In This Report:
- In response to the pandemic, states were temporarily required to keep people covered by Medicaid enrolled over the course of the COVID-19 public health emergency in exchange for enhanced federal funding. This Medicaid protection helped to reduce the number and rate of uninsured children; 3.9 million children were uninsured in 2022 – tying 2017 for the second-lowest number in recent memory. The only year with fewer uninsured children was 2016. The uninsured rate for children was 5.1% in 2022, compared to 5.7% in 2019, the year before Medicaid’s pandemic-era continuous coverage protection took effect. Prior to the pandemic, the number of uninsured children had been increasing.
- Twenty-one states saw statistically significant declines in the rate and/or number of uninsured children, with Wyoming, North Dakota, Utah, New Mexico, and Texas seeing the greatest improvements. Despite these improvements, many of these states still had some of the highest uninsured rates in the country in 2022.
- Four states moved in the wrong direction, with Iowa, Maryland, Pennsylvania, and Wisconsin seeing statistically significant increases in the number and rate of uninsured children from 2019 to 2022. Iowa saw the largest jump with a 27% increase in the number of uninsured children. More than one in five uninsured children live in Texas, which has far more uninsured children than any other state.
- Nationally, child uninsured rates across demographic groups with children of nearly every age, race and ethnicity, and family income level seeing increased coverage. American Indian and Alaska Native children and children in low-income families saw the biggest reductions in their uninsured rates, likely reflecting the impact of the Medicaid continuous coverage protection. However, this protection has now been lifted and coverage losses resulting from the current process of renewing eligibility for all children threaten to reverse much of the progress seen over recent years. This unprecedented process of redetermining eligibility for nearly everyone covered by Medicaid, otherwise known as “unwinding” of the continuous coverage protection, will likely cause the uninsured rate for children to start moving in the wrong direction again as many eligible children lose Medicaid coverage and become uninsured.
Data from the U.S. Census Bureau’s American Community Survey (ACS) for 2022 finds that the number of uninsured children continued to decline over the pandemic period – most likely as a consequence of the continuous coverage protection in Medicaid put in place by one of the first COVID-19 rescue packages, the Families First Coronavirus Relief Act of 2020 (P.L. 116-127).1 The uninsured rate for children declined to 5.1 percent in 2022 from 5.7 percent in 2019. (See Figure 1.) Medicaid is the single largest source of coverage for children, and children were protected from administrative churning during the pandemic period. Prior to the pandemic, the uninsured rate for children had been rising 2 and it is likely to rise again, absent very aggressive action by federal and state policymakers, now that continuous coverage protections have been lifted and states are reassessing eligibility for everyone covered by Medicaid.3
The number of uninsured children nationwide in 2022 was 3.9 million, tying 2022 with 2017 for the second-lowest number in recent memory – with the exception of 2016 when continued implementation of the Affordable Care Act helped drive the number of uninsured children to its lowest level at 3.6 million (See Figure 2).
How are specific states doing?
Most states (36) saw a decline in the number and rate of uninsured children; twenty states saw a statistically significant decline in number from 2019 to 2022 and 17 states saw a statistically significant decline in rate over the examined time period. Children in Texas saw the greatest improvement in number by a considerable margin (a 141,000 decline in the number of uninsured children); Wyoming saw the greatest improvement in its child uninsured rate moving from 10.6% to 7.9% in 2022. Tables 1 and 2 list the top ten states where the largest declines in the number and rate of uninsured children occurred.
Only four states saw significant growth in their number and rate of uninsured children during the pandemic period (Iowa, Maryland, Pennsylvania, Wisconsin), with Iowa seeing the largest number increase in the country in percentage terms. See Appendix Tables 3 and 4 for a full list of state changes.
Despite improvement, Texas continues to be home to the largest number of uninsured children by far, accounting for 22% of all uninsured children. About 854,000 Texas children are uninsured. Florida and California follow with 336,000 and 287,000 respectively. Together these states account for more than one-third of uninsured children nationwide.
Six of the top ten metropolitan areas in the U.S. with the highest rates of uninsured children are in Texas (See Table 3). The map (Figure 3) shows the 12 Texas metro areas where more than 10% of children are uninsured.
While states in the Northeast tend to do better than the national average in terms of child uninsured rates, and states in the South and the Mountain West do worse, there is significant regional variation as Figure 4 shows.
What is the demographic profile of uninsured children?
Uninsured rates in the U.S. fell for children of nearly every age, race and ethnicity, and income level. Young children under age 6 saw their uninsured rate fall from 4.7% in 2021 to 4.3% in 2022, and the uninsured rate for school-aged children (ages 6 to 18) also fell from 6.1% in 2021 to 5.4% in 2022.
By race, White children and American Indian and Alaska Native children saw the largest improvements in their uninsured rates, although the share of American Indian and Alaska Native children who do not have coverage is still substantially higher than it is for other groups (See Figure 5). Children of another race or multiple races were the only group to see a significant increase in their uninsured rate, but this is likely related to recent demographic and survey changes that have meant that more children than ever are identified as “some other race” or as multiple races.4
Uninsured rates for both Hispanic/Latino and non-Hispanic/Latino children also improved. Although Latino children saw larger coverage gains from 2019-2022, their uninsured rate is still nearly twice as high as for non-Latino children.
Children in lower-income families also saw the largest improvements in uninsurance rates. Children in families at the lowest end of the income spectrum earning less than 138% of the Census Poverty Threshold (about $24,860 for a family of 3) saw the largest improvement from 2019-2022, likely reflecting the protective effect of Medicaid continuous coverage that kept low-income children enrolled in Medicaid coverage during the pandemic (See Table 4). Citizen children under 138% of the poverty line must be covered by Medicaid in every state; 35 states cover lawfully residing children as well and 11 cover all children regardless of immigration status (CA, DC, IL, MA, ME, NJ, NY, OR, RI, VT, WA).5
While the number of uninsured children declined over the pandemic period, these gains are unlikely to be sustained given the current Medicaid renewal process that is underway. As of this writing there has been a net decline in child Medicaid enrollment of at least two million.6 Procedural termination rates have been high in many states;7 and since children are more likely to be disenrolled while remaining eligible 8 this does not bode well for child uninsured rates when data become available for 2023 next year.
Data Sources and Changes
This report from the Georgetown University Center for Children and Families (CCF) analyzes data from the U.S. Census Bureau’s American Community Survey (ACS). The ACS randomly selects about 3.5 million households each year to be surveyed and conducts the survey year-round, with results published annually.
This report uses two ACS data products: 1) Health Insurance Historical Table HIC-5. Health Insurance Coverage Status and Type of Coverage by State — Children Under 19: 2008 to 2022; and 2) the 2022 1-Year ACS Estimates Detailed Tables published by the Census Bureau on data.census.gov. Please note that, because of differences in sample size and data processing, the estimates published in this report may differ from other estimates produced using either the 5-year ACS estimates or ACS microdata (including the Census Bureau’s Public Use Microdata Sample (PUMS) or the University of Minnesota’s Integrated Public Use Microdata Series (IPUMS)), despite the fact that all of these datasets are based on the American Community Survey.
Because of data quality issues related to the pandemic, the Census Bureau did not publish standard, comparable 1-year estimates for 2020; CCF excludes 2020 ACS data from all of its analyses.
In 2017, the Census Bureau updated the age categories to define children as individuals under age 19. (In previous years, children were classified as individuals under age 18). As a result, detailed table data from before and after 2017 should not be compared. When examining longer-term trends, CCF instead uses the HIC-5 table, which harmonizes the age group to children under age 19 before and after 2017.
Margin of Error, Data Reliability and Suppression, and Statistical Significance
The Census Bureau provides a margin of error (MOE) at a 90% confidence level for each estimate it publishes. Because ACS data are based on a sample of the population (as opposed to the full population), there is a level of uncertainty associated with each estimate. This uncertainty is captured by the MOE. When CCF calculates a new estimate with ACS data (such as when we combine racial/ethnic groups or calculate percentages/rates), we also calculate its margin of error, using formulas provided by the Census Bureau. CCF does not account for MOEs when ranking states by the number and percent of uninsured children by state. Although we do not publish MOEs in this report, they are available upon request.
CCF uses the Census Bureau’s Statistical Testing Tool to determine statistical significance between estimates at a 90% confidence level. Differences between estimates should not be assumed to be statistically significant unless specifically discussed or marked as such.
CCF calculates coefficients of variation (CVs, also known as relative standard errors) to measure data reliability for each estimate. The CV measures the relative amount of error in an estimate by comparing how large its standard error is to the estimate itself, with the lower the CV, the more reliable the estimate. CCF suppresses any estimate with a CV larger than 25 percent.
The Census Bureau publishes 1-year ACS estimates for all geographic areas with a population of 65,000 or more, which includes all regions, states (including the District of Columbia), and some counties. Please note that 1-year estimates will differ from 5-year estimates, which CCF may use elsewhere for analyses of smaller geographic areas like counties or school districts. CCF uses Census Bureau designations to report regional data. The HIC-5 table used throughout this report does not contain data for Puerto Rico or other territories; please see CCF's State Data Hub for additional data for Puerto Rico.
Data on poverty thresholds only include individuals for whom the Census Bureau could determine poverty status for the past year. This population is slightly smaller than the total non-institutionalized population of the U.S. (the universe for all other data used in this report). The Census Bureau determines an individual’s poverty status by comparing that person’s income in the past 12 months to Census Poverty Thresholds (CPTs). Census Poverty Thresholds differ from the poverty guidelines (commonly known as the Federal Poverty Level or FPL) determined by the Department of Health and Human Services (HHS), and may differ considerably from the separate FPLs that HHS determines for Alaska and Hawaii. Additionally, Census Poverty Thresholds may include some income sources that state Medicaid and CHIP agencies do not count for purposes of determining income eligibility using Modified Adjusted Gross Income (MAGI).
Health Insurance Coverage and Medicaid Undercount
ACS data represents a “point-in-time” estimate of an individual’s insurance coverage, meaning that the survey collects information on the respondent’s coverage only at the moment they complete the form, not at another point during the year. (The ACS is conducted over the course of the year.) The ACS groups coverage into the following categories: employer-based health insurance only, direct purchase health insurance only, Medicare coverage only, Medicaid/means-tested public coverage only (including CHIP), TRICARE/military health coverage only, VA health coverage only, two or more types of health insurance coverage, and no health insurance coverage. The Census Bureau does not consider access to Indian Health Service (IHS) services alone as a comprehensive form of health insurance coverage. Consequently, individuals who indicate that IHS is their only source of coverage are designated as uninsured. Individuals can report more than one source of coverage.
Please note that ACS estimates are not adjusted by the Census Bureau (or by CCF) to address the “Medicaid undercount” observed when comparing the number of individuals covered by Medicaid and CHIP in surveys such as the ACS to the reported numbers of individuals enrolled in Medicaid and CHIP using federal and state administrative data. For example, ACS data show that 30.1 million children had Medicaid/CHIP coverage (either alone or in combination with another type of coverage) in 2022, while administrative data show average enrollment over the same period equaled about 41.9 million: a difference of nearly 12 million children. This undercount is not unique to the ACS, though the extent of the undercount varies among federal surveys. Researchers attribute the Medicaid undercount to a combination of factors like sampling error and differences in demographic characteristics (for example, adults and individuals with higher incomes are less likely to report Medicaid coverage); reporting error, where individuals may respond that they do not have coverage or have a type of coverage other than Medicaid; and differences in how surveys and administrative data define coverage, such as estimates taken at a point in time versus over the course of a year. In 2022, the Medicaid continuous coverage provision may affect children’s reported coverage source—including uninsurance—if more misreported their coverage source including families who were unaware that they still had Medicaid coverage. Moreover, previous research shows that the Medicaid undercount has appeared to increase substantially since the start of the pandemic. Finally, recent research on the decennial Census shows that young children as a group are consistently and significantly undercounted, likely further worsening the Medicaid undercount among children.
“Children” are defined as individuals under age 19 (ages 0-18).
The ACS allows respondents to self-identify as the following races: White, Black/African-American, American Indian/Alaska Native, Asian, Native Hawaiian/Pacific Islander, “Some other race,” and “Two or more races.” To improve sample sizes and data reliability, CCF combines estimates for Asian and Native Hawaiian or Other Pacific Islander and reports the calculations as “Asian, Native Hawaiian, or Other Pacific Islander” and also combines “Some other race” alone and “Two or more races” and reports the calculations as “Other/Multiracial.” Except for Other/Multiracial, all racial categories refer to individuals who reported belonging only to one race.
The Census Bureau recognizes and reports race and Hispanic origin (i.e., ethnicity) as separate and distinct concepts and variables. “Hispanic or Latino” refers to individuals who self-identified as being Hispanic or Latino, while “non-Hispanic/Latino” refers to individuals who indicated that they were not of Hispanic or Latino origin. CCF calculates estimates for non-Hispanic or Latino populations by subtracting estimates for Hispanic or Latino individuals from the total population estimate for children. As “Hispanic or Latino” refers to a person’s ethnicity, Hispanic and non-Hispanic individuals may be of any race.
In 2020, the Census Bureau made changes to the ACS race and ethnicity questions, which may affect health coverage comparisons related to race and ethnicity. These included changes to the instructions and examples listed with some race and Hispanic origin response options, additional write-in response options for “White” and “Black or African American” categories, and changes to the way the Census Bureau processes write-in responses. These changes may affect the “Some Other Race” or multiple race categories in particular. For example, as noted above, 10.2 million children identified as another race or multiracial in 2019, representing 13 percent of the total child population. In 2022, this number increased to 21.3 million or 28 percent of the child population. This increase, which may be related to changes in question design, may also affect the distribution of children across other racial groups. As a result, the Census Bureau recommends caution in comparing 2019-2021 ACS estimates related to race and caution in comparing both 2019-2021 and 2021-2022 ACS estimates related to ethnicity.
1 T. Brooks and A. Schneider, “Families First Coronavirus Response Act Medicaid and CHIP Provisions Explained” (Washington: Georgetown Center for Children and Families, March 2020), available at here.
4 Beginning in 2020, the Census Bureau made changes to the race and ethnicity questions on the ACS which may affect health coverage comparisons related to race and ethnicity. These changes may affect the “Some Other Race” or multiple race categories in particular. For example, 10.2 million children identified as another race or multiracial in 2019, representing 13 percent of the total child population. In 2022, this number increased dramatically to 21.3 million or 28 percent of the child population.
5 T. Brooks, et al., “Medicaid and CHIP Eligibility, Enrollment, and Renewal Policies as States Prepare for the Unwinding of the Pandemic-Era Continuous Enrollment Provision” (Washington: Kaiser Family Foundation and Georgetown University Center for Children and Families, April 2023), available here.
7 See “What is happening with Medicaid renewals in each state?” Georgetown University Center for Children and Families, available here, and “Medicaid Enrollment and Unwinding Tracker” Kaiser Family Foundation, available here.
8 Assistant Secretary for the Office of Planning and Evaluation, “Unwinding the Medicaid Continuous Enrollment Provision: Projected Enrollment Effects and Policy Approaches*” (Washington: August 2022), available here.