VISIT STATE HEALTH COMPARE
Publication
Sobering Statistics: Acceleration of Alcohol-Attributable Deaths Across the United States During the COVID-19 Pandemic
Alcohol has long been one of the few legal mind-altering substances in the United States. While legal, messaging around its use – and misuse – has often been mixed. Moderate levels of drinking, such as a glass of wine or beer with dinner, were once recommended as a way to promote better heart health and to help control blood sugar and cholesterol levels.1,2
Lately, however, the public health sphere has become awakened to the fact that even a small amount of alcohol can lead to negative health consequences, increasing risks for a number of chronic diseases and different types of cancer.3 These risks are even more pronounced for women who, biologically, process alcohol differently than men, and face higher odds of developing chronic health conditions, disease, and even increased risk of death from alcohol-induced causes.4,5
Using vital statistics data from the CDC’s WONDER system, a new brief from SHADAC researchers examines the concerning rise in alcohol-attributable deaths among women, which underscore larger patterns of growth seen across the U.S. We also examine differences in alcohol-attributable deaths between demographic groups, including by age, race and ethnicity, and geographic location during the COVID-19 pandemic period (2019-2022).
Key findings from our analysis of alcohol-attributable deaths during this time include:
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While men have traditionally seen high rates of alcohol-attributable deaths, women saw a 33% increase in alcohol-attributable deaths from 2019 to 2022 – an acceleration over the 28% growth in the rates of their male counterparts.
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Alcohol-attributable death rates for American Indian and Alaska native people, already at historic highs, surged by over 20 percentage points (from 54.0 deaths per 100,000 people in 2019 to 78.4 per 100,000 people in 2022) – well over the rate for the overall U.S. population (13.5 deaths per 100,000 people).
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Rates also increased for people living in non-metro (i.e., rural) areas during the pandemic, rising by 36% from 14.5 per 100,000 people in 2019 to 19.6 per 100,000 people in 2022.
Each of these individual trends make up an alarming larger pattern of accelerating alcohol-attributable death rates reaching all the way back to 2006, the year that the data for alcohol-attributable deaths first revealed any increase. While rates for years prior to 2006 remained generally stable, rates began steadily rising from 2006 onward, growing by nearly 30% from 7.4 alcohol-attributable deaths per 100,000 people to 10.4 per 100,000 people just prior to the COVID-19 pandemic in 2019. During the pandemic, this rate grew again by 30% from 10.4 deaths per 100,000 people to 13.5 death per 100,000 in 2022 in just three years – a worrying acceleration.
To learn more about alcohol-related deaths and our analysis of these trends, read the full brief, "Sobering Statistics: Acceleration of Alcohol-Attributable Deaths Across the United States During the COVID-19 Pandemic".
SHADAC has also built an interactive map that shows rates of alcohol-attributable deaths for the U.S. and the states from 2006 to 2022 for you to explore the data yourself. Start exploring below.
Notes and Citations
1. Callahan, A. (2024, February 17). How Red Wine Lost Its Health Halo. The New York Times. https://www.nytimes.com/2024/02/17/well/eat/red-wine-heart-health.html
2. Richardson, C. (2023, February 10). Is beer healthy? How much should people drink? Medical News Today. https://www.medicalnewstoday.com/articles/is-beer-healthy
3. National Cancer Institute. (2021, July 14). Alcohol and Cancer Risk. National Institutes of Health. https://www.cancer.gov/about-cancer/causes-prevention/risk/alcohol/alcohol-fact-sheet
4. Centers for Disease Control and Prevention (2024, September 19). Sex and Gender Considerations on Alcohol Use and Health. https://www.cdc.gov/alcohol/about-alcohol-use/alcohol-and-gender-considerations.html
5. Zhao, J., Stockwell, T., Naimi, T., Churchill, S., Clay, J., & Sherk, A. (2023, March 31). Association Between Daily Alcohol Intake and Risk of All-Cause Mortality: A Systematic Review and Meta-analyses. JAMA Network Open, 6(3), e236185. doi:10.1001/jamanetworkopen.2023.6185
Blog & News
Food Insecurity in America: New Social Determinants State Health Compare Measure Tracks Percent of Households Experiencing Food Insecurity
December 16, 2024: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
|
Breakdown |
Subgroups |
Available Time Frames |
|---|---|---|
|
Total |
N/A |
2011 – 2013 2014 – 2016 2017 – 2019 2020 – 2022 |
|
Race/ethnicity |
Hispanic/Latino White African-American/Black Asian/Pacific Islander Other/Multiple Races |
2013 – 2017 2018 – 2022 |
|
Presence of Child in Household |
Child in household No child in household |
2011 – 2013 2014 – 2016 2017 – 2019 2020 – 2022 |
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
|
State |
Race/Ethnicity |
Food Insecurity Prevalence |
|---|---|---|
|
North Dakota |
African-American / Black |
29.0% |
|
Oklahoma |
African-American / Black |
28.4% |
|
Nebraska |
Hispanic / Latino |
27.5% |
|
Nebraska |
African-American / Black |
27.4% |
|
Michigan |
African-American / Black |
27.4% |
Lowest Food Insecurity Prevalence by State and Race/Ethnicity
|
State |
Race/Ethnicity |
Food Insecurity Prevalence |
|---|---|---|
|
District of Columbia |
White |
1.3% |
|
Texas |
Asian / Pacific Islander |
4.4% |
|
Illinois |
Asian / Pacific Islander |
4.5% |
|
New Jersey |
White |
4.8% |
|
Maryland |
White |
5.4% |
Publication
Underlying Factors of Medicaid Inequities: Conversations with Experts on Racism and Medicaid
Medicaid serves as a vital public health safety net for over 79 million people, including many from historically excluded or marginalized communities. There is a great opportunity to improve Medicaid programs’ accountability for persistent health inequities by confronting the historical and structural racism perpetuated in the administration, policies, and practices that undergird the program.
The Medicaid Equity Monitoring Tool (MET) project is a collaborative effort from the State Health Access Data Assistance Center (SHADAC) with support from the Robert Wood Johnson Foundation (RWJF) and partner organizations working to assess whether a data tool could increase accountability for state Medicaid programs to advance health equity while also improving population health.
During the first phase of this project, a wireframe was created to organize the different sections of a potential tool, including a section on "Underlying Factors" that lead to and perpetuate health inequities for people of color and other historically marginalized communities.
In order to inform the Medicaid Equity Monitoring Tool (MET) project and the Underlying Factors section of the tool, SHADAC produced an annotated bibliography of resources to better understand the available academic and gray literature on those underlying factors of health inequities in Medicaid.
While the bibliography covers a number of structural and systemic underlying factors of health inequities (e.g., ableism, sexual orientation and gender identity discrimination), most of the resources compiled in the bibliography address structural racism specifically. These resources discuss the history, policy context, and impacts of systemic racism on Medicaid recipients.
As a follow-up to the creation of the annotated bibliography, SHADAC’s Health Equity Fellow held consulting conversations with authors of select resources cited in the structural racism section. Through these conversations, our goal was to:
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Connect with experts in order to elicit feedback on key insights from SHADAC’s annotated bibliography
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Ask experts questions about what topics related to systemic racism need to be discussed within the tool
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Discuss strategies on how best to convey and disseminate this important information
This brief summarizes these conversations, including specific examples and quotes from experts, for audiences interested in communicating about the effects of structural racism with the aim to dismantle it.
Publication
PRESENTATION: Trends and Patterns in Fatal Drug Overdoses Since the COVID-19 Pandemic
SHADAC Senior Research Fellow Colin Planalp presented at the APHA Annual Meeting in October 2024. In this presentation, Mr. Planalp reviews trends and patterns in fatal drug overdoses since the COVID-19 pandemic, including the increase in fentanyl related overdose deaths, which significantly increased from 11.4 deaths per 100,000 in 2019 to 22.7 deaths per 100,000 in 2022.
Click the image below to view the slides from this presentation in a PDF format. If you would like to view the presentation in a different format, please contact us.
Are you interested in learning more about the opioid epidemic? You can view all of our latest opioid crisis resources on our Opioid Epidemic in the United States page.
Publication
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.
[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
