ADD5107: Week 8 Discussion: Evidence-Based Approaches and Co-Occurring Disorders

R E S E A R CH AR T I C L E

Multiple DSM‐5 substance use disorders: A national study of US adults

Sean Esteban McCabe1,2 | Brady T. West3 | Emily M. Jutkiewicz4 | Carol J. Boyd1,5,6

1 Institute for Research on Women and

Gender, University of Michigan, Ann Arbor,

Michigan, USA

2Substance Abuse Research Center,

University of Michigan, Ann Arbor, Michigan,

USA

3Survey Research Center, Institute for Social

Research, University of Michigan, Ann Arbor,

Michigan, USA

4Department of Pharmacology, University of

Michigan, Ann Arbor, Michigan, USA

5School of Nursing, University of Michigan,

Ann Arbor, Michigan, USA

6Addiction Center, Department of Psychiatry,

University of Michigan, Ann Arbor, Michigan,

USA

Correspondence

Sean Esteban McCabe, Institute for Research

on Women and Gender, University of

Michigan, 204 S. State St., Ann Arbor, MI

48109‐1290, USA. Email: [email protected]

Funding information

National Institute on Drug Abuse, National

Institutes of Health, Grant/Award Number:

R01DA031160 and R01DA036541

Abstract

Objective: Our aim is to determine the lifetime and past‐year prevalence estimates of

multiple Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM‐5) substance

use disorders (SUDs) among U.S. adults.

Methods: The 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions

featured in‐person interviews with a nationally representative sample of adults aged 18 and older.

Results: The majority of past‐year nonalcohol DSM‐5 SUDs had at least 1 other co‐occurring

past‐year SUD, ranging from 56.8% (SE = 3.4) for past‐year prescription opioid use disorder to

97.5% (SE = 2.7) for past‐year hallucinogen use disorder. In contrast, only 15.0% (SE = 0.6) of

past‐year alcohol use disorders had a co‐occurring past‐year SUD. The odds of past‐year multiple

SUDs were greater among males, younger adults, African‐Americans, and those with mood,

personality, posttraumatic stress, or multiple psychiatric disorders.

Conclusions: Assessment, diagnosis, and treatment often focus on individual substance‐spe-

cific SUDs rather than multiple SUDs, despite evidence for substantial rates of polysubstance use

in clinical and epidemiological studies. There are notable differences in the prevalence of multiple

SUDs between alcohol use disorders and other nonalcohol SUDs that have important clinical

implications; for example, multiple SUDs are more persistent than individual SUDs. These findings

suggest that clinical assessment and diagnosis should screen for multiple SUDs, especially among

adults with nonalcohol DSM‐5 SUDs.

KEYWORDS

DSM‐5, epidemiology, polysubstance, substance use disorders

1 | INTRODUCTION

Substance use disorders (SUDs) contribute substantially to morbidity

and mortality in the United States and worldwide (Compton, Thomas,

Stinson, & Grant, 2007; Grant et al., 2016; Hasin et al., 2016). Drug

overdose deaths are the leading cause of injury death in the United

States, with over 47,000 drug overdose deaths occurring in 2014

and many involving polysubstance use behaviors (Centers for Disease

Control and Prevention, 2014; Rudd, Aleshire, Zibbell, & Gladden,

2016). Approximately one in every 10 U.S. adults will develop a

nonalcohol drug use disorder involving cannabis, cocaine, heroin, hallu-

cinogens, inhalants, prescription opioids, sedatives or tranquilizers,

stimulants, and/or other drugs in their lifetime (Grant et al., 2016;

Hasin et al., 2016). Although several studies have documented high

rates of polysubstance use behaviors, these studies often fail to

examine concurrent or multiple Diagnostic and Statistical Manual of

Mental Disorders fifth edition (DSM‐5) SUDs (Armour, Shorter, Elhai,

Elklit, & Christoffersen, 2014; Carter et al., 2013; Chen, Yi, & Moss,

2014; Connor, Gullo, White, & Kelly, 2014; McCabe, West, Schepis,

& Teter, 2015; Midanik, Tam, & Weisner, 2007; Olthuis, Darredeau,

& Barrett, 2013; Quek et al., 2013; Reyes, Pérez, Colón, Dowell, &

Cumsille, 2013; Smith, Farrell, Bunting, Houston, & Shevlin, 2011).

On the basis of these high rates of polysubstance use behaviors, future

research is needed that shifts from measures that are substance

specific to more sophisticated measures that account for multiple

SUDs (Connor et al., 2014).

There is also evidence that the profile of substance use behaviors

among individuals entering U.S. substance abuse treatment facilities

has changed dramatically over the past two decades based on the

Treatment Episode Data Set (Substance Abuse and Mental Health

Received: 25 January 2017 Revised: 29 April 2017 Accepted: 20 June 2017

DOI: 10.1002/hup.2625

Hum Psychopharmacol Clin Exp. 2017;32:e2625. https://doi.org/10.1002/hup.2625

Copyright © 2017 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/hup 1 of 10

Services Administration [SAMHSA], 2006, 2012, 2014a). More spe-

cifically, there has been a significant shift in the primary substances

of abuse observed in those entering substance abuse treatment facil-

ities. For instance, the percentage of substance abuse treatment

facility admissions reporting alcohol as the primary substance of

abuse has decreased from 57% in 1993 to 38% in 2013, whereas

the percentage of substance abuse treatment facility admissions for

cannabis, opioids, and stimulants as the primary substance increased

from 22% in 1993 to 53% in 2013 (SAMHSA, 2006, 2012, 2014a). In

addition, there is growing evidence that adverse consequences

appear to be more severe among polysubstance users relative to

single‐drug users (Abé et al., 2013; McCabe, Cranford, Morales, &

Young, 2006; SAMHSA, 2014a).

Although prior studies have found that DSM‐IV andDSM‐5 alcohol

and cannabis use disorders often co‐occur with other SUDs, most of

these studies have aggregated less prevalent substance‐specific SUDs

such as cocaine, heroin, hallucinogens, inhalants, prescription opioids,

sedatives or tranquilizers, stimulants, and/or other drugs (Compton

et al., 2007; Grant & Pickering, 1996; Grant et al., 2016; Hasin et al.,

2016; Stinson et al., 2005). As a result, several studies have concluded

that more in‐depth investigations regarding the prevalence of multiple

DSM‐5 SUDs for these less prevalent substance‐specific SUDs are

warranted because the epidemiology of SUDs may differ across

individual drug classes (Compton et al., 2007, 2013; Grant et al.,

2016). Although prior research has found that substance‐specific SUDs

are significantly associated with sociodemographic characteristics (e.g.,

sex, race, and age) and other psychiatric disorders (e.g., anxiety, eating,

mood, and personality disorders), the associations with these and

multiple SUDs have not been well examined (Grant, Goldstein, Saha,

et al., 2015; Grant et al., 2004; Hasin et al., 2016; Kessler, Chiu, Demler,

Merikangas, & Walters, 2005).

The current lack of information regarding multiple DSM‐5 SUDs

for these less studied drug classes represents an important gap in our

knowledge with direct relevance for enhanced screening, diagnosis,

prevention, and treatment efforts. Therefore, the primary objective

of this study was to examine the lifetime, prior‐to‐past‐year, and

past‐year prevalence and correlates associated with multiple DSM‐5

SUDs for 10 drug classes among U.S. adults based on a large nationally

representative sample: the 2012–2013 National Epidemiologic Survey

on Alcohol and Related Conditions (NESARC‐III).

2 | METHODS

2.1 | Sample

This study used data collected from the 2012–2013 NESARC‐III as

the primary source of information regarding DSM‐5 SUDs among

the general civilian noninstitutionalized population of individuals

18 years of age and older in the United States. The NESARC‐III

included the National Institute on Alcohol Abuse and Alcoholism

Alcohol Use Disorder and Associated Disabilities Interview Schedule

5 (AUDADIS‐5), a fully structured diagnostic interview conducted in

households. The NESARC‐III sample included persons living in

households, military personnel living off base, and persons residing

in the following group quarters: boarding or rooming houses,

nontransient hotels, shelters, facilities for housing workers, college

quarters, and group homes. In‐person interviews were conducted,

and the household, person, and overall response rates were 72%,

84%, and 60.1%, respectively. The NESARC‐III sample design and

weighting procedures, which adjust for potential biases introduced

by nonresponse, have been described in more detail elsewhere

(Grant, Chu, Sigman, et al., 2015; Grant, Goldstein, Saha, et al.,

2015). All procedures, including informed consent, received full

human subjects review and institutional review board approval,

and all relevant ethical safeguards have been met in relation to

human subject protection.

2.2 | Measures

The measures in the AUDADIS‐5 assessed several domains, including

sociodemographic and background characteristics, DSM‐5 SUDs, and

other DSM‐5 psychiatric disorders.

Sociodemographic and background characteristics were measured

with several items, including sex, age, race or ethnicity, marital status,

and geographical region based on the U.S. Census (northeast, south,

north central, and west).

DSM‐5 SUDs were assessed according to the criteria of the

DSM‐5 using the AUDADIS‐5, including drug‐specific diagnoses

for 10 substances: alcohol, cannabis, cocaine, heroin, hallucinogens,

inhalants, prescription opioids, sedatives or tranquilizers, stimulants,

and other drugs (e.g., ecstasy and ketamine). Substance‐specific

diagnoses were made for three different timeframes: past year,

prior to past year, and lifetime. Each DSM‐5 SUD diagnosis

required positive responses to two or more of the 11 criteria in

the 12 months preceding the interview or previously for each

drug‐specific SUD. In this study, remission from SUDs was defined

as not meeting criteria for SUD for a period of 12 months or lon-

ger among those who met full criteria for at least one SUD previ-

ously. The test–retest reliability and validity of each AUDADIS‐5

DSM‐5 SUD diagnosis have been examined in psychometric stud-

ies, with test–retest reliability ranging from fair to good (κ = .4–.7)

and dimensional criterion scales (intraclass correlation coeffi-

cient = .5–.9, respectively) ranging from fair to excellent in a large

general population sample (Grant, Goldstein, Smith, et al., 2015;

Grant, Goldstein, Saha, et al., 2015; Grant et al., 2016; Hasin,

Greenstein, et al., 2015). More specifically, the procedural validity

of the SUD diagnoses of the AUDADIS‐5 was previously assessed

using a clinician‐administered semistructured interview Psychiatric

Research Interview for Substance and Mental Disorders DSM‐5

version (PRISM‐5) in a large general population sample (Hasin,

Greenstein, et al., 2015). The concordance between AUDADIS‐5

and PRISM‐5 diagnoses of lifetime, prior‐to‐past‐year, and past‐year

DSM‐5 binary diagnoses were good for all substances except for

lifetime stimulants, prior‐to‐past‐year hallucinogens and stimulants,

and past‐year opioids.

DSM‐5 other psychiatric disorders were assessed using the

AUDADIS‐5, including lifetime anxiety disorders (i.e., agoraphobia,

generalized anxiety disorder, panic, and social and specific phobias),

mood disorders (i.e., bipolar, dysthymia, and major depressive

2 of 10 MCCABE ET AL.

disorder), eating disorders (i.e., anorexia nervosa, binge eating disorder,

and bulimia nervosa), personality disorders (i.e., antisocial personality

disorders, borderline, and schizotypal), and posttraumatic stress disor-

der. Consistent with DSM‐5, all these diagnoses excluded substance‐

and medical‐illness‐induced disorders. Reliability and validity of the

DSM‐5‐based AUDADIS‐5 diagnoses of other psychiatric disorders

have been established in numerous psychometric studies (Grant, Gold-

stein, Smith, et al., 2015; Hasin, Shmulewitz, et al., 2015).

2.3 | Data analyses

All analyses in this study were design‐based, using the survey weights

provided in the NESARC‐III data set to compute unbiased population

estimates of the descriptive parameters of interest and the available

codes describing the sampling strata and sampling clusters from the

multistage stratified cluster sampling design to compute linearized var-

iance estimates for the weighted estimates. Initial analyses focused on

estimation of the lifetime, prior‐to‐past‐year, and past‐year prevalence

of SUDs for specific drugs, multiple SUDs for specific drug classes, and

ratios of the prevalence of multiple SUDs to the prevalence of individ-

ual SUDs for 10 specific drug classes. Ratios closer to 100% in this case

would indicate that nearly all of the SUDs for a specific drug were

accompanied by other SUDs.

Subsequent analyses focused on differences between subgroups

defined by sociodemographic characteristics and prior psychiatric his-

tory in the prevalence of individual and multiple SUDs. These differ-

ences were tested using design‐adjusted Rao–Scott chi‐square tests.

The lifetime, prior‐to‐past‐year, and past‐year prevalence of multiple

SUDs were compared for subgroups defined by sex (female or male),

race or ethnicity (White, African American, Native American, Asian or

Pacific Islander, or Hispanic), age (18–29, 30–44, 45–64, or 65 years

and over), and presence of other DSM‐5 psychiatric conditions includ-

ing anxiety, eating, mood, personality, and posttraumatic stress disor-

ders (yes or no), in both bivariate analyses and multivariate logistic

regression models. Importantly, given the overlap in some of the

sociodemographic variables used to compute poststratification adjust-

ments for the NESARC‐III weights (Grant, Chu, Sigman, et al., 2015)

and the variables used as covariates in our analytic models, we consid-

ered both weighted and unweighted estimates of the coefficients to

assess possible inflation of the standard errors of the weighted esti-

mates relative to changes in the actual estimates of the coefficients

(Korn & Graubard, 1999). Finally, males and females were compared

in terms of the probability of having any past‐year SUD, having only

one past‐year SUD, and having multiple past‐year SUDs, as a function

of prior‐to‐past‐year SUD status. The svy: commands in the Stata soft-

ware (Version 14.1) were used for all analyses.

3 | RESULTS

3.1 | Estimated population characteristics and prevalence of multiple DSM‐5 SUDs

The NESARC‐III sample consisted of 36,309 adults and, after the final

survey weights were applied, represented a population that was 51.9%

women, 66.2% White, 14.7% Hispanic, 11.8% African American, 5.7%

Asian, and 1.6% Native American or other racial category.

As shown in Table 1, the estimated prevalence ratios indicate that

the majority of lifetime, prior‐to‐past‐year, and past‐year nonalcohol

drug‐specific DSM‐5 SUDs (i.e., cannabis, cocaine, heroin, hallucino-

gens, inhalants, prescription opioids, sedatives or tranquilizers, stimu-

lants, or other drugs) were accompanied by at least one other DSM‐5

SUD. More specifically, the prevalence ratios for past‐year nonalcohol

drug use disorders ranged from 56.8% for prescription opioid use dis-

order to 97.5% for inhalant use disorder, indicating that the majority

of past‐year nonalcohol drug‐specific SUDs were part of multiple

past‐year SUDs. The exception was alcohol use disorder, which

regardless of the timeframe had significantly lower prevalence ratios

of multiple SUDs.

3.2 | Prevalence and adjusted odds of multiple SUDs by sex, race, age, and other psychiatric disorders

The overall prevalence rates ofmultipleDSM‐5 SUDs amongU.S. adults

were 7.8% (lifetime), 6.2% (prior to past year), and 2.3% (past year),

whereas the prevalence rates of individual nonmultiple DSM‐5 SUDs

were 23.8% (lifetime), 19.2% (prior to past year), and 13.4% (past year).

As illustrated in Table 2, there were significant differences in rates of

multiple DSM‐5 SUDs by sex, race, age, and other psychiatric disorders.

Multiple SUDs were generally more prevalent among males, young

adults aged 18–29, African Americans, Native Americans, Whites, and

those with a lifetime history of DSM‐5 anxiety, mood, personality,

eating, and posttraumatic stress disorders, in addition to those with

multiple psychiatric disorders.

As shown in Table 3, the adjusted odds of past‐year multiple

SUDs were greater among males, younger adults, African Americans,

and those with mood, personality, or posttraumatic stress disorders,

after adjusting for the other covariates. In addition, the adjusted odds

of past‐year multiple SUDs were over 3 times greater among adults

with one lifetime psychiatric disorder (AOR = 3.40, 95% CI [2.68,

4.32], p < .001) compared to those with no lifetime psychiatric disor-

der. Furthermore, the adjusted odds of past‐year multiple SUDs were

nearly 9 times greater among those with multiple psychiatric disor-

ders (AOR = 8.97, 95% CI [7.22, 11.14], p < .001; weighted esti-

mates, not shown in Table 3), relative to those with no lifetime

history of psychiatric disorders, after adjusting for the other

covariates.

When comparing the weighted and unweighted estimates of

the coefficients in our models, we found evidence of some

increases in efficiency (i.e., lower standard errors and narrower

confidence intervals) for the unweighted estimates, as might be

expected given the covariates that were also used to develop

weighting adjustments, but no changes were substantial enough

to change the inferences that we would make using the weighted

estimates (see Table 3). In general, the lack of substantial changes

in the estimates of the adjusted odds ratios does suggest that using

the weights to fit these models may be unnecessary, given the

factors that were used for poststratification. This is also evidence

that our model has been well specified (Heeringa, West, &

Berglund, 2017, Chapter 7).

MCCABE ET AL. 3 of 10

3.3 | Prevalence of past‐year SUDs as a function of prior‐to‐past‐year SUD status

Table 4 shows that individuals with multiple prior‐to‐past‐year SUDs

are less likely to remit from SUDs than those with an individual

(nonmultiple) prior‐to‐past‐year DSM‐5 SUD. The estimated past‐year

prevalence rate of any SUD among those with no prior‐to‐past‐year

DSM‐5 SUDs was lowest at 8.2%. In contrast, the past‐year prevalence

rate of any SUD was highest among those with multiple prior‐to‐past‐

year alcohol and other drug use disorders (49.9%), followed by those

with only a prior‐to‐past‐year nonalcohol drug use disorder (40.5%)

and those with only a prior‐to‐past‐year alcohol drug use disorder

(32.9%). There were also sex differences in the past‐year prevalence

rates of any SUD among adults with no prior‐to‐past‐year SUDs or only

alcohol use disorders. However, once individuals had multiple prior‐to‐

past‐year SUDs or prior‐to‐past‐year nonalcohol other drug SUDs, the

prevalence of any past‐year SUDs was high in general, and male versus

female differences in the past‐year SUD prevalence rates were no lon-

ger present.

3.4 | Prevalence of substance‐specific versus any SUDs as a function of prior SUD for 10 drug classes

As illustrated in Table 5, the past‐year prevalence rates of any DSM‐5

SUD among those with prior‐to‐past‐year drug‐specific DSM‐5 drug

use disorders ranged from 37.2% for prior‐to‐past‐year DSM‐5 alcohol

use disorder to 53.5% for prior‐to‐past‐year DSM‐5 prescription opioid

use disorder. There were no significant sex differences in the past‐year

prevalence rates of any SUD among adults with prior‐to‐past‐year

SUDs. Among individuals with a prior‐to‐past‐year alcohol use disorder,

other SUDs involving different substances were quite unlikely to

develop in the past year (3.0%). However, among individuals with

prior‐to‐past‐year SUDs not related to alcohol, the development of

TABLE 1 Prevalence of multiple DSM‐5 drug‐specific use disorders

Disorder timeframe Prevalence of SUD % (SE) Prevalence of multiple SUDs % (SE) Ratio of prevalence estimates (SE)

Lifetime disorder

Lifetime alcohol use disorder 29.1 (0.5) 7.4 (0.2) 25.5 (0.6)

Lifetime cannabis use disorder 6.3 (0.2) 5.1 (0.2) 80.8 (1.0)

Lifetime cocaine use disorder 2.4 (0.1) 2.2 (0.1) 91.9 (1.0)

Lifetime prescription opioid use disorder 2.1 (0.1) 1.7 (0.1) 83.9 (1.6)

Lifetime prescription stimulant use disorder 1.7 (0.1) 1.5 (0.1) 89.1 (1.5)

Lifetime prescription sedative use disorder 1.1 (0.1) 1.0 (0.1) 93.4 (1.2)

Lifetime hallucinogen use disorder 0.6 (0.1) 0.6 (0.1) 97.1 (1.2)

Lifetime other drug use disorder 0.5 (<0.1) 0.5 (<0.1) 93.7 (2.1)

Lifetime heroin use disorder 0.5 (<0.1) 0.4 (<0.1) 92.0 (2.8)

Lifetime inhalant use disorder 0.2 (<0.1) 0.2 (<0.1) 95.8 (2.5)

Prior to past year (PPY) disorder

PPY alcohol use disorder 23.1 (0.5) 5.8 (0.2) 25.2 (0.6)

PPY cannabis use disorder 5.0 (0.2) 3.9 (0.2) 77.6 (1.2)

PPY cocaine use disorder 2.3 (0.1) 2.0 (0.1) 89.0 (1.2)

PPY prescription opioid use disorder 1.6 (0.1) 1.3 (0.1) 85.7 (2.0)

PPY prescription stimulant use disorder 1.6 (0.1) 1.4 (0.1) 87.1 (1.6)

PPY prescription sedative use disorder 0.9 (0.1) 0.8 (0.1) 94.3 (1.6)

PPY hallucinogen use disorder 0.6 (0.1) 0.5 (0.1) 97.0 (1.3)

PPY other drug use disorder 0.4 (<0.1) 0.4 (<0.1) 95.3 (2.0)

PPY heroin use disorder 0.4 (<0.1) 0.4 (<0.1) 91.5 (3.0)

PPY inhalant use disorder 0.1 (<0.1) 0.1 (<0.1) 95.1 (2.9)

Past‐year disorder

Past‐year alcohol use disorder 13.9 (0.3) 2.1 (0.1) 15.0 (0.6)

Past‐year cannabis use disorder 2.5 (0.1) 1.6 (0.1) 63.5 (1.6)

Past‐year prescription opioid use disorder 0.9 (0.1) 0.5 (<0.1) 56.8 (3.4)

Past‐year prescription sedative use disorder 0.4 (<0.1) 0.3 (<0.1) 73.7 (4.0)

Past‐year cocaine use disorder 0.3 (<0.1) 0.3 (<0.1) 86.0 (3.7)

Past‐year prescription stimulant use disorder 0.3 (<0.1) 0.2 (<0.1) 73.1 (4.3)

Past‐year other drug use disorder 0.2 (<0.1) 0.1 (<0.1) 82.3 (5.5)

Past‐year heroin use disorder 0.1 (<0.1) 0.1 (<0.1) 77.1 (8.3)

Past‐year hallucinogen use disorder <0.1 (<0.1) <0.1 (<0.1) 91.0 (4.9)

Past‐year inhalant use disorder <0.1 (<0.1) <0.1 (<0.1) 97.5 (2.7)

Note. All percentages weighted using AUDWEIGHT. SUD = substance use disorder; PPY = prior to past year; DSM‐5 = Diagnostic and Statistical Manual of Mental Disorders fifth edition. Source: National Epidemiologic Survey on Alcohol and Related Conditions III.

4 of 10 MCCABE ET AL.

other SUDs in the past year was more prevalent. For example, approxi-

mately one third of individuals with prior‐to‐past‐year cocaine use

disorder were estimated to develop a different SUD in the past year.

4 | DISCUSSION

This study represents the first investigation to examine the prevalence

of multiple DSM‐5 SUDs for 10 different substances among noninsti-

tutionalized U.S. adults. The findings of the study indicate that more

than four in every five U.S. adults with a lifetime nonalcohol sub-

stance‐specific SUDs involving cannabis, cocaine, heroin, hallucino-

gens, inhalants, prescription opioids, sedatives or tranquilizers,

stimulants, or other drugs also meet criteria for at least one other life-

time SUD (ranging from 80.8% for cannabis use disorder to 97.1% for

hallucinogen use disorder). The past‐year prevalence rates of multiple

SUDs for nonalcohol SUDs ranged from 56.8% for prescription opioid

use disorder to 97.5% for inhalant use disorder. In contrast, we found

that the majority of those with lifetime, prior‐to‐past‐year, or past‐year

alcohol use disorders did not meet DSM‐5 criteria for a second SUD.

These findings were similar to trends based on the National Survey

on Drug Use and Health and NESARC that found the majority of those

with a past‐year alcohol use disorder not meeting DSM‐IV criteria for a

second SUD (Center for Behavioral Health Statistics and Quality,

2015; Grant & Pickering, 1996; Stinson et al., 2005).

The findings of this study have important implications not only for

clinical practice and treatment, but also for human, preclinical, and

neurobiological research investigating the mechanisms of SUDs. We

found evidence for a more persistent pattern associated with multiple

SUDs as compared to nonmultiple SUDs among U.S. adults, although

drug classes differed. More specifically, U.S. adults with multiple prior‐

to‐past‐year SUDs were considerably more likely to report a past‐year

SUD and less likely to remit than those with a prior‐to‐past‐year

nonmultiple SUD. This finding is in line with a recent study that found

that U.S. adults with multiple past‐year DSM‐IV SUDs are more likely

than those with an individual past‐year DSM‐IV SUD to report at least

one past‐year SUD 3 years later, suggesting a more persistent 3‐year

course of disease associated with multiple SUDs over time relative to

individual SUDs (McCabe & West, 2017). Despite evidence indicating

high rates and increases in polysubstance use behaviors, increases in

multiple SUDs, and a more persistent course associated with multiple

SUDs, there is no current diagnosis involving multiple SUDs in the DSM‐

5 (Connor et al., 2014; McCabe et al., 2008). More long‐term prospective

investigations are needed to examine the developmental course and

associated disabilities of multiple SUDs over time as well as the causa-

tive mechanisms that lead to the persistent course of multiple SUDs.

The age‐adjusted drug overdose death rate has more than doubled

from 6.2 per 100,000 persons in 2000 to 14.7 per 100,000 in 2014, and

many of these deaths involve polysubstance use (Rudd et al., 2016).

There has also been a significant shift nationally in the profile of individ-

uals entering U.S. substance abuse treatment facilities (SAMHSA, 2006,

2012, 2014a), and previous evidence from national surveys suggests

that the prevalence of multiple SUDs among U.S. adults with prescrip-

tion drug use disorders increased significantly from 1991–1992 to

2001–2002 (McCabe et al., 2008). At least two prior studies examined

the prevalence of multiple SUDs associated with drug‐specific use dis-

orders involving prescription drug classes and found that the majority

of individuals with lifetime and past‐year DSM‐IV prescription opioid,

sedative, stimulant, and tranquilizer use disorders also met DSM‐IV

criteria for an additional lifetime and past‐year SUD, respectively

TABLE 2 Prevalence of multiple DSM‐5 substance use disorders by sex, age, race, and other psychiatric disorders

Sociodemographic characteristics and other psychiatric disorders

Lifetime Prior to past year Past year

% (SE) % (SE) % (SE)

Sex

Female 5.9 (0.2) 4.8 (0.2) 1.6 (0.1)

Male 9.9 (0.4)*** 7.7 (0.3)*** 3.0 (0.2)***

Age

65 years and older 1.2 (0.2) 1.0 (0.2) 0.1 (<0.1)

45–64 years 7.5 (0.4) 6.6 (0.4) 1.2 (0.1)

30–44 years 9.7 (0.4) 8.0 (0.4) 2.3 (0.2)

18–29 years 11.4 (0.5)*** 7.7 (0.4)*** 5.6 (0.4)***

Race

Hispanic 5.4 (0.4) 3.9 (0.4) 2.2 (0.2)

Black 6.8 (0.5) 4.4 (0.4) 3.5 (0.3)

Native American 15.1 (2.3) 12.3 (2.1) 3.6 (1.1)

Asian/Pacific Islander 2.8 (0.5) 2.2 (0.4) 0.7 (0.2)

White 8.8 (0.3)*** 7.3 (0.3)*** 2.2 (0.1)***

Any psychiatric disorder

No 3.3 (0.2) 2.5 (0.2) 0.8 (0.1)

Yes 15.4 (0.4)*** 12.5 (0.4)*** 4.7 (0.2)***

Anxiety disorder

No 6.0 (0.2) 4.6 (0.2) 1.8 (0.1)

Yes 16.7 (0.7)*** 14.1 (0.7)*** 4.6 (0.3)***

Mood disorder

No 5.1 (0.2) 3.8 (0.2) 1.4 (0.1)

Yes 16.4 (0.6)*** 13.7 (0.6)*** 5.0 (0.3)***

Personality disorder

No 4.6 (0.2) 3.5 (0.1) 1.1 (0.1)

Yes 25.9 (0.7)*** 21.2 (0.8)*** 8.7 (0.5)***

Eating disorder

No 7.6 (0.2) 6.0 (0.2) 2.2 (0.1)

Yes 18.0 (1.6)*** 15.9 (1.6)*** 6.0 (1.0)***

Posttraumatic stress disorder

No 6.7 (0.2) 5.2 (0.2) 1.9 (0.1)

Yes 25.3 (1.3)*** 21.2 (1.2)*** 8.0 (0.8)***

Multiple psychiatric disorders

None 3.3 (0.2) 2.5 (0.2) 0.8 (0.1)

One 8.8 (0.5) 6.7 (0.4) 2.6 (0.2)

Multiple (2+) 21.5 (0.6)*** 17.8 (0.6)*** 6.6 (0.4)***

Note. All percentages weighted using AUDWEIGHT. Tests of association are based on design‐adjusted Rao–Scott tests. Any lifetime psychiatric disorders refer to any history of lifetime anxiety, mood, eating, personality, or posttraumatic stress disorders. Anxiety disorders refer to agoraphobia, generalized anxiety disorder, panic, and social and specific phobias; mood disorders refer to bipolar, dysthymia, and major depressive disorders; personality disorders refer to antisocial, borderline, and schizotypal personality disorders; eating disorders refer to anorexia nervosa, binge‐eat- ing disorder, and bulimia nervosa. DSM‐5 = Diagnostic and Statistical Manual of Mental Disorders, fifth edition. Source: National Epidemiologic Survey on Alcohol and Related Conditions III.

***p < .001 (for Rao–Scott test of bivariate association).

MCCABE ET AL. 5 of 10

(Blanco, Secades‐Villa, García‐Rodríquez, et al., 2013; McCabe et al.,

2008). Taken together, the findings from the present study and the

two prior studies provide evidence from three independent nation-

ally representative samples over the past two decades that the

majority of adults with drug‐specific past‐year prescription drug

use disorders involving opioids, sedatives or tranquilizers, and stim-

ulants also met criteria for another SUD (Blanco et al., 2013;

McCabe et al., 2008).

This study found that multiple SUDs were more prevalent among

males, African Americans, Native Americans, Whites, and younger

adults. These findings extend prior work that has found that

polysubstance use behaviors are generally more prevalent among

males, Whites, and younger age groups such as adolescents and young

adults (Connor et al., 2014; Garnier et al., 2009; McCabe et al., 2006).

For example, previous work found that the majority of adolescents and

young adults who engage in nonmedical use of prescription drugs

TABLE 3 Adjusted odds ratios of multiple DSM‐5 substance use disorders (weighted and unweighted estimates)

Sociodemographic characteristics and other psychiatric disorders

Lifetime Prior to past year Past year AOR [95% CI] AOR [95% CI] AOR [95% CI]

Sex

Female Ref Ref Ref

Male 2.17 [1.96, 2.40]*** 2.04 [1.81, 2.29]*** 2.16 [1.76, 2.64]*** 2.28 [2.08, 2.49]*** 2.06 [1.85, 2.27]*** 2.33 [2.00, 2.72]***

Age

65 or more years Ref Ref Ref

45–64 years 5.35 [3.67, 7.81]*** 5.80 [3.69, 9.13]*** 7.27 [3.28, 16.12]*** 5.44 [4.14, 7.16]*** 6.28 [4.48, 8.83]*** 7.40 [3.62, 15.11]***

30–44 years 7.46 [5.18, 10.74]*** 7.52 [4.90, 11.53]*** 13.47 [6.01, 30.16]*** 7.22 [5.59, 9.34]*** 7.73 [5.65, 10.57]*** 12.83 [6.31, 26.08]***

18–29 years 9.03 [6.22, 13.12]*** 7.16 [4.56, 11.24]*** 35.01 [15.60, 78.55]*** 8.73 [6.68, 11.41]*** 7.36 [5.27, 10.29]*** 30.08 [14.87, 60.85]***

Race

Hispanic Ref Ref Ref

Black 1.34 [1.11, 1.62] 1.16 [0.92, 1.46] 1.80 [1.37, 2.35]*** 1.32 [1.10, 1.59] 1.20 [0.96, 1.50] 1.76 [1.40, 2.22]***

Native American 2.42 [1.65, 3.54]*** 2.48 [1.56, 3.95]*** 1.48 [0.78, 2.79] 2.13 [1.63, 2.77]*** 2.23 [1.58, 3.14]*** 1.29 [0.73, 2.30]

Asian/Pacific Islander 0.67 [0.45, 1.00] 0.74 [0.48, 1.16] 0.44 [0.27, 0.72] 0.64 [0.45, 0.92] 0.72 [0.49, 1.06] 0.52 [0.33, 0.81]

White 1.91 [1.62, 2.24]*** 2.12 [1.73, 2.60]*** 1.21 [0.97, 1.49] 1.84 [1.60, 2.12]*** 2.03 [1.69, 2.44]*** 1.16 [0.98, 1.38]

Anxiety disorder

No Ref Ref Ref

Yes 1.42 [1.23, 1.63]*** 1.45 [1.26, 1.67]*** 1.16 [0.93, 1.46] 1.43 [1.27, 1.61]*** 1.45 [1.28, 1.63]*** 1.24 [1.02, 1.51]

Mood disorder

No Ref Ref Ref

Yes 1.90 [1.68, 2.16]*** 1.99 [1.71, 2.31]*** 1.96 [1.59, 2.40]*** 2.00 [1.80, 2.21]*** 2.10 [1.86, 2.38]*** 1.93 [1.65, 2.25]***

Personality disorder

No Ref Ref Ref

Yes 4.08 [3.63, 4.60]*** 3.99 [3.49, 4.58]*** 4.59 [3.66, 5.75]*** 4.12 [3.74, 4.55]*** 3.90 [3.50, 4.36]*** 4.68 [3.93, 5.57]***

Eating disorder

No Ref Ref Ref

Yes 1.08 [0.83, 1.40] 1.17 [0.89, 1.53] 1.21 [0.83, 1.77] 1.26 [1.01, 1.56] 1.34 [1.06, 1.70] 1.38 [0.97, 1.97]

Posttraumatic stress disorder

No Ref Ref Ref

Yes 1.71 [1.43, 2.04]*** 1.68 [1.37, 2.06]*** 1.56 [1.20, 2.03]*** 1.68 [1.46, 1.95]*** 1.71 [1.46, 2.00]*** 1.55 [1.28, 1.88]***

Note. Anxiety disorders refer to agoraphobia, generalized anxiety disorder, panic, and social and specific phobias; mood disorders refer to bipolar, dysthymia, and major depressive disorder; personality disorders refer to antisocial, borderline, and schizotypal personality disorders; eating disorders refer to anorexia nervosa, binge‐eating disorder, and bulimia nervosa. Unweighted results are in italics. Source: National Epidemiologic Survey on Alcohol and Related Conditions III.

***p < .001.

6 of 10 MCCABE ET AL.

coingest other substances at the same time when they use prescription

drugs (Barrett, Darredeau, & Pihl, 2006; Garnier et al., 2009; McCabe

et al., 2006, 2015). There is a need to distinguish between simulta-

neous and concurrent polysubstance use behaviors among individuals

with multiple SUDs because the longitudinal trajectories and related

adverse substance‐related consequences may differ between these

two types of polysubstance use behaviors (Abé et al., 2013; Garnier

et al., 2009; McCabe et al., 2006; SAMHSA, 2014b).

We found that multiple SUDs were more prevalent among adults

with other DSM‐5 psychiatric disorders, especially mood, personality,

and posttraumatic stress disorders. Notably, adults with multiple life-

time psychiatric disorders had more than 9 times greater odds of hav-

ing past‐year multiple SUDs relative to those with no lifetime

psychiatric disorders, which is consistent with earlier work suggesting

a small subset of U.S. adults with extremely high rates of psychiatric

comorbidity based on previous versions of the DSM (Kessler et al.,

2005). Previous studies have found high rates of psychiatric comorbid-

ity associated with nonalcohol drug use disorders, including other

SUDs (Blanco et al., 2013; Compton et al., 2007, 2013; Fenton et al.,

2012; Hasin et al., 2016; McCabe et al., 2008). At least one national

study found that psychiatric comorbidity was greater among U.S.

adults with a nonalcohol drug use disorder who had sought substance

abuse treatment or help seeking as compared to others in the general

population with a drug use disorder (Compton et al., 2007). A more

recent study found that majority of individuals with multiple past‐year

SUDs had a lifetime personality disorder and did not utilize substance

abuse treatment or other help seeking (McCabe &West, 2017). Future

work is needed to examine the associations between DSM‐5 tobacco

use disorders and other DSM‐5 SUDs.

This study and the NESARC‐III had several strengths and limita-

tions that should be taken into account while considering implica-

tions of these findings. The NESARC‐III represents the first

nationally representative study to assess substance‐specific SUDs

and other psychiatric comorbidity based on DSM‐5 criteria. The lim-

itations of the NESARC‐III included the cross‐sectional design of the

study, which prevents assessment and testing of causal relationships.

The response rate was lower than previous administrations of the

NESARC (Grant & Kaplan, 2005; Grant, Kaplan, Shepard, & Moore,

2003), and despite the fact that nonresponse adjustments were

applied to the base sampling weights (Grant, Chu, Sigman, et al.,

2015), the higher rate of nonresponse may have biased survey esti-

mates. Although more research is needed to determine the charac-

teristics of nonrespondents in national substance use studies such

as the NESARC‐III, recent studies have found that attrition was

higher among individuals with no SUDs in prior longitudinal versions

TABLE 4 Prevalence and sex differences in past‐year SUD as a func- tion of PPY SUD status

PPY number of disorders

Past year Past year Past year Any SUD Single SUD Multiple SUD % (SE) % (SE) % (SE)

No PPY SUD

Overall (n = 27,681) 8.2 (0.2) 7.7 (0.2) 0.5 (0.1)

Female (n = 16,583) 6.0 (0.3) 5.7 (0.3) 0.3 (0.1)

Male (n = 11,098) 11.1 (0.4)*** 10.3 (0.4)*** 0.7 (0.1)***

PPY alcohol use disorder only

Overall (n = 5,773) 32.9 (0.9) 29.8 (0.8) 3.0 (0.3)

Female (n = 2,596) 30.4 (1.2) 27.9 (1.2) 2.5 (0.4)

Male (n = 3,177) 34.6 (1.0)** 31.2 (1.0)* 3.4 (0.4)

PPY alcohol + other drug use disorder(s)

Overall (n = 2,012) 49.9 (1.4) 30.6 (1.2) 19.3 (1.1)

Female (n = 882) 49.6 (2.1) 30.3 (1.8) 19.3 (1.5)

Male (n = 1,130) 50.2 (1.8) 30.8 (1.5) 19.3 (1.4)

PPY other drug use disorder only

Overall (n = 843) 40.5 (2.1) 29.6 (1.9) 10.8 (1.1)

Female (n = 386) 39.6 (3.0) 30.5 (2.7) 9.1 (1.7)

Male (n = 457) 41.2 (2.6) 29.0 (2.5) 12.2 (1.7)

Note. All percentages weighted using AUDWEIGHT. Male versus female differences (based on Rao–Scott chi‐square tests). SUD = substance use disorder; PPY = prior to past year. Source: National Epidemiologic Survey on Alcohol and Related Conditions III.

*p < .05.

**p < .01.

***p < .001.

TABLE 5 Prevalence of past‐year substance‐specific versus any SUD as a function of PPY SUD status across 10 drug classes

PPY substance‐specific use disorders

Past year Past year Past year Any SUD Substance‐specific SUD Different SUD % (SE) % (SE) % (SE)

PPY alcohol use disorder (n = 7,785) 37.2 (0.8) 34.2 (0.8) 3.0 (0.2)

PPY cannabis use disorder (n = 1,748) 47.9 (1.5) 25.6 (1.3) 22.3 (1.2)

PPY cocaine use disorder (n = 809) 42.5 (2.1) 9.2 (1.2) 33.3 (2.3)

PPY heroin use disorder (n = 145) 44.7 (4.8) 20.3 (4.5) 24.4 (4.1)

PPY hallucinogen use disorder (n = 172) 34.1 (3.7) 1.5 (0.8) 32.6 (3.7)

PPY inhalant use disorder (n = 43) 44.0 (9.3) 13.0 (7.5) 31.0 (8.3)

PPY prescription opioid use disorder (n = 505) 53.5 (2.6) 25.6 (2.1) 27.8 (2.3)

PPY prescription sedative use disorder (n = 286) 52.4 (3.9) 19.4 (2.7) 33.0 (3.4)

PPY prescription stimulant use disorder (n = 514) 38.9 (2.8) 10.2 (1.5) 28.7 (2.4)

PPY other drug use disorder (n = 159) 48.3 (4.4) 10.4 (2.6) 37.9 (4.5)

Note. All percentages weighted using AUDWEIGHT. SUD = substance use disorder; PPY = prior to past year. Source: National Epidemiologic Survey on Alco- hol and Related Conditions III.

MCCABE ET AL. 7 of 10

of the NESARC (Dawson, Goldstein, Pickering, & Grant, 2014;

McCabe & West, 2016). In addition, the NESARC‐III was interviewer

administered, so caution should be exercised when comparing results

from these studies and other sources of data based on different modes

of data collection; the survey methodology literature suggests that our

estimates may be biased low, given the ability of self‐administered

modes to generate more frequent reports of sensitive behaviors such

as drug use (Turner, 2005). Furthermore, the AUDADIS‐5/PRISM‐5

concordance was fair on some binary SUD diagnoses (e.g., past‐year

opioids). Finally, the exclusion of some institutionalized subpopulations

with higher rates of SUDs, including inmate populations currently in jails

and prisons, may have led to underestimation of SUD prevalence in the

NESARC‐III (Compton, Dawson, Duffy, & Grant, 2010).

The majority of U.S. adults with a DSM‐5 SUD involving cannabis,

cocaine, heroin, hallucinogens, inhalants, prescription opioids, seda-

tives or tranquilizers, stimulants, or other drugs had at least one other

SUD. The prevalence rates of multiple SUDs associated with DSM‐5

alcohol use disorders were significantly lower than other nonalcohol

drug use disorders. Past‐year multiple SUDs had greater odds among

males, young adults aged 18–29, and those with a history of DSM‐5

anxiety, mood, personality, posttraumatic stress disorder, or multiple

psychiatric disorders. Individuals with prior‐to‐past‐year multiple SUDs

were significantly more likely than those with a single (nonmultiple)

SUD to report past‐year SUDs. The findings of this study indicate that

the majority of adults with a nonalcohol drug use disorder also meet

criteria for at least one other SUD and that such cases are less likely

to remit, which has important implications for treating DSM‐5

nonalcohol drug use disorders.

In conclusion, the findings of the current study indicate that clini-

cal assessment and diagnosis should screen for multiple SUDs, espe-

cially when working with patients with a history of nonalcohol drug

use disorders. The current study identified several subgroups that are

at increased risk for multiple SUDs including males, African Americans,

Native Americans, Whites, young adults, and those with other DSM‐5

psychiatric disorders (e.g., mood, personality, and posttraumatic stress

disorders) that can be considered in clinical practice. The long‐term

drug use trajectories of individuals with multiple SUDs as compared

with single SUDs may be indicative of distinct causal mechanisms con-

tributing to multiple SUDs. For instance, prior‐to‐past‐year multiple

SUDs may produce robust, long‐term changes in neurobiological path-

ways and circuits that lead to persistent multiple SUDs and relapse. In

addition, multiple SUDs may be initiated by or exaggerated by

preexisting aberrant neurobiology, as suggested by a history of psychi-

atric disorders. The contributing mechanisms are likely not mutually

exclusive and together may amplify disease status. On the basis of

the higher rates of psychiatric comorbidity among those with multiple

DSM‐5 SUDs and the more persistent course of multiple SUDs, a

greater emphasis toward treating multiple SUDs and comorbid psychi-

atric disorders is warranted. Future research is needed to determine

whether treating multiple SUDs and comorbid psychiatric disorders

at the same time is more effective than treating each disorder individ-

ually and sequentially according to severity. The distinct characteristics

and causal mechanisms of multiple SUDs as compared with single

SUDs should be further investigated to better understand vulnerability

to multiple SUDs and potential points of intervention and to improve

treatment outcomes. Future work should include prospective studies

and preclinical studies in which neurobiological changes can be

thoroughly examined and contributing factors are readily controlled.

CONFLICT OF INTEREST

The authors have no conflicts of interest to report.

ACKNOWLEDGEMENTS

The development of this manuscript was supported by research grants

R01DA031160 and R01DA036541 from the National Institute on

Drug Abuse, National Institutes of Health. This manuscript was

prepared using a limited access data set obtained from the National

Institute on Alcohol Abuse and Alcoholism. The funders had no role

in the design and conduct of the study; collection, management,

analysis, and interpretation of the data; preparation, review, or

approval of the manuscript; and decision to submit the manuscript

for publication. The content is solely the responsibility of the authors

and does not necessarily represent the official views of the National

Institute on Alcohol Abuse and Alcoholism, National Institute on Drug

Abuse, National Institutes of Health, or the U.S. Government.

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How to cite this article: McCabe SE, West BT, Jutkiewicz EM,

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