In 2023, 10.9 percent of people aged 18 to 64 in the United States didn't have health insurance, the lowest in the provided time interval. This statistic contains data on the percentage of U.S. Americans without health insurance coverage from 1997 to 2023, by age.

In 2023, 25 million people in the United States had no health insurance. The share of Americans without health insurance saw a steady increase from 2015 to 2019 before starting to decline in 2020 to 2023. Factors like the implementation of Medicaid expansion in additional states and growth in private health insurance coverage led to the decline in uninsured population, despite the economic challenges due to the pandemic in 2020. Positive impact of Affordable Care Act In the U.S. there are public and private forms of health insurance, as well as social welfare programs such as Medicaid and programs just for veterans such as CHAMPVA. The Affordable Care Act (ACA) was enacted in 2010, which dramatically reduced the share of uninsured Americans, though there’s still room for improvement. In spite of its success in providing more Americans with health insurance, ACA has had an almost equal number of proponents and opponents since its introduction, though the share of Americans in favor of it has risen since mid-2017 to the majority. Persistent disparity among ethnic groups The share of uninsured people is higher in certain demographic groups. For instance, Hispanics continue to be the ethnic group with the highest rate of uninsured people, even after ACA. Meanwhile the share of uninsured White and Asian people is lower than the national average.

The graph presents the number of people with health insurance in the United States from 2013 to 2023. The x-axis represents the years, ranging from 2013 to 2023, while the y-axis shows the number of insured individuals in millions. Throughout this period, the number of people with health insurance rose from approximately 271.6 million in 2013 to 305 million in 2023, marking the lowest value in 2013 and the highest in 2023. The data exhibits a steady upward trend in health insurance coverage over the ten-year span. This information is depicted in a line graph, effectively highlighting the annual increase in the insured population.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black). Later vintages of this layer have a different age group for children that includes age 18. This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Graph and download economic data for Health Insurance Coverage: People Not Covered in Indiana (DISCONTINUED) (INHICNOTCOV) from 1999 to 2012 about covered, health, insurance, IN, persons, and USA.

As of 2023, nearly *** million people in the United States had some kind of health insurance, a significant increase from around *** million insured people in 2010. However, as of 2023, there were still approximately ** million people in the United States without any kind of health insurance. Insurance coverage The United States does not have universal health insurance, and so health care cost is mostly covered through different private and public insurance programs. In 2021, almost ** percent of the insured population of the United States were insured through employers, while **** percent of people were insured through Medicaid, and **** percent of people through Medicare. As of 2022, about *** percent of people were uninsured in the U.S., compared to ** percent in 2010. The Affordable Care Act The Affordable Care Act (ACA) significantly reduced the number of uninsured people in the United States, from **** million uninsured people in 2013 to **** million people in 2015. However, since the repeal of the individual mandate the number of people without health insurance has risen. Healthcare reform in the United States remains an ongoing political issue with public opinion on a Medicare-for-all plan consistently divided.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

This layer shows the percentage of people without health insurance in the U.S. by state and county, from American Community Survey 5-year estimates: 2011-2015 (Table GCT2701). The map switches from state data to county data as the map zooms in. The national average was 13.0%, down from approximately 20% in 2005.A person’s ability to access health services has a profound effect on every aspect of his or her health. Many Americans do not have a primary care provider (PCP) or health center where they can receive regular medical services. People without medical insurance are more likely to lack a usual source of medical care, such as a PCP, and are more likely to skip routine medical care due to costs, increasing their risk for serious and disabling health conditions. When they do access health services, they are often burdened with large medical bills and out-of-pocket expenses. Increasing access to both routine medical care and medical insurance are vital steps in improving the health of all Americans.

Graph and download economic data for Health Insurance Coverage: Total Number of People in California (DISCONTINUED) (CAHICTOTAL) from 1999 to 2012 about health, insurance, CA, persons, and USA.

In 2023, nearly ** percent of people in the United States had public health insurance, the share of people with private health insurance has gradually increased in the provided time interval. This statistic contains data on the number of U.S. Americans with government health insurance coverage from 1997 to 2023.

This layer shows health insurance coverage sex and race by age group and is symbolized to show shows the percentage of the Black or African American population without health insurance. This is shown by 2020 census tract centroids. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black)This layer uses the 2020 American Community Survey (ACS) 5-year data and contains estimates and margins of error. There are additional calculated attributes related to this topic, which can be mapped or used within analysis. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. For more information regarding the ACS vintage, table sources and data processing notes, please see the item page for the source map service.

Table contains county residents without health insurance. Data are summarized as people of all ages and those 19 to 64 years old. Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B27001; data accessed on June 30, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographypop (Numeric): Population for whom health insurance coverage was assessedt_uninsured (Numeric): Number of people (all ages) who were without health insurancep_uninsured (Numeric): Percent of people (all ages) who were without health insurancet_19_64 (Numeric): Population ages 19 to 64 years for whom health insurance coverage was assessedt_unins_19_64 (Numeric): Number of people ages 19 to 64 years who were without health insurancep_unins_19_64 (Numeric): Percent of people ages 19 to 64 years who were without health insurance

Graph and download economic data for Health Insurance Coverage: Total Number of People in New York (DISCONTINUED) (NYHICTOTAL) from 1999 to 2012 about health, insurance, NY, persons, and USA.

As of 2016, the projected number of people that would become uninsured would increase dramatically if President Trump were to recall or replace the Affordable Care Act (also called Obamacare). Should President Trump repeal the Affordable Care Act without a replacement, it is estimated that the number of U.S. residents that would become uninsured would increase from 27 million to 49 million.

U.S. health insurance

The U.S. health insurance system is considered a hybrid system of private funding, private business funding and some government funding for individual health coverage. There is currently no universal health insurance system for U.S. residents. The leading health insurance company in the U.S. as of 2017, by direct premiums written was UnitedHealth Group Inc., followed by Anthem Inc. Revenues generated by life and health insurance companies have more or less stagnated in recent history.

The Affordable Care Act

The Affordable Care Act was enacted in 2010 with the goals of making affordable health insurance available to more people and to expand Medicaid coverage in the U.S. Since 2010 the number of U.S. residents under the age of 65 without health insurance has dropped dramatically. Recent data also indicates that Medicaid enrollment has increased in recent years. It is estimated that repealing the Affordable Care Act in the United States could result in the approximately 26.5 thousand excess deaths per year.

Graph and download economic data for Health Insurance Coverage: People Not Covered in the District of Columbia (DISCONTINUED) (DCHICNOTCOV) from 1999 to 2012 about covered, DC, health, insurance, persons, and USA.

Graph and download economic data for Health Insurance Coverage: Total Number of People in Hawaii (DISCONTINUED) (HIHICTOTAL) from 1999 to 2012 about HI, health, insurance, persons, and USA.

This layer shows the predominant level of insurance coverage for non-citizens in the USA. This is shown by county centroids. The data values are from the 2012-2016 American Community Survey 5-year estimate in the B27020 Table for health insurance coverage status and type by citizenship status. This map helps to answer a few questions:Do non-citizens have health insurance?Where are the non-citizens in the US?The color of the symbols represent the most common form of insurance held by foreign born non-citizens in the USA. This predominance map style compares the count of people who are insured or not insured, and returns the value with the highest count.Foreign born non-citizen without insuranceForeign born non-citizen with insuranceThe size of the symbol represents the count of all non-citizens in the area, which shows in the legend as "sum of categories". The strength of the color represents HOW predominant the form of insurance is for non-citizens. The stronger the symbol, the larger proportion of the non-citizens.This map is designed for a dark basemap such as the Human Geography Basemap or the Dark Gray Canvas Basemap. It helps show a regional pattern about the uninsured and insured non-citizen population. This data was downloaded from the United States Census Bureau American Fact Finder on March 1, 2018. It was then joined with 2016 vintage centroid points and hosted to ArcGIS Online and into the Living Atlas. The data contains additional attributes that can be used for mapping and analysis. Nationally, the breakdown of insurance for the civilian noninstitutionalized population in the US is:Total:313,576,137+/-10,365Native Born:271,739,505+/-102,340With health insurance coverage246,142,724+/-281,131With private health insurance186,765,058+/-576,448With public coverage92,452,853+/-209,370No health insurance coverage25,596,781+/-190,502Foreign Born:41,836,632+/-109,590Naturalized:19,819,629+/-35,976With health insurance coverage17,489,342+/-42,261With private health insurance12,927,060+/-50,505With public coverage6,687,375+/-16,733No health insurance coverage2,330,287+/-20,148Noncitizen:22,017,003+/-118,842With health insurance coverage13,243,825+/-44,108With private health insurance9,320,483+/-26,031With public coverage4,459,972+/-34,270No health insurance coverage8,773,178+/-86,951Data note from the US Census Bureau:[ACS] data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

Graph and download economic data for Health Insurance Coverage: People Covered in Montana (DISCONTINUED) (MTHICCOVER) from 1999 to 2012 about covered, MT, health, insurance, persons, and USA.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from American Community Survey 5-year estimates for 2011-2015 to show health insurance coverage and type of coverage, by state House district for the State of Georgia. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. ACS data presented here represent combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For further explanation of ACS estimates and methodology, click here. Attributes: DISTRICT = GA House District POPULATION = District Population (2010 Census) Name = GA House District Name Total_Population_2011_2015_ACS = Total Population, 2011-2015 American Community Survey (ACS) profile_url = Web address of district profile- - - - - -Pop_wHealth_Insurance = #, Civilian noninstitutionalized population with health insurance coverage Pct_Pop_wHealth_Ins = %, Civilian noninstitutionalized population with health insurance coverage Pop_wPriv_Health_Ins = #, Civilian noninstitutionalized population with private health insurance Pct_Pop_wPriv_Health_Ins = %, Civilian noninstitutionalized population with private health insurance Population_with_public_coverage = #, Civilian noninstitutionalized population with public coverage Pct_Pop_with_public_coverage = %, Civilian noninstitutionalized population with public coverage Pop_wNo_Health_Ins = #, Civilian noninstitutionalized population with no health insurance coverage Pct_Pop_wNo_Health_Ins = %, Civilian noninstitutionalized population with no health insurance coverage Pop_u18_wNo_Health_Ins = #, Civilian Noninstitutionalized Population Under 18 years with no health insurance Pct_Pop_u18_wNo_Health_Ins = %, Civilian Noninstitutionalized Population Under 18 years with no health insurance Pop_18to64_Employed = #, Civilian noninstitutionalized ages 18 to 64, employed Pop_18to64_Empl_wNo_Health_Ins = #, Civilian noninstitutionalized ages 18 to 64, employed with no health insurance Pct_Pop_18to64_Emp_wNo_Hlth_Ins = %, Civilian noninstitutionalized ages 18 to 64, employed with no health insurance Pop_18to64_Unemployed = #, Civilian noninstitutionalized ages 18 to 64, unemployed Pop_18to64_Unemp_wNo_Health_Ins = #, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurance Pct_Pop_18to64_Unemp_No_HlthIns = %, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurance Pop_18to64_Not_in_Labor_Force = #, Civilian noninstitutionalized ages 18 to 64, not in labor force Pop_18to64_Not_LabFor_NoHlthIns = #, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurance PctPop_18to64_NotLFor_NoHlthIns = %, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurance Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2011-2015 For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com. Credits

U.S. Census Bureau, Atlanta Regional Commission

For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com.