OBJECTIVES:

To assess trends in the incidence of nicotine use disorder (NUD) and describe associated factors among adolescents in the pediatric emergency department (ED) and inpatient settings.

METHODS:

We conducted a retrospective cohort study of all adolescents (11–18 years) with a hospital encounter (inpatient, observation, or ED) in the Pediatric Health Information System between January 1, 2012, and September 30, 2019. After excluding adolescents with a previous International Classification of Diseases, Ninth Revision, and International Classification of Diseases, Tenth Revision, NUD diagnosis in the past 2 years, adolescents with new NUD diagnosis (ie, NUD incidence) were identified. A multivariable generalized liner mixed model was used to assess adjusted NUD incidence and investigate the relationship of NUD with patient characteristics and any interactions between characteristics and time. Spearman’s correlation coefficient was used to assess the correlation between NUD incidence and e-cigarette use reported among youth.

RESULTS:

Of 3 963 754 adolescents, 15 376 (0.4%) had a new diagnosis of NUD. Between 2012 and 2019, NUD incidence increased from 0.3% to 0.4% (P < .001). Findings from the time interaction effect analysis revealed increasing NUD incidence among certain subpopulations, including boys, those with a commercial or other insurance type, adolescents seen in the ED, those from the lowest and highest median household income quartile, and those in the South and West US Census regions. The correlation between NUD incidence and e-cigarette use among high school students was ρ = 0.884 (P = .006).

CONCLUSIONS:

The incidence of NUD among adolescents is increasing. Efforts to increase the screening and treatment of NUD among adolescents in the hospital, particularly among the at-risk populations identified, are needed.

The use of electronic cigarettes (e-cigarettes) (eg, vaping devices) among adolescents has increased dramatically over the past 10 years, whereas cigarette smoking has steadily decreased.1,2  According to the National Youth Tobacco Survey (NYTS), between 2011 and 2019, past 30-day e-cigarette use increased from 1.5% to 27.5% among high school students and 0.6% to 10.5% among middle school students.1,3  Because e-cigarettes often contain high levels of nicotine, adolescent users are at risk for nicotine dependence after even brief periods of exposure.2,4,5 

Mental health and substance use disorders are among the top reasons for adolescent hospital visits, including emergency department (ED) and inpatient settings, and are increasing among adolescents with certain mental health and substance use disorders (eg, depression and alcohol use disorder).6  Additionally, in the past year, there has also been an outbreak of hospitalizations for vaping-associated lung injury with many (16%) of these cases occurring among children and adolescents (≤18 years).7  However, to date, little is known about the current rates of nicotine use disorder (NUD) among adolescents in the hospital setting. Given these concerning recent trends, it is important to understand changes in new NUD diagnoses (ie, incidence) in adolescents cared for in the ED and inpatient settings.8,9  The purpose of this study was therefore to (1) assess recent trends in the incidence of NUD among adolescents in the ED and inpatient settings and (2) describe characteristics associated with increasing NUD incidence in this population.

We conducted a retrospective cohort study of adolescents aged 11 to 18 years with a hospital encounter at 52 children’s hospitals in the Pediatric Health Information System (PHIS) database using data extracted between January 1, 2012, and September 30, 2019, because, at the time of analysis, these were the most recent PHIS data available. We excluded adolescents with a diagnosis of NUD within 2 years of the study start to capture only adolescents with a new NUD diagnosis. The PHIS database contains administrative and billing data on discharges from 52 tertiary care children's hospitals across the United States. Data quality is maintained by a joint effort between the Children’s Hospital Association (Lenexa, KS), participating hospitals, and International Business Machines Corporation Watson Health Truven Health Analytics (Ann Arbor, MI).

Our primary outcome was incidence of NUD, which we defined on the basis of International Classification of Diseases, Ninth Revision, (ICD-9) and International Classification of Diseases, Tenth Revision, (ICD-10) diagnosis codes during any hospital encounter (ie, inpatient, observation, or ED). The change from ICD-9 to ICD-10 codes increased the number of possible NUD codes to provide more detailed tobacco use information. We used multivariable generalized liner mixed models with a random hospital effect assuming a binomial distribution to assess the annual change in NUD incidence, adjusting for age, sex, race and ethnicity, payer type, median household income quartiles, and US Census region. We also performed a time interaction effect analysis, adjusting for interactions of time with age, sex, race and ethnicity, payer type, median household income quartiles (a proxy for socioeconomic status [SES]),10  and US Census region, to identify characteristics that correlated with the change in NUD incidence over time. We performed a sensitivity analysis with data only from 2012 to 2015 to determine if there was any indication that results were influenced by increased coding related to increased national visibility after 2015 when JUUL, the most popular e-cigarette product, came to the market. Spearman’s correlation coefficient was used to validate the NUD incidence trend by assessing the correlation between current e-cigarette use trends reported among middle and high school students from the NYTS from 2012 to 2019.1,3  All analyses were performed by using SAS version 9.4 (SAS Institute, Inc, Cary, NC); P < .05 was considered statistically significant. Because of use of deidentified data, this study was determined to be nonhuman subject research by the institutional review board.

Of 3 963 754 adolescents with 847 439 (21%) inpatient and 3 116 315 (79%) ED visits, 15 376 (0.4%) had a new diagnosis of NUD between 2012 and 2019. The incidence of NUD increased from 0.3% to 0.4% (P < .001) over the study years (Fig 1). The adjusted odds ratio (aOR) of NUD incidence was 1.04 (95% confidence interval [CI]: 1.03–1.05) over all study years, which equates to a 4% increase in NUD incidence annually. The correlation between incidence in NUD among adolescents and self-reported current e-cigarette use among high school students from the NYTS was ρ = 0.884 (P = .006).

In adjusted analyses, the odds of NUD incidence over the study years were different among all ages, with the highest adjusted odds among 17-year-olds versus 11-year-olds (aOR: 73.42 [95% CI: 58.25–92.52]), boys versus girls (aOR: 1.07 [95% CI: 1.04–1.11]), those with inpatient visits versus ED visits (aOR: 10.65 [95% CI: 10.25–11.07]), and those of non-Hispanic white versus non-Hispanic Black race and ethnicity (aOR: 1.52 [95% CI: 1.44–1.59]; all P < .001; Table 1). Across all years, our adjusted time interaction effect analysis (Table 2) revealed there was a greater increase over time compared to the overall adjusted odds (aOR: 1.04 [95% CI: 1.03–1.05]) among boys (aOR: 1.07 [95% CI 1.04–1.10]; P = .02), those with other (aOR: 1.10 [95% CI: 1.05–1.16]) and commercial (aOR: 1.08 [95% CI: 1.06–1.11]) payer types (P < .001), and those cared for in the ED setting (aOR: 1.16 [95% CI: 1.13–1.19]; P < .001). Additionally there was a greater increase in the adjusted odds of NUD incidence among those in the lowest (aOR: 1.08 [95% CI: 1.05–1.11]) and highest (aOR: 1.08 [95% CI: 1.05–1.11]) median household income quartiles (P < .001) and the south (aOR: 1.14 [95% CI: 1.11–1.17]) and west (aOR: 1.08 [95% CI: 1.05–1.11]) US Census regions (P < .001). The findings from the sensitivity analysis revealed a higher aOR of NUD in the early study years (2012–2015; aOR: 1.08 [95% CI: 1.06–1.11]) compared with all study years (2012–2019; aOR: 1.04 [95% CI 1.03–1.05]).

With our findings, we suggest there is a recent trend of increasing incidence of NUD among adolescents in the pediatric ED and inpatient settings, which strongly correlates with the increasing trend of self-reported current e-cigarette use among middle and high school students. Overall, the adolescent characteristics associated with increased odds of NUD are consistent with previous literature describing e-cigarette use, as well as any tobacco use, among youth on the basis of data from the NYTS.1,11 

In our findings from the time interaction effect analysis, we identified important differences in the increase of NUD incidence among certain patient subpopulations. Specifically, the increase in the odds of NUD incidence over time was most pronounced among boys, those with a commercial or other insurance type, adolescents cared for in the ED, and those from the West and South US Census regions. Notably, the increase in NUD incidence was also pronounced in adolescents from households in the lowest and highest median income quartiles. Low SES is correlated with increased tobacco use among youth as well as an increased likelihood for tobacco use in adulthood.12  However, literature describing SES and e-cigarette use has revealed mixed findings, with, in some studies, researchers noting an association between low SES and e-cigarette use, others linking high SES, and others finding no association at all.13,14  A recent study revealed a correlation between high SES and e-cigarette use among adolescents, thought to be mediated by exposure to e-cigarette advertising.15 Our findings indicating a greater increase in adjusted NUD incidence among those in the lowest as well as the highest median household incomes could be driven by different factors (eg, household smoke exposure and e-cigarette advertising) and thus warrant further investigation. With these findings, we also highlight the importance of screening for tobacco and e-cigarette use as well as nicotine dependence among adolescents, particularly among these at-risk adolescents.

The limitations of the study include the use of administrative data, which is subject to misclassification bias and likely underestimates the true NUD incidence. The increasing NUD incidence could be partly due to the change from ICD-9 to ICD-10 codes or an increase in coding among providers; however, in our sensitivity analysis findings, it is suggested this may only partially explain the observed trend. Our findings are also limited to adolescents with a hospital encounter and thus may not be generalizable to other settings. Further study is needed to investigate the trends in NUD incidence among adolescents in additional clinical settings (eg, primary care and school-based).

Despite these limitations, with our findings, we suggest there are increasing trends in NUD among adolescents in the ED and inpatient settings. This increasing trend in NUD incidence correlates strongly with increasing trends in e-cigarette use among youth. Further study is warranted into the factors associated with the greatest increase in adjusted NUD incidence among adolescents, particularly the influence of SES. Additionally, increased efforts to screen and treat adolescents for NUD in the ED and inpatient setting, particularly among the at-risk populations identified, are warranted.

Dr Masonbrink conceptualized and designed the study, critically reviewed the study data, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Hall, Catley, and Wilson participated in study design, critically reviewed the study data, and reviewed and revised the manuscript; Dr Richardson conceptualized and designed the study, conducted data analyses, drafted sections of the initial manuscript, and critically reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

1
Wang
TW
,
Gentzke
AS
,
Creamer
MR
, et al
.
Tobacco product use and associated factors among middle and high school students - United States, 2019
.
MMWR Surveill Summ
.
2019
;
68
(
12
):
1
22
2
National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health
.
E-Cigarette Use Among Youth and Young Adults: A Report of the Surgeon General
.
Atlanta, GA
:
Centers for Disease Control and Prevention
;
2016
3
Gentzke
AS
,
Creamer
M
,
Cullen
KA
, et al
.
Vital signs: tobacco product use among middle and high school students - United States, 2011-2018
.
MMWR Morb Mortal Wkly Rep
.
2019
;
68
(
6
):
157
164
4
Vogel
EA
,
Prochaska
JJ
,
Ramo
DE
,
Andres
J
,
Rubinstein
ML
.
Adolescents’ e-cigarette use: increases in frequency, dependence, and nicotine exposure over 12 months
.
J Adolesc Health
.
2019
;
64
(
6
):
770
775
5
Jankowski
M
,
Krzystanek
M
,
Zejda
JE
, et al
.
E-cigarettes are more addictive than traditional cigarettes-A study in highly educated young people
.
Int J Environ Res Public Health
.
2019
;
16
(
13
):
2279
6
Mojtabai
R
,
Olfson
M
,
Han
B
.
National trends in the prevalence and treatment of depression in adolescents and young adults
.
Pediatrics
.
2016
;
138
(
6
):
e20161878
7
Navon
L
,
Jones
CM
,
Ghinai
I
, et al
.
Risk factors for e-cigarette, or vaping, product use-associated lung injury (EVALI) among adults who use e-cigarette, or vaping, products - Illinois, July-October 2019
.
MMWR Morb Mortal Wkly Rep
.
2019
;
68
(
45
):
1034
1039
8
Moore
BJ
,
Freeman
WJ
,
Jiang
HJ
.
Statistical Brief #250: Costs of Pediatric Hospital Stays, 2016.
Rockville, MD
:
Agency for Healthcare Research and Quality
;
2019
. Available at: www.hcup-us.ahrq.gov/reports/statbriefs/sb250-Pediatric-Stays-Costs-2016.jsp. Accessed March 22, 2020
9
Sun
R
,
Karaca
Z
,
Wong
HS
.
Trends in hospital emergency department visits by age and payer, 2006–2015: statistical brief #238
. In:
Healthcare Cost and Utilization Project (HCUP) Statistical Briefs
.
Rockville, MD
:
Agency for Healthcare Research and Quality
;
2018
. Available at: www.ncbi.nlm.nih.gov/books/NBK513766/. Accessed February 20, 2019
10
Berkowitz
SA
,
Traore
CY
,
Singer
DE
,
Atlas
SJ
.
Evaluating area-based socioeconomic status indicators for monitoring disparities within health care systems: results from a primary care network
.
Health Serv Res
.
2015
;
50
(
2
):
398
417
11
Azagba
S
,
Manzione
L
,
Shan
L
,
King
J
.
Trends in smoking behaviors among US adolescent cigarette smokers
.
Pediatrics
.
2020
;
145
(
3
):
e20193047
12
Soneji
S
,
Barrington-Trimis
JL
,
Wills
TA
, et al
.
Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis
.
JAMA Pediatr
.
2017
;
171
(
8
):
788
797
13
Simon
P
,
Camenga
DR
,
Kong
G
, et al
.
Youth E-cigarette, blunt, and other tobacco use profiles: does SES matter?
Tob Regul Sci
.
2017
;
3
(
1
):
115
127
14
Moore
G
,
Hewitt
G
,
Evans
J
, et al
.
Electronic-cigarette use among young people in Wales: evidence from two cross-sectional surveys
.
BMJ Open
.
2015
;
5
(
4
):
e007072
15
Simon
P
,
Camenga
DR
,
Morean
ME
, et al
.
Socioeconomic status and adolescent e-cigarette use: the mediating role of e-cigarette advertisement exposure
.
Prev Med
.
2018
;
112
:
193
198

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.