In 2024, 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 2024.

The Health Insurance Marketplace Public Use Files contain data on health and dental plans offered to individuals and small businesses through the US Health Insurance Marketplace.

Exploration Ideas

To help get you started, here are some data exploration ideas:

• How do plan rates and benefits vary across states?
• How do plan benefits relate to plan rates?
• How do plan rates vary by age?
• How do plans vary across insurance network providers?

See this forum thread for more ideas, and post there if you want to add your own ideas or answer some of the open questions!

Data Description

This data was originally prepared and released by the Centers for Medicare & Medicaid Services (CMS). Please read the CMS Disclaimer-User Agreement before using this data.

Here, we've processed the data to facilitate analytics. This processed version has three components:

1. Original versions of the data

The original versions of the 2014, 2015, 2016 data are available in the "raw" directory of the download and "../input/raw" on Kaggle Scripts. Search for "dictionaries" on this page to find the data dictionaries describing the individual raw files.

2. Combined CSV files that contain

In the top level directory of the download ("../input" on Kaggle Scripts), there are six CSV files that contain the combined at across all years:

• BenefitsCostSharing.csv
• BusinessRules.csv
• Network.csv
• PlanAttributes.csv
• Rate.csv
• ServiceArea.csv

Additionally, there are two CSV files that facilitate joining data across years:

• Crosswalk2015.csv - joining 2014 and 2015 data
• Crosswalk2016.csv - joining 2015 and 2016 data

3. SQLite database

The "database.sqlite" file contains tables corresponding to each of the processed CSV files.

The code to create the processed version of this data is available on GitHub.

In 2023, **** 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.

As of 2024, 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 2024, 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.

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.

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

Context

The Affordable Care Act (ACA) is the name for the comprehensive health care reform law and its amendments which addresses health insurance coverage, health care costs, and preventive care. The law was enacted in two parts: The Patient Protection and Affordable Care Act was signed into law on March 23, 2010 by President Barack Obama and was amended by the Health Care and Education Reconciliation Act on March 30, 2010.

Content

This dataset provides health insurance coverage data for each state and the nation as a whole, including variables such as the uninsured rates before and after Obamacare, estimates of individuals covered by employer and marketplace healthcare plans, and enrollment in Medicare and Medicaid programs.

Acknowledgements

The health insurance coverage data was compiled from the US Department of Health and Human Services and US Census Bureau.

Inspiration

How has the Affordable Care Act changed the rate of citizens with health insurance coverage? Which states observed the greatest decline in their uninsured rate? Did those states expand Medicaid program coverage and/or implement a health insurance marketplace? What do you predict will happen to the nationwide uninsured rate in the next five years?

This layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. 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)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. Current Vintage: 2019-2023ACS 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: December 12, 2024National 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 is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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.

The percentage of people in the United States with health insurance has increased over the past decade with a noticeably sharp increase in 2014 when the Affordable Care Act (ACA) was enacted. As of 2024, around ** percent of people in the United States had some form of health insurance, compared to around ** percent in 2010. Despite the increases in the percentage of insured people in the U.S., there were still over ** million people in the United States without health insurance as of 2024. Insurance coverage Health insurance in the United States consists of different private and public insurance programs such as those provided by private employers or those provided publicly through Medicare and Medicaid. Almost half of the insured population in the United States were insured privately through an employer as of 2021, while **** percent of people were insured through Medicaid, and **** percent through Medicare . The Affordable Care Act The Affordable Care Act (ACA), enacted in 2014, has significantly reduced the number of uninsured people in the United States. In 2014, the percentage of U.S. individuals with health insurance increased to almost ** percent. Furthermore, the percentage of people without health insurance reached an all time low in 2022. Public opinion on healthcare reform in the United States remains an ongoing political issue with public opinion consistently divided.

In 2024, 27 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 from 2020 to 2024. Factors like the implementation of Medicaid expansion in additional states and growth in private health insurance coverage led to the decline in the 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 Affordable Care Act created the new Pre-Existing Condition Insurance Plan (PCIP) program to make health insurance available to Americans denied coverage by private insurance companies because of a pre-existing condition. People living with conditions like diabetes, asthma, cancer, and HIV-AIDS have often been priced out of affordable health insurance options, and this has left millions without insurance.

PCIP is a temporary program that covers a broad range of health benefits and is designed as a bridge for people with pre-existing conditions who cannot obtain health insurance coverage in todays private insurance market. As of May 31, 2011 24,712 Americans had insurance through PCIP and the coverage is making a difference. As of May 31, 2011 data from the federally run PCIP plan shows that of claims paid for the top 20 diagnoses, 30.2 percent were for diagnoses of heart disease and 25.8 percent were for diagnoses of cancer. A range of professional, inpatient and drug treatments were provided to these individuals.

Imputed employer-sponsored health insurance coverage data which when linked to the March Annual Social and Economic Supplement to the Current Population Survey (March CPS), generates estimates of the number of individuals with different types of insurance coverage.

The current health expenditure as a share of the GDP in the United States was forecast to continuously increase between 2024 and 2029 by in total 0.8 percentage points. According to this forecast, in 2029, the share will have increased for the seventh consecutive year to 17.98 percent. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Canada and Mexico.

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.

In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. The Oregon Health Insurance Experiment follows and compares those selected in the lottery (treatment group) with those not selected (control group). The data collected and provided here include data from in-person interviews, three mail surveys, emergency department records, and administrative records on Medicaid enrollment, the initial lottery sign-up list, welfare benefits, and mortality. This data collection has seven data files: Dataset 1 contains administrative data on the lottery from the state of Oregon. These data include demographic characteristics that were recorded when individuals signed up for the lottery, date of lottery draw, and information on who was selected for the lottery, applied for the lotteried Medicaid plan if selected, and whose application for the lotteried plan was approved. Also included are Oregon mortality data for 2008 and 2009. Dataset 2 contains information from the state of Oregon on the individuals' participation in Medicaid, Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance to Needy Families (TANF). Datasets 3-5 contain the data from the initial, six month, and 12 month mail surveys, respectively. Topics covered by the surveys include demographic characteristics; health insurance, access to health care and health care utilization; health care needs, experiences, and costs; overall health status and changes in health; and depression and medical conditions and use of medications to treat them. Dataset 6 contains an analysis subset of the variables from the in-person interviews. Topics covered by the survey questionnaire include overall health, health insurance coverage, health care access, health care utilization, conditions and treatments, health behaviors, medical and dental costs, and demographic characteristics. The interviewers also obtained blood pressure and anthropometric measurements and collected dried blood spots to measure levels of cholesterol, glycated hemoglobin and C-reactive protein. Dataset 7 contains an analysis subset of the variables the study obtained for all emergency department (ED) visits to twelve hospitals in the Portland area during 2007-2009. These variables capture total hospital costs, ED costs, and the number of ED visits categorized by time of the visit (daytime weekday or nighttime and weekends), necessity of the visit (emergent, ED care needed, non-preventable; emergent, ED care needed, preventable; emergent, primary care treatable), ambulatory case sensitive status, whether or not the patient was hospitalized, and the reason for the visit (e.g., injury, abdominal pain, chest pain, headache, and mental disorders). The collection also includes a ZIP archive (Dataset 8) with Stata programs that replicate analyses reported in three articles by the principal investigators and others: Finkelstein, Amy et al "The Oregon Health Insurance Experiment: Evidence from the First Year". The Quarterly Journal of Economics. August 2012. Vol 127(3). Baicker, Katherine et al "The Oregon Experiment - Effects of Medicaid on Clinical Outcomes". New England Journal of Medicine. 2 May 2013. Vol 368(18). Taubman, Sarah et al "Medicaid Increases Emergency Department Use: Evidence from Oregon's Health Insurance Experiment". Science. 2 Jan 2014.

This layer shows the percentage of the civilian noninstitutionalized population who do not have insurance. This is shown by census tract centroids. The data values are from the 2012-2016 American Community Survey 5-year estimate in the B27001 Table for health insurance coverage status broken down by by age and sex characteristics.This map helps to answer a few questions:How many people in the United States don't have health insurance?Where are the concentrations of uninsured population?This map helps to tell a local pattern about insurance in the United States. The data can be stratified by different age and sex characteristics in order to create additional maps. By default, the pop-up provides a breakdown of total male and female uninsured 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 +/-10,365

Male: 153,162,940 +/-12,077

Under 6 years: 12,227,441 +/-11,224

With health insurance coverage 11,643,526 +/-12,783

No health insurance coverage 583,915 +/-6,438

6 to 17 years: 25,282,489 +/-12,396

With health insurance coverage 23,659,835 +/-16,339

No health insurance coverage 1,622,654 +/-14,500

18 to 24 years: 15,350,990 +/-8,369

With health insurance coverage 12,112,729 +/-19,586

No health insurance coverage 3,238,261 +/-24,081

25 to 34 years: 20,901,264 +/-8,155

With health insurance coverage 15,669,472 +/-36,401

No health insurance coverage 5,231,792 +/-38,887

35 to 44 years: 19,499,072 +/-6,321

With health insurance coverage 15,722,620 +/-41,969

No health insurance coverage 3,776,452 +/-41,916

45 to 54 years: 20,965,500 +/-5,283

With health insurance coverage 17,819,431 +/-33,014

No health insurance coverage 3,146,069 +/-31,181

55 to 64 years: 19,068,251 +/-3,959

With health insurance coverage 17,076,497 +/-20,830

No health insurance coverage 1,991,754 +/-19,813

65 to 74 years: 12,168,198 +/-3,453

With health insurance coverage 12,041,594 +/-4,736

No health insurance coverage 126,604 +/-3,207

75 years and over: 7,699,735 +/-3,458

With health insurance coverage 7,657,815 +/-3,794

No health insurance coverage 41,920 +/-1,719

Female: 160,413,197 +/-8,724

Under 6 years: 11,684,980 +/-10,395

With health insurance coverage 11,115,775 +/-13,062

No health insurance coverage 569,205 +/-7,132

6 to 17 years: 24,280,468 +/-11,445

With health insurance coverage 22,723,174 +/-14,642

No health insurance coverage 1,557,294 +/-13,468

18 to 24 years: 15,151,707 +/-5,432

With health insurance coverage 12,591,379 +/-16,744

No health insurance coverage 2,560,328 +/-18,826

25 to 34 years: 21,367,510 +/-4,829

With health insurance coverage 17,505,087 +/-32,122

No health insurance coverage 3,862,423 +/-31,651

35 to 44 years: 20,279,901 +/-4,751

With health insurance coverage 17,146,763 +/-32,076

No health insurance coverage 3,133,138 +/-31,659

45 to 54 years: 21,975,842 +/-5,087

With health insurance coverage 19,083,932 +/-27,415

No health insurance coverage 2,891,910 +/-25,022

55 to 64 years: 20,665,987 +/-3,867

With health insurance coverage 18,537,874 +/-18,484

No health insurance coverage 2,128,113 +/-16,614

65 to 74 years: 13,896,484 +/-3,882

With health insurance coverage 13,730,727 +/-6,177

No health insurance coverage 165,757 +/-3,857

75 years and over: 11,110,318 +/-3,977

With health insurance coverage 11,037,661 +/-4,391

No health insurance coverage 72,657 +/-2,120 Data 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.

This historic dataset with total enrollment in separate CHIP programs by month and state was created to fulfill reporting requirements under section 1902(tt)(1) of the Social Security Act, which was added by section 5131(b) of subtitle D of title V of division FF of the Consolidated Appropriations Act, 2023 (P.L. 117-328) (CAA, 2023). For each month from April 1, 2023, through June 30, 2024, states were required to submit to CMS (on a timely basis), and CMS was required to make public, certain monthly data, including the total number of beneficiaries who were enrolled in a separate CHIP program. Accordingly, this historic dataset contains separate CHIP enrollment by month and state between April 2023 and June 2024. CMS will continue to publicly report separate CHIP enrollment by month and state (beyond the historic CAA/Unwinding period) in a new dataset, which is available at [link]. Please note that the methods used to count separate CHIP enrollees differ slightly between the two datasets; as a result, data users should exercise caution if comparing separate CHIP enrollment across the two datasets. Sources: T-MSIS Analytic Files (TAF) and state-submitted enrollment totals. The data notes indicate when a state’s monthly total was a state-submitted value, rather than from T-MSIS.TAF data were pulled as follows:April 2023 enrollment - TAF as of August 2023May 2023 enrollment - TAF as of August 2023June 2023 enrollment - TAF as of September 2023July 2023 enrollment - TAF as of October 2023August 2023 enrollment - TAF as of November 2023September 2023 enrollment - TAF as of December 2023October 2023 enrollment - TAF as of January 2024November 2023 enrollment - TAF as of February 2024December 2023 enrollment - TAF as of March 2024January 2024 enrollment - TAF as of April 2024February 2024 enrollment - TAF as of May 2024March 2024 enrollment - TAF as of June 2024April 2024 enrollment – TAF as of July 2024May 2024 enrollment – TAF as of August 2024June 2024 enrollment – TAF as of September 2024 TAF are produced one month after the T-MSIS submission month. For example, TAF as of August 2023 is based on July T-MSIS submissions. Notes: The separate CHIP enrollment in this report is not inclusive of enrollees covered by Medicaid expansion CHIP. Enrollment includes individuals enrolled in separate CHIP at any point during the month but excludes those enrolled in both Medicaid and separate CHIP during the month. See the Data Sources and Metrics Definitions Overview document for a full description of the data sources, metric definitions, and general data limitations.Alaska, District of Columbia, Hawaii, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, South Carolina, Vermont, and Wyoming do not have separate CHIP Programs. Maryland has a separate CHIP program that began in July 2023; April 2023 - June 2023 data for Maryland represents retroactive coverage. This document includes separate CHIP data submitted to CMS by states via T-MSIS or a separate collection form. These data include reporting metrics consistent with section 1902(tt)(1) of the Social Security Act.CHIP: Children's Health Insurance Program Data notes: (a) State-submitted value; data not from T-MSIS(b1) May 2023 enrollment pulled from TAF as of September 2023(b2) Data was restated using TAF as of October 2023(b3) Data was restated using TAF as of April 2024(b4) Data was restated using TAF as of July 2024(b5) Data was restated using TAF as of August 2024(c) Enrollment counts include postpartum women with coverage funded via a Health Services Initiative

Users can customize table and download data sets to gather information on Americans' use and experience of health care and on the costs associated with health care. Background MEPS is a series of large scale surveys designed to increase understanding of Americans use of health care and the cost of that care. Data is collected on the frequency and type of care, cost of health care and how it is paid for, and health insurance. There are two components to MEPS- the Household Component gathers information from individuals, families and medical providers, and the Insurance Component gathers information from employers to gain understanding on employ er-based health insurance. Examples of information from both components includes, but is not limited to: health conditions, health status, satisfaction with care, demographics, insurance plans offered, premiums, and benefits. User Functionality There are a variety of ways that users can interface with MEPS data. To download summary data tables from the Household Component, users can specify the year of interest (or use all available years) and then specify the table series from a drop down list. To download summary data tables from the Insurance Component, users must first choose between national level and state/ metro area level information. They can then determine the specific year and table series t o gather the data on the topic of interest to them. MEPS also has a Query Tools section that allows users to customize the year, variables, records and descriptive statistics and how the data is presented. Finally, some portions of the data sets are available to download. Data Notes MEPS provides a schedule of when specific pieces of data will be released. The surveys began in 1996 and have since been conducted annually. The most recent data is from 2006, while some portions of the 2009 data have been released. The sample is considered to be nationally representative of households in the United States.

Key Table Information.Table Title.Types of Health Insurance Coverage by Age.Table ID.ACSDT1Y2024.B27010.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and ...

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