To show count of Post 9/11 Veterans (Living only) by County for the creation of a heat map to align with Wounded Warrior Projects’ programming.

This report provides county-level estimates of the number of Veterans who were receiving VA Disability Compensation benefits as of the end of fiscal year 2023. It includes the Veterans’ total service-connected disability (SCD) rating, age group, and sex. Blank values represent small cell counts that have been suppressed to protect the identity of Veterans as well as some cell counts that have been suppressed in order to prevent the determination of the values of the aforementioned small cell counts. Some categories may not sum to the total due to missing information (e.g., age, sex, etc.). The availability of sex and age data is limited as some records have no sex or birthdate available. In the table, there are 404 Veterans whose sex is not available and 113 Veterans whose age is not available. The number of Veterans who were disability compensation recipients during FY 2023 but were no longer disability compensation recipients at the end of FY 2023 is 138,646. These Veterans are not included in the table. Source: Department of Veterans Affairs, Office of Enterprise Integration, Veteran Object FY23 data and Veterans Benefits Administration VETSNET FY 2023 compensation data. Prepared by National Center for Veterans Analysis & Statistics, www.va.gov/vetdata.

The Compensation and Pension by County dataset is a count of the number of veterans receiving disability compensation or pension payments from the Department of Veterans Affairs. The data is reported at the county level, by age group and by % disability rating for each state plus recipients in Guam, Philippines and Puerto Rico.

These spreadsheets contain the percent of Veteran farmers and dairymen by county for the state of California.

The Geographic Distribution of VA Expenditures (GDX) is an annual report that shows estimated VA expenditures for major programmatic areas by geographic area (state, county, and congressional district). The major programmatic areas are: Compensation and Pension; Readjustment (Education) and Vocational Rehabilitation; Insurance; Construction; and, Medical and Administrative.

This map shows the percent of population who are veterans. This pattern is shown by states, counties, and tracts. The data is from the most current American Community Survey (ACS) data from the U.S. Census Bureau. 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.The pop-up highlights the breakdown of veterans by gender.Zoom to any area in the country to see a local or regional pattern, or use one of the bookmarks to see distinct patterns of poverty through the US. Data is available for the 50 states plus Washington D.C. and Puerto Rico.The data comes from this ArcGIS Living Atlas of the World layer, which is part of a wider collection of layers that contain the most up-to-date ACS data from the Census. The layers are updated annually when the ACS releases their most current 5-year estimates. Visit the layer for more information about the data source, vintage, and download date for the data.

This data contains the number of veterans per county who have an Illinois address recorded in the IDVA Veteran Database(not all Illinois veterans).

The Geographic Distribution of VA Expenditures (GDX) is an annual report that shows estimated VA expenditures for major programmatic areas by geographic area (state, county, and congressional district). The major programmatic areas are: Compensation and Pension; Readjustment (Education) and Vocational Rehabilitation; Insurance; Construction; and, Medical and Administrative.

Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Loudoun County, VA (DISCONTINUED) (NETMIGNACS051107) from 2009 to 2020 about Loudoun County, VA; migration; Washington; flow; VA; Net; 5-year; and population.

To show count of Veterans with an SCD rating (including 0%) (Living only) by County for DoD.

In 2020, surveys conducted among people experiencing homelessness in King County, Washington found that 55 percent of those who were veterans suffered from post-traumatic stress disorder (PTSD), compared to 39 percent of those who were not veterans. This statistic shows the percentage of veteran and non-veteran homeless persons in King County, Washington who stated they had select health conditions as of 2020.

This is a simple proportion analysis to determine the number of veterans who may be impacted by food scarcity in the United states by county. The population of veterans in each county (9L_VetPop2016_County) was used with the total population in each county (DataDownload3.18) to determine the proportion of veterans in each county. We assumed that veterans were just as likely as anyone else to be in food scarcity and multiplied the proportion of veterans in each county by the number of low access people in the county to determine the number of food insecure veterans by county. We also used statewide very low food secure percentage as a conservative estimate of the number of veterans affected by food scarcity.This dataset was not created to be a perfect representation of the exact number of food insecure veterans. In fact, it is a very rough calculation. However, this back of the envelope calculation shows that the number of food insecure veterans is likely very high. Using county level food access we find that up to 3 million veterans could be affected by low food access, as a conservative estimate, we use the state level "very low food security percentage" and find that a minimum of 200 thousand veterans are likely food insecure. For calculations see sheet "Calculations" in DataDownload3.18.xlsVeteran Population in counties of the United States.(9L_VetPOP2016_Count.csv)https://va.gov/vetdata/Veteran_Population.aspFood Insecurity By County (DataDownload3.18.xls)https://www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentation-downloads/

Veterans served by Pierce County Veterans Assistance Programs.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Alleghany County, VA (S1701ACS051005) from 2012 to 2023 about Alleghany County, VA; VA; percent; poverty; 5-year; population; and USA.

About this dataset

Context

The dataset tabulates the Rockbridge County population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Rockbridge County. The dataset can be utilized to understand the population distribution of Rockbridge County by age. For example, using this dataset, we can identify the largest age group in Rockbridge County.

Key observations

The largest age group in Rockbridge County, VA was for the group of age 55 to 59 years years with a population of 2,125 (9.41%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Rockbridge County, VA was the 80 to 84 years years with a population of 567 (2.51%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 in consideration
• Population: The population for the specific age group in the Rockbridge County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Rockbridge County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Rockbridge County Population by Age. You can refer the same here

Graph and download economic data for Resident Population in Westmoreland County, VA (VAWEST3POP) from 1970 to 2024 about Westmoreland County, VA; VA; residents; population; and USA.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Greensville County, VA (S1701ACS051081) from 2012 to 2023 about Greensville County, VA; VA; percent; poverty; 5-year; population; and USA.

Graph and download economic data for Resident Population in Richmond County, VA (VARICH9POP) from 1970 to 2024 about Richmond County, VA; VA; residents; population; and USA.

The Department of Veterans Affairs (VA) provides healthcare services to its veterans across the USA including territories and possessions. Healthcare services are delivered through 18 geographically divided administrative areas called Veterans Integrated Services Networks (VISN). Each VISN is divided into healthcare areas called Markets and Submarkets. Each Submarket is divided into Sectors and each Sector comprises one or more counties. In 1995 a process was created to coordinate and review the realignment of the Heath Care Networks. The Capital Asset Realignment for Enhanced Services (CARES) process established VISN 'subsets' called Markets, Submarkets and Sectors which, being smaller than VISNs, allowed for more precise analyses for greater access measurement to health care.

The County layer is the base geographic unit of the VISN-Market-Submarket-Sector-County hierarchy. The key attribute in this data set is the FIPS which is defined as a string of 5 characters with unique alphanumeric combinations for each site. The first 2 are the State FIPS code and the next 3 designate the County FIPS code. Example: '01031' is the FIPS for Coffee County, Alabama.

A Sector is a cluster of geographically adjacent counties within a VA Submarket. The process of aggregating counties into sectors uses a combination of automated algorithms and manual inspection of maps. The key attribute in this data set is the SECTOR which is defined as a string of eight characters broken down into four parts in the order of VISN (2-char), Market (1-char), Submarket (1-char), and Sector(1-char) connected by a hyphen. For example, Sector 12-a-3-A indicates VISN 12, Market a, Submarket 3 and Sector A.

Sub-markets reflect a clustering of the enrollee population within a market and are an aggregation of Sectors. The key attribute in this data set is the SUBMARKET which is defined as a string of six characters broken down in three parts in the order of VISN (2-char), Market (1-char), and Submarket (1-char) connected by a hyphen. For example, Submarket 12-a-3 indicates VISN 12, Market a, and Submarket 3.

CARES defines Markets as "an aggregated geographic area having a sufficient population and geographic size to both benefit from the coordination and planning of health care services and to support a full healthcare delivery system (i.e. primary care, mental health care, inpatient care, tertiary care, and long term care)". Each Market is built from Submarkets. The key attribute in this data set is the MARKET which is defined as a string of four characters broken down in two parts in the order of HCN (2-char) and Market (1-char) connected by a hyphen. For example, Market 12-a indicates VISN 12 and Market a.

The key attribute in the VISN data set is defined as a string of two characters from 01-23, excluding 3, 11, 13, 14 and 18; a VISN also has an officially recognized VA title. For example, VISN 06 is the Mid-Atlantic Health Care Network. VISNs can span across neighboring countries to include areas that are not contiguous. For example, VISN 08 includes Florida and Puerto Rico in addition to most of Florida and southern Georgia, and VISN 20 includes Alaska and parts of the northwest conterminous United States. Each VISN is built from Markets, Submarkets, Sectors and Counties derived from Census (2010) County data.

Because VISNs are composed of VHA markets, VISN boundaries align with the outer edges of their constituent markets’ boundaries. Markets cross state borders wherever it is necessary to keep outpatient clinics (e.g. Community-Based Outpatient Clinics(CBOCs)) and their catchment areas in the same market as their parent medical centers. Thus, VISN boundaries also cross state borders. In 2016 senior leadership considered the challenge of conforming VISN boundaries to MyVA Districts, which coincide with state boundaries. It was agreed that VHA would not separate outpatient clinics from their parent medical centers due to added complexity. Many outpatient providers hold clinics at their mother facilities and clinics are on the same health record as their parent facilities. VISN and market maps created by VHA Policy and Planning conform to these principals and are the official maps for VHA VISNs and markets.

While the Planning Systems Support Group (PSSG) develops the feature classes depicting the various VHA geographies, the PSSG does not have the authority to modify or reorganize the boundaries. The boundaries are developed at higher levels of the VHA and passed to the PSSG to be translated into spatial features.

About this dataset

Context

The dataset tabulates the population of Orange County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Orange County. The dataset can be utilized to understand the population distribution of Orange County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Orange County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Orange County.

Key observations

Largest age group (population): Male # 60-64 years (1,521) | Female # 55-59 years (1,516). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Orange County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Orange County is shown in the following column.
• Population (Female): The female population in the Orange County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Orange County for each age group.

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 Orange County Population by Gender. You can refer the same here