, 5 -- Countries and territories that have received a rating of 3, 4, or 5 range from those that are in at least partial compliance with virtually all checklist standards to those with a combination of high or medium scores for some questions and low or very low scores on other questions. The level of oppression increases at each successive rating level, including in the areas of censorship, political terror, and the prevention of free association. There are also many cases in which groups opposed to the state engage in political terror that undermines other freedoms. Therefore, a poor rating for a country is not necessarily a comment on the intentions of the government, but may reflect real restrictions on liberty caused by nongovernmental actors. Rating of 6 -- People in countries and territories with a rating of 6 experience severely restricted rights of expression and association, and there are almost always political prisoners and other manifestations of political terror. These countries may be characterized by a few partial rights, such as some religious and social freedoms, some highly restricted private business activity, and relatively free private discussion. Rating of 7 -- States and territories with a rating of 7 have virtually no freedom. An overwhelming and justified fear of repression characterizes these societies. Countries and territories generally have ratings in political rights and civil liberties that are within two ratings numbers of each other. Without a well-developed civil society, it is difficult, if not impossible, to have an atmosphere supportive of political rights. Consequently, there is no country in the survey with a rating of 6 or 7 for civil liberties and, at the same time, a rating of 1 or 2 for political rights.

Analysis unit

The units of analysis in the survey arel countries

Kind of data

Observation data/ratings [obs]

Mode of data collection

Other [oth]

This data collection contains two files of world military expenditures and arms trade data for 145 countries in the period 1967-1976. Part 1 data consist of a yearly series of data for population and national military expenditures, including the value of weapons exports and imports. The country and the year form the unit of analysis, so that each country appears ten times, once for each year. Data are provided in millions of United States current and constant dollars for the total arms imports and exports, as well as for the total imports and exports of goods and services. Various socioeconomic data are presented to provide a comparative background for the series. Data are provided in millions of United States current and constant dollars for the gross national product (GNP), and for military expenditures, central government expenditures, public health expenditures, and public education expenditures as a percentage of the gross national product. Additional variables provide information on the number of armed forces personnel, teachers, and physicians per 1,000 people. Part 2 data consist of information on the total transactions in the transfer of armaments. Data are provided for the total value of arms imported by each country from individual major arms suppliers, which include the United States, United Kingdom, France, Canada, China, Poland, West Germany, and Czechoslovakia. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR07713.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

KAV 8745 cover memo

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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.