The Opioid Crisis and Educational Performance

• DOI: http://doi.org/10.1177/00027162231151523
• Published date: 01 September 2022
• Date: 01 September 2022

188 ANNALS, AAPSS, 703, September 2022

DOI: 10.1177/00027162231151523

The Opioid

Crisis and

Educational

Performance

By

RAJEEV DAROLIA,

SAM OWENS,

and

JOHN TYLER

1151523ANN The Annals of the American AcademyThe Opioid Crisis and Educational Performance

research-article2023

We propose a simple model of how opioids in a com-

munity can impact the educational outcomes of chil-

dren based on both the extent of exposure to opioids in

the community and on the child’s vulnerability to any

given level of exposure. We then use national data to

document where and how the opioid crisis has inter-

sected with students’ performance on standardized test

scores in the U.S., focusing particularly on rural com-

munities. Finally, we estimate the extent to which vari-

ation in one measure of the opioid crisis, drug-related

mortality, is related to variation in test scores. We find

strong relationships between the two, as well as evi-

dence that the relationship is particularly salient for

third-grade students in rural communities.

Keywords: opioids; rural schools; at-risk students;

children’s vulnerability; educational per-

formance

The opioid crisis is now widely recognized as

one of the most important public health

emergencies of our time. Opioid overdoses led

to over forty thousand deaths in 2016, more

than fivefold the levels from the late 1990s

(U.S. Department of Health and Human

Services 2019). The issue is particularly acute

for rural communities, where residents may

face higher opioid prescription and drug-

related mortality (DRM) rates, and which may

face relatively high barriers to effective policy

responses that rely on the adequacy of infra-

structure like transportation and healthcare

(García et al. 2019; Hancock et al. 2017).

Rajeev Darolia (Rajeev.darolia@uky.edu) is the Wendall

H. Ford Professor of Public Policy in the Martin School

of Public Policy and Administration at the University

of Kentucky.

Sam Owens (Samuel.owens@uky.edu) is a PhD candi-

date in the Martin School of Public Policy and

Administration at the University of Kentucky.

John Tyler (John_tyler@brown.edu) is a professor of edu-

cation, economics, and public policy at Brown University.

Correspondence: Rajeev.Darolia@uky.edu

THE OPIOID CRISIS AND EDUCATIONAL PERFORMANCE 189

Recent high-profile litigation and settlements among states and local govern-

ments with drug companies have highlighted some of the costs of the opioid

epidemic. The dollar amounts discussed in some of these cases have been huge;

for example, Purdue Pharma and Mallinckrodt agreed to national settlements of

about $10 billion and $1.6 billion, respectively, and a judge in Oklahoma recently

awarded a settlement of $465 million in a suit brought against Johnson and

Johnson (although this award was later overturned). The settlements in these

cases brought by various state attorneys general are based on estimated addi-

tional costs to state and local governments generated by the opioid crisis such as

public healthcare, treatment facilities, law enforcement, criminal justice, and jail

expenses. While these figures are notable, the total societal costs of the opioid

epidemic are likely much higher when the less direct harm that is visited on com-

munities by the crisis is factored into the equation. In this study, we examine one

such source of indirect cost: the extent to which exposure to the opioid crisis may

be negatively affecting the education outcomes of children.

Drawing from literature on the effects of childhood exposure to environmen-

tal stressors and violence, we propose a simple model of how opioids in a com-

munity can impact the education outcomes of young children. The model

suggests that children’s education outcomes will be influenced by the level or

intensity of the crisis in a community, the extent of a child’s exposure to the

community-wide crisis level, and the child’s vulnerability given their level of

exposure.

Following a discussion of the model relating the opioid crisis to education

outcomes, we use national data to document where and how the opioid crisis has

intersected with students’ performance on standardized test scores in the U.S.,

focusing particularly on rural communities. County-level DRM rates are our

primary measure of the intensity of the opioid crisis in a given county and year,

and third-grade and eighth-grade test scores from the years 2009 to 2014 repre-

sent the education outcomes of interest. Mapping the intersection of DRM and

test scores reveals remarkable spatial differences, with notable “hot spots” in the

Appalachian Belt and the industrial Midwest. It also shows areas of concern in

the Southwest and West, suggesting a more acute need for concern in some areas

of the country than in others. We then go on to estimate the extent to which vari-

ation in one measure of the opioid crisis—average lifetime DRM rate—is related

to variation in test scores, finding strong relationships between the two, as well as

evidence that the relationship is particularly salient for third-grade students in

rural communities.

Education can be a pathway to economic and social mobility, especially for

children from disadvantaged backgrounds; and when this pathway is imperiled,

it is the most vulnerable children who have the most to lose. The fact that some

of the areas hardest hit by the opioid crisis—the Appalachian belt, the industrial

Midwest, impoverished rural communities across the nation—are also areas asso-

ciated with markers of childhood disadvantage, such as high levels of poverty and

parental unemployment, lends urgency to the opioid crisis–education question.

In other words, if the opioid crisis has negative spillover effects on the educa-

tional achievement of children, it is likely that the opioid crisis will exacerbate

190 THE ANNALS OF THE AMERICAN ACADEMY

already existing gaps in the structure of economic opportunity for the next

generation.

The Phases and Geography of the Opioid Crisis

The opioid crisis is generally divided into three waves, with each wave character-

ized by the category of opiate—first natural and semisynthetic substances, then

heroin, and finally synthetically derived substances—that is the primary driver of

overdose rates at the time.1 The first wave began in the 1990s with a steady rise

in overdose deaths from prescription natural and semisynthetic opioids, as well

as prescribed methadone. In 2010, the second phase began with a dramatic rise

in heroin overdose deaths, tripling between 2010 and 2015. An even steeper

increase in overdose deaths from synthetic opioids brought the third and current

phase, which began around 2013 (Dasgupta, Beletsky, and Ciccarone 2018). The

timeframe for our analysis coincides with the end of the first wave and beginning

of the third wave, capturing the changing face of the crisis as legislative actions

on prescription drugs lowered the supply of semisynthetic drugs, setting the

stage for increased heroin and synthetic opioid usage across the nation.

Our primary measure for the intensity of opioid use in our analysis is county-

level DRM rates from the Institute for Health Metrics and Evaluation (IHME;

http://www.healthdata.org/). Centers for Disease Control and Prevention (CDC)

DRM data are limited due to issues including the suppression of counties with

low DRM numbers and the potential underreporting of overdose deaths. IHME

DRM data are imputed using CDC DRM data, Census population counts, and

small area Bayesian estimation models. It is important to note that while these

data are not exact counts of overdose deaths by county, they are the best approxi-

mation and allow comparison across counties and years. See Appendix A for a

more detailed description of the data used in this article. While IHME DRM

rates are based on all drug-related deaths which overestimates mortality rates

due strictly to opioid-related deaths, the latter are estimated to account for about

70 percent of DRM in recent years and opioid-related deaths are the primary

driver of the growth in drug-related deaths over the past 20 years (CDC 2018a).

Moreover, mortality related to all types of drugs, not just opioids, would be

expected to affect students according to our conceptual model, presented below.

Of course, in addition to fatalities, there are other potential negative effects of

opioid use, including nonfatal overdose emergencies that lead to hospitalization

and ongoing addiction with all the associated negative societal spillovers.

Moreover, opioid abuse can co-occur with other substance use disorders, depres-

sion, and other physical and psychological ailments. Thus, our measure repre-

sents a relatively extreme consequence of opioid use.

We display the trend in average county-level DRM rates from 1980 to 2014 in

Figure 1 (see Monnat Forthcoming for more trends in more recent years). DRM

rates have been increasing since the early 1980s, with an uptick in mortality rates

in the 1990s and a steeper increase starting around the year 2000. As displayed

in panel A, from 2000 to 2014, average DRM in counties rose from 3.7 to 10.0