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

Children's Uninsurance by Race and Ethnicity Using American Community Survey (ACS) Data

The table below provides data for children's uninsurance by race and ethnicity from 2017 through 2022. This data was obtained from SHADAC analysis of American Community Survey (ACS) Public Use Microdata Sample (PUMS) files.

Children's Uninsurance by Race and Ethnicity, 2017 - 2022
Race/Ethnicity	2017	2018	2019	2021	2022
African-American / Black	4.6%	4.4%	4.6%	4.7%	4.4%
American Indian / Alaska Native	14.2%	14.0%	14.3%	13.0%	11.8%
Asian	4.0%	3.8%	4.1%	3.6%	3.6%
Hispanic / Latino	7.8%	8.1%	9.3%	8.7%	8.1%
Native Hawaiian and Other Pacific Islander	5.1%	5.0%	8.4%	6.9%	9.4%
Other / Multiple Races	3.6%	3.7%	3.8%	4.0%	3.9%
White	3.9%	4.1%	4.3%	4.1%	3.9%

Source: SHADAC analysis of the American Community Survey (ACS) Public Use Microdata Sample (PUMS) files

Notes

Respondents are asked about their health insurance coverage at the time of the interview and may select multiple types of coverage. 

Data for 2020 were not officially released by the U.S. Census Bureau due to pandemic-related disruptions to data collection and resulting problems with data quality.

Find more data on SHADAC's State Health Compare

Walsh, Elliot
Hest, Robert
Lukanen, Elizabeth

What Do the New Census Data Say About Insurance Coverage for Children and Adults? A Look at Both the National and State Level (SHVS Cross-Post)

The following Expert Perspective (EP) is cross-posted from State Health & Value Strategies.

Authors: Elizabeth Lukanen, Elliot Walsh, Robert Hest, SHADAC

Original posting date October 30, 2024. Find the original post here on the SHVS website.

Walsh, Elliot
Research Dissemination Coordinator

e wals0421@umn.edu

What Are Adverse Childhood Experiences (ACEs)? ACEs Definition, Data Challenges, and Resources

Basics Blog Introduction

SHADAC has created a series of “Basics Blogs” to familiarize readers with common terms, concepts, and topics that are frequently covered.

Children’s health is impacted by a number of factors – family life and income, housing, neighborhood, nutrition, health care access and cost, amongst others.

Adverse Childhood Experiences (ACEs) is a broad term for a range of negative experiences people may experience as children that can have profound implications for their health. Sometimes ACEs may occur in the form of a single traumatic event, such as a violent incident, but ACEs may also be the result of recurring, lower-grade stress, such as continual food insecurity.

Many research studies conducted over the course of decades have found ACEs to be linked not only with short-term health implications for children, but also long-term health burden that can last well into adulthood. Unfortunately, they are quite common. One SHADAC brief reports that nearly half (46.3%) of U.S. children have experienced at least one adverse childhood experience, with the CDC reporting that 1 in 6 adults have experienced four or more ACEs in their childhood.

There is ample evidence that ACEs are linked to increased risk of chronic health conditions (asthma, chronic obstructive pulmonary disease, stroke, obesity, etc.), engaging in coping behaviors with health risks (drug use, heavy drinking, unprotected sex, etc.), and long-term behavioral and/or mental health issues (depression, anxiety, substance use disorders, etc.). Evidence also shows that those who experience ACEs have poorer health outcomes, lower educational attainment, and higher unemployment rates.

In this blog, we will provide you with:

• Adverse childhood experience definition and examples

• Data collection challenges

• Comments on ACEs and health equity

• Resources on ACEs and related topics from SHADAC

Gaining a better understanding of ACEs can help people recognize them. With that knowledge, people can seek to prevent ACEs and seek health care that recognizes them as underlying risk factors that can influence people’s health. Understanding ACEs and disparities in their prevalence may help to improve public health and enhance health equity. We can work towards reducing the prevalence of childhood trauma and stresses that can comprise ACEs, as well as their impacts on health in both the short- and the long-term for different and diverse communities.

What Are Adverse Childhood Experiences?

First coined by Vincent Felitti, Robert Anda, and their colleagues in a study published in 1998, Adverse Childhood Experiences (ACEs) are defined by the CDC as, “potentially traumatic events that occur in childhood.”

There is no single, comprehensive definition of what experiences do and don’t constitute ACEs. Initial definitions focused heavily on childhood abuse and neglect, and dysfunction and violence in the household, but some experts have proposed broader definitions that encompass systemic issues, such as housing instability and food insecurity, which research suggests can have similar long-term health impacts.

Some examples of potential adverse childhood experiences include:

• Experiencing neglect or abuse (e.g., emotional, physical, sexual)

• Separation from a parent, guardian, or caregiver due to death, incarceration or divorce

• Witnessing violence and/or domestic violence

• Family member attempting or dying by suicide

• Growing up in a household with substance abuse and/or mental health problems

• Housing instability and food insecurity

• Peer-based bullying

• Experiencing or witnessing racism

These only represent a small number of what could be considered an adverse childhood experience.

ACEs and Health Equity

It has been established by a number of studies that certain populations experience ACEs at a higher prevalence. In the SHADAC study on ACEs and Health Equity, we found that, “Black children had the highest rate of ACEs exposure, at 63.7%, followed closely by American Indian and Alaska Native children, at 63.0%. Each of those was significantly different from the total population rate of 46.3%.”

Figure 1. Percent of children with one or more adverse childhood experiences by race and ethnicity, 2016-2019

The CDC reports groups with the highest prevalence of ACEs in the U.S. include:

• Women

• Racial and ethnic minorities (particularly American Indian or Alaska Native (AIAN) people and multiracial people)

• Members of the LGBTQ+ community

• Those considered low-income

• Those who are unemployed or can’t work

• Adults with less than a high school education

It follows, then, that these groups with a higher prevalence of ACEs would also experience the health impacts of these events at higher rates, which goes on to impact quality of life, overall health, and can impact the children of people in these groups as well. This can perpetuate a cycle of generational trauma and continue to widen the disparities between these and other groups.

It is also worth noting that even with the finding that these groups have higher prevalence of ACEs exposure compared to the total population, it could still be an overall underestimation of ACE prevalence because of demographic data collection challenges both for minority groups and for collection of ACE data in general.

You can learn more about demographic data collection and its impacts in the SHADAC brief on The Collection of Race, Ethnicity, Language Data on Medicaid Applications.

Adverse Childhood Experiences and Data Collection Challenges

As noted earlier, there are challenges when it comes to ACEs data collection.

One such challenge is who the data is collected from. Many surveys are filled out by a parent or guardian reporting on their child. This can result in underestimation of ACEs experienced by the child for a few reasons. Firstly, the parent or guardian filling out the survey could be unaware of a traumatic experience their child has had. Additionally, the parent or guardian could feel uncomfortable or unable to report that their child has had certain adverse experiences, like abuse or experiencing a parent’s mental health issues.

If a child is filling out the survey themselves, some of the questions may be inappropriate to ask of young children, the children may be reluctant to report some forms of trauma, or they may not even recognize that an event was a traumatic one.

As SHADAC researcher Colin Planalp mentions in his brief on ACEs and health equity, “Another approach [for data collection] could be to survey adults about their experiences as children, but that approach may also face some of the same limitations of reluctance to report some forms of trauma, and adults may simply not recall traumatic experiences that occurred decades ago. And by surveying adults about their own traumatic experiences as children, those data would by nature be retrospective— telling us little about the prevalence and types of ACEs among today’s children, which may change over time.”

Another issue is the feasibility of including all types of ACEs in a survey. As we mentioned in the previous section, we only listed a small number of possible ACEs. Surveys often condense or simplify the number of ACEs that it asks about – it simply isn’t feasible to list out every single type of ACE or trauma, which likely results in an overall underestimation of experienced ACEs in the population.

Adverse Childhood Experiences: Resources from SHADAC

Hopefully this has given you a general overview on the question, “What are ACEs?” But, as you could probably glean, this is a complex topic with many factors to consider and learn about. ACEs and their impact touch upon a number of issues, including health care cost & access, mental health care, housing, generational trauma, drug and substance use, structural oppression (like racism, homophobia, ableism, etc.), children’s health, and more. Each factor exists amongst and with the others, creating complex systems to unravel and intersectional identities to consider.

Additionally, this is a relatively new area of study, with that original Felitti et al. study published in 1998. New information and research continue to expand our understanding of ACEs, health disparities, and their impacts on health later in life – for example, a study published in Health Affairs in 2024 found a link between ACEs and adults experiencing financial and housing problems, social network problems, and food insecurity, and found that “those with ACEs had substantially higher [health care] utilization and 26.3 percent higher expenditures.”

Continued study and research can help us identify these issues, understand the groups impacted, and work towards both prevention and post-trauma support. Working on this issue has implications to improve the health of children and adults, reduce risk of chronic and mental health conditions, reduce related costs, and, hopefully, reduce the impact and prevalence of childhood trauma.

Keep learning about ACEs and related topics with some of the following SHADAC products:

Changing Dynamics in the Opioid Crisis Since the COVID-19 Pandemic

Soaring rates of fatal fentanyl, methamphetamine, and cocaine overdoses have worsened and spread to previously insulated groups, including teenagers and the elderly

It has been more than a decade since the U.S. Centers for Disease Control and Prevention (CDC) declared a national opioid “epidemic,” also known as the opioid crisis. In that time, hundreds of thousands of people have died, with the impact rippling out amongst friends, family, and communities: One in three U.S. adults know someone who has died of an overdose.¹ 

Despite knowledge of this crisis and efforts to reduce fatal overdoses and impacts of substance use disorder, we have seen the opioid epidemic continually worsen and evolve. Evidence suggests that increased regulations on prescription opioids pushed many to illicit alternatives.² The COVID-19 pandemic coincided with a huge increase in overdose deaths. Fentanyl, a once lesser-known contributor to the epidemic, has skyrocketed in its impact. Once insulated groups, like adolescents and the elderly, have seen overdose rates rise.

In this new brief from SHADAC, we examine changes in drug overdose death rates, and the types of drugs that cause these fatal overdoses, during the pandemic period (2019-2022). We also look at the history of the opioid epidemic: its beginnings, factors that influenced its evolution, and what it looks like now.

With this brief focusing on the four most common causes of drug overdoses — fentanyl, prescription opioids, methamphetamine, and cocaine — just some of the findings from this pandemic period include:

• Fatal overdoses from fentanyl increased 99%
• Fatal overdoses from methamphetamine increased 108%, and 
• Fatal overdoses from cocaine increased 69%

While overdose death rates generally increased across all the measured racial and ethnic groups, “we […] found evidence of dramatic and growing disparities across racial and ethnic groups in rates of fatal overdoses, with the crisis increasingly harming American Indian and Alaska Native people and Black people during the pandemic era,” lead author and Senior Researcher Colin Planalp says. 

In this brief, we explore these findings and more, including looking deeper at the impacts of the opioid crisis on different communities, demographics, and states. Click here to read the brief in full. The appendix for this piece is available here.

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[1] Kennedy-Hendricks, A., Ettman, C. K., Gollust, S. E., Bandara, S. N., Abdalla, S. M., Castrucci, B. C., & Galea, S. (2024). Experience of Personal Loss Due to Drug Overdose Among US Adults. JAMA health forum, 5(5), e241262. https://pubmed.ncbi.nlm.nih.gov/38819798/

[2] Pitt, A.L., Humphreys, K., & Brandeau, M.L. (2018). Modeling Health Benefits and Harms of Public Policy Responses to the US Opioid Epidemic. American Journal of Public Health, 108(10), 1394-1400. https://ajph.aphapublications.org/doi/pdfplus/10.2105/AJPH.2018.304590