Global References
• |
change in population from 2010-2015. Higher values are better. Change in county population between July 1, 2010 and July 1, 2015 as a percentage of the initial population. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. To qualify for change in population from 2010-2015, the number of population in 2015 must be at least 5,000. |
• |
population in 2015. Population estimate in county as of July 1st. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change in population from 2010-2015 due to net inbound migration. Higher values are better. Change in county population between July 1, 2010 and July 1, 2015 due to net inbound migration (including both domestic migration and immigration) as a percentage of the initial population. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change in population from 2010-2015 due to net international immigration. Higher values are better. Change in county population between July 1, 2010 and July 1, 2015 due to net international migration, as a percentage of the initial population. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
foreign-born population. Percent of county population during 2010-2014 born outside the United States, regardless of citizenship status, excluding population born at sea. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
population age 65 or older. Percent of population age 65 or older, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
white non-Hispanic population. Percent Non-Hispanic White, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
black non-Hispanic population. Percent Non-Hispanic African-American, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Asian population. Percent Non-Hispanic Asian, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Native American non-Hispanic population. Percent Non-Hispanic Native American, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Hispanic population. Percent Hispanic, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
multi-racial population. Percent multiple race, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
European-born population. Percent of county population during 2010-2014 born in Europe, regardless of citizenship status. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Mexican-born population. Percent of county population during 2010-2014 born in Mexico, regardless of citizenship status. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
non-English speaking households. Percent of county households during 2010-2014 that are linguistically isolated, defined as households in which all members 14 years old or older have some difficulty with English. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 25+ with no high school diploma or GED. Lower values are better. Percent of persons during 2010-2014 with no high school diploma or GED, adults 25 and over, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 25+ with a bachelors degree or higher. Higher values are better. Percent of county population during 2010-2014 who are 25 years old or older with bachelor's degree or higher. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
average household size. average size of households: Number of people in the county during 2010-2014 divided by the number of households. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
female-headed family households. Percent of county households during 2010-2014 headed by a female with no husband present. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 65+ living alone. Percent of county households during 2010-2014 with one person 65 years old or older living alone. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
owner-occupied housing. Percent of occupied housing units in the county during 2010-2014 that are owner occupied. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Central or South American-born population. Percent of county population during 2010-2014 born in Central or South America. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Caribbean-born population. Percent of county population during 2010-2014 born in Caribbean. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
African-born population. Percent of county population during 2010-2014 born in Africa, regardless of citizenship status. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
Asian-born population. Percent of county population during 2010-2014 born in Asia. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
land area. Land area in square miles, 2010. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
median household income. Higher values are better. Median household income, 2014 (in 2014 dollars). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
per-capita income. Higher values are better. Per-capita income in the past 12 months (in 2014 inflation adjusted dollars), 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
poverty rate for children age 0-17. Lower values are better. Poverty rate for children age 0-17, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
poverty rate. Lower values are better. Poverty rate for all ages, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
deep-poverty rate. Lower values are better. Deep poverty rate for all ages, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
deep-poverty rate for children age 0-17. Lower values are better. Deep poverty rate for children, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
unemployment rate. Lower values are better. Unemployment rate, 2015. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
residents employed in agriculture or other resource-based industries. Percent employed in agriculture and other resourced based industries, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
residents employed in manufacturing. Percent employed in manufacturing, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
residents employed in services. Percent employed in services, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
residents employed in government. Percent employed in government, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
rural. 9-level classification of counties by metro-nonmetro status, location, and urban size. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
contain a high-density urban area. Classification of counties into metro or nonmetro. Metro areas include all counties containing one or more urbanized areas: high-density urban areas containing 50,000 people or more; metro areas also include outlying counties that are economically tied to the central counties, as measured by the share of workers commuting on a daily basis to the central counties. Nonmetro counties are outside the boundaries of metro areas and have no cities with 50,000 residents or more. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
type. Classification of counties by measures of earnings and employment into: Nonspecialized, farm-dependent, Mining-dependent, Manufacturing-dependent, Federal/State government-dependent, and Recreation county. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
have low employment. A 'no' value is good. A county was classified as low-employment if 65 percent or less of residents age 25-64 years were employed. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
have lost population in the decade between the last two censuses. A 'no' value is good. Classification of counties by whether they were losing population. A county was classified as population loss if the number of residents declined between the 1990 and 2000 censuses, and between the 2000 and 2010 censuses. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
a retirement destination. A 'yes' value is good. Classification of counties by in-migration of older residents into retirement-destination county andother counties. A county is defined as a retirement destination if the number of residents 60 years old or older grew by 15 percent or more between 2000 and 2010 due to net in-migration. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
have decades-long substantial poverty. A 'no' value is good. A county was classified as persistent poverty if 20 percent or more of its residents were poor as measured by the 1980, 1990, and 2000 decennial censuses and the American Community Survey 5-year estimates for 2007-2011. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
have decades-long substantial child poverty. A 'no' value is good. A county was classified as persistent poverty if 20 percent or more of related children under 18 years were poor as measured by the 1980, 1990, and 2000 decennial censuses and the American Community Survey 5-year estimates for 2007-2011. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
high in poverty. A 'no' value is good. A county was classified as high poverty if 20 percent or more of its residents were poor as measured by American Community Survey five-year estimates for 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
high in natural amenities. A high natural amenities county falls in the top quartile of counties ranked by the ERS natural amenities scale; the scale combines six measures of climate, topography, and water area that reflect environmental qualities most people prefer. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
high in creative professions. A 'yes' value is good. A creative class county falls in the top quartile of counties ranked by percent of employed persons 16 years old or older in occupations that involve 'thinking creatively.' This skill element is defined as developing, designing, or creating new applications, ideas, relationships, systems, or products, including artistic contributions. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
gas-change. High Growth if 2011 value – 2000 value equals or exceeds $20 million. High Decline if 2011 value – 2000 value equals or is less than -$20 million. Status Quo if 2011 value – 2000 value change is less than $20 million in either direction, or if no data. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
oil-change. High Growth if 2011 value – 2000 value equals or exceeds $20 million. High Decline if 2011 value – 2000 value equals or is less than -$20 million. Status Quo if 2011 value – 2000 value change is less than $20 million, or no data. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
oil-gas-change. High Growth if 2011 value – 2000 value equals or exceeds $20 million. High Decline if 2011 value – 2000 value equals or is less than -$20 million. Status Quo if 2011 value – 2000 value change is less than $20 million, or no data. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
residents who are veterans. Percent of the civilian county population 18 years and over that are veterans. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
proportion of veterans who are male. Percent of the civilian veteran population 18 years and over that are male. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
proportion of veterans who are female. Percent of the civilian veteran population 18 years and over that are female. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
unemployment rate for veterans. Lower values are better. Percent of civilian veterans age 18 to 64 that report they are unemployed and looking for work. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
male obesity. Lower values are better. Percent of men in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html. |
• |
female obesity. Lower values are better. Percent of women in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html. |
• |
residents who have diabetes. Lower values are better. Percent of the resident population in 2013 who suffer from diabetes. Source: http://www.cdc.gov/diabetes/data/county.html. |
• |
median rent for a 0-bedroom (studio/efficiency) unit. Lower values are better. 50th percentile rent in 2017 for a 0-bedroom unit. Source: https://www.huduser.gov/portal/datasets/50per.html. |
• |
median rent for a 1-bedroom unit. Lower values are better. 50th percentile rent in 2017 for a 1-bedroom unit. Source: https://www.huduser.gov/portal/datasets/50per.html. |
• |
median rent for a 3-bedroom unit. Lower values are better. 50th percentile rent in 2017 for a 3-bedroom unit. Source: https://www.huduser.gov/portal/datasets/50per.html. |
• |
religious adherents. All denominations/groups--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Evangelical Protestants. Evangelical Protestant--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Mainline Protestants. Mainline Protestant--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Catholics. Catholic Church--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Mormons. Church of Jesus Christ of Latter-day Saints, The--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Evangelical Lutherans. Evangelical Lutheran Church in America--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
Southern Baptists. Southern Baptist Convention--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
United Methodists. United Methodist Church, The--Rates of adherence per 1,000 population (2010). Source: http://www.thearda.com/Archive/Files/Descriptions/RCMSCY10.asp. |
• |
enrollees in a health plan through HealthCare.gov. The total number of unique individuals who have a non-canceled plan selection with March 1, 2016 coverage for one of the 38 states that use the HealthCare.gov platform during the open enrollment period from November 1, 2015 through January 31, 2016, including additional special enrollment period activity reported through February 1, 2016. Source: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Marketplace-Products/Plan_Selections_County.html. |
• |
enrollment frequency in a health plan through HealthCare.gov. The total number of unique individuals, as a percentage of the estimated 2015 county population, who have a non-canceled plan selection with March 1, 2016 coverage for one of the 38 states that use the HealthCare.gov platform during the open enrollment period from November 1, 2015 through January 31, 2016, including additional special enrollment period activity reported through February 1, 2016. Source: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Marketplace-Products/Plan_Selections_County.html. To qualify for enrollment frequency in a health plan through HealthCare.gov, the number of population in 2015 must be at least 5,000. |
• |
total domestic water use. Estimated total domestic water use (withdrawals + deliveries) in 2010, in millions of gallons per day. Source: http://water.usgs.gov/watuse/data/2010/index.html. |
• |
total water usage for all purposes. Estimated total withdrawals of fresh and saline water in 2010, in millions of gallons per day. Source: http://water.usgs.gov/watuse/data/2010/index.html. |
• |
total domestic water use per capita. Estimated total domestic water use (withdrawals + deliveries) in gallons per day per capita, based on total domestic water use in 2010 (source: http://water.usgs.gov/watuse/data/2010/index.html) and total county population in 2015 (source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx). To qualify for total domestic water use per capita, the number of population in 2015 must be at least 5,000. |
• |
farmland. Data on farmland as the percent of total county land comes from the Area Health Resources File (http://ahrf.hrsa.gov/download.htm) and is attributed to the year 2002. |
• |
total arrests per thousand residents for all offenses. Lower values are better. Grand total of arrests for all offenses (Part I and Part II) (source: http://www.icpsr.umich.edu/icpsrweb/NACJD/studies/36399) times 1,000, divided by the population estimate in the county as of July 1st, 2015 (source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx). To qualify for total arrests per thousand residents for all offenses, the number of population in 2015 must be at least 5,000. |
• |
arrests per thousand residents for Part I offenses. Lower values are better. Grand total of arrests for all Part I offenses (definitions: http://www.ucrdatatool.gov/offenses.cfm and data source: http://www.icpsr.umich.edu/icpsrweb/NACJD/studies/36399) times 1,000, divided by the population estimate in the county as of July 1st, 2015 (source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx). To qualify for arrests per thousand residents for Part I offenses, the number of population in 2015 must be at least 5,000. |
• |
arrests per thousand residents for Part I violent offenses. Lower values are better. Grand total of arrests for all Part I violent offenses (definitions: http://www.ucrdatatool.gov/offenses.cfm and data source: http://www.icpsr.umich.edu/icpsrweb/NACJD/studies/36399) times 1,000, divided by the population estimate in the county as of July 1st, 2015 (source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx). To qualify for arrests per thousand residents for Part I violent offenses, the number of population in 2015 must be at least 5,000. |
• |
arrests per thousand residents for Part I property offenses. Lower values are better. Grand total of arrests for all Part I property offenses (definitions: http://www.ucrdatatool.gov/offenses.cfm and data source: http://www.icpsr.umich.edu/icpsrweb/NACJD/studies/36399) times 1,000, divided by the population estimate in the county as of July 1st, 2015 (source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx). To qualify for arrests per thousand residents for Part I property offenses, the number of population in 2015 must be at least 5,000. |
• |
change, relative to its home state, in per-capita income. Higher values are better. County per-capita income in the past 12 months (in 2014 inflation adjusted dollars), 2010-14, as a percentage increase/decrease relative to the per-capita income of the state in which the county lies. Source for data inputs: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change, relative to its home state, in the poverty rate. Lower values are better. Difference between (1) County poverty rate for all ages in 2014 and (2) the poverty rate of the state in which the county lies. Source for data inputs: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change, relative to its home state, in the net inbound migration rate. Higher values are better. Difference between (1) county population between July 1, 2010 and July 1, 2015 due to net inbound migration (including both domestic migration and immigration) as a percentage of the initial population, and (2) the same quantity but for the state overall. For example, if the net inbound migration rates for the county were 3% and state were 2%, then the value would be 3% - 2% = 1%. Source for data inputs: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 25+ with no college credits. Lower values are better. Percent of county population during 2010-2014 who are 25 years old or older with no college credits. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED)and Ed2HSDiplomaOnlyPct (high school diploma only). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 25+ with less than an associate degree. Lower values are better. Percent of county population during 2010-2014 who are 25 years old or older with no associate degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), and Ed3SomeCollegePct (some college credit but no associate degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
adults of age 25+ with less than a bachelors degree. Lower values are better. Percent of county population during 2010-2014 who are 25 years old or older with no bachelor's degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), Ed3SomeCollegePct (some college credit but no associate degree or higher), and Ed4AssocDegreePct (associate degree but no bachelor's degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change in unemployment rate over the last 4 years. Lower values are better. Change in unemployment rate from 2011 to 2015. Source data: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change in unemployment rate over the last 8 years. Lower values are better. Change in unemployment rate from 2007 to 2015. Source data: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
change over 4 years in the prevalence of male obesity. Lower values are better. Change in the prevalence of male obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
change over 4 years in the prevalence of female obesity. Lower values are better. Change in the prevalence of female obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
difference in obesity prevalence among men over women. Difference in obesity prevalence in 2013 among men over women. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
difference in obesity prevalence among women over men. Difference in obesity prevalence in 2013 among women over men. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
obesity. Lower values are better. Percent of county population in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html. |
• |
change over 4 years in the prevalence of obesity. Lower values are better. Change in the prevalence of obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
change over 9 years in the prevalence of diabetes. Lower values are better. Change in the prevalence of diabetes from 2004 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
change in median rent for a 0-bedroom (studio/efficiency) unit over the last decade. Lower values are better. Change in median rent for a 0-bedroom (studio/efficiency) unit over the last decade 2007-2017. Source data: https://www.huduser.gov/portal/datasets/50per.html. |
• |
change in median rent for a 1-bedroom unit over the last decade. Lower values are better. Change in median rent for a 1-bedroom unit over the last decade 2007-2017. Source data: https://www.huduser.gov/portal/datasets/50per.html. |
• |
change in median rent for a 3-bedroom unit over the last decade. Lower values are better. Change in median rent for a 3-bedroom unit over the last decade 2007-2017. Source data: https://www.huduser.gov/portal/datasets/50per.html. |
• |
improved or maxed out on all the population and employment change metrics (5 of these; each county needs at least 4 with actual values to qualify). A 'yes' value is good. Has the county improved, or already reached an absolute best, on population increase, inbound migration, and unemployment rates?. |
• |
got worse or bottomed out on all the population and employment change metrics (5 of these; each county needs at least 4 with actual values to qualify). A 'no' value is good. Has the county gotten worse, or already reached an absolute worst, on population increase, inbound migration, and unemployment rates?. |
• |
improved or maxed out on all the obesity and diabetes change metrics (4 of these; each county needs at least 3 with actual values to qualify). A 'yes' value is good. Has the county improved, or already reached an absolute best, on obesity and diabetes rates?. |
• |
got worse or bottomed out on all the obesity and diabetes change metrics (4 of these; each county needs at least 3 with actual values to qualify). A 'no' value is good. Has the county gotten worse, or already reached an absolute worst, on obesity and diabetes rates?. |
• |
are better than the nationwide income averages in. Bigger sets are better. (1) The average nationwide value of median household income is $47,125, so better is above that. Median household income, 2014 (in 2014 dollars). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (2) The average nationwide value of per-capita income is $24,058, so better is above that. Per-capita income in the past 12 months (in 2014 inflation adjusted dollars), 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (3) The average nationwide value of poverty rate is 16.8%, so better is below that. Poverty rate for all ages, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (4) The average nationwide value of poverty rate for children age 0-17 is 23.7%, so better is below that. Poverty rate for children age 0-17, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (5) The average nationwide value of deep-poverty rate is 7.1%, so better is below that. Deep poverty rate for all ages, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (6) The average nationwide value of deep-poverty rate for children age 0-17 is 10.4%, so better is below that. Deep poverty rate for children, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
are worse than the nationwide income averages in. Smaller sets are better. (1) The average nationwide value of median household income is $47,125, so worse is below that. Median household income, 2014 (in 2014 dollars). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (2) The average nationwide value of per-capita income is $24,058, so worse is below that. Per-capita income in the past 12 months (in 2014 inflation adjusted dollars), 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (3) The average nationwide value of poverty rate is 16.8%, so worse is above that. Poverty rate for all ages, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (4) The average nationwide value of poverty rate for children age 0-17 is 23.7%, so worse is above that. Poverty rate for children age 0-17, 2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (5) The average nationwide value of deep-poverty rate is 7.1%, so worse is above that. Deep poverty rate for all ages, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (6) The average nationwide value of deep-poverty rate for children age 0-17 is 10.4%, so worse is above that. Deep poverty rate for children, 2010-2014. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
are better than the nationwide averages in. Bigger sets are better. (1) The average nationwide value of overall obesity (obesity) is 31.0%, so better is below that. Percent of county population in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (2) The average nationwide value of male obesity is 30.9%, so better is below that. Percent of men in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (3) The average nationwide value of female obesity is 31.0%, so better is below that. Percent of women in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (4) The average nationwide value of change over 4 years in overall obesity (change over 4 years in the prevalence of obesity) is +5.2%, so better is below that. Change in the prevalence of obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html (5) The average nationwide value of change over 4 years in male obesity (change over 4 years in the prevalence of male obesity) is +5.7%, so better is below that. Change in the prevalence of male obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html (6) The average nationwide value of change over 4 years in female obesity (change over 4 years in the prevalence of female obesity) is +4.8%, so better is below that. Change in the prevalence of female obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
are worse than the nationwide averages in. Smaller sets are better. (1) The average nationwide value of overall obesity (obesity) is 31.0%, so worse is above that. Percent of county population in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (2) The average nationwide value of male obesity is 30.9%, so worse is above that. Percent of men in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (3) The average nationwide value of female obesity is 31.0%, so worse is above that. Percent of women in 2013 who are obese. Source: http://www.cdc.gov/diabetes/data/county.html (4) The average nationwide value of change over 4 years in overall obesity (change over 4 years in the prevalence of obesity) is +5.2%, so worse is above that. Change in the prevalence of obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html (5) The average nationwide value of change over 4 years in male obesity (change over 4 years in the prevalence of male obesity) is +5.7%, so worse is above that. Change in the prevalence of male obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html (6) The average nationwide value of change over 4 years in female obesity (change over 4 years in the prevalence of female obesity) is +4.8%, so worse is above that. Change in the prevalence of female obesity from 2009 to 2013. Source data: http://www.cdc.gov/diabetes/data/county.html. |
• |
are better than the nationwide averages in adults of age 25+ with. Bigger sets are better. (1) The average nationwide value of a bachelors degree or higher (adults of age 25+ with a bachelors degree or higher) is 20.1%, so better is above that. Percent of county population during 2010-2014 who are 25 years old or older with bachelor's degree or higher. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (2) The average nationwide value of less than a bachelors degree (adults of age 25+ with less than a bachelors degree) is 79.9%, so better is below that. Percent of county population during 2010-2014 who are 25 years old or older with no bachelor's degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), Ed3SomeCollegePct (some college credit but no associate degree or higher), and Ed4AssocDegreePct (associate degree but no bachelor's degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (3) The average nationwide value of less than an associate degree (adults of age 25+ with less than an associate degree) is 71.8%, so better is below that. Percent of county population during 2010-2014 who are 25 years old or older with no associate degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), and Ed3SomeCollegePct (some college credit but no associate degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (4) The average nationwide value of no college credits (adults of age 25+ with no college credits) is 49.8%, so better is below that. Percent of county population during 2010-2014 who are 25 years old or older with no college credits. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED)and Ed2HSDiplomaOnlyPct (high school diploma only). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (5) The average nationwide value of no high school diploma or GED (adults of age 25+ with no high school diploma or GED) is 15.0%, so better is below that. Percent of persons during 2010-2014 with no high school diploma or GED, adults 25 and over, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |
• |
are worse than the nationwide averages in adults of age 25+ with. Smaller sets are better. (1) The average nationwide value of a bachelors degree or higher (adults of age 25+ with a bachelors degree or higher) is 20.1%, so worse is below that. Percent of county population during 2010-2014 who are 25 years old or older with bachelor's degree or higher. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (2) The average nationwide value of less than a bachelors degree (adults of age 25+ with less than a bachelors degree) is 79.9%, so worse is above that. Percent of county population during 2010-2014 who are 25 years old or older with no bachelor's degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), Ed3SomeCollegePct (some college credit but no associate degree or higher), and Ed4AssocDegreePct (associate degree but no bachelor's degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (3) The average nationwide value of less than an associate degree (adults of age 25+ with less than an associate degree) is 71.8%, so worse is above that. Percent of county population during 2010-2014 who are 25 years old or older with no associate degree or higher. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED), Ed2HSDiplomaOnlyPct (high school diploma only), and Ed3SomeCollegePct (some college credit but no associate degree or higher). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (4) The average nationwide value of no college credits (adults of age 25+ with no college credits) is 49.8%, so worse is above that. Percent of county population during 2010-2014 who are 25 years old or older with no college credits. Calculated by adding Ed1LessThanHSPct (no high school diploma or GED)and Ed2HSDiplomaOnlyPct (high school diploma only). Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx (5) The average nationwide value of no high school diploma or GED (adults of age 25+ with no high school diploma or GED) is 15.0%, so worse is above that. Percent of persons during 2010-2014 with no high school diploma or GED, adults 25 and over, 2010-14. Source: http://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america.aspx. |