Uninsured Adults*
About
Percentage of adults under age 65 without health insurance. The 2025 Annual Data Release used data from 2022 for this measure.
Lack of health insurance coverage is a significant barrier to accessing needed health care and maintaining financial security. The high cost of insurance is the main reason many individuals remain uninsured. Additionally, many do not have employer-sponsored coverage, and some, especially low-income adults in states that have not expanded Medicaid, are ineligible for financial assistance for coverage. Compared to those with insurance, uninsured individuals are less likely to receive preventive care and treatment for severe health conditions or chronic illnesses. When they do seek medical care, they often encounter overwhelming medical expenses.1
Data and methods
Data Source
Small Area Health Insurance Estimates
The US Census Bureau's Small Area Health Insurance Estimates (SAHIE) program produces estimates of health insurance coverage for all states and counties. In July 2005, SAHIE released the first nationwide set of county-level estimates on the number of people without health insurance coverage for all ages and those under 18 years old. SAHIE releases estimates of health insurance coverage by age, sex, race, Hispanic origin, and income categories at the state level and by age, sex, and income categories at the county level.
Website to download data
For more detailed methodological information
Key Measure Methods
Uninsured Adults is a percentage
Uninsured Adults is the percentage of the population ages 18 to 64 that have no health insurance coverage in a given county.
Uninsured Adults is created using statistical modeling
Uninsured Adults is created using complex statistical modeling. Modeling generates more stable estimates for places with small numbers of residents or survey responses. There are also drawbacks to using modeled data. The smaller the population or sample size of a county, the more the estimates are derived from the model itself and the less they are based on survey responses. Models make statistical assumptions about relationships that may not hold in all cases. Finally, there is no perfect model and each model generally has limitations specific to their methods.
Caution should be used when comparing these estimates across states
The data source uses modelling, and it is not clear if the model accounts for state-level effects.
Numerator
The numerator is the number of people ages 18 to 64 who currently have no health insurance coverage. A person is uninsured if they are not currently covered by insurance through a current/former employer or union, purchased from an insurance company, Medicare, Medicaid, Medical Assistance, any kind of government-assistance plan for those with low incomes or disability, TRICARE or other military health care, Indian Health Services, VA, or any other health insurance or health coverage plan.
Denominator
The denominator is the county population ages 18 to 64.
Can This Measure Be Used to Track Progress
This measure can be used to track progress with come caveats. Modeled estimates have specific drawbacks with regard to their usefulness in tracking progress in communities. Modeled data are not particularly good at incorporating the effects of local conditions, such as health promotion policies or unique population characteristics, into their estimates. Counties trying to measure the effects of programs and policies on the data should use great caution when using modeled estimates. In order to better understand and validate modeled estimates, confirming this data with additional sources of data at the local level is particularly valuable.
Finding More Data
Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:
- Age
- Gender
- Race
- Income
- Subcounty Area
On the Small Area Health Insurance Estimates (SAHIE) website, you can stratify by age, gender, and poverty ratios. In addition, the Community Health Needs Assessment Report has a variety of data available, including health insurance by gender, age group, race/ethnicity at the county-level as well as a census-tract level map. These data are available by clicking “view tool,” selecting a location, selecting your indicators (insurance is under Other Social & Economic Factors), and clicking on reports.
References
- Tolbert J, Cervantes S, Bell C, Damico A. Key facts about the uninsured population. KFF. 2024.