Prevalence of Opioid Use Disorder and Other Substance Use among Adolescents and Young Adults in Medicaid/CHIP, 2015–2019

Abstract

Among adolescents (ages 12–17) and young adults (ages 18–25) enrolled in Medicaid or the Children’s Health Insurance Program (CHIP), 0.5% of adolescents had opioid use disorder (OUD), 3.0% had other risky opioid use, 3.4% had another substance use disorder, and 21.6% used other substances without disorder. Compared to adolescents, the prevalence of OUD and other risky opioid use was about 3 and 2 times higher among young adult enrollees, among whom 1.6% had OUD and 5.8% had other risky opioid use. Among young adults, 8.6% had another SUD and 61.8% used other substances without disorder. Prevalence of OUD or other risky opioid use was substantially higher among Medicaid-enrolled youth with other substance use or health risk factors including more than double among those with fair or poor health, more than 3 times higher among those with heavy alcohol use, and more than 1.5 times higher among those with a major depressive episode. Results underscore the need to take a whole person approach to addressing risks for OUD.

Keywords:

• Opioid use disorder
• substance use disorder
• adolescents
• young adults
• Medicaid

Introduction

Opioid use disorder (OUD) and other risky substance use are associated with substantial financial, health, and other burdens for individuals and their families and communities (Degenhardt et al., 2018; Sacks et al., 2015). Factors associated with developing OUD and other risky opioid use often emerge when individuals are adolescents or young adults and include opioid use as well as mental health conditions and alcohol, tobacco, marijuana, and other substance use (Barnett et al., 2019; Darke et al., 2017; Schepis & Hakes, 2017). The use of one substance by adolescents is associated with increased risk for using other substances (DuPont et al., 2018). OUD and other risky opioid use can have immediate and long-term adverse consequences for youth, families, and communities, particularly for early initiators (National Academies of Sciences, 2019). In 2018, an estimated 2.8% of adolescents and 5.6% of young adults in the US had past-year risky opioid use (Lipari and Park-Lee, 2019). Medicaid and the Children’s Health Insurance Program (CHIP) are central to efforts to address OUD and other substance use among youth because Medicaid/CHIP (hereafter referred to as Medicaid) cover a large share of youth and young adults (Brooks & Gardner, 2020). In addition, many states are innovating their Medicaid programs to improve substance use related services, including services specifically tailored to youth (MACPAC, 2016, 2017). However, to date, no studies estimate the prevalence of risky opioid use and other substance use risk factors for OUD among adolescents and young adults with Medicaid coverage.

In this study, we first provide new detail on prevalence of risky opioid use and other substance use among Medicaid-enrolled youth, we then assess prevalence by demographic characteristics, health status, and depressive episode, and substance use risk factors such as heavy alcohol use and driving after substance use. We conclude with a discussion of Medicaid-relevant policy options.

Materials and methods

We pool five years of publicly-available data 2015–2019 of the National Survey of Drug Use and Health (NSDUH), the primary source of information on the prevalence, patterns, and consequences of alcohol and drug use in the US civilian noninstitutionalized population ages 12 and older. The NSDUH is an annual, nationally representative cross-sectional survey administered by the Substance Abuse and Mental Health Services Administration that uses computer-assisted self-interviews to collect data on substance use (Center for Behavioral Health Statistics and Quality, 2016, 2017, 2018, 2019). Our sample of interest is adolescents ages 12–17 (n = 26,516) and young adults ages 18–25 (n = 15,732) who were reported to have coverage from Medicaid or the Children’s Health Insurance Program (hereafter Medicaid) at the time of the survey.

We use directly reported and constructed variables to produce descriptive statistics of substance use prevalence among both adolescents and young adults overall and by demographic and other characteristics. We focus on mutually exclusive categories based on self-reported substance use in the past 12 months: (1) those classified by the NSDUH as having OUD based on reporting opioid use and consequences that meet criteria for opioid dependence or abuse in the Diagnostic and Statistical Manual of Mental Disorder, 4th edition (DSM-IV); (2) those with other (non-OUD) risky opioid use defined as using opioids in a way not directed by a doctor; (3) those classified as having another substance (including cocaine, hallucinogens, inhalants, methamphetamine, ecstasy, lysergic acid diethylamide (LSD), Phenylcyclohexyl piperidine (PCP), sedatives, stimulants, and tranquilizers) use disorder based on reporting substance use and consequences that meet criteria for dependence or abuse in the DSM-IV; (4) those reporting other substance use, including tobacco use; and (5) those with no substance use, including no use of the tobacco products asked about in the NSDUH (cigarettes, cigars, and smokeless tobacco but not vaping).

Tobacco includes cigarettes, cigars, pipes, and smokeless tobacco but does not include e-cigarettes because it is not available in all years of the NSDUH. We estimate prevalence of substance use by interviewer classified gender and self-reported demographic characteristics. Race and ethnicity categories were derived from the U.S Office of Management and Budget definitions.

We also estimate prevalence by health characteristics and select risky substance use behaviors. To measure health related risk factors, we used the categorical variable for self-reported past month health status (excellent, good, fair, poor) for general health and the NSDUH-constructed measure for past 12-month major depressive episode for mental health. For substance use risk factors, we used the NSDUH constructed variables for heavy alcohol use in the past month and cigarette dependence in the past month (defined according to the Nicotine Dependence Syndrome Scale (NDSS) and Fagerstrom Test of Nicotine Dependence (FTND)). For substance use risk factors, we also used self-reported marijuana use in the past year and self-reported driving after substance use (i.e., “under the influence” of a substance excluding alcohol and tobacco) in the past 12 months.

We used analysis weight to account for the complex survey design and calculated 95% confidence intervals for estimates and used a 2-tailed t-test with p < .05 as the threshold for statistical significance. The analysis was conducted using Stata version 15 (StataCorp) and followed NSDUH guidelines for calculating and reporting (including suppression) estimates. Data analysis was conducted between October 2020 and July 2021.

This study has several limitations. The NSDUH data we use are mostly self- or proxy-reported and thus subject to recall and social desirability bias which may vary by the characteristics we study. Interviewer classification of gender may not comport with self-reported gender. Similarly, the race/ethnicity categories may not reflect how respondents prefer to self-identify. The sample excludes some individuals who may be at heightened risk of risky substance use, including individuals in the active duty military, in prisons/jails, and living on the street and not going to shelters (Center for Behavioral Health Statistics and Quality 2017).

We are limited to analyzing select risk factors for OUD that are asked about in the NSDUH used in our study. The NSDUH we used did not ask about vaping of any products thus our measure of tobacco use likely misses a substantial percentage of youth who use tobacco (Cullen et al., 2019). Vaping is a predictor of smoking cigarettes and using other substances thus future studies should examine it among Medicaid-enrolled youth (McCabe et al., 2018; Miech et al., 2017). The NSDUH also did not ask about child maltreatment and trauma which are known to be associated with increased substance use (Dube et al., 2003; Hagborg et al., 2020). Our analysis also excludes individuals who had risky substance use or a use disorder more than 12 months ago and may still need supports to sustain treatment or otherwise avoid recurrence of the substance use.

Results

Past year prevalence of risky opioid and other substance use among all adolescents and young adults

During 2015–2019, a substantial percentage of adolescents and young adults had a past year substance use risk factor for OUD or OUD. Among adolescents, 0.5% had OUD, 3.0% had other risky opioid use, 3.4% had another SUD, and 21.6% used other substances without disorder (Figure 1). Compared to adolescents, the prevalence of OUD and other risky opioid use was about 3 and 2 times higher among young adults, among whom 1.6% had OUD and 5.8% had other risky opioid use (Figure 1). In addition, among young adults, 8.6% had another SUD and 61.8% used other substances without disorder (Figure 1).

Figure 1. Past year prevalence of opioid use disorder and other substance use among Medicaid-enrolled adolescents and young adults, 2015–2019.

Prevalence by demographic category

The prevalence of OUD and other substance use varied by demographic category. Prevalence was lower for younger age groups in each substance use category we studied (Figure 2). The prevalence of OUD and other risky opioid use was lower among adolescent boys than adolescent girls. In contrast, among young adults, the prevalence of OUD was lower for young women and other risky opioid use was similar compared to young men (Figure 2).

Figure 2. Prevalence of opioid use disorder and other substance use among Medicaid-enrollees by demographic characteristics, 2015–2019.

The prevalence of OUD and other risky opioid use was similar by race and ethnicity in adolescence but among young adults, it was lower among individuals who identify as Black/African American (0.7% and 5.0%), Asian (0.9% and 4.3%) or Hispanic/Latinx (1.0% and 5.1%) compared to individuals who identify as White (2.8% and 7.0%) (Figure 2). The prevalence of OUD and other risky opioid use among people who identify as American Indian/Alaska Native or two or more races was on par to levels observed among people who are White (Figure 2). Adolescents who are Black/African American had lower levels of SUD and other SU and adolescents who are Asian or Hispanic/Latinx had lower levels of other SU compared to adolescents who are White (Figure 2). Among young adults the prevalence of other SU was also lower among those who are Black/African American, Asian or Hispanic/Latinx as well as those who are American Indian/Alaska Native. However, the prevalence of SUD was similar across racial/ethnic categories of young adults except for among those who are Asian (4.5%) or American Indian/Alaska Native (20.3%).

The prevalence of OUD was lower among non-metro adolescents compared to urban adolescents (0.5% compared to 0.3%) but among young adults, OUD prevalence was similar across MSA type. Similarly, other risky opioid use was equivalent across MSA categories of adolescents, but prevalence was higher among young adults in non-metro and small MSAs (7.4% and 6.5%) compared to urban young adults (5.0%) (see Appendix).

Prevalence by health status and depressive episode

The prevalence of OUD and other substance use was substantially higher among the roughly 1 in 20 adolescents and young adults who had fair or poor health and the roughly 1 in 10 adolescents and young adults who had a major depressive episode compared to other youth. Among adolescents, the prevalence of OUD and other risky opioid use was more than 4 and 2 times higher respectively among those who had a major depressive episode compared to other adolescents (1.7% and 6.0% respectively among those who had a major depressive episode compared to 0.4% and 2.5% among others) (Figure 3). Similarly, among young adults, the prevalence of OUD and other risky opioid use was more than 3 and 1.5 times higher respectively among those who had a major depressive episode compared to other young adults (4.2% and 9.5% respectively among those who had a major depressive episode compared to 1.2% and 5.4% among others) (Figure 3). Similarly, the prevalence of OUD was about 3 and 2 times higher respectively among adolescents and young adults whose health was fair or poor compared to other youths (1.5% compared to 0.5% among adolescents and 3.0% compared to 1.4% among young adults) (Figure 3).

Figure 3. Prevalence of opioid use disorder and other substance use among Medicaid-enrollees by health status and select health conditions, 2015–2019.

Prevalence by select substance use risk factors

The prevalence of OUD and other substance use was higher among adolescents and young adults who had heavy alcohol use or cigarette dependence or drove after using a substance (excluding tobacco and alcohol) compared to other adolescents and young adults. The prevalence of OUD or other risky opioid use was about 20 and 6 times higher respectively among the roughly 1 in 50 adolescents with heavy alcohol use (with an OUD/risky opioid use prevalence of 10.7% and 17.3% respectively compared to 0.5% and 2.9% among adolescents with no heavy alcohol use) (Figure 4). For young adults, OUD/risky opioid use prevalence was about 3 times higher among the 1 in 20 with heavy alcohol use compared to other young adults (with an OUD/risky opioid use prevalence of 5.1% and 15.3% compared to 1.4% and 5.3% among young adults with no heavy alcohol use). (Figure 4)

Figure 4. Prevalence of opioid use disorder and other substance use among Medicaid-enrollees by select types of substance use and select behaviors, 2015–2019.

Among young adults, cigarette dependence was especially associated with OUD and other risky opioid use. The prevalence of OUD or other risky opioid use was more than 10 and 2 times higher respectively among the roughly 1 in 10 identified as dependent on cigarettes (with an OUD/risky opioid use prevalence of 7.3% and 12.3% respectively compared to 0.7% and 4.9% among other young adults not dependent on cigarettes) (Figure 4).

Additionally, prevalence was especially high for the roughly 2% of adolescents and 10% of young adults who reported driving after using a substance (excluding alcohol and tobacco). Prevalence of OUD or other risky opioid use was about 20 and 9 times higher respectively among adolescents who reported driving after using a substance compared to those who did not (8.0% and 21.4% respectively among those who drove after substance use compared to 0.4% and 2.3% among others) (Figure 4). Prevalence of OUD or other risky opioid use was about 7 and 4 times higher respectively among young adults who reported driving after using a substance compared to those who did not (6.6% and 17.9% respectively among those who drove after substance use compared to 0.9% and 4.3% among others) (Figure 4).

Discussion

The results of this study point to ways that state governments and their Medicaid agencies can reduce opioid-related risks among youth. As states seek to educate clinicians and other health providers who participate in Medicaid about the prevalence and risk factors for OUD and other risky substance use, these results show that a substantial share of adolescents and young adults had a past year substance use risk factor for OUD or OUD. This study’s finding that the prevalence of OUD or other risky opioid use was substantially higher among Medicaid-enrolled youth with heavy alcohol use, a major depressive episode or other substance use or health risk factor studied also suggests that whole person care considering the full spectrum of behavioral, physical and social services beyond addressing risky opioid use is needed.

Services delivered in schools, such as interventions strengthening protective factors and health services delivered by school-based health centers, have been found to reduce adolescent substance use (Hodder et al., 2017; Knopf et al., 2016). Screening, Brief Intervention, and Referral to Treatment (SBIRT) is a promising practice to prevent, identify, and reduce adolescent substance use, including in schools (Beaton et al., 2016; Community Catalyst, 2021; McCarty et al., 2019). Social and emotional learning in schools has been shown to save states money and is especially important for youth enrolled in Medicaid given that many only get mental health services in school (Ali et al., 2019; Belfield et al., 2015). Since 2014, states can seek authorization to expand the school Medicaid program to include services that are not specified in individualized plans written for youth served under the Individuals with Disabilities Education Act, however many states still do not get Medicaid reimbursement for school-based services or get a small amount relative to the size of their Medicaid population (MACPAC, 2018; Mann, 2015). Local school leaders report that collaboration between state Medicaid agencies and schools and technical assistance from the Centers for Medicare and Medicaid Services help them develop policies for expanding Medicaid services in schools but as of 2020, over half of all states have Medicaid policies that limit Medicaid billing for school-based health services, and only 10 states had authorization to expand the school Medicaid program to include services for all youth with Medicaid (Wilkinson et al., 2020). The study’s finding of different patterns of OUD and other substance use prevalence by age, gender, and race and ethnicity suggest that interventions to address youth substance use could be tailored to specific protective and risk factors among different subpopulations of youth. Brief interventions are intended to leverage individuals’ strengths (SAMHSA, 1998). However, there are Medicaid reimbursement restrictions on SBIRT based on state, setting, and provider type, including in the emergency department where substance use navigators with peer training have been found to be effective (Community Catalyst, 2021; Maxwell-Jolly & Wurden, 2020). Youth experiencing poverty express a preference for prevention initiatives focused on strengths as well as assets and safety (West-Bey & Flores, 2017; West-Bey & Mendoza, 2019). This is consistent with a wellness framework (National Research Council (US) and Institute of Medicine (US) Committee on the Prevention of Mental Disorders and Substance Abuse Among Children, Youth, and Young Adults: Research Advances and Promising Interventions, 2009). This study’s findings suggest that addressing youth substance use will also need to incorporate effective harm reduction efforts to reduce driving after substance use and heavy alcohol use (Knight et al., 2019; Stockings et al., 2016).

The study’s finding of need for substance use services and OUD treatment among Medicaid-enrolled adolescents across all demographic groups studied underscores the importance of training providers to provide culturally effective care including as described by youth (Betancourt et al., 2002). Medication treatment and retention rates are very low for adolescents and young adults with OUD, particularly Black/African American youth who are less likely to receive medication treatment for OUD (Acevedo et al., 2020; Alinsky et al., 2020; Hadland et al., 2018). In order to better identify and eliminate racial disparities in OUD care among Medicaid enrollees, Medicaid agencies should support better collection of data on race and ethnicity to reduce the high levels of missing race and ethnicity data which limit analysis of care inequities.

OUD and risky opioid use is present among all groups of adolescents and young adults in Medicaid that we studied, and takes place in the context of widespread substance use. This suggests that Medicaid state agencies have substantial opportunities to reduce the burden of unhealthy youth substance use by working with providers, schools, and communities to improve whole person wellness, prevention, and intervention services.

Disclosure statement

The authors have no conflicts of interest to disclose.

Additional information

Funding

This work was supported by the Foundation for Opioid Response Efforts under a grant signed on January 17, 2020. The views expressed are those of the authors and should not be attributed to the Foundation for Opioid Response Efforts, the Urban Institute, trustees, or others. Funders do not determine research findings or the insights and recommendations of Urban Institute experts. Further information on the Urban Institute funding principles is available at https://www.urban.org/aboutus/funding-principles.

 

Appendix Table 1. Socioeconomic characteristics and risk factors among Medicaid-enrolled adolescents (12–17) by type of substance use, 2015–2019.

	Opioid use disorder (OUD)	Other risky opioid use (no OUD)	Other substance use disorder (and no risky opioid use)	Other substance use (no use disorder or other risky opioid use)	No substance use
	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)
Age group
12–14	0.3 (0.2, 0.5)	1.9 (1.5, 2.3)	1.2 (1.0, 1.5)	12.8 (11.9, 13.8)	83.7 (82.7, 84.7)
15–17	0.8 (0.6, 1.0)***	4.2 (3.7, 4.7)***	5.7 (5.2, 6.3)***	30.7 (29.5, 32.0)***	58.6 (57.4, 59.8)***
Gender
Boys	0.4 (0.3, 0.6)	2.5 (2.2, 2.9)	3.4 (3.1, 3.8)	20.5 (19.5, 21.5)	73.2 (72.0, 74.3)
Girls	0.7 (0.5, 0.9)**	3.5 (3.0, 4.0)***	3.4 (3.0, 3.9)	22.7 (21.6, 23.9)***	69.7 (68.4, 71.0)***
Race/Hispanic ethnicity
White	0.6 (0.5, 0.9)	3.2 (2.8, 3.7)	3.7 (3.2, 4.3)	25.2 (23.9, 26.5)	67.2 (66.0, 68.5)
Black or African American	0.4 (0.3, 0.7)	3.1 (2.6, 3.8)	2.7 (2.2, 3.4)**	18.5 (17.4, 19.7)***	75.2 (73.9, 76.4)***
American Indian/Alaska Native	0.5 (0.1, 1.8)	2.7 (1.7, 4.3)	5.4 (3.6, 8.1)	26.0 (21.4, 31.2)	65.4 (59.8, 70.7)
Native Hawaiian/Other Pacific Islander	0.7 (0.2, 2.8)	S	3.9 (1.7, 8.5)	22.7 (14.9, 32.9)	70.1 (59.4, 78.9)
Asian	0.7 (0.2, 2.1)	2.3 (1.3, 4.1)	2.5 (1.4, 4.5)	12.8 (10.1, 16.1)***	81.6 (78.0, 84.7)***
Identifies as two or more races	0.6 (0.3, 1.2)	3.2 (2.2, 4.7)	4.0 (2.8, 5.5)	25.6 (22.6, 28.9)	66.6 (63.5, 69.7)
Hispanic	0.5 (0.3, 0.7)	2.7 (2.3, 3.3)	3.6 (3.1, 4.1)	20.0 (18.6, 21.5)***	73.2 (71.5, 74.8)***
Metropolitan statistical area
Large	0.5 (0.4, 0.7)	3.0 (2.5, 3.4)	3.6 (3.1, 4.1)	20.5 (19.5, 21.6)	72.4 (71.4, 73.4)
Small	0.7 (0.5, 0.9)	3.0 (2.6, 3.5)	3.1 (2.7, 3.5)	22.1 (21.0, 23.3)**	71.1 (69.9, 72.3)**
Nonmetropolitan	0.3 (0.2, 0.5)**	3.1 (2.6, 3.7)	3.6 (3.0, 4.3)	23.9 (22.3, 25.6)***	69.1 (67.5, 70.6)***
Family income as a % of the federal poverty level
<100	0.6 (0.5, 0.9)	2.8 (2.4, 3.3)	3.1 (2.8, 3.6)	19.4 (18.4, 20.5)	74.0 (72.9, 75.1)
100–200	0.4 (0.3, 0.6)	3.2 (2.7, 3.7)	3.5 (3.0, 4.1)	22.4 (21.1, 23.7)***	70.5 (69.1, 71.9)***
>200	0.5 (0.3, 0.9)	3.2 (2.6, 3.9)	4.0 (3.4, 4.7)**	24.9 (23.5, 26.3)***	67.5 (65.7, 69.2)***
Household composition
Both parents in household	0.5 (0.4, 0.8)	2.8 (2.4, 3.3)	2.9 (2.6, 3.3)	19.9 (18.9, 21.0)	73.7 (72.8, 74.7)
Mother only in household	0.5 (0.3, 0.7)	3.0 (2.6, 3.5)	3.9 (3.4, 4.4)***	22.7 (21.6, 23.9)***	70.0 (68.7, 71.2)***
Father only in household	1.1 (0.6, 2.1)	4.1 (2.8, 5.9)	3.6 (2.4, 5.3)	23.6 (20.4, 27.3)**	67.6 (64.0, 71.0)***
Parental status
Does not have a child in the household and not pregnant	0.5 (0.4, 0.7)	3.0 (2.7, 3.3)	3.4 (3.1, 3.7)	21.5 (20.7, 22.3)	71.6 (70.7, 72.4)
Pregnant with first child	0.2 (0.0, 1.5)	5.8 (3.0, 10.8)	S	37.5 (27.7, 48.4)***	46.1 (35.1, 57.5)***
Has one child in the household	S	2.6 (1.1, 6.1)	4.6 (1.7, 11.9)	S	S
Has more than one children in the household	S	S	S	S	S
Number of religious services attended in past year
0	0.5 (0.4, 0.7)	2.5 (2.2, 2.9)	3.4 (3.0, 3.9)	21.9 (20.8, 23.0)	71.7 (70.5, 72.8)
1–2	0.6 (0.4, 1.0)	4.1 (3.3, 5.0)***	3.9 (3.2, 4.9)	24.2 (22.0, 26.5)	67.1 (64.8, 69.4)***
3+	0.5 (0.4, 0.8)	3.2 (2.7, 3.9)**	3.3 (2.8, 3.9)	20.6 (19.3, 22.0)	72.3 (71.0, 73.6)
Number of church or faith-based activities^a
0	0.4 (0.3, 0.7)	3.1 (2.8, 3.5)	3.9 (3.4, 4.4)	23.2 (22.1, 24.2)	69.4 (68.2, 70.6)
1	0.7 (0.5, 1.0)	2.7 (2.1, 3.5)	3.2 (2.6, 3.8)	21.4 (20.2, 22.8)**	72.0 (70.5, 73.5)***
2	0.7 (0.4, 1.2)	3.8 (3.0, 4.8)	3.5 (2.7, 4.6)	22.2 (20.2, 24.3)	69.7 (67.6, 71.8)
3+	0.4 (0.2, 0.7)	2.6 (2.0, 3.3)	2.7 (2.2, 3.3)***	18.2 (16.8, 19.7)***	76.1 (74.6, 77.5)***
Attended school in the past 12 months
Yes	0.5 (0.4, 0.7)	2.8 (2.5, 3.2)	3.2 (2.9, 3.5)	21.2 (20.4, 22.1)	72.3 (71.4, 73.2)
No	0.7 (0.5, 1.1)	3.8 (3.3, 4.5)***	4.6 (3.7, 5.7)***	23.3 (21.6, 25.1)**	67.5 (65.7, 69.3)***
Number of school-based activities^b
0	0.4 (0.3, 0.6)	2.6 (2.1, 3.2)	3.9 (3.2, 4.7)	21.4 (19.9, 22.9)	71.7 (70.0, 73.3)
1	0.5 (0.3, 0.8)	2.8 (2.3, 3.4)	3.2 (2.7, 3.8)	20.6 (19.3, 21.9)	72.9 (71.5, 74.3)
2+	0.6 (0.5, 0.8)**	3.3 (2.8, 3.8)	3.4 (3.0, 3.8)	22.2 (21.1, 23.4)	70.5 (69.3, 71.7)
Health status
Excellent, very good or good	0.5 (0.4, 0.6)	2.9 (2.6, 3.3)	3.3 (3.0, 3.6)	21.5 (20.6, 22.3)	71.9 (71.0, 72.7)
Fair or poor	1.5 (0.9, 2.4)***	3.9 (2.6, 5.8)	6.3 (4.9, 8.0)***	23.2 (20.4, 26.3)	65.2 (61.1, 69.1)***
Number of chronic conditions^c
0	0.4 (0.3, 0.6)	2.8 (2.5, 3.1)	3.4 (3.1, 3.7)	21.4 (20.5, 22.3)	72.0 (71.0, 73.0)
1	0.7 (0.5, 1.1)**	3.6 (2.8, 4.6)	3.5 (2.9, 4.2)	22.7 (21.4, 24.1)	69.5 (67.9, 71.0)***
2+	1.5 (0.8, 2.7)**	4.3 (3.1, 6.0)**	4.3 (2.9, 6.1)	20.1 (17.3, 23.3)	69.8 (66.6, 72.9)
Cigarette dependence in past month
No	0.5 (0.4, 0.6)	2.8 (2.5, 3.1)	3.1 (2.8, 3.4)	21.0 (20.2, 21.9)	72.6 (71.7, 73.4)
Yes	4.5 (2.4, 8.4)***	15.0 (11.3, 19.6)***	25.6 (20.7, 31.3)***	54.9 (48.6, 60.9)***	S
Sexually transmitted disease, past year
No	0.5 (0.4, 0.6)	2.9 (2.6, 3.2)	3.3 (3.0, 3.6)	21.4 (20.5, 22.2)	72.0 (71.1, 72.8)
Yes	3.3 (1.4, 7.2)**	9.8 (5.7, 16.2)**	16.1 (12.1, 21.1)***	33.2 (27.7, 39.1)***	37.8 (30.8, 45.3)***
Depressive episode in the last year
No	0.4 (0.3, 0.5)	2.5 (2.3, 2.8)	2.8 (2.5, 3.1)	19.9 (19.1, 20.8)	74.4 (73.5, 75.3)
Yes	1.7 (1.2, 2.5)***	6.0 (4.8, 7.5)***	7.6 (6.5, 8.9)***	32.5 (30.5, 34.5)***	52.1 (50.3, 54.0)***
Driven after substance use, past year^d
No	0.4 (0.3, 0.5)	2.3 (2.0, 2.7)	2.7 (2.4, 3.0)	20.9 (20.0, 21.9)	73.7 (72.7, 74.6)
Yes	8.0 (4.9, 12.8)***	21.4 (17.1, 26.4)***	35.7 (29.9, 41.9)***	35.0 (28.6, 41.9)***	S
Heavy alcohol use, past month^e
No	0.5 (0.4, 0.6)	2.9 (2.6, 3.3)	3.3 (3.0, 3.6)	21.5 (20.7, 22.3)	71.9 (71.0, 72.7)
Yes	10.7 (5.5, 19.7)***	17.3 (10.8, 26.5)***	35.5 (25.6, 46.8)***	36.6 (26.6, 47.8)***	S

Source: All estimates are from SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2015–2019.

Notes: Substance use disorder is defined as meeting criteria for dependence or abuse according to the Diagnostic and Statistical Manual of Mental Disorder, 4th edition (DSM-IV) based on self-reported substance use and consequences from any of the following substances: alcohol, marijuana, cocaine, hallucinogens, inhalants, methamphetamine, ecstasy, lysergic acid diethylamide (LSD), Phenylcyclohexyl piperidine (PCP), or non-medical use of sedatives, stimulants, or tranquilizers. “Other risky opioid use" includes individuals the NSDUH identifies as "misusing" opioids because they report using opioids in a way not directed by a doctor. Other substances use is defined as use of the aforementioned substances as well as the use of tobacco.

Adolescents include people ages 12–17 and young adults include people ages 18–25.

Note. ***/** indicates that the estimate differs significantly from the first level of each row variable, within each substance use column (e.g., the estimate for girl respondents with opioid use disorder differs significantly from the estimate for boy respondents with opioid use disorder) at the .01/.05 level, respectively, using a two-tailed test of significance.

"S" Data were suppressed using NSDUH's suppression criteria for unreliable estimates.

^aChurch or faith-based activities include clubs, youth groups, Saturday or Sunday school, prayer groups, youth trips, service or volunteer activities. NSDUH only asks this question of youth ages 12–17.

^bSchool-based activities include team-based sports, cheerleading, choir, band, student government, and other clubs. NSDUH only asks this question of youth ages 12–17.

^cChronic conditions include high blood pressure, heart conditions, diabetes, cancer, asthma, COPD, HIV/AIDS, Hepatitis B, Hepatitis C, cirrhosis, and kidney disease.

^dThis variable corresponds to a question that asks respondents if they have driven under the influence of the following substances: marijuana, cocaine or crack, heroin, hallucinogens, inhalants, and methamphetamine.

^eHeavy alcohol use is computed using NSDUH definitions which were developed for adults and is defined as drinking five or more drinks on the same occasion for boys or four or more drinks on the same occasion for girls on each of 5 or more days in the past 30 days. For this variable, "occasion" means at the same time or within a couple hours of each other.

Appendix Table 2. Socioeconomic characteristics and risk factors among Medicaid-enrolled young adults (18–25) by type of substance use, 2015–2019.

	Opioid use disorder (OUD)	Other risky opioid use (no OUD)	Other substance use disorder (and no risky opioid use)	Other substance use (no use disorder or other risky opioid use)	Nonter substance use
	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)
Age group
18–20	1.1 (0.9, 1.4)	5.0 (4.5, 5.6)	7.7 (6.9, 8.6)	47.3 (45.8, 48.8)	38.9 (37.3, 40.5)
21–23	1.7 (1.4, 2.2)**	6.9 (6.0, 7.8)***	9.9 (9.0, 11.0)***	61.3 (59.7, 62.9)***	20.1 (18.9, 21.5)***
24–25	2.4 (1.8, 3.1)***	6.2 (5.3, 7.2)**	8.5 (7.6, 9.5)	62.8 (61.2, 64.3)***	20.2 (18.7, 21.7)***
Gender
Men	1.9 (1.6, 2.3)	5.8 (5.0, 6.8)	10.7 (9.8, 11.6)	51.5 (50.0, 53.0)	30.1 (28.7, 31.5)
Women	1.4 (1.2, 1.6)**	5.8 (5.4, 6.4)	7.2 (6.6, 7.8)***	57.4 (56.1, 58.7)***	28.2 (27.3, 29.1)**
Race/Hispanic ethnicity
White	2.8 (2.3, 3.3)	7.0 (6.3, 7.8)	8.4 (7.4, 9.6)	60.0 (58.2, 61.8)	21.9 (20.4, 23.4)
Black or African American	0.7 (0.4, 1.1)***	5.0 (4.3, 5.9)***	9.3 (8.0, 10.8)	52.0 (49.7, 54.3)***	32.9 (31.2, 34.7)***
American Indian/Alaska Native	1.7 (0.6, 4.8)	7.1 (4.0, 12.3)	20.3 (13.0, 30.5)***	48.9 (40.5, 57.3)**	22.0 (17.4, 27.5)
Native Hawaiian/Other Pacific Islander	S	S	8.1 (4.0, 15.5)	S	S
Asian	0.9 (0.3, 2.7)***	4.3 (2.5, 7.1)**	4.5 (3.0, 6.7)***	44.8 (40.9, 48.9)***	45.5 (41.1, 50.0)***
Identifies as two or more races	1.8 (0.9, 3.5)	7.3 (4.8, 10.8)	8.9 (6.8, 11.6)	61.9 (57.6, 66.0)	20.1 (16.5, 24.4)
Hispanic	1.0 (0.6, 1.4)***	5.1 (4.3, 6.0)***	8.4 (7.5, 9.3)	52.9 (50.9, 55.0)***	32.6 (31.0, 34.3)***
Metropolitan statistical area
Large	1.4 (1.1, 1.9)	5.0 (4.4, 5.7)	9.0 (8.4, 9.8)	53.9 (52.7, 55.0)	30.6 (29.5, 31.8)
Small	1.7 (1.3, 2.1)	6.5 (5.7, 7.4)***	8.3 (7.4, 9.3)	55.4 (53.6, 57.2)	28.1 (26.5, 29.7)**
Nonmetropolitan	1.9 (1.3, 2.7)	7.4 (6.1, 9.0)***	7.4 (6.2, 8.9)**	58.8 (56.5, 61.1)***	24.4 (22.5, 26.5)***
Family income as a % of the federal poverty level
<100	1.4 (1.1, 1.8)	6.3 (5.5, 7.1)	7.7 (7.0, 8.6)	53.6 (52.3, 55.0)	31.0 (29.9, 32.1)
100–200	1.9 (1.5, 2.4)	5.3 (4.5, 6.1)	8.1 (7.1, 9.1)	56.4 (54.3, 58.5)**	28.4 (26.5, 30.3)**
>200	1.6 (1.2, 2.2)	5.9 (4.9, 7.0)	10.5 (9.4, 11.7)***	56.0 (53.9, 58.1)	26.0 (24.4, 27.8)***
Parental status
Does not have a child in the household and not pregnant	1.6 (1.3, 1.8)	5.7 (5.2, 6.2)	9.3 (8.7, 9.9)	52.4 (51.4, 53.5)	31.1 (30.0, 32.2)
Pregnant with first child	1.3 (0.6, 3.0)	7.2 (3.9, 12.9)	9.1 (6.2, 13.2)	50.7 (45.2, 56.1)	31.7 (26.2, 37.8)
Has one child in the household	1.9 (1.3, 2.8)	5.5 (4.5, 6.7)	7.5 (6.2, 9.0)**	61.1 (58.5, 63.6)***	24.0 (21.6, 26.6)***
Has more than one children in the household	1.3 (0.9, 1.9)	6.7 (5.5, 8.0)	5.8 (4.7, 7.0)***	64.0 (61.7, 66.2)***	22.2 (20.1, 24.6)***
Number of religious services attended in past year
0	1.8 (1.5, 2.1)	6.2 (5.5, 7.0)	9.0 (8.2, 9.8)	55.2 (54.0, 56.4)	27.9 (26.8, 29.0)
1–2	1.8 (1.2, 2.7)	5.5 (4.4, 6.9)	10.1 (8.7, 11.7)	58.1 (55.6, 60.5)**	24.5 (22.2, 27.0)**
3+	1.2 (0.8, 1.8)	5.4 (4.7, 6.2)	7.5 (6.6, 8.5)**	54.0 (52.4, 55.6)	32.0 (30.2, 33.8)***
Attended school in the past 12 months
Yes	0.9 (0.7, 1.2)	4.4 (3.9, 5.0)	8.2 (7.5, 9.1)	52.2 (50.8, 53.6)	34.3 (32.7, 35.8)
No	2.0 (1.7, 2.4)***	6.8 (6.2, 7.4)***	8.9 (8.2, 9.6)	57.2 (56.1, 58.3)***	25.1 (24.0, 26.3)***
Health status
Excellent, very good or good	1.4 (1.2, 1.6)	5.5 (5.0, 5.9)	8.3 (7.8, 8.8)	55.1 (54.1, 56.0)	29.7 (28.9, 30.6)
Fair or poor	3.0 (2.2, 4.2)***	9.2 (7.6, 11.0)***	10.8 (9.0, 13.0)**	54.8 (51.3, 58.2)	22.2 (19.5, 25.1)***
Number of chronic conditions^a
0	1.3 (1.1, 1.6)	5.4 (4.9, 5.9)	8.6 (8.1, 9.1)	55.1 (54.2, 56.0)	29.6 (28.8, 30.4)
1	2.4 (1.8, 3.1)***	6.7 (5.7, 8.0)**	8.7 (7.5, 10.1)	55.2 (52.8, 57.5)	27.0 (24.8, 29.3)**
2+	3.1 (2.0, 4.7)**	9.8 (6.9, 13.9)**	8.0 (5.3, 11.9)	53.4 (48.4, 58.4)	25.7 (22.4, 29.3)**
Cigarette dependence in past month
No	0.7 (0.5, 0.9)	4.9 (4.4, 5.3)	7.4 (7.0, 7.8)	53.7 (52.8, 54.6)	33.4 (32.5, 34.2)
Yes	7.3 (6.1, 8.7)***	12.3 (10.5, 14.3)***	16.4 (14.7, 18.3)***	64.0 (61.6, 66.3)***	S
Sexually transmitted disease, past year
No	1.5 (1.2, 1.7)	5.5 (5.0, 5.9)	8.1 (7.7, 8.6)	55.3 (54.5, 56.1)	29.7 (28.9, 30.5)
Yes	4.5 (2.9, 6.9)***	11.9 (9.6, 14.7)***	18.1 (14.6, 22.2)***	52.4 (47.6, 57.3)	13.1 (10.0, 16.9)***
Depressive episode in the last year
No	1.2 (1.0, 1.4)	5.4 (4.8, 5.9)	7.5 (7.0, 8.1)	55.3 (54.4, 56.2)	30.6 (29.7, 31.4)
Yes	4.2 (3.3, 5.3)***	9.5 (8.0, 11.1)***	16.4 (14.4, 18.7)***	52.9 (50.6, 55.3)	16.9 (14.7, 19.5)***
Sexual identity
Heterosexual	1.5 (1.3, 1.7)	5.2 (4.7, 5.8)	8.3 (7.9, 8.8)	54.9 (54.0, 55.8)	30.1 (29.2, 31.0)
Lesbian or gay	0.8 (0.3, 1.9)	9.8 (6.4, 14.7)**	10.4 (7.5, 14.4)	62.1 (56.1, 67.8)**	16.8 (12.8, 21.8)***
Bisexual	2.8 (1.9, 3.9)**	9.5 (7.9, 11.5)***	11.0 (9.2, 13.2)**	60.5 (56.8, 64.1)***	16.2 (13.8, 18.9)***
Driven after substance use, past year^b
No	0.9 (0.7, 1.2)	4.3 (3.8, 4.7)	6.5 (6.0, 6.9)	55.7 (54.5, 56.8)	32.7 (31.8, 33.6)
Yes	6.6 (5.1, 8.4)***	17.9 (15.1, 21.0)***	31.1 (28.0, 34.3)***	44.5 (41.4, 47.6)***	S
Heavy alcohol use, past month^c
No	1.4 (1.2, 1.6)	5.3 (4.9, 5.8)	7.4 (7.0, 7.8)	55.4 (54.6, 56.3)	30.5 (29.7, 31.3)
Yes	5.1 (3.8, 6.9)***	15.3 (12.5, 18.6)***	31.7 (27.8, 35.9)***	47.9 (43.2, 52.6)***	S

Source: All estimates are from SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2015–2019.

Notes: Substance use disorder is defined as meeting criteria for dependence or abuse according to the Diagnostic and Statistical Manual of Mental Disorder, 4th edition (DSM-IV) based on self-reported substance use and consequences from any of the following substances: alcohol, marijuana, cocaine, hallucinogens, inhalants, methamphetamine, ecstasy, lysergic acid diethylamide (LSD), Phenylcyclohexyl piperidine (PCP), or non-medical use of sedatives, stimulants, or tranquilizers. “Other risky opioid use" includes individuals the NSDUH identifies as "misusing" opioids because they report using opioids in a way not directed by a doctor. Other substances use is defined as use of the aforementioned substances as well as the use of tobacco.

Adolescents include people ages 12–17 and young adults include people ages 18–25.

Note. ***/** indicates that the estimate differs significantly from the first level of each row variable, within each substance use column (e.g., the estimate for girl respondents with opioid use disorder differs significantly from the estimate for boy respondents with opioid use disorder) at the .01/.05 level, respectively, using a two-tailed test of significance.

"S" Data was suppressed using NSDUH's suppression criteria for unreliable estimates.

^aChronic conditions include high blood pressure, heart conditions, diabetes, cancer, asthma, COPD, HIV/AIDS, Hepatitis B, Hepatitis C, cirrhosis, and kidney disease.

^bThis variable corresponds to a question that asks respondents if they have driven under the influence of the following substances: marijuana, cocaine or crack, heroin, hallucinogens, inhalants, and methamphetamine.

^cHeavy alcohol use is computed using NSDUH definitions which were developed for adults and is defined as drinking five or more drinks on the same occasion for boys or four or more drinks on the same occasion for girls on each of 5 or more days in the past 30 days. For this variable, "occasion" means at the same time or within a couple hours of each other.