US Census Bureau States And Counties Health Insurance Estimates

$716 / year

This dataset contains estimates of health insured and uninsured population from 2008 and until 2015 at county and state level based on US Census Bureau program, The Small Area Health Insurance Estimates (SAHIE) program. For every state and county for each demographic group, defined by age, gender, race/ethnicity and income relative to poverty, the estimated number of persons insured and uninsured is given along with the margin of error.

Complexity

The Small Area Health Insurance Estimates (SAHIE) program at the U.S. Census Bureau produces estimates of numbers and proportions of those with and without health insurance coverage for demographic groups within states and counties. The demographic groups are defined by age, sex, and income, and in addition, for states by race and ethnicity. Income groups are defined in terms of income-to-poverty ratio (IPR), which is the family income divided by the appropriate federal poverty level.

The estimates are for groups that some of them overlap or are contained in one or another domain. However, actual modeling is done at a “base” level at which domains are disjoint, and are chosen so that the estimates needed for publication can be obtained as needed by aggregation. For example, for states, was done the actual modeling for the full cross-classification of:

– Four age categories: 0-64, 18-64, 40-64, 50-64; a fifth age category, 21-64, was added in release year 2014.
– Five race/ethnicity categories: all races, Hispanic, White not Hispanic, Black not Hispanic and Hispanic (any race)
– Three sex categories: all sexes, male, female
– Five income groups: all incomes, and IPR categories 0-138%, 0-200%, 0-250%, and 0-400%; a sixth IPR category, 138-400%, was added in release year 2012.

The 2013 SAHIE were updated in order to provide a basis of comparison for the 2014 SAHIE which, for the first time, used more up-to-date Medicaid and Children’s Health Insurance Program (CHIP) source data. Both data, original and updated is contained in this dataset.

The SAHIE model is an “area level” model (Rao 2003) in that it uses survey estimates for areas or domains of interest rather than individual responses, and it uses other data that are aggregates rather than for individuals. Each part of the SAHIE model is similar to a well-known small area-level model, the Fay-Herriot model. The Fay-Herriot model is a hierarchical model in which the variables of interest occupy a “middle” level, between high-level parameters such as regression coefficients, and observed data.

The following primary data sources were used for states and counties:

– Census 2010
– Single-year ACS (American Community Survey) direct estimates
– 5-year ACS direct estimates
– Federal Tax Returns data
– Supplementary Nutrition Assistance Program data
– Medicaid/Children’s Health Insurance Program participation data
– Demographic population estimates
– County Business Patterns

Date Created

2011-11-28

Last Modified

2017-10-05

Version

2017-10-05

Update Frequency

Annual

Temporal Coverage

2008-2015

Spatial Coverage

United States

Source

John Snow Labs => United States Census Bureau

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

N/A

Keywords

Health Insurance Statistics, Health Insured, Health Uninsured, State Level Insurance, County Level Insurance, Small Area Estimates, Age Groups Insurance Estimates, Gender Groups Insurance Estimates, Race Groups Insurance Estimates, Income Groups Insurance Estimates

Other Titles

US Census Bureau Small Area Health Insurance Estimates Starting 2008, US State And County Level Health Insured Among Demographic Groups

NameDescriptionTypeConstraints
YearThe year to which the estimates are correspondingdaterequired : 1
VersionThe version of 2013 estimatesstringenum : Array
Geographic_LevelThe geographic level of the estimatesstringenum : Array required : 1
StateThe name of the state where the demographic group is livingstringlevel : Required
State_AbbreviationThe abbreviated name of the state where the demographic group is livingstringrequired : 1
CountyThe name of the county or equivalent area where the demographic group is livingstring-
State_County_FIPS_CodeThe 5 digits state Federal Information Processing Standard (FIPS) codeintegerrequired : 1 level : Nominal
Age_GroupThe age group of the demographic groupstringenum : Array required : 1
GenderThe gender of the demographic groupstringenum : Array required : 1
RaceThe race/ethnicity of the demographic groupstringenum : Array required : 1
Income_To_Poverty_RatioThe ratio of family income to the federal poverty threshold of the demographic groupstringenum : Array required : 1
PopulationThe number of persons in the demographic groupintegerlevel : Ratio
Margin_Of_Error_PopulationThe margin of error of the estimated number of persons in the demographic group; it is the difference between an estimate and its upper or lower confidence bounds (based on a 90 percent confidence level); values of 0 should be assumed to be <1integerlevel : Ratio
Count_of_Health_Uninsured_PopulationThe estimated number of health uninsured persons in the demographic groupintegerlevel : Ratio
Margin_Of_Error_UninsuredThe margin of error of the estimated number of health uninsured persons in demographic group; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <1integerlevel : Ratio
Count_of_Health_Insured_PopulationThe estimated number of health insured persons in the demographic groupintegerlevel : Ratio
Margin_Of_Error_InsuredThe margin of error of the estimated number of health insured persons in demographic group; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <1integerlevel : Ratio
Percent_Of_UninsuredThe estimated percent of health uninsured persons in the demographic groupnumberlevel : Ratio
Margin_Of_Error_Percent_Of_UninsuredThe margin of error of the estimated percent of health uninsured persons in demographic group; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <0.1numberlevel : Ratio
Percent_Of_InsuredThe estimated percent of health insured persons in the demographic groupnumberlevel : Ratio
Margin_Of_Error_Percent_Of_InsuredThe margin of error of the estimated percent of health insured persons in demographic group; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <0.1numberlevel : Ratio
Percent_Of_Uninsured_All_IncomeThe estimated percent of health uninsured persons in the demographic group, regardless of the income levelnumberlevel : Ratio
Margin_Of_Error_Percent_Of_Uninsured_All_IncomeThe margin of error of the estimated percent of health uninsured persons in demographic group, regardless of the income level; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <0.1numberlevel : Ratio
Percent_Of_Insured_All_IncomeThe estimated percent of health insured persons in the demographic group, regardless of the income levelnumberlevel : Ratio
Margin_Of_Error_Percent_Of_Insured_All_IncomeThe margin of error of the estimated percent of health insured persons in demographic group, regardless of the income level; it is the difference between an estimate and its upper or lower confidence bounds; values of 0 should be assumed to be <0.1numberlevel : Ratio
YearVersionGeographic_LevelStateState_AbbreviationCountyState_County_FIPS_CodeAge_GroupGenderRaceIncome_To_Poverty_RatioPopulationMargin_Of_Error_PopulationCount_of_Health_Uninsured_PopulationMargin_Of_Error_UninsuredCount_of_Health_Insured_PopulationMargin_Of_Error_InsuredPercent_Of_UninsuredMargin_Of_Error_Percent_Of_UninsuredPercent_Of_InsuredMargin_Of_Error_Percent_Of_InsuredPercent_Of_Uninsured_All_IncomeMargin_Of_Error_Percent_Of_Uninsured_All_IncomePercent_Of_Insured_All_IncomeMargin_Of_Error_Percent_Of_Insured_All_Income
2012CountyHawaiiHIKalawao County150050-64MaleAll races138% - 400%
2014CountyHawaiiHIKalawao County150050-64MaleAll races138% - 400%
2015CountyHawaiiHIKalawao County150050-64MaleAll races138% - 400%
2012CountyHawaiiHIKalawao County1500518-64MaleAll races138% - 400%
2012CountyHawaiiHIKalawao County1500540-64MaleAll races138% - 400%
2012CountyHawaiiHIKalawao County1500550-64MaleAll races138% - 400%
2014CountyHawaiiHIKalawao County1500518-64MaleAll races138% - 400%
2014CountyHawaiiHIKalawao County1500540-64MaleAll races138% - 400%
2014CountyHawaiiHIKalawao County1500550-64MaleAll races138% - 400%
2014CountyHawaiiHIKalawao County1500521-64MaleAll races138% - 400%