Hest, Robert
Lanigan, Lindsey
Stewart, Andrea

CPS ASEC: 2022 National Health Insurance Coverage Estimates Show Falling Rates of Uninsurance and Direct-Purchase Coverage (Infographic)

The U.S. Census Bureau has released an initial report detailing the state of health insurance coverage in the United States for 2022.

Drawing on data from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), the report highlights good news overall as the percentage of the population without health insurance coverage at any point in 2022 fell to 7.9% from 8.3% in 2021—a decrease of 0.4 percentage points or approximately 1.3 million people (25.9 million in 2022 vs. 27.2 million in 2021). 

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 - for nonelderly adults (age 19-64) and for children (age 0-18). While neither group saw an overall significant change in uninsured rates, both experienced shifts across demographic subgroups.

Additionally of note, though not within the scope of this blog to explore further, elderly adults (age 65+) saw a significant increase in Medicare rates, which the Census Bureau notes is due to a larger elderly population overall, not a larger share of those adults having Medicare. The continued growth of an aging population will continue to have ramifications for a number of health-related measures, including health insurance coverage rates, and bears following in future research.

Changes in Uninsurance by Age (Nonelderly Adults age 19-64, and Children age 0-18) and Characteristics

Among nonelderly adults, the overall rate of uninsurance fell to 10.8% in 2022, a 0.8 percentage point (PP) decrease from 2021.

Comparatively, the uninsured rate among children remained statistically unchanged from 2021 (5.0%) at 5.4% in 2022.

Race and ethnicity
In 2022, rates of uninsurance fell among nonelderly Black, Hispanic, and White adults, declining to 11.4%, 23.4%, and 6.8% (versus 12.7%, 25.1%, and 7.5%), respectively. Rates of uninsurance among nonelderly Asian adults were unchanged at 7.4%.

Similarly, while uninsurance rates remained stable for children of several racial and ethnic groups in 2022 - 4.1% for Asian children, 4.7% for Black children, and 8.6% for Hispanic children - the rate of uninsurance rose significantly among White children, increasing to 4.1% in 2022 from 3.4% in 2021.

Immigration status
The rate of uninsurance among native-born nonelderly adults fell to 8.2% in 2022 from 9.1% in 2021, while the uninsurance rate among foreign-born adults remained statistically unchanged at 22.1% in 2022 compared to 22.8% in 2021.

Rates of uninsurance were unchanged among native-born children at 4.7% in 2022 and among foreign-born children at 20.6% in 2022.

Poverty level
When examining coverage by poverty level, rates of uninsurance were unchanged at 24.2% among nonelderly adults with incomes below 100% poverty, decreased to 15.2% from 16.8% for those between 100%-399% poverty, and decreased to 3.9% from 4.5% for those living at or above 400% poverty.

In 2022, rates of uninsurance were unchanged for children in the two lower poverty level categories—8.9% for those in families with incomes below 100% poverty and 6.1% for those living in families with incomes between 100%-399% poverty. However, uninsured rates rose to 2.6% among children in families with incomes at or above 400% of poverty, an increase of 0.9 PP from 2021.

Medicaid expansion status
As of January 1, 2022, 38 states and the District of Columbia have chosen to act on the option provided by the Affordable Care Act (ACA) and expand Medicaid eligibility requirements, with the additions of Missouri and Oklahoma last year. Comparing rates of uninsurance by expansion and nonexpansion states revealed divergent trends for nonelderly adults and children.

In 2022, the uninsured rate fell to 8.4% in 2022 from 9.2% in 2021 for nonelderly adults living in expansion states and fell to 16.2% in 2022 from 17.0% in 2021 for those in nonexpansion states.

However, children in expansion and nonexpansion states saw no significant change in uninsured rates for 2022 compared to 2021 at 4.1% and 8.1%, respectively.

Notable Public and Private Coverage Changes

Among nonelderly adults, rates of public coverage and private coverage were unchanged at 19.1% and 72.9%, respectively. Rates of employer-based coverage increased to 63.5% in 2022 among nonelderly adults, up 0.6 PP from 2021. Rates of Medicare coverage fell to 3.6% among nonelderly adults in 2022, down from 3.8% in 2021.

By Race and Ethnicity (Total Population)
Rates of private and public coverage were statistically unchanged among Asian (72.2% and 27.8%, respectively) and Hispanic individuals (49.4% and 37.7%, respectively).

Among Black persons, the percentage with private coverage rose to 56.6% in 2022, up from 55.1% in 2021, and the percentage with public coverage fell to 41.2% in 2022, down from 42.7% in 2021.

Among White individuals, the percentage with private coverage fell to 72.3% in 2022, down from 73.2% in 2021, and the percentage with public coverage rose to 35.4% in 2022, up from 34.6% in 2021.

Immigration Status (Total Population)
Rates of private and public coverage were unchanged among the native-born population at 67.6% and 36.7%, respectively. Among the foreign-born population, the percent with private coverage was unchanged at 54.4% while the percentage with public coverage rose to 32.8% in 2022 from 31.7% in 2021.

Medicaid Expansion Status (Total Population)
In expansion states, the share with private coverage fell to 66.6% in 2022 from 67.1% in 2021 while the share with public coverage rose to 37.6% in 2022 from 36.9% in 2021. In nonexpansion states, the share of the population with private coverage and public coverage were unchanged at 63.6% and 32.9%, respectively.

Employment Status (Nonelderly Adults)
Public coverage rose among working nonelderly adults in 2022 to 12.6% from 11.8% in 2021 while the share with private coverage was stable at 80.0%. Public coverage rose among those who worked full-time year round and those who worked less than full-time, year round, rising to 8.9% and 23.5%, respectively. Private coverage was unchanged among these groups at 84.8% and 66.0%, respectively. Private and public coverage were unchanged among those who did not work, at 47.5% and 42.6%, respectively.

More on the insurance coverage changes among working-age adults can be found in a topically focused blog released today by the Census Bureau.

Notes
All changes are tested at the 90% confidence level.
All estimates come from the 2022 and 2023 Current Population Survey Annual Social and Economic Supplements, which provide data for years 2021 and 2022, 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.

COVID-19 Public Health Emergency Impacts

Continuous Coverage Requirement

The continuous coverage requirement that prevented states from terminating individuals’ Medicaid coverage during the 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 each state has a year to navigate a return to normal operations while also meeting reporting requirements set by CMS for publicly sharing coverage transitions and outcomes data during this time. While the health insurance estimates released by the US Census Bureau for 2022 precede the beginning of the unwinding process, the data will provide an essential baseline for understanding how health insurance coverage is distributed across the U.S. and among the states prior to the unwinding, as well as marker to measure the impacts of this seismic coverage transition as potentially millions of individuals, both adults and children, are poised to lose Medicaid and must either find another form of coverage (e.g., state-based marketplace or employer-sponsored insurance [ESI]), or risk becoming uninsured.

Several resources have been compiled by SHADAC to track the unwinding process in a variety of avenues, falling under several broader categories:

Guidance for States

• Using Surveys to Monitor Coverage Transitions During the Unwinding of the Medicaid Continuous Coverage Requirement
• Best Practices for Publicly Reporting State Unwinding Data

Health Insurance Coverage Data Tracking

• State-Based Marketplace Transition Data During the Unwinding
• State Dashboards to Monitor the Unwinding of the Medicaid Continuous Coverage Requirement
• Tracking Health Insurance Coverage During the Unwinding: Monthly Data from the Household Pulse Survey

Data Collection and Dissemination - Nonresponse Bias

While Census Bureau researchers have not cited any concerns with CPS ASEC data collection or release processes, an ongoing issue of persistently lower response rates and resultant nonresponse bias has been documented for the past few years, coinciding with the beginning of the COVID-19 pandemic. In March 2023 (the point in time that the CPS is administered), the response rate fell to its lowest point yet, at 68.9%, compared to a pre-pandemic rate of 82% (March 2019). This lower response rate particularly affects the CPS measures of income, and since 2020, the Census Bureau has been working to address the bias in higher reported earnings using new weighting methods to create adjusted income and poverty estimates. More detail on this methodology can be found in a companion blog released today by Census Bureau researchers.

5-year ACS Tables: State and County Uninsured Estimates

February 2023:

Following the release of 2021 single-year estimates of health insurance coverage, household income, and poverty levels, the U.S. Census Bureau has published 5-year ACS data files. These estimates are created by pooling together five years of ACS data to produce estimates for areas and subgroups with smaller populations.

The interactive map below provides users with the opportunity to view health insurance coverage estimates, specifically the percentage of uninsured for each state and all counties for the pooled years 2017-2021,* which can be found via the Census Bureau’s data.census.gov tool. Click on a county in the map below to access state/county data tables. Counties are searchable by bookmark in each state file.

2017-2021 American Community Survey (ACS) 5-Year Estimates: Percent Uninsured, Total Civilian Noninstitutionalized Population by County

Click here to view estimates for Puerto Rico by municipio.
Click here to view a 50-state table of estimates.

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About the ACS
The ACS is a household survey that began in 2005 and produces annually updated data on a variety of population characteristics, including health insurance coverage. In total, the ACS surveys approximately three million US households each year. An important feature of the ACS is that it includes a large enough sample for state‐level and sub‐state estimates.

The Census Bureau publishes 1-year estimates for areas with populations of 65,000 or more and 5-year estimates (covering 60 months) for all statistical, legal, and administrative entities.

The ACS began asking survey respondents about health insurance coverage during the 2008 calendar year. Specifically, the survey asks respondents about current coverage for each person in the respondent’s household. A person is categorized as “insured” if he or she has coverage at the point in time at which the survey is administered.

*The U.S. Census Bureau has extensively cautioned against the use of single-year 2020 ACS estimates due to disruptions caused by the COVID-19 pandemic (e.g., limited means of data collection, such as shutdowns of mail operations, switches to telephone-first methodologies, etc., leading to low response rates and nonresponse bias). However, the Census Bureau believes that course corrections to address nonresponse bias, and the larger sample resulting from pooled data mean that the “data are fit for public release, government and business uses, and understanding the social and economic characteristics of the U.S. population and economy.”[1]

How Are These Estimates Different from the Estimates that SHADAC Publishes Using Census Bureau Micro-Data Files?
Two definitions used by the Census Bureau to generate the tabulations above differ from those that SHADAC uses to generate tabulations for State Health Compare. The definitional differences are as follows:

Family
The Census Bureau defines a family as “all related people in a household.”

SHADAC defines a family using a measure called the “Health Insurance Unit” (HIU), which includes all individuals who would likely be considered a family unit in determining eligibility for either private or public coverage.

To learn more about the 2020 update of SHADAC's Health Insurance Unit (HIU) see our HIU resource page, which houses two issue briefs: The first describes the SHADAC HIU, its purpose, the most recent update, and improvements to HIU data inputs; and the second outlines the impacts of using the SHADAC HIU in analysis so that researchers can assess whether the SHADAC HIU is suitable for their research and what the potential impacts of its use might be. The page also provides a link to STATA and SAS codes to aid in the use of the HIU variable.

Family Income
The Census Bureau determines family income as a percentage of the Federal Poverty Level (FPL), which is a definition of poverty used primarily for statistical purposes. For example, FPL is used to estimate the number of Americans living in poverty each year.

SHADAC determines family income as a percentage of the U.S. Department of Health and Human Services’ Federal Poverty Guideline (FPG), which is a measure used for administrative purposes. For example, FPG is used to determine eligibility for federal programs such as Medicaid and the Supplemental Nutrition Assistance Program (SNAP).

Check out our blog post from May 2022 to learn more about the difference between FPL and FPG.

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Related ACS Materials:

An Annual Conversation with the U.S. Census Bureau: Health Insurance Coverage Estimates from the 2021 ACS and CPS (Webinar)

2021 ACS Tables: State and County Uninsured Rates, with Comparison Year 2019 (Blog)

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[1] U.S. Census Bureau. (2022, February 7). Census Bureau Update on 2016–2020 American Community Survey (ACS) 5-Year Estimates [Press Release CB22-RTQ.01]. https://www.census.gov/newsroom/press-releases/2022/acs-5-year-estimates-update.html

2021 ACS Data: State and County Uninsured Rates, with Comparison Year 2019

January 2023:

Each year, SHADAC uses data released from the American Community Survey (ACS) via the U.S. Census Bureau's data.census.gov tool to produce estimates of uninsurance at the state and county level.*

Click on a state in the interactive map below to view a PDF table of uninsured rates by state and sub-state geographies, but also by demographic characteristics (e.g., age, race/ethnicity, and poverty level) for 2021 and comparison year 2019.^

Click here to view uninsurance estimates for the United States.
Click here to view uninsurance estimates for Puerto Rico and its municipios.

Note: These tables present uninsured rates, which indicate the share of the population that is uninsured. For example, a 10 percent uninsured rate for adult women indicates that 10 percent of all adult women are uninsured.

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Additional Estimates (50-State Comparisons)

Maps & Tables of Private, Public, & Uninsured Changes from 2019 to 2021
Private Coverage Rates by State, Change from 2019 to 2021, for All People
Public Coverage Rates by State, Change from 2019 to 2021, for All People
Uninsurance Rates by State, Change from 2019 to 2021, for All People
Uninsurance Rates by State, Change from 2019 to 2021, for Children under age 18

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About the ACS
The ACS is a household survey that began in 2005 and produces annually updated data on a variety of population characteristics, including health insurance coverage. In total, the ACS surveys approximately three million U.S. households each year. An important feature of the ACS is that it includes a large enough sample for state‐level and sub‐state estimates.

The ACS began asking survey respondents about health insurance coverage during the 2008 calendar year. Specifically, the survey asks respondents about current coverage for each person in the respondent’s household. A person is categorized as “insured” if he or she has coverage at the point in time at which the survey is administered.

*Why Aren’t Estimates Provided for All Counties?
Due to sample size constraints, single-year ACS estimates are available at the county level only for counties with a population greater than 65,000.

^Why Are the Estimates Being Compared to 2019 and not to 2020?
Impacts of the COVID-19 pandemic on survey data collection and dissemination efforts, as well as the presence of measurable nonresponse bias, resulted in ACS estimates from data year 2020 being released on an “experimental only” basis, and the Census Bureau has recommended that these estimates not be used or compared to any other data year.

How Are These Estimates Different from the Estimates that SHADAC Publishes Using Census Bureau Micro-Data Files?
Two definitions used by the Census Bureau to generate the tabulations above differ from those that SHADAC uses to generate tabulations for State Health Compare. The definitional differences are as follows:

Family
The Census Bureau defines a family as “all related people in a household.”

SHADAC defines a family using a measure called the “Health Insurance Unit” (HIU), which includes all individuals who would likely be considered a family unit in determining eligibility for either private or public coverage.

To learn more about the 2020 update of SHADAC's Health Insurance Unit (HIU) see our HIU resource page, which houses two issue briefs: The first describes the SHADAC HIU, its purpose, the most recent update, and improvements to HIU data inputs; and the second outlines the impacts of using the SHADAC HIU in analysis so that researchers can assess whether the SHADAC HIU is suitable for their research and what the potential impacts of its use might be. The page also provides a link to STATA and SAS codes to aid in the use of the HIU variable.

Family Income
The Census Bureau determines family income as a percentage of the Federal Poverty Level (FPL), which is a definition of poverty used primarily for statistical purposes. For example, FPL is used to estimate the number of Americans living in poverty each year.

SHADAC determines family income as a percentage of the U.S. Department of Health and Human Services’ Federal Poverty Guideline (FPG), which is a measure used for administrative purposes. For example, FPG is used to determine eligibility for federal programs such as Medicaid and the Supplemental Nutrition Assistance Program (SNAP).

Check out our blog post from May 2022 to learn more about the difference between FPL and FPG,

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Related ACS Materials:

• 2021 ACS: Estimates Show Declining Uninsurance Rates Across 28 States, Driven by Rise in Public Coverage and Fall in Private Coverage (Interactive Maps)
• Webinar: An Annual Conversation with the U.S. Census Bureau: Coverage Estimates from the 2021 ACS and CPS

Planalp, Colin
Research Fellow

p 612-624-4850
e cplanalp@umn.edu

Charting Two Decades of the Evolving Opioid Crisis

Just over a decade after the U.S. Centers for Disease Control and Prevention (CDC) declared an “epidemic” of overdoses from prescription painkillers in 2011, the opioid crisis is worse than ever—yet it only vaguely resembles those earlier days. While people are still dying of overdoses tied to prescription opioids, the problem has largely shifted to illicitly trafficked opioids, such as fentanyl, and is now deeply intertwined with other non-opioid substances, such as methamphetamine and cocaine.

This blog examines the history and evolution of the opioid crisis through several charts based on data from SHADAC’s State Health Compare.

Changing attitudes in opioid prescribing

Today, it is broadly accepted that the over-prescribing of opioid painkillers—such as the blockbuster drug Oxycontin (a brand-name version of oxycodone produced by Purdue Pharma) and related semi-synthetic opioid hydrocodone—sparked what became an epidemic of overdoses and deaths. Over more than 10 years, deaths from overdoses involving those medications gradually crept upward until they finally capture widespread attention. When the toll of overdose deaths from prescription opioids was fully recognized and the U.S. healthcare system started to grapple with the problem, efforts to curb prescribing began.

In the first chart, data from the U.S. Drug Enforcement Agency show how legal sales of oxycodone and hydrocodone began the early days of the crisis at about 5 kilograms per 100,000 people in 2000. But within a decade, oxycodone sales roughly quadrupled and hydrocodone sales almost tripled (Figure 1). Following growing awareness of the problem, legal sales of both drugs—driven by prescriptions written by healthcare providers—have declined substantially. In 2021, hydrocodone sales had fallen to about 5 kilograms per 100,000 people, and oxycodone sales to less than 10 kilograms per 100,000 people.

Figure 1: Prescription opioid painkiller sales, 2000-2021

Source: SHADAC analysis of U.S. Drug Enforcement Agency's Automated Reports and Consolidated Ordering System (ARCOS) Retail Drug Summary Reports, obtained from statehealthcompare.shadac.org.

These data demonstrate that legal sales of prescription opioid painkillers are down dramatically from their heights when the CDC first rang alarm bells over the issue. However, some experts and advocates argue that the abrupt pivot in opioid prescribing practices was not done carefully enough, with many people who were already addicted to opioids suddenly cut off without sufficient screening for addiction or access to treatment. And data show that although deaths from prescription opioids have essentially plateaued since prescribing of opioid painkillers dropped, opioid overdose deaths have still continued to climb.

Persistently growing rates of opioid overdose deaths

Because overdose deaths were driven largely by prescription opioid painkillers in the early days of the epidemic, the hope and expectation was that death rates would drop as healthcare providers curtailed their prescribing of the risky medications. But this next set of charts shows that this hope was not fully realized.

In fact, the enhanced scrutiny on opioid prescribing and declining sales of prescription opioid painkillers appears to have marked a turning point in the epidemic. While deaths from prescription opioid painkillers have not declined dramatically, their growth trend leveled off and has remained relatively steady, around 4 deaths per 100,000 people, for almost a decade (Figure 2).

Figure 2: Prescription opioid painkiller death rates, 1999-2020

Source: SHADAC analysis of National Center for Health Statistics mortality files, obtained from statehealthcompare.shadac.org.

But to the shock and horror of many, overall overdose death rates—including prescription opioid painkillers as well as all other kinds of opioids—only continued to accelerate.

Figure 3: Death rates from all opioid types, 1999-2020

Source: SHADAC analysis of National Center for Health Statistics mortality files, obtained from statehealthcompare.shadac.org.

In less than a decade, the overdose death rate from all opioids roughly tripled, from 7.3 deaths per 100,000 people in 2011 to 21.4 deaths per 100,000 people in 2020 (Figure 3). But this time, the growth came from different types of opioids. First came heroin—an opioid that is without legal medical uses in the U.S. and is only available through the illicit drug trade. This was followed by fentanyl (and other closely related synthetic opioids), which does have legal medical uses but has been adopted by traffickers as a new drug of choice.

Figure 4: Death rates from fentanyl and other synthetic opioids, 1999-2020

Source: SHADAC analysis of National Center for Health Statistics mortality files, obtained from statehealthcompare.shadac.org.

In just a few years, the opioid crisis had transformed. What began as a problem rooted in widespread availability of prescription opioid painkillers shifted to illicitly trafficked opioids as legal opioid sales started to fall. By 2020, heroin overdose death rates had more than tripled since the CDC declared an opioid epidemic. And overdose death rates from fentanyl and similar synthetic opioids had grown more than 20 times (Figure 4).

In some ways, those developments may not be surprising. Economics tells us that when a good becomes scarce—such as prescription opioids after recognition of the crisis—people tend to cut back their consumption. But when people can’t simply stop their consumption, as in the case of addiction, they often turn to substitutes. With opioids, that unfortunately left many people to seek out substances such as heroin on the illicit market, where the purity and potency is unreliable, making them even riskier than prescription opioids. And once drug traffickers embraced the potent opioid fentanyl, it pervaded the illegal drug trade and became entangled with non-opioid substances, such as cocaine and methamphetamine.

A metastatic phase of the crisis

The opioid crisis is complex, and definitive evidence of how the epidemic evolved is hard to find. That is particularly the case in understanding the role of the illicit drug trade. However, it is widely accepted that some people shifted to heroin as prescription opioid painkillers became harder to obtain. Afterward, drug traffickers incorporated fentanyl into their supplies, sometimes to cheaply boost the potency of their heroin or simply to pass fentanyl off as heroin. Another approach was manufacturing counterfeit prescription medications, such as fake Oxycontin pills that actually contained fentanyl rather than the less-potent opioid oxycodone.

Over time, fentanyl became ubiquitous in the U.S. illicit drug market. Non-opioid illicitly trafficked substances, particularly cocaine and methamphetamine, are now often contaminated with fentanyl and related powerful opioids. And various kinds of illicitly trafficked counterfeit medications are found to contain fentanyl. In some cases, those counterfeit pills may mimic prescription opioid painkillers, but other counterfeit pills may contain fentanyl, even if the legitimate version does not. For instance, law enforcement agencies have reported interdicting fake stimulants (e.g., Ritalin and Adderall pills) that are mixtures of methamphetamine and fentanyl, even though the genuine medications do not contain opioids.

Ultimately, the pernicious impact of fentanyl and related synthetic opioids have transformed the opioid crisis. The prescription opioid painkillers that sparked this epidemic now only account for a fraction of drug overdose deaths in the U.S. (Figure 5), dwarfed by the toll of synthetic opioids such as fentanyl. And largely because of the pervasiveness of fentanyl in the market for illicit substances, deaths involving non-opioids also have grown to historic levels.

Figure 5: National Death rates for opioid and non-opioid substances, 2020

Source: SHADAC analysis of National Center for Health Statistics mortality files, obtained from statehealthcompare.shadac.org.

Lessons from opioids data

More than two decades into the opioid crisis, the main consistency is that the problem is continually evolving. When the role of prescription opioids in overdose deaths led the health care system to curtail dangerously generous prescribing of those medications, some people seemingly transitioned to illicitly trafficked opioids. When drug traffickers saw an opportunity to enhance their profits on heroin sales by using fentanyl and by manufacturing counterfeit pills, the epidemic became even deadlier. And as fentanyl became more pervasive, it also became intertwined with non-opioid substances, such as cocaine and methamphetamine—further extending the deadly reach of opioids.

To better understand and address the opioid crisis, it is important to use data to identify evolving patterns and trends and to anticipate new developments before they snowball into larger public health threats. Examining the history of the opioid crisis may prove useful to avoid recurrences of similar situations in the future, but it is also important to recognize the limitations of retrospective data for designing solutions to a dynamic situation. For instance, an overemphasis on prescribing of opioid painkillers now, when the vast majority of drug overdose deaths are caused by illicitly trafficked substances, could be considered akin to driving down a busy interstate highway while fixed on the rearview mirror.

Related Reading:

Blog: 2020 U.S. alcohol-involved deaths climbed by 26.6%, and drug overdose deaths by 30.6%

Brief: Strategies to Increase Access to Medications for Opioid Use Disorder during the COVID-19 Pandemic and Beyond

Resource Page: The Opioid Epidemic in the United States

Planalp, Colin
Research Fellow

p 612-624-4850
e cplanalp@umn.edu

Pandemic drinking may exacerbate upward-trending alcohol deaths

Even before 2020, alcohol-involved deaths reached a modern record

Considering the well-deserved attention paid to the opioid crisis in recent years, few people might guess that rates of alcohol-involved deaths were as high as or higher than opioid overdose death rates in nearly half of states (Figure 1).¹ Like the opioid crisis, the trend in alcohol-involved deaths is also worsening, having grown by roughly 50 percent in just over a decade. All this was before the coronavirus crisis had even begun.

Figure 1. State alcohol death rates vs. opioid death rates, 2019

Now, evidence is accumulating that the pandemic precipitated dangerous changes in the way people consume alcohol in the United States. For instance, research has found increased alcohol sales since the crisis began, a finding illustrated by data showing that liquor taxes represented a rare instance of increased revenues for some states, such as Minnesota, during the COVID pandemic.^2,3 Other studies have found that U.S. adults report consuming more alcohol in order to deal with pandemic-related stress, and that they are drinking more frequently and engaging in more high-risk drinking behaviors, such as heavy drinking and binge drinking.^4,5,6

As we climb our way out of the immediate crisis, the U.S. will need to shift attention back to long-running public health threats. Beyond the obvious toll of the virus itself, another legacy of the pandemic may be the exacerbation of existing problems, including alcohol-related deaths and the opioid crisis. The opioid crisis was commonly recognized before 2020, but the upward trend in alcohol deaths was still occurring largely under the radar (Figure 2). But recent attention to risky pandemic-related alcohol consumption can sharpen our focus on this emerging concern.

Figure 2. U.S. alcohol-involved death rates, 2000-2019

With alcohol especially, the U.S. has a window of opportunity to intervene before many people’s pandemic-era risky drinking habits result in deaths, since the bulk of alcohol-involved deaths result from years of excessive drinking. In the coming years, it will be vital for states to monitor and study these issues and to consider doubling down on policy initiatives to curb the tide through efforts such as enhancing access to treatment of substance use disorder and by persuading and assisting people in recalibrating their alcohol consumption to healthier levels.