Uninsured Children*

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Percentage of children under age 19 without health insurance. The 2024 Annual Data Release used data from 2021 for this measure.

Lack of health insurance coverage is a significant barrier to accessing needed health care and to maintaining financial security. A Kaiser Family Foundation report on access to healthcare foung that those without health insurance frequently delay their care and receive fewer preventative services, which can severely impact their health. In addition, there may be significant financial consequences; not having insurance can make people unable to cover their medical costs, leading to medical debt.1 Uninsured children are less likely to receive preventive care such as vaccinations and well child visits on time.2,3

Find strategies to address Uninsured Children*

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 Children is a percentage

Uninsured Children is the percentage of the population under age 19 that has no health insurance coverage in a given county.

Uninsured Children is created using statistical modeling

Uninsured Children 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.  


The numerator is the number of people under age 19 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.


The denominator is the county population under age 19.

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 uninsured children 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 Social & Economic Factors), and clicking on reports. 


1 Garfield R, Orgera K, Damico A. The uninsured and the ACA: A primer - key facts about health insurance and the uninsured amidst changes to the Affordable Care Act. San Francisco: Kaiser Family Foundation; 2019.

2 Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kang Y. coverage among children aged 19–35 months - United States, 2017. Morbidity and Mortality Weekly Reports (MMWR). 2018;67(40):1123-1128. 

3 Health insurance coverage improves child well-being. Rockville: Child Trends; 2017. Accessed: November 27, 2019. https://www.childtrends.org/publications/health-insurance-coverage-improves-child-well 

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