- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Mean Job Proximity Index?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Mean Environmental Health Hazard Index?
The population count of Fairbanks North Star Borough, AK was 99,319 in 2014.
Demographics and Population Datasets Involving Fairbanks North Star Borough, AK
- API data.pa.gov | Last Updated 2017-07-31T18:19:23.000Z
This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.
- API data.vbgov.com | Last Updated 2017-10-12T13:51:45.000Z
This dataset provides demographic information from the American Community Survey about residents of Virginia Beach. This data was originally provided in the executive summary of the City of Virginia Beach’s Operating Budget.
- API opendata.utah.gov | Last Updated 2014-10-31T18:29:13.000Z
Median Household Income All States 2000-2012
- API chhs.data.ca.gov | Last Updated 2017-02-17T22:34:56.000Z
This table contains data on the percentage of the total population living within 1/4 mile of alcohol outlets (off-sale, on-sale, total) for California, its regions, counties, county divisions, cities, towns, and Census tracts. Population data is from the 2010 Decennial Census, while the alcohol outlet location data is from 2014 (April). Race/ethnicity stratification is included in the table. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity (http://www.cdph.ca.gov/programs/Pages/HealthyCommunityIndicators.aspx). Some studies have found that proximity to alcohol outlets (living within walking distance) is positively associated with outcomes like excessive alcohol consumption and other alcohol related harms like injuries and violence. More information on the data table and a data dictionary can be found in the About/Attachments section.
- API opendata.utah.gov | Last Updated 2015-03-17T17:38:04.000Z
Number Of Minor Effect Illnesses From Exposure To All Pesticides By States
- API chhs.data.ca.gov | Last Updated 2017-06-14T18:09:22.000Z
This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity (https://www.cdph.ca.gov/Programs/OHE/Pages/Healthy-Communities-Data-and-Indicators-Project-(HCI).aspx). Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.
- API data.pa.gov | Last Updated 2017-07-19T15:40:20.000Z
This is a listing of Federal Information Processing Standard (FIPS) codes for each of the 67 counties in Pennsylvania. Information gathered from census data - https://www.census.gov/geo/reference/codes/cou.html For more technical details : Federal Information Processing Standards Publications (FIPS PUBS) are issued by the National Institute of Standards and Technology (NIST) after approval by the Secretary of Commerce pursuant to Section 111 (d) of the Federal Property and Administrative Services Act of 1949 as amended by the Computer Security Act of 1987, Public Law 100-235. Federal Information Processing Standard (FIPS) 6-4, Counties and Equivalent Entities of the U.S., Its Possessions, and Associated Areas -- 90 Aug 31 , provides the names and codes that represent the counties and other entities treated as equivalent legal and/or statistical subdivisions of the 50 States, the District of Columbia, and the possessions and freely associated areas of the United States. Counties are considered to be the "first-order subdivisions" of each State and statistically equivalent entity, regardless of their local designations (county, parish, borough, etc.).
- API opendata.utah.gov | Last Updated 2015-03-17T17:59:52.000Z
Incidence Of Brain And Central Nervous System Cancer Age 15 Under Per 1,000,000 All States
- API opendata.utah.gov | Last Updated 2015-03-17T17:35:10.000Z
Rates Of Esophageal Cancer Per 100,000 All States
- API opendata.utah.gov | Last Updated 2015-03-17T17:55:38.000Z
Incidence Rate Of Pancreatic Cancer Per 100,000 All States