This dataset uses U.S. Census table B17020 - Poverty Status by Age The data shows the number of people per locality, the overall number of people living below the poverty level per locality, and then the number of people under age 18 living below the poverty level per locality. This last data element is broken down into three segments - aged <6 years, 6-11 years, and 12-17 years, which when added together equal the total number of children under age 18 living below the poverty level per locality.

2013-2023 Virginia Ratio of Income to Poverty Level in the Past 12 Months by Census Block Group. Contains estimates and margins of error.

U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table C17002 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

Employment, occupation, income, payroll, and poverty data for North Carolina, counties, and municipalities.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

Appalachian Coal Data were prepared in late 2019 and early 2020 to support technical writing about Appalachian coalfield history, environment, and communities. The data originate from US federal government publications. All data sources are non-copyrighted. The data concern Appalachian and US coal production quantities, pricing, and revenue generation; Appalachian coal’s role in the USA’s energy economy; land areas disturbed by Appalachian coal mining; and selected coal-production, population, economic, and human-health metrics for counties and independent cities in seven states encompassing the Appalachian coalfield classified by coal-production status. The posted data are time series covering differing periods, some extending as far back as the late 1700s and all terminating in recent years, 2011 through 2019. The database was constructed while considering the Appalachian coalfield to include coal-mining areas of Tennessee, eastern Kentucky, West Virginia, Maryland, Pennsylvania, and the southwestern coalfield area of Virginia.

This link contains downloadable data for the Atlas of Rural and Small-Town America which provides statistics by broad categories of socioeconomic factors: People: Demographic data from the American Community Survey (ACS), including age, race and ethnicity, migration and immigration, education, household size, and family composition. Jobs: Economic data from the Bureau of Labor Statistics and other sources, including information on employment trends, unemployment, and industrial composition of employment from the ACS. County classifications: Categorical variables including the rural-urban continuum codes, economic dependence codes, persistent poverty, persistent child poverty, population loss, onshore oil/natural gas counties, and other ERS county typology codes. Income: Data on median household income, per capita income, and poverty (including child poverty). Veterans: Data on veterans, including service period, education, unemployment, income, and other demographic characteristics.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

Data for population, gender, race, labor force, educational attainment, income, poverty, households and housing units from the American Community Survey.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.

WV Waterlink aims to democratize water resources management, governance, and equity in the mountain state by including citizen and community participation in the decision-making process around water security and climate change adaptation. In order to do this, communities need to be knowledgeable about the state (e.g., health, availability) and vulnerability of this critical resource and for whom water resources are currently being managed. Waterlink explores the connection between social, political, and economic conditions that impact water security. Datasets are collected fromThe key datasets that were essential for this analysis included American Community Survey, Flash Flood Events, National Resource Defense Council Safe Drinking Water Act violations, toxic release inventory, and Social Vulnerability data. By having these datasets, we were able to perform an analysis of the differences in counties in West Virginia and study how the Safe Drinking Water Act varies throughout the state.CDC/ ATSDR Social Vulnerability Index: https://www.atsdr.cdc.gov/placeandhealth/svi/index.htmlThis data was collected in 2020 at the county-level scale. Data was filtered at the state level initially to collect information related to West Virginia.NYU Flood Zone: https://floodzonedata.us/This data was collected in 2020 at the county-level scale. Data was collected to understand flash flood vulnerability in each county. This data is sorted from the Federal Emergency Management Agency. The lighter color counties exhibit a higher percent of people living in a 100-year flood plain zone. The darker color counties exhibit a lower percent of people living in a 100-year flood plain zone. There are two different flood plain events that were most significant towards impacting a community. Those flash floods included 100 year flood plain zone and a100 + 500 year flood plain zone.American Community Survey: https://www.census.gov/programs-surveys/acsData was collected in 2020 at the county level scale for West Virginia. Once data was joined to the state, it was filtered to highlight where income was the lowest verse to the highest.Natural Resource Defense Council: https://www.nrdc.org/resources/watered-down-justiceTo analyze communities safe drinking water act violations and the different factors that make one more vulnerable, we received data directly from Kristi Fedinick in her Watered Downed Justice Report. Overall Vulnerability is calculated by the longest average time out of compliance per system and the highest racial, ethnic, and language vulnerability. Data was collected in 2018 at the county level scale for West Virginia. Pop-Ups are coded to include information such as population, person below poverty level estimate, housing units, civilian over the age of 16 unemployed, person (age 25+) with no high school diploma, minority, housing in structure with 10 or more units, mobile homes, and households with no vehicles.