The census of population and housing, taken by the Census Bureau in years ending in 0 (zero). Article I of the Constitution requires that a census be taken every ten years for the purpose of reapportioning the U.S. House of Representatives. Title 13 of the U. S. Code provides the authorization for conducting the census in Puerto Rico and the Island Areas. After each decennial census, the results are released to the public in a variety of ways, including publishing multiple series of reports titled Census of Population and Housing. The abbreviation for these reports was CPH for some decades (including 1990 and 2010) and PHC for some decades (including 1970 and 2000).

The downloadable ZIP file contains Esri shapefiles and PDF maps. Contains the information used to determine the location of the new legislative and congressional district boundaries for the state of Idaho as adopted by Idaho's first Commission on Redistricting on March 9, 2002. Contains viewable and printable legislative and congressional district maps, viewable and printable reports, and importable geographic data files.These data were contributed to INSIDE Idaho at the University of Idaho Library in 2001. CD/DVD -ROM availability: https://alliance-primo.hosted.exlibrisgroup.com/permalink/f/m1uotc/CP71156191150001451These files were created by a six-person, by-partisan commission, consisting of six commission members, three democrats and three republicans. This commission was given 90 days to redraw congressional and legislative district boundaries for the state of Idaho. Due to lawsuits, the process was extended. This legislative plan was approved by the commission on March 9th, 2002 and was previously called L97. All digital data originates from TIGER/Line files and 2000 U.S. Census data.Frequently asked questions:How often are Idaho's legislative and congressional districts redrawn? Once every ten years after each census, as required by law, or when directed by the Idaho Supreme Court. The most recent redistricting followed the 2000 census. Redistricting is not expected to occur again in Idaho until after the 2010 census. Who redrew Idaho's legislative and congressional districts? In 2001, for the first time, Idaho used a citizens' commission to redraw its legislative and congressional district boundaries. Before Idaho voters amended the state Constitution in 1994 to create a Redistricting Commission, redistricting was done by a committee of the Idaho Legislature. The committee's new district plans then had to pass the Legislature before becoming law. Who was on the Redistricting Commission? Idaho's first Commission on Redistricting was composed of Co-Chairmen Kristi Sellers of Chubbuck and Tom Stuart of Boise and Stanley. The other four members were Raymond Givens of Coeur d'Alene, Dean Haagenson of Hayden Lake, Karl Shurtliff of Boise, John Hepworth of Buhl (who resigned effective December 4, 2001), and Derlin Taylor of Burley (who was appointed to replace Mr. Hepworth). What are the requirements for being a Redistricting Commissioner? According to Idaho Law, no person may serve on the commission who: 1. Is not a registered voter of the state at the time of selection; or 2. Is or has been within one (1) year a registered lobbyist; or 3. Is or has been within two (2) years prior to selection an elected official or elected legislative district, county or state party officer. (This requirement does not apply to precinct committeepersons.) The individual appointing authorities may consider additional criteria beyond these statutory requirements. Idaho law also prohibits a person who has served on the Redistricting Commission from serving in either house of the legislature for five years following their service on the commission. When did Idaho's first Commission on Redistricting meet? Idaho law allows the Commission only 90 days to conduct its business. The Redistricting Commission was formed on June 5, 2001. Its 90-day time period would expire on September 3, 2001. After holding hearings around the state in June and July, a majority of the Commission voted to adopt new legislative and congressional districts on August 22, 2001. On November 29th, the Idaho Supreme Court ruled the Commission's legislative redistricting plan unconstitutional and directed them to reconvene and adopt an alternative plan. The Commission did so, adopting a new plan on January 8, 2000. The Idaho Supreme Court found the Commission's second legislative map unconstitutional on March 1, 2002 and ordered the Commission to try again. The Commission adopted a third plan on March 9, 2002. The Supreme Court denied numerous challenges to this third map. It then became the basis for the 2002 primary and General elections and is expected to be used until the 2012 elections. What is the basic timetable for Idaho to redraw its legislative and congressional districts?Typically, and according to Idaho law, the Redistricting Commission cannot be formally convened until after Idaho has received the official census counts and not before June 1 of a year ending in one. Idaho's first Commission on redistricting was officially created on June 5, 2001. By law, a Commission then has 90 days (or until September 3, 2001 in the case of Idaho's first Commission) to approve new legislative and congressional district boundaries based on the most recent census figures. If at least four of the six commissioners fail to approve new legislative and congressional district plans before that 90-day time period expires, the Commission will cease to exist. The law is silent as to what happens next. Could you summarize the important dates for Idaho's first Commission on Redistricting one more time please? After January 1, 2001 but before April 1, 2001: As required by federal law, the Census Bureau must deliver to the states the small area population counts upon which redistricting is based. The Census Bureau determines the exact date within this window when Idaho will get its population figures. Idaho's were delivered on March 23, 2001. Why conduct a census anyway? The original and still primary reason for conducting a national census every ten years is to determine how the 435 seats in the United States House of Representatives are to be apportioned among the 50 states. Each state receives its share of the 435 seats in the U.S. House based on the proportion of its population to that of the total U.S. population. For example, the population shifts during the 1990's resulted in the Northeastern states losing population and therefore seats in Congress to the Southern and the Western states. What is reapportionment? Reapportionment is a federal issue that applies only to Congress. It is the process of dividing up the 435 seats in the U.S. House of Representatives among the 50 states based on each state's proportion of the total U.S. population as determined by the most recent census. Apportionment determines the each state's power, as expressed by the size of their congressional delegation, in Congress and, through the electoral college, directly affects the selection of the president (each state's number of votes in the electoral college equals the number of its representatives and senators in Congress). Like all states, Idaho has two U.S. senators. Based on our 1990 population of 1,006,000 people and our 2000 population of 1,293,953, and relative to the populations of the other 49 states, Idaho will have two seats in the U.S. House of Representatives. Even with the state's 28.5% population increase from 1990 to 2000, Idaho will not be getting a third seat in the U.S. House of Representatives. Assuming Idaho keeps growing at the same rate it did through the decade of the 1990's, it will likely be 30 or 40 years (after 3 or 4 more censuses) before Idaho gets a third congressional seat. What is redistricting? Redistricting is the process of redrawing the boundaries of legislative and congressional districts within each state to achieve population equality among all congressional districts and among all legislative districts. The U.S. Constitution requires this be done for all congressional districts after each decennial census. The Idaho Constitution also requires that this be done for all legislative districts after each census. The democratic principle behind redistricting is "one person, one vote." Requiring that districts be of equal population ensures that every elected state legislator or U.S. congressman represents very close to the same number of people in that state, therefore, each citizen's vote will carry the same weight. How are reapportionment and redistricting related to the census? The original and still primary reason for conducting a census every ten years is to apportion the (now) 435 seats in the U.S. House of Representatives among the several states. The census records population changes and is the legally recognized basis for redrawing electoral districts of equal population. Why is redistricting so important? In a democracy, it is important for all citizens to have equal representation. The political parties also see redistricting as an opportunity to draw districts that favor electing their members and, conversely, that are unfavorable for electing their political opposition. (It's for this reason that redistricting has been described as "the purest form of political bloodsport.") What is PL 94-171? Public Law (PL) 94-171 (Title 13, United States Code) was enacted by Congress in 1975. It was intended to provide state legislatures with small-area census population totals for use in redistricting. The law's origins lie with the "one person, one vote" court decisions in the 1960's. State legislatures needed to reconcile Census Bureau's small geographic area boundaries with voting tabulation districts (precincts) boundaries to create legislative districts with balanced populations. The Census Bureau worked with state legislatures and others to meet this need beginning with the 1980 census. The resulting Public Law 94-171 allows states to work voluntarily with the Census Bureau to match voting district boundaries with small-area census boundaries. With this done, the Bureau can report to those participating states the census population totals broken down by major race group and Hispanic origin for the total population and for persons aged 18 years and older for each census subdivision. Idaho participated in the Bureau's Census 2000 Redistricting Data Program and, where counties used visible features to

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. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2010 Census.

The Population and Dwellings data from the 2021 Federal Census covers population in private households by age and gender. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Population in private households refers to all persons or group of persons who occupy the same dwelling and do not have a usual place of residence elsewhere in Canada or abroad. For census purposes, households are classified into three groups: private households, collective households, and households outside Canada. Unless otherwise specified, all data in census products are for private households only. Population in private households includes Canadian citizens and landed immigrants whose usual place of residence is Canada. Also includes refugee claimants, holders of work and study permits, Canadian citizens and landed immigrants at sea or in port aboard merchant or government vessels, and Canadian citizens away from Canada on military or diplomatic business. Excludes government representatives and military members of other countries and residents of other countries visiting Canada.

Age refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well‑defined reference date).

Gender refers to an individual's personal and social identity as a man, woman, or non‑binary person (a person who is not exclusively a man or a woman). A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport, or driver's licence. A person's gender may change over time. Statistics Canada collected data about transgender and non-binary populations for the first time on the 2021 Census. The category "Men+" includes men (and/or boys), as well as some non-binary persons. The category "Women+" also includes women (and/or girls), as well as some non-binary persons.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

Urban AreasThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Urban Areas within the United States. Per USCB, "Urban areas represent densely developed territory, and encompass residential, commercial, and other non-residential urban land uses. The Census Bureau delineates urban areas after each decennial census by applying specified criteria to decennial census and other data."Washington/Arlington Urban AreaData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Urban Areas) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 61 (Series Information for 2020 Census Urban Area National TIGER/Line Shapefiles, Current)OGC API Features Link: Urban Areas copy this link to embed it in OGC Compliant viewersFor more information, please visit: Urban and Rural, 2020 Census Urban Areas FactsFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The 2019 Census of State and Federal Adult Correctional Facilities (CCF) was the ninth enumeration of state institutions and the sixth enumeration of federal institutions sponsored by the Bureau of Justice Statistics and its predecessors. Earlier censuses were completed in 1979 (ICPSR 7852), 1984 (ICPSR 8444), 1990 (ICPSR 9908), 1995 (ICPSR 6953), 2000 (ICPSR 4021), 2005 (ICPSR 24642), and 2012 (ICPSR 37294). The 2019 CCF consisted of two data collection instruments - one for confinement facilities and one for community-based facilities. For each facility, information was provided on facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, race/ethnicity, special populations, and holding authority; number of walkaways occurring over a one-year period; and educational and other special programs offered to prisoners. Additional information was collected from confinement facilities, including physical security level; housing for special populations; capacity; court orders for specific conditions; one-day count of correctional staff by payroll status and sex; one-day count of security staff by sex and race/ethnicity; assaults and incidents caused by prisoners; number of escapes occurring over a one-year period; and work assignments available to prisoners. Late in the data collection to avoid complete nonresponse from facilities, BJS offered the option of providing critical data elements from the two data collection instruments. These elements included facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, and holding authority. Physical security level was an additional critical data element for confinement facilities. The census counted prisoners held in the facilities, a custody count. Some prisoners who are held in the custody of one jurisdiction may be under the authority of a different jurisdiction. The custody count is distinct from a count of prisoners under a correctional authority's jurisdiction, which includes all prisoners over whom a correctional authority exercises control, regardless of where the prisoner is housed. A jurisdictional count is more inclusive than a prison custody count and includes state and federal prisoners housed in local jails or other non-correctional facilities.

Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Retail Trade: Income (Loss) After Income Taxes (QFR115RETUSNO) from Q4 2000 to Q1 2025 about gains/losses, finance, tax, retail trade, corporate, sales, retail, income, industry, and USA.

Graph and download economic data for Homeownership Rate in the United States (RHORUSQ156N) from Q1 1965 to Q2 2025 about homeownership, housing, rate, and USA.

The Employment data from the 2021 Federal Census covers labour force status, employment status, labour force participation rate, industry, and occupation. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Labour force status refers to whether a person was employed, unemployed or not in the labour force during the reference period. Not in the labour force refers to persons who were neither employed nor unemployed during the reference period. This includes persons who, during the reference period were either unable to work or unavailable for work. It also includes persons who were without work and who had neither actively looked for work in the past four weeks nor had a job to start within four weeks of the reference period.

Employment status refers to the employment status of a person during the period of Sunday, May 2 to Saturday, May 8, 2021. An employed person is one who did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment. This category excludes persons not at work because they were on layoff or between casual jobs, and those who did not then have a job (even if they had a job to start at a future date). While an unemployed person is one who was without paid work or without self-employment work and was available for work. An unemployed person either: had actively looked for paid work in the past four weeks; was on temporary lay-off and expected to return to his or her job; or had definite arrangements to start a new job in four weeks or less.

Labour force participation rate refers to the total labour force in that group, expressed as a percentage of the total population in that group.

Industry refers to the general nature of the business carried out in the establishment where the person worked. The industry data are produced according to the North American Industry Classification System (NAICS).

Occupation refers to the kind of work performed in a job, a job being all the tasks carried out by a particular worker to complete their duties. An occupation is a set of jobs that are sufficiently similar in work performed. The occupation data are produced according to the National Occupational Classification (NOC) 2021.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.

Every 10 years, after the federal census, California must redraw the boundaries of its Congressional, State Senate, State Assembly, and State Board of Equalization districts, to reflect the new population data. Now those lines are drawn by the Commission. California voters authorized the creation of the Commission when they passed the Voters First Act, which appeared as Proposition 11 on the November 2008 general election ballot. Under the Act, the Commission is charged with drawing the boundaries of California’s Congressional, Senate, Assembly and Board of Equalization electoral districts.The commission has14 members from varied ethnic backgrounds and geographic locations in the state and includes five Democrats, five Republicans, and four Decline to State.http://wedrawthelines.ca.gov/

Us House Congressional Representatives serving Macon-Bibb County.Congressional districts are the 435 areas from which members are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states, which is based on decennial census population counts, each state with multiple seats is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The boundaries and numbers shown for the congressional districts are those specified in the state laws or court orders establishing the districts within each state.

Congressional districts for the 108th through 112th sessions were established by the states based on the result of the 2000 Census. Congressional districts for the 113th through 115th sessions were established by the states based on the result of the 2010 Census. Boundaries are effective until January of odd number years (for example, January 2015, January 2017, etc.), unless a state initiative or court ordered redistricting requires a change. All states established new congressional districts in 2011-2012, with the exception of the seven single member states (Alaska, Delaware, Montana, North Dakota, South Dakota, Vermont, and Wyoming).

For the states that have more than one representative, the Census Bureau requested a copy of the state laws or applicable court order(s) for each state from each secretary of state and each 2010 Redistricting Data Program state liaison requesting a copy of the state laws and/or applicable court order(s) for each state. Additionally, the states were asked to furnish their newly established congressional district boundaries and numbers by means of geographic equivalency files. States submitted equivalency files since most redistricting was based on whole census blocks. Kentucky was the only state where congressional district boundaries split some of the 2010 Census tabulation blocks. For further information on these blocks, please see the user-note at the bottom of the tables for this state.

The Census Bureau entered this information into its geographic database and produced tabulation block equivalency files that depicted the newly defined congressional district boundaries. Each state liaison was furnished with their file and requested to review, submit corrections, and certify the accuracy of the boundaries.

Census Tracts from the 2020 US Census for New York City clipped to the shoreline. These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map. Because some census tracts are under water not all census tracts are contained in this file, only census tracts that are partially or totally located on land have been mapped in this file.

All previously released versions of this data are available at the DCP Website: BYTES of the BIG APPLE.

Source of update: American Community Survey 5-year 2006-2010 data for poverty. For source tables refer to InfoUSA update procedural documentation. The 2010 MSSA Detail layer was developed to update fields affected by population change. The American Community Survey 5-year 2006-2010 population data pertaining to total, in households, race, ethnicity, age, and poverty was used in the update. The 2010 MSSA Census Tract Detail map layer was developed to support geographic information systems (GIS) applications, representing 2010 census tract geography that is the foundation of 2010 medical service study area (MSSA) boundaries. ***This version is the finalized MSSA reconfiguration boundaries based on the US Census Bureau 2010 Census. In 1976 Garamendi Rural Health Services Act, required the development of a geographic framework for determining which parts of the state were rural and which were urban, and for determining which parts of counties and cities had adequate health care resources and which were "medically underserved". Thus, sub-city and sub-county geographic units called "medical service study areas [MSSAs]" were developed, using combinations of census-defined geographic units, established following General Rules promulgated by a statutory commission. After each subsequent census the MSSAs were revised. In the scheduled revisions that followed the 1990 census, community meetings of stakeholders (including county officials, and representatives of hospitals and community health centers) were held in larger metropolitan areas. The meetings were designed to develop consensus as how to draw the sub-city units so as to best display health care disparities. The importance of involving stakeholders was heightened in 1992 when the United States Department of Health and Human Services' Health and Resources Administration entered a formal agreement to recognize the state-determined MSSAs as "rational service areas" for federal recognition of "health professional shortage areas" and "medically underserved areas". After the 2000 census, two innovations transformed the process, and set the stage for GIS to emerge as a major factor in health care resource planning in California. First, the Office of Statewide Health Planning and Development [OSHPD], which organizes the community stakeholder meetings and provides the staff to administer the MSSAs, entered into an Enterprise GIS contract. Second, OSHPD authorized at least one community meeting to be held in each of the 58 counties, a significant number of which were wholly rural or frontier counties. For populous Los Angeles County, 11 community meetings were held. As a result, health resource data in California are collected and organized by 541 geographic units. The boundaries of these units were established by community healthcare experts, with the objective of maximizing their usefulness for needs assessment purposes. The most dramatic consequence was introducing a data simultaneously displayed in a GIS format. A two-person team, incorporating healthcare policy and GIS expertise, conducted the series of meetings, and supervised the development of the 2000-census configuration of the MSSAs.

About this dataset

Context

The dataset tabulates the data for the Dana, IA population pyramid, which represents the Dana population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 5-Year estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Dana, IA, is 25.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Dana, IA, is 30.0.
• Total dependency ratio for Dana, IA is 55.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Dana, IA is 3.3.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

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

Five (5) Supervisoral Districts of San Diego CountyRedistricting takes place every 10 years after the federal census. District boundaries for federal, state and local elected offices are redrawn to reflect new population data and shifting populations. The County’s district boundaries will change so the five County supervisors elected to represent those districts each serve about 650,000 residents and reflects the County’s diverse population. Fourteen people were selected for the County's IRC. The process will act independently from the influence of the Board of Supervisors and reasonably represent the County’s diversity.On January 12, 2022, the IRC approved technical changes to the 2021 Redistricting Plan and Final Report adjusting boundaries of the supervisorial districts of the County of San Diego Board of Supervisors(https://www.sandiegocounty.gov/content/sdc/redistricting/2021-redistricting-plan-map1.html)The Board adopted the redistricting ordinance on December 14, 2021 (https://www.sandiegocounty.gov/content/dam/sdc/redistricting/docs/ircmeetings/irc-meeting-12-14-21/Item%2005%20-%20Resolution%20Adopting%20Final%20Report%20re-%20Final%20Redistricting%20Plan%20-%20SIGNED.pdf)

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. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.

A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

The TIGER/Line Files are shapefiles and related database files (.dbf) that 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 File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.

After each decennial census, the Census Bureau delineates Public Use Microdata Areas (PUMAs) for the tabulation and dissemination of decennial census Public Use Microdata Sample (PUMS) data, American Community Survey (ACS) PUMS data, and ACS period estimates. Nesting within states, or equivalent entities, PUMAs cover the entirety of the United States, Puerto Rico, Guam, and the U.S. Virgin Islands. PUMA delineations are subject to population, building block geography, geographic nesting, and contiguity criteria. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name. 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.