Liu, Grace
Research Analyst

e gtliu@umn.edu

Food Insecurity in America: New Social Determinants State Health Compare Measure Tracks Percent of Households Experiencing Food Insecurity

Social determinants of health are social factors that impact an individual or community’s health. As explained by the Robert Wood Johnson Foundation, “Good health begins where we live, learn, work and play. Stable housing, quality schools, access to good jobs, and neighborhood safety are all important influences, as is culturally competent health care.”  

Access to food, nutritious and varied, is also considered a social determinant of health.¹ Numerous studies have shown that food insecurity, aka having limited or unstable access to food, is linked to poorer health outcomes, higher chronic disease prevalence, and overall financial hardship.

Newly added to SHADAC’s State Health Compare tool, our ‘Food Insecurity’ measure provides state-level estimates of the prevalence of household-level food insecurity by state and by a number of breakdowns. In this post, we will review a food insecurity definition, the details of SHADAC’s food insecurity measure, and some food insecurity statistics & data highlights from that measure.

What Is Food Insecurity?

As we stated earlier, a general food insecurity definition is when an individual or household has limited or unstable access to food. There are specific definitions, though, that the USDA Economic Research Service follows, which informed SHADAC’s Food Insecurity Measure on State Health Compare.

The USDA Economic Research Service defines a food insecure household as a household that, at times during the year, was “uncertain of having or unable to acquire enough food to meet the needs of all their members because they had insufficient money or other resources for food.”² 

Further, a household is designated as ‘low food security’ by the USDA if they reported reduced quality, variety, or desirability of diet with little or no indication of reduced food intake; the USDA designates a household as ‘very low food security’ if they reported multiple indications of disrupted eating patterns and reduced food intake.² 

The food insecurity estimates presented on State Health Compare indicate the percentage of households experiencing food insecurity defined as those experiencing either low or very low food security. 

SHADAC’s Food Insecurity Measure on State Health Compare

State Health Compare is SHADAC’s online, interactive data tool providing data visualizations, tables, and data sets of state-level health estimates on a variety of measures, including measures on:  

• Access to Care (e.g., Had usual source of medical care, broadband internet access, etc.)
• Cost of Care (e.g., People with high medical cost burden, forgone care, etc.)
• Health Outcomes (e.g., suicide deaths, chronic disease prevalence, etc.)
• Social and Economic Factors (e.g., adverse childhood experiences, etc.)

The new “Food Insecurity” measure falls under the ‘Social and Economic Factors’ category. Data for this measure is available for 2011 – 2022, produced using the Current Population Survey Food Security Supplement (CPS-FSS).

We have also added a number of breakdowns to this measure to allow for further analysis and disaggregation. The Food Insecurity measure is available by the following breakdowns, shown in Table 1:

Table 1. Available Breakdowns and Time Frames for Food Insecurity Measure on SHC

Accessible version of Table 1 found in "Accessible Tables" section in Conclusion.

Now that we have gone over the available data and breakdowns for this measure, let’s take a look at a few food insecurity statistics and data highlights straight from State Health Compare.

Food Insecurity in America: Data Highlights from State Health Compare

Nationwide, 11.2% of households experienced food insecurity in 2020-2022. During this same time frame, food insecurity ranged from as high as 16.6% of households in Arkansas, to as low as 6.2% of households in New Hampshire. 

Food Insecurity Over Time: Vast Majority of States Have Seen Decreased Food Insecurity Rates

When we examine food insecurity over time, we can see that the vast majority of states have experienced a statistically significant decrease in food insecurity between 2011 – 2013 and 2020 – 2022.  

Figure 1. Change in Percentage of Food Insecure Households by State Between 2011 and 2022  

Figure 1 shows the changes in food insecurity for the full range of time available on State Health Compare. When comparing the 2020 – 2022 time frame to the 2011 – 2013 time frame, the majority of states (40) saw statistically significant decreases in the percent of households experiencing food insecurity. 

The largest decrease was in North Carolina, which was down 6.6 Percentage Points (PP). The smallest statistically significant decrease was in Pennsylvania, which was down 1.8 PP. 

South Carolina was the only state to experience an increase in food insecurity between these two time frames (statistically significant or not) with an increase of 0.4 PP.  

Food Insecurity by Race / Ethnicity: African-American / Black Households Experienced the Highest Levels of Food Insecurity

As we saw in the previous section, most states had significant decreases in rates of food insecure households over time. However, when we break down this data by race/ethnicity, disparities in food insecurity levels are revealed.

Table 2. Five States and Racial/Ethnic Groups with the Highest and Lowest Percentages of Food Insecurity, 2020 - 2022

Accessible version of Table 2 found in "Accessible Tables" section in Conclusion.

Table 2 shows the five highest and lowest rates of insecurity for any race/ethnicity in the 2018 – 2022 time frame, which reveals that food insecurity varied greatly by race/ethnicity. 

Across the country and by race, the lowest rate of food insecurity in 2018-2022  was 1.3% for White individuals in the District of Columbia, while the highest rate was 29.0% for Black individuals in North Dakota. Food insecurity prevalence was generally highest for African American/Black households, with the lowest rate of household level food insecurity for African American/Black households in any state, in Massachusetts at 14.2%, still being higher than the highest rate for White households in any state, in West Virginia at 14.1%. 

Food Insecurity by Presence of Children in Household: Those with Children Experienced Higher Levels of Food Insecurity

Figure 2 presents the prevalence of household level food insecurity by presence of child in the household.

Figure 2. Change in Percentage of Food Insecure Households by State and by Presence of Children in Household Between 2020 and 2022  

During the 2020 – 2022 time frame, households in almost every state that included children experienced food insecurity at higher rates than households in the same state without children. 

The exceptions to this were Colorado, Connecticut, Vermont, and West Virginia, which saw more households without children experiencing food insecurity compared to those with children. 

The greatest difference in food insecurity between these two groups (households with and without children) was in Delaware (11.3 PP), while the smallest difference was in Connecticut (0.3 PP).

Conclusion 

As  we can see just from using State Health Compare, many factors can, and do, influence levels of food insecurity. Household makeup, the state you live in, and current events in time can all impact the stability and availability of food to different populations and families. Continued research into what impacts levels of food insecurity can hopefully help us identify where supports are needed, and what kind of actions would be most effective and efficient at providing people with stable and accessible food, care, and support.

You can get started on this important research yourself by exploring and using State Health Compare. Build data tables, visualizations, and more on a number of health care and public health related measures on our simple and easy to use site.

We’d love to hear what you discover on State Health Compare – tag us on LinkedIn, or send us an email with comments or questions at shadac@umn.edu.

Notes and Citations

1. NAMI, Social Determinants of Health: Food Security

2. USDA ERS - Key Statistics & Graphic

Accessible Tables

Table 1. Available Breakdowns and Time Frames for Food Insecurity Measure on SHC

Table 2. Five States and Racial/Ethnic Groups with the Highest and Lowest Percentages of Food Insecurity, 2020 - 2022

Highest Food Insecurity Prevalence by State and Race/Ethnicity

Lowest Food Insecurity Prevalence by State and Race/Ethnicity

Hest, Robert
Stewart, Andrea

CPS ASEC: 2023 National Health Insurance Coverage Estimates Remain Steady for Adults but Rise for Children

This post is a part of our Survey Data Season series where we examine data from various surveys that are released annually from the summer through early fall. Find all of the Survey Data Season series posts on our Survey Data Season 2024 page here.

Today, September 10, 2024, the U.S. Census Bureau released an initial report containing data on health insurance coverage across the United States in 2023, drawn from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC). This latest issue in the long-running line of Current Population Reports did not include any state-level estimates, as the Census Bureau plans to release those data from the American Community Survey (ACS) on Thursday, September 12, 2024. 

The following blog post explores changes in national-level coverage rates by demographic characteristics such as age, employment, race and ethnicity, immigration status, poverty status, and Medicaid expansion status. 

Uninsured Rates Across the Nation in 2023

Overall, data from the “Health Insurance Coverage in the United States” report highlights good news for 2023: the share of the total population without health insurance coverage remained statistically unchanged from 2022 at 8.0%, representing 26.4 million people. Nonelderly adults (age 19-64) similarly did not see any statistically significant change in their uninsurance rate from 2022 (10.8%) to 2023 (10.9%).

However, the report does note that the rate of uninsurance among children (age 0-18) rose significantly to 5.8% in 2023 from 5.4% in 2022.

The overarching stability of uninsured rates in 2023 for the total U.S. population held mostly true when looking across demographic groups, as well. The data show no significant changes for uninsurance among nonelderly adults and children for all measured racial and ethnic groups and by immigration status.

There were some slight changes in uninsurance by region, with both nonelderly adults and children in the Midwest seeing rate increases from 7.2% to 8.1% for the former and from 3.3% to 4.6% for the latter. Children in the West also experienced increasing uninsured rates from 4.2% in 2022 to 5.1% in 2023.

Changes in Uninsurance by Medicaid Expansion Status and Poverty Level

The one subcategory to experience any larger changes in 2023 was uninsurance for individuals in states that have or have not expanded Medicaid.

The rate of uninsurance among nonelderly adults in Medicaid expansion states rose to 8.9% in 2023 from 8.4% in 2022. The rate among those in nonexpansion states remained statistically unchanged at 15.5%. Among children, the rate of uninsurance rose to 4.6% in expansion states (from 4.1%) and was unchanged in nonexpansion states at 8.3%.

Rate of Uninsurance for Nonelderly Adults in Expansion States by Income Level

The rate of uninsurance among nonelderly adults in expansion states with incomes between 100% and 399% of the poverty level rose to 13.3% in 2023 from 12.4% in 2022. The rate of uninsurance among nonelderly adults in expansion states was unchanged among those with incomes below 100% of the poverty level (18.7%) and among those at or above 400% of the poverty level (3.5%).

Rate of Uninsurance for Nonelderly Adults in Nonexpansion States By Income Level

The rate of uninsurance among nonelderly adults in nonexpansion states with incomes below 100% of the poverty level fell to 32.5% in 2023 from 37.9% in 2022. The rate of uninsurance among nonelderly adults in nonexpansion states was unchanged among those with incomes between 100% and 399% of the poverty level (21.4%) and at or above 400% of the poverty level (5.4%).

Public and Private Coverage Across the Nation in 2023

Among all persons, overall rates of public coverage and private coverage in 2023 remained unchanged at 36.4% and 65.4%, respectively. Much like uninsured rates, rates of public and private coverage remained steady across demographic groups by race and ethnicity, immigration status, and even mostly across Medicaid expansion status. 

The only exception of note was in expansion states, which saw a decrease in rates of private coverage, falling 0.7 percentage points to 65.9% in 2023. (The rate of public coverage remained unchanged at 37.8%.)

Changes in Employment-Based, Medicaid, and Medicare Coverage 

However, there was more change in coverage when looking at specific types of private and public coverage. 

Within private coverage types, the rate of employment-based coverage fell 0.7 percentage points to 53.7% in 2023 while the rate of direct purchase and Marketplace coverage each increased to 10.2% (0.3 percentage point increase) and 4.0% (0.4 percentage point increase), respectively. 

Within public coverage types, the rate of Medicare coverage increased 0.2 percentage points to 18.9% while the rate of Medicaid coverage was unchanged at 18.9%.

Image Text: Health Insurance Coverage by Employment Status for Nonelderly Adults in 2023: Among nonelderly adults who worked full-time, year-round, the rate of uninsurance increased to 8.9% in 2023 from 8.4% in 2022. However, the rate of uninsurance actually decreased to 12.9% from 13.8% among those who worked less than full-time, year-round. Rates were unchanged among those who did not work (14.7%) and among all workers (10.0%). There was no change in rates of either private or public coverage among all workers; those who worked full-time, year-round; those who worked less than full-time, year-round; and those who did not work.

COVID-19 Public Health Emergency, Medicaid Unwinding, and Related Impacts

Concluding the Continuous Coverage Requirement and the Medicaid Unwinding

The continuous coverage requirement that prevented states from terminating individuals’ Medicaid coverage during the COVID-19 pandemic ended on March 31, 2023. The resumption of Medicaid eligibility redeterminations and renewals (and potential disenrollments), a process commonly referred to as the “unwinding,” began on April 1, 2023 and has since ended on June 30, 2024. 

Each state was given a 14-month period to navigate returning to normal operations while also meeting reporting requirements set by the Centers for Medicare & Medicaid Services (CMS), such as submitting monthly “Unwinding Data Reports,” in order to publicly share coverage transitions and outcomes data during this time. Though the unwinding period has come to a close, a May 30, 2024, State Health Official (SHO) letter announced that CMS will extend these requirements for the foreseeable future. Beginning on July 1, 2024, all states are expected to continue to submit certain metrics contained in the Unwinding Data Report, now referred to as an “Eligibility Processing Report,” on an ongoing basis.

For more information on the post-unwinding period and reporting process, see a recent blog written by SHADAC researchers for State Health & Value Strategies:

Unwinding Ends, but States’ Reporting of Medicaid Renewal Data Continues (SHVS Cross-Post)

It is important to note that full-year 2023 estimates from all surveys, including the CPS and ACS, will not be fully reflective of a Medicaid unwinding process that began mid-year. However, provisional data from sources like the Census Bureau’s Household Pulse Survey, can give us an indicator of coverage trends during this time.

If you are interested in learning more, SHADAC researchers have compiled a clear, concise, and informative data resource that can be found here:

Tracking Health Insurance Coverage During the Unwinding: Monthly Data from the Household Pulse Survey

CPS ASEC Data Collection - Response Rates and Nonresponse Bias

Continuing a trend that began in 2020 during the COVID-19 pandemic, Census Bureau researchers once again noted an issue of lower response rates for the CPS ASEC this year (67.2% in March 2024 compared to 81.5% in March 2019). While a newly published CPS companion blog from Census points out that low response rates in and of themselves are not inherently problematic, issues can arise when certain types of respondents are overrepresented in the data as compared to nonrespondents.

For example, starting in 2020, the CPS ASEC began to see more respondents with reported higher earnings than in years prior, and Census researchers have found that differences in median earnings between respondents and nonrespondents were statistically significant in each year since 2019 (2020-2024). This difference has the potential to, in turn, affect overall income and poverty estimates.

The Census Bureau has continued to monitor these issues since they first arose during the COVID-19 pandemic, and has begun to develop a number of methods to address them, including combining data from different sources to produce improved estimates of the income distribution as well as creating and employing an alternative weighting scheme.

Related Releases and Materials

ACS 2023: After Two Years of Decline, Uninsured Rates Increased for Children; Public and Private Coverage Rates See Variations Across the States

As previously mentioned, the Census Bureau released 2023 estimates from the American Community Survey (ACS) - including coverage rates at the state level - on Thursday, September 12, 2024. SHADAC has now created and released a blog post analyzing the new ACS data.

You can check for other updates on our Survey Data Season 2024 Resource Page.

Upcoming Webinar: U.S. Census Bureau Data Explained: Breaking Down 2023 Health Insurance Coverage Estimates from the ACS & CPS - featuring a Q&A with a Census Bureau Expert

On Thursday, September 26th at 1:00 PM CST, SHADAC will host a webinar covering the release of new Census data on health insurance coverage estimates for 2023. The estimates come from two key federal surveys conducted by the U.S. Census Bureau: The American Community Survey (ACS) and the Current Population Survey (CPS).

SHADAC researchers and presenters Robert Hest and Andrea Stewart will discuss the 2023 health insurance data at national and state levels, as well as by coverage type, and a range of other demographic categories (age, geography, poverty level, and more).

In addition, SHADAC will walk through how to access the data and examples of how to use it to answer research questions. We are also pleased to once again welcome a special guest from the Census Bureau, Sharon Stern, who will join us to answer questions from attendees after the presentation.

Notes

• All changes are tested at the 90% confidence level.
• All estimates come from the 2023 and 2024 Current Population Survey Annual Social and Economic Supplements, which provide data for years 2022 and 2023, respectively.
• Uninsured estimates represent individuals with no health insurance coverage for the entire calendar year.
• Estimates of health insurance coverage type represent individuals with that type of coverage at any point during the calendar year. Types of health insurance coverage are not mutually exclusive.

WEBINAR: U.S. Census Bureau Data Explained: Breaking Down 2023 Health Insurance Coverage Estimates from the ACS & CPS - featuring a Q&A with a Census Bureau Expert

 

This presentation is a part of our Survey Data Season series where we examine data from various surveys that are released annually from the summer through early fall. Find all of the Survey Data Season series posts on our Survey Data Season 2024 page here.

 

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On Thursday, September 26th at 1:00 PM CST, SHADAC hosted a webinar covering the release of new Census data on health insurance coverage estimates for 2023. The estimates come from two key federal surveys conducted by the U.S. Census Bureau: The American Community Survey (ACS) and the Current Population Survey (CPS).

SHADAC researchers and presenters Robert Hest and Andrea Stewart discussed the 2023 health insurance data at national and state levels, as well as by coverage type, and a range of other demographic categories (age, geography, poverty level, and more). In addition, SHADAC walked through how to access the data and examples of how to use it to answer research questions. We were also pleased to once again welcome a special guest from the Census Bureau, Sharon Stern, who joined the end of the webinar to participate in a Q&A, answering questions from attendees. 

Webinar attendees came away knowing more about:

• The new 2023 health insurance coverage estimates
• How to access the estimates via Census reports and the data.census.gov website
• How to access state-level estimates from the ACS using SHADAC’s State Health Compare web tool
• When and how to use 2023 Census data to understand health insurance coverage trends

Find a recording of this webinar, along with presentation slides and a transcript of webinar audio, below.

Find the slides from this presentation here. Find a transcript of this webinar here.

Speakers

Elizabeth Lukanen, Moderator
Deputy Director, SHADAC

Ms. Lukanen serves as the Deputy Director for SHADAC, overseeing center research and providing strategic direction and oversight. With 20 years of experience in the health policy arena, Ms. Lukanen specializes in managing complex projects and translating quantitative findings into actionable, policy-relevant information. Ms. Lukanen currently oversees SHADAC’s technical assistance to states in the areas of data use, analysis, and evaluation. Ms. Lukanen is vocal about the importance of collecting and reporting disaggregated data to explore issues related to health equity, while actively working with policymakers to improve data on race, ethnicity, sexual orientation, and gender identity.

 

Robert Hest, Speaker
Senior Research Fellow, SHADAC

Robert Hest joined SHADAC in 2017, providing expertise in survey data, quantitative data analysis, data visualization, and health coverage policy. Mr. Hest leads SHADAC’s work monitoring and investigating developments in the measurement of health insurance coverage and health care access, affordability and utilization in federal survey data. He also manages SHADAC’s State Health Compare website, coordinating data processing, quality assurance, dissemination, and documentation of data used on the site and leads SHADAC’s work in the Minnesota Research Data Center applying restricted-use data to analyze health care affordability, access, and utilization at the state level.

 

 

Andrea Stewart, Speaker
Research Fellow, SHADAC

Andrea Stewart joined SHADAC in 2018 as a Marketing and Communications Specialist, transitioning to a Research Fellow in 2022. Currently, Ms. Stewart leads SHADAC’s efforts to track and report health insurance coverage data from major federal surveys, and is involved in several other ongoing projects, including an effort to explore the potential for the creation of a Medicaid Equity Monitoring Tool. Portions of her other research work range in topic from health equity measurement to understanding the impacts of COVID-19 on federal survey data.

 

 

Sharon Stern, Speaker
Assistant Division Chief, U.S. Census Bureau

Sharon Stern is the Assistant Division Chief for employment characteristics in the U.S. Census Bureau’s Social, Economic and Housing Statistics Division. In her position, Ms. Stern oversees statistics on the labor force, health insurance and disability from several Census Bureau surveys. She has authored a wide variety of Census Bureau reports and papers on topics related to poverty, disability, and health insurance.

 

 

 

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Comparing Federal Government Surveys That Count the Uninsured: 2023

How many Americans are uninsured? The exact answer is unclear, but general estimates can be obtained by comparing various federal government surveys that estimate uninsurance.

SHADAC has recently updated our annual “Comparing Federal Government Surveys that Count the Uninsured” brief following the release of new insurance coverage estimates from surveys conducted by the US Census Bureau, the Agency for Healthcare Research and Quality (AHRQ), and the Centers for Disease Control and Prevention (CDC).

Accurate estimates of the number of people that do not have insurance coverage (also referred to as uninsured or uninsurance) are important in understanding trends and the impacts of actions (policy changes), events (like public health emergencies), or shifts in the economic landscape (like periods of recession) that may affect health insurance coverage.

The brief provides an annual update to comparisons of uninsurance estimates from five federal surveys. As in prior years, we have included estimates from:

• The American Community Survey (ACS)
• The Current Population Survey (CPS)
• The Medical Expenditure Panel Survey - Household Component (MEPS-HC)
• The National Health Interview Survey (NHIS)

This year we have included data from an additional source:

• The Behavioral Risk Factor Surveillance System (BRFSS)

In this brief, SHADAC provides up-to-date and past national uninsurance estimates, as well as the latest state-level estimates from surveys (where feasible). 

 

We also analyze the primary factors contributing to variations in these estimates among surveys, along with potential reasons for their incomparability both within and across surveys.

View and download the Comparing Federal Government Surveys 2023 Brief to learn more about our findings and analysis.

Interested in insurance coverage trends? Learn more with the following SHADAC products:

• Comparing Federal Surveys That Count the Uninsured 2022 (last year’s version of this brief) 
• Tracking Health Insurance Coverage During the Unwinding: Monthly Data from the Household Pulse Survey
• Unemployment Rate Trends of the Past 5 Years: Pre-, Mid-, and Post-Pandemic

Categorization of Health Insurance Coverage Type from Survey Questions after Health Reform: The Case of the Current Population Survey

This article, coauthored by SHADAC Investigator Kathleen Call alongside colleagues from the Humphrey School of Public Affairs Angela Fertig and U.S. Census Bureau Joanne Pascale, used administrative records linked with survey data to explore how to categorize private marketplace coverage versus public coverage in the redesigned Current Population Survey (CPS) health insurance module.

To begin, using data from an experimental study called Comparing Health Insurance Measurement Error (CHIME) two algorithms were created.  

One algorithm, dubbed 'CON', classifies coverage type relying solely on a conceptual understanding of the general tendencies of the health insurance landscape. 

The second algorithm, dubbed 'AR', classifies coverage type by leveraging survey responses matched to administrative records from a private health insurer.

The two algorithms were then compared by examining three reporting accuracy metrics of coverage type classification: underreporting, overreporting, and prevalence. Then, they used the results to assess whether the AR algorithm improved, or could improve, the accurate categorization of private versus public coverage on the CPS.

Principal Findings

This study’s findings show that the AR algorithm produced measurable improvements over the CON algorithm, with only one minor trade-off. Underreporting of public coverage was reduced by about 5 percentage points, and overreporting of private, marketplace, and nongroup/marketplace coverage was reduced (by almost 2 percentage points; almost 7 percentage points; and almost 11 percentage points, respectively).

The cost of these improved metrics was higher underreporting of marketplace and nongroup/marketplace coverage.

However, because one of the main goals and motivations for this research project was to address the problem of the chronic underreporting of public coverage, researchers suggest that the trade off to improve reporting of public coverage with a cost of underreporting marketplace coverage (that has relatively low prevalence) might be acceptable.

To read the full article, visit this link.