- What is the Number of Residents Without Insurance ?
- What is the Percent With Health Insurance?
- What is the Number of Residents?
- What is the Population Count?
- 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?
The percent without health insurance of Bethel Census Area, AK was 36.10% for 18 to 64, all races, both sexes and all income levels in 2014.
Percent Uninsured by Income Level
Percent Uninsured by Race
Health and Health Insurance Datasets Involving Bethel Census Area, AK
- API data.pa.gov | Last Updated 2018-07-25T18:50:47.000Z
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 chhs.data.ca.gov | Last Updated 2017-02-17T22:33:14.000Z
The poverty rate (US Census-defined) table contains data on the percentage of the total population living below the poverty level, percentage of children living below the poverty level, and concentrated poverty data for California, its regions, counties, cities, towns, and Census tracts. Data for multiple time periods (2000, 2005-2007, 2008-2010, and 2006-2010) and with race/ethnicity stratification is included in the table. Concentrated poverty is the percentage of the poor living in Census tracts where 40% of the population or higher, are poor. The poverty rate 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). Poverty is an important social determinant of health (see http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=39) that can impact people’s access to basic necessities (housing, food, education, jobs, and transportation), and is associated with higher incidence and prevalence of illness, and with reduced access to quality health care. More information on the data table and a data dictionary can be found in the About/Attachments section.
- 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.ramseycounty.us | Last Updated 2017-08-10T19:21:17.000Z
Dataset showing responses to questions on race and ethnicity. The data on race were derived from answers to the question on race that was asked of all people during the decennial (every ten years) Census. The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country, and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or socio-cultural groups. Definitions from OMB guide the Census Bureau in classifying written responses to the race question: White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander Some Other Race Two or More Races There are two minimum categories for ethnicity: Hispanic or Latino and Not Hispanic or Latino. The federal government considers race and Hispanic origin to be two separate and distinct concepts. Hispanics and Latinos may be of any race
- API chhs.data.ca.gov | Last Updated 2017-06-14T18:11:25.000Z
This table contains data on the percent of residents aged 25 years and older educational attainment (percent completing high school, associates degree, college or more advanced degree) for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. 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). Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information about the data table and a data dictionary can be found in the About/Attachments section.
- API chhs.data.ca.gov | Last Updated 2017-02-17T22:10:28.000Z
This table contains data on the percent of population residing within ½ mile of a major transit stop for four California regions and the counties, cities/towns, and census tracts within the regions. The percent was calculated using data from four metropolitan planning organizations (San Diego Association of Governments, Southern California Association of Governments, Metropolitan Transportation Commission, and Sacramento Council of Governments) and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. A strong and sustainable transportation system supports safe, reliable, and affordable transportation opportunities for walking, bicycling, and public transit, and helps reduce health inequities by providing more opportunities for access to healthy food, jobs, health care, education, and other essential services. Active and public transportation promote health by enabling individuals to increase their level of physical activity, potentially reducing the risk of heart disease and obesity, improving mental health, and lowering blood pressure. More information about the data table and a data dictionary can be found in the About/Attachments section.
- API opendata.ramseycounty.us | Last Updated 2017-08-11T13:25:58.000Z
Dataset showing the average income in dollars per capita by race and ethnicity.
- API opendata.ramseycounty.us | Last Updated 2017-08-10T19:18:13.000Z
Dataset showing the percent of residents in poverty by county. Following the Office of Management and Budget’s (OMB’s) Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If the total income for a family or unrelated individual falls below the relevant poverty threshold, then the family (and every individual in it) or unrelated individual is considered in poverty.
- API opendata.ramseycounty.us | Last Updated 2017-08-14T12:50:41.000Z
Dataset showing average income for households and individuals by race and ethnicity.
- 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.