Disordered eating is associated with non-medical use of prescription stimulants among college students

Journal Pre-proof Disordered eating is associated with non-medical use of prescription stimulants among college students Sara K Nutley, Carol A Mathews, Catherine W Striley

PII:

S0376-8716(20)30072-7

DOI:

https://doi.org/10.1016/j.drugalcdep.2020.107907

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DAD 107907

To appear in:

Drug and Alcohol Dependence

Received Date:

15 October 2019

Revised Date:

15 January 2020

Accepted Date:

9 February 2020

Please cite this article as: Nutley SK, Mathews CA, Striley CW, Disordered eating is associated with non-medical use of prescription stimulants among college students, Drug and Alcohol Dependence (2020), doi: https://doi.org/10.1016/j.drugalcdep.2020.107907

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier.

Title: Disordered eating is associated with non-medical use of prescription stimulants among college students Author names and affiliations: Sara K Nutley, MSa Email: [email protected] Carol A Mathews, MDb Email: [email protected] Catherine W Striley, PhD, MSW, ACSW, MPEa Email: [email protected] b

Department of Epidemiology, University of Florida, 2004 Mowry Road, PO Box 100231, Gainesville, FL 32610 Department of Psychiatry, University of Florida, 100 S Newell Drive, Gainesville FL, 32610

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Corresponding Author: Sara K Nutley, MS, Department of Epidemiology, University of Florida Email: [email protected] Telephone: (708) 692-1336 Address: 2004 Mowry Road, PO Box 100231, Gainesville, FL 32610

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Highlights  Disordered eating is common among students using stimulants non-medically.  Risk for non-medical use increases with the number of disordered eating behaviors.  Disordered eating does not increase the odds of medical use.  Need to query for non-medical use among students with disordered eating. Abstract

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Background: Disordered eating behaviors are associated with non-medical use of prescription stimulants for weight and appetite-related purposes. Yet, estimates of the prevalence and types of disordered eating associated

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with non-medical use vary. Additionally, little is known about the association between medical use of prescription stimulants and disordered eating.

Method: Data were collected from 87,296 college students at 127 institutions that participated in the Healthy

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Minds Study. We assessed the relationship between disordered eating, medical and nonmedical prescription stimulant use using multivariable logistic regression models adjusted for demographic characteristics, lifestyle and behavioral factors, and psychiatric comorbidity. Results: Non-medical use of prescription stimulants (NMUPS) was reported by 2.8% (n=2,435) of the sample. One-third of students using prescription stimulants non-medically reported two or more disordered eating attitudes and behaviors. Disordered eating was a significant predictor of non-medical, but not medical use of

prescription stimulants. A dose-response relationship was identified between disordered eating and non-medical use, where risk for non-medical use increased with the number of disordered eating attitudes and behaviors reported. Conclusions: The risk for NMUPS increases with disordered eating symptomatology. There is a need to assess for NMUPS among college students presenting with disordered eating.

Keywords: Nonmedical Prescription Stimulant Use; Nonmedical Prescription Drug Use; Eating Disorder

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1.1 Introduction Non-medical use of prescription stimulants (NMUPS) is a growing public health concern, particularly

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among college students, of whom nearly one-fifth use prescription stimulants non-medically (Benson et al., 2015).

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Previous findings have identified a variety of demographic, behavioral, and psychiatric characteristics associated with NMUPS among college students, such as being male, membership in a Greek-life organization, poor

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academic performance, symptoms of attention-deficit/hyperactivity disorder, problems with alcohol or marijuana use, and use of other substances (Benson et al., 2015).

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College students report a variety of motivations for using prescription stimulants non-medically including cognitive enhancement, to get high or prolong the effects of other substances, and weight loss (Benson et al.,

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2015). Though the estimated prevalence of NMUPS for weight- or appetite-related purposes varies widely between studies, individuals endorsing weight motives for NMUPS more frequently report body image concerns (Jeffers et al., 2013; Jeffers et al., 2014; Kilwein et al., 2016), eating disorder symptomatology (Jeffers et al., 2013; Jeffers et al., 2014; Kilwein et al., 2016; Gibbs et al., 2016), appearance-related motivations for weight loss

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(Jeffers et al., 2013), and negative attitudes toward obesity (Kilwein et al., 2016) than do peers who do not endorse NMUPS and peers reporting NMUPS for purposes unrelated to weight loss. Unhealthy weight management practices commonly endorsed among individuals reporting NMUPS for weight-related purposes primarily include binge-eating and purging, especially objective binge eating (Gibbs et al., 2016;), vomiting for weight loss (Jeffers et al., 2014; Gibbs et al., 2016; Striley et al., 2017) and use of laxatives, diet pills, or diuretics (Jeffers et al., 2013;

Jeffers et al., 2014; Gibbs et al., 2016; Striley et al., 2017). While some studies have found that food restriction may also occur more frequently among those endorsing NMUPS for weight or appetite purposes (Kilwein et al., 2016; Striley et al., 2017; Clayton et al., 2017), the data are less consistent and other studies have found no relationship (Gibbs et al., 2016; Owens et al., 2017). Nevertheless, previous findings indicate that a dose-response relationship may exist between weight control behaviors and NMUPS. In one study, adolescent girls between the ages of 10 and 18 with unhealthy and extreme weight control behaviors were over five times more likely to endorse non-medical use of prescription

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stimulants than peers who did not endorse these weight control behaviors (Striley et al., 2017). Those endorsing

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only unhealthy weight control behaviors (i.e. “not eating for a day or two” or “exercising too much” for weight loss) or extreme weight control behaviors (i.e. “taking pills” or “making yourself vomit” for weight loss), rather

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than both, nearly doubled and quadrupled (respectively) the odds of NMUPS. However, these findings have yet to be expanded to the college population.

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Despite evidence that NMUPS for weight and appetite-related purposes is associated with eating disorder

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psychopathology, estimates of the prevalence and types of disordered eating attitudes and behaviors associated with non-medical use of prescription stimulants vary widely between studies, and the generalizability of findings

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has been limited by use of relatively small, homogenous samples. Additionally, no studies have compared disordered eating attitudes and behaviors of college students who use prescription stimulants medically and those using prescription stimulants non-medically. Understanding the association between disordered eating, NMUPS, and medical use of prescription stimulants (Rx Only) may be useful in identifying college students who may be

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at an increased risk for comorbid eating disorders (ED) and misuse of prescription stimulants or other substance use disorders (SUD). We hypothesized that disordered eating attitudes and behaviors, especially binge-eating and purging, would increase the odds of non-medical, but not medical, use of prescription stimulants after adjusting for demographic, behavioral, and psychiatric characteristics. We further hypothesized that the odds of NMUPS would increase linearly with the number of disordered eating attitudes and behaviors reported.

2.1 Materials and Methods Data were collected from 104,051 college students who participated in the Healthy Minds Study (HMS) between the fall of 2015 and the spring of 2018. The HMS is an annual, web-based survey that aims to examine the mental health status and counseling service utilization of college students (Healthy Minds Network, 2015; Healthy Minds Network, 2016; Healthy Minds Network, 2017). At participating institutions, a random sample of 4,000-20,000 degree-seeking students at large institutions, or all students at smaller institutions, were recruited to participate using e-mail. Between Fall 2015 and Spring 2018, 57 private (44.9%) and 61 public (48.0%)

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institutions, as well as 9 community colleges (7.1%), participated in the Healthy Minds Study. Of 127

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participating colleges and universities, nearly one-third of campuses are located in the Midwest (29.9%) and approximately two-thirds are distributed evenly between the Northeastern (18.1%), Southern (21.9%), and

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Western (21.3%) regions of the United States (Figure 1). Additionally, two participating institutions are located in Canada (7.4%). Overall participation rates are as follows: 27% in 2015–2016, 23% in 2016–2017, and 23% in

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2017–2018. To reduce bias introduced by differences in participation by student demographic characteristics, the

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HMS team constructed response weights using administrative data (e.g. gender, race-ethnicity, academic level, grade point average) from participating institutions. Of students who participated in the HMS between the fall of

complete data.

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2015 and the spring of 2018, the present analysis consists of 87,296 students (83.9% of the total) who provided

2.2 Use of Prescription Stimulants

Non-medical use of prescription stimulants may be defined as any use of a prescribed stimulant medication

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in a manner that is inconsistent with the recommendations of the prescribing physician (Arria & Wish, 2006). Though some individuals may engage in non-medical use by using stimulant medication without a prescription, others who have been medically prescribed stimulants may non-medically use the drug by manipulating dosage or frequency of use. Participants were asked to identify any illicit substances they had used in the past 30 days, including use of stimulant medications without a prescription. Additionally, students were asked if they had taken any of the

following prescription medications several times per week in the preceding 12 months: psychostimulants; antidepressants; anti-psychotics; anti-anxiety medications; mood stabilizers; sleep medications; or other medications for mental or emotional health. Participants who endorsed the use of one or more medications were further asked about the source of the most recent prescription for the medications. Students were classified as using prescription stimulants non-medically if they endorsed taking prescription stimulants in the past 12 months without a prescription or more than prescribed. Students who used prescription stimulants with a prescription from a general practitioner, nurse practitioner, primary care physician,

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psychiatrist, or other type of doctor and did not endorse taking more medication than prescribed were classified

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as medically using prescription stimulants (Rx Only). Participants who did not report use of prescription stimulant medication were classified as not taking prescription stimulants. Where patterns of use were unclear (i.e.

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individuals who reported taking two or more medications and receiving medication from two or more sources), cases were dropped (n=91, 1.0%).

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2.3 Disordered Eating

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Disordered eating were assessed using the SCOFF questionnaire, a five-item screening tool to measure the possible presence of an eating disorder (Morgan et al., 1999). Students who answered yes to two or more of the following questions were classified as engaging in disordered eating: “Do you make yourself sick because

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you feel uncomfortably full?”; “Do you worry you have lost control over how much you eat?”; “Have you recently lost more than fifteen pounds in a 3 month period?”; “Do you believe yourself to be fat when others say you are too thin?”; and “Would you say that food dominates your life?”. In a recent multiethnic population-based sample

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of adults between the ages of 16 and 90, sensitivity and specificity of the SCOFF were 53.7% and 93.5%, respectively, indicating that the SCOFF may be a good measure for excluding those without disordered eating, but may omit a substantial number of individuals with eating disorder attitudes and behaviors (Solmi et al., 2015). In addition to the SCOFF questionnaire, the HMS asks students to report their current height and weight, which was used to calculate body mass index using the following formula: weight(lbs)/[height(in)]2 × 703

(CDC, 2015). Students categorized their perception of their current weight using a 5-point Likert scale ranging from very underweight to very overweight. 2.4 Demographics Demographic variables in this analysis include age (18-22, 23-31, 31+), gender (male/female), race (white/non-white), degree program (graduate/undergraduate), grade point average (GPA), citizenship (US/international), parent education (first generation/non-first generation college student), housing situation (oncampus/off-campus/other), and current financial situation (sometimes-always stressful/never-rarely stressful).

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Additionally, students were asked about their involvement in school activities, participation in varsity or club

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athletics, and fraternity or sorority membership. 2.5 Health Behaviors and Psychiatric Comorbidity

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Participants were asked about their lifetime history of eating disorders, depression, anxiety, attention or learning disorders, and substance use disorders. Current symptomatology of depression and anxiety was measured

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using the Patient Health Questionnaire (PHQ-9), and the Generalized Anxiety Disorder 7-item (GAD-7) scale

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(Kroenke et al., 2001; Spitzer et al., 2006). Moderately severe or severe depressive symptoms were considered present if the total PHQ-9 score was greater than or equal to 15. Moderate or severe anxiety symptoms were

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considered present if the total GAD-7 score was greater than or equal to 10. Additionally, participants reported use of medical services in the past year and lifetime use of therapy or counseling services. In terms of substance use, students who reported ever smoking cigarette(s) in the past 30 days were classified as currently using tobacco products and students who reported ever using marijuana in the past 30 days

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were classified as currently using marijuana products. 2.6 Statistical Analysis

For all relevant variables, we assessed the data for normality and missing values. We began by using

Pearson’s chi-square and one-way analysis of variance (ANOVA) tests, as well as pairwise independent sample t-tests, to describe the demographic, behavioral, and psychiatric characteristics of students using prescription stimulants non-medically, medically, and those not using prescription stimulants. We compared the prevalence

of disordered eating attitudes and behaviors, stratified by the use of prescription stimulants, using Pearson’s chisquare test for independence. For all ANOVA, Pearson’s chi-square, and independent sample t-tests, Bonferroni adjustment for multiple testing was applied (3 prescription stimulant groups considered, α=0.015). Finally, we assessed the relationship between disordered eating, NMUPS, and medical use of prescription stimulants using separate multivariate logistic regression models adjusted for demographic (gender, race, age, housing, financial status, GPA, fraternity/sorority membership, and BMI) and psychiatric or behavioral characteristics (tobacco use, marijuana use, current symptoms of anxiety or depression, and lifetime diagnosis of

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depression, anxiety, attention/learning or substance use disorders, lifetime use of therapy/counseling, past year

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visit to medical provider). In the first set of models, non-medical use of prescription stimulants was used as the outcome variable and various disordered eating attitudes and behaviors were used as separate predictor variables

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(i.e. separate models). In the second set of models, medical use of prescription stimulants was used as the outcome variable and various disordered eating characteristics were used as separate predictor variables. Significance was

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determined using 95% confidence intervals. Analyses were conducted using SAS version 9.4.

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3.1 Results

Of the 87,296 students who were included in this study, 2.8% (n=2,435) reported using prescription

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stimulants non-medically, 4.1% (n=3,545) used prescription stimulants for medical purposes only, and 93.1% (n=81,316) did not use prescription stimulants. A detailed comparison of students using prescription stimulants non-medically, medically, and those not using prescription stimulants is provided in Table 1; significant differences were observed among the three categories of prescription stimulant use in terms of all demographic

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characteristics except participation in varsity or club athletics. In terms of use of other substances, students endorsing NMUPS were more than four times as likely to report use of tobacco products (40.6% vs. 8.5%) and marijuana (73.5% vs. 17.6%) than students not using prescription stimulants. Individuals using prescription stimulants for medical purposes reported using both tobacco and marijuana at rates intermediate to those reported by individuals endorsing NMUPS and those who did not report using prescription stimulants.

Compared to those who did not report use of prescription stimulants, twice as many students using prescription stimulants, either medically or non-medically, reported current symptomatology of depression (NMUPS: 23.8%, MUPS: 23.5%, No Use: 11.4%). Anxiety rates were also significantly increased among these groups (NMUPS: 37.9%, MUPS: 39.2%, No Use: 24.1%). Students using prescription stimulants for medical purposes were significantly more likely to report a lifetime history of depression, anxiety, attention or learning disorders, and substance use disorders (SUD) than those not using prescription stimulants. However, among individuals who reported a lifetime SUD, type of SUD (i.e. alcohol use disorder, other) did not differ by use of

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stimulant medication.

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Students using prescription stimulants non-medically reported rates of psychiatric diagnosis intermediate to those reported by individuals using prescription stimulants for medical purposes and those who do not use

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3.2 Disordered Eating

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prescription stimulants. A similar pattern was observed for lifetime use of counseling or therapy services and use

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Individuals who used prescription stimulants non-medically were significantly more likely to endorse all disordered eating attitudes and behaviors compared to students not using prescription stimulants (Table 2). For

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all disordered eating attitudes and behaviors, individuals who used prescription stimulants for medical purposes endorsed disordered eating at rates intermediate to those reported by individuals endorsing NMUPS and those who do not use prescription stimulants.

After adjusting for demographic, behavioral, and psychiatric characteristics, students who endorsed two

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or more disordered eating attitudes and behaviors were 35% more likely to endorse NMUPS than those who endorsed fewer than two disordered eating attitudes and behaviors (AOR: 1.35, 95% CI:[1.23,1.49]; Table 3).1 In

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Given the established relationship of binge-eating and purging behaviors with alcohol use disorders (Gadalla & Piran, 2007), we conducted a sensitivity analysis to test the addition of past 30-day alcohol use to the hypothesized models. However, when alcohol was added to the models at a loss of almost 7,000 participants due to missing data, there was little change to AORs (e.g. 2+ Disordered Eating Behaviors (SCOFF  2) from 1.35 to 1.32) and there was no change in significance for any odds ratio. Therefore, these models are not shown.

separate logistic regression models, positive endorsement of each disordered eating attitude and behavior was associated with increased odds of NMUPS. Specifically, making yourself sick when feeling uncomfortably full was associated with a 46% increased risk of NMUPS (AOR: 1.46, 95% CI:[1.31,1.62]), worrying you’ve lost control over how much you eat and believing yourself to be fat when others say you are thin were each associated with a 22% increased risk of NMUPS (AOR:1.22, 95% CI:[1.10,1.34] and AOR:1.22, 95% CI:[1.09,1.37], respectively), and believing food dominates your life was associated with a 20% increased risk of NMUPS (AOR:1.20, 95% CI:[1.07,1.34]). Additionally, the odds of NMUPS significantly increased with the number of

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disordered eating attitudes and behaviors reported.

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While recently losing 15 or more pounds in three months was associated with 25% increased odds of using prescription stimulants for medical purposes (AOR:1.25, 95% CI:[1.09,1.44]), the odds of each remaining

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disordered eating attitude or behavior did not differ between individuals using prescription stimulants for medical purposes and those not using prescription stimulants. However, reporting five disordered eating symptoms

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doubled the odds of medical use (AOR 2.08, 95% CI [1.25,3.45]).

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3.2 Patterns of Non-medical Use

Given that type of non-medical use may differ (i.e. using stimulant medication without a prescription vs.

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manipulating dosage of medically prescribed medication), we conducted a sensitivity analysis to explore potential variation in disordered eating behavior among those endorsing NMUPS by specific pattern of stimulant use. Students who reported using prescription stimulants both medically and non-medically were more likely to use marijuana (75.8% vs. 60.3%) and tobacco (42.8% vs. 28.3%) products than students who reported only using

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stimulants non-medically (Supplemental Table 1). Further, students who reported both medical and non-medical use were more likely to endorse current symptoms of moderately severe or severe depression (25.8% vs. 12.8%) and anxiety (39.4% vs. 29.1%) than students who reported only using stimulants non-medically. In terms of disordered eating attitudes and behaviors, students who reported both medically and nonmedically using prescription stimulants were slightly more likely to report disordered eating attitudes and

behaviors (35.2% vs. 27.5%) and twice as likely to report recently losing more than 15 pounds in a 3-month period (15.5% vs.6.5%) than students who reported only using stimulants non-medically (Supplemental Table 2). 4.1 Discussion The results of this study confirm previous findings demonstrating that college students using prescription stimulants for non-medical purposes report higher rates of disordered eating than students using prescription stimulants for medical purposes and those not using prescription stimulants, and for the first time, indicate that disordered eating is associated with an increased risk of non-medical, but not medical use of prescription

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stimulants. Importantly, our results suggest a dose-response relationship between disordered eating symptoms

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and non-medical use among college students after adjusting for demographic characteristics, lifestyle and behavioral factors, and psychiatric comorbidity. In particular, these findings expand previous work indicating a

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dose-response relationship between unhealthy and extreme weight control behaviors and NMUPS among adolescent girls (Striley et al., 2017) to the college population and to men. Additionally, though not the primary

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focus of this study, our findings support previous reports of an association between non-medical use of

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prescription stimulants, use of other substances, and fraternity/sorority membership (McCabe & Tetor, 2007; Benson et al., 2015; Witcraft et al., 2019). In particular, non-medical users were over four times as likely to use

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marijuana and tobacco products, and over twice as likely to be in a Greek-life organization than non-users. Contrary to our hypothesis, disordered eating in general, rather than specific eating disorder symptoms, was associated with non-medical use of prescription stimulants. Specifically, this analysis confirms previous reports of a relationship between NMUPS, binge-eating, and purging (Jeffers et al., 2013; Jeffers et al., 2014; Gibbs et

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al., 2016; Striley et al., 2017), and adds to literature supporting a significant association between NMUPS and dietary restriction (Kilwein et al., 2016; Striley et al., 2017; Clayton et al., 2017). While the causal mechanism underlying the association between disordered eating and NMUPS remains unclear, it is possible that a desire to lose weight is a motivating factor for non-medical use among those with a variety of disordered eating attitudes and behaviors. This hypothesis is supported by previous findings suggesting that college students who endorse weight motives for NMUPS more frequently report low self-esteem (Jeffers et al., 2013), body image concerns

(Jeffers et al., 2013; Jeffers et al., 2014; Kilwein et al., 2016) and greater eating disorder pathology (Jeffers et al., 2013; Jeffers et al., 2014; Kilwein et al., 2016; Gibbs et al., 2016) than students not using prescription stimulants and those reporting NMUPS for purposes unrelated to weight or appetite. It is also possible that specific personality traits increase vulnerability to development of co-occurring disordered eating and NMUPS. A multitude of personality characteristics found to predate ED onset have also been identified as risk factors for the development of SUDs, including novelty-seeking, impulsivity, neuroticism, and negative affectivity (Harrop & Marlatt, 2010). Interestingly, recent findings suggest that neither perfectionism nor impulsivity – traits commonly

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associated with dietary restriction, binge-eating, and purging – were significantly associated with NMUPS for

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appetite- or weight-related purposes (Thiel, Kilwein, De Young & Looby, 2019). While it is possible that other personality traits common to a range of eating disorder symptoms (i.e. negative emotionality) may increase

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susceptibility to co-occurring disordered eating and NMUPS, it has been suggested that factors other than personality characteristics, such as drug use history, may be stronger predictors of ED/SUD comorbidity

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(Thompson‐Brenner et al., 2008; Harrop & Marlatt, 2010).

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It is worth noting that weight loss and atypical eating patterns may also occur as a consequence of using prescription stimulants, thus artificially inflating measures of disordered eating. However, our findings do not

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support this hypothesis as we observed few significant relationships between disordered eating and the use of prescription stimulants for medical purposes, and marginal differences in disordered eating behavior among students who reported only using stimulants non-medically and those who reported both medically and nonmedically using prescription stimulants. As an exception to this trend, we found that endorsement of five or more

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disordered eating attitudes and behaviors was associated with increased risk of medical use of prescription stimulants. While physician-advised weight loss programs for young adults are most often comprised of recommendations for lifestyle and behavioral change, physicians may elect to prescribe weight loss medication in combination with nutrition- and activity-related programs in cases where patients are at increased medical risk due to obesity (“Prescription Medications to Treat Overweight and Obesity,” n.d.; Yanovski & Yanovski, 2014; US Preventive Services Task Force, 2018). Given that overweight and obese individuals are more likely to

experience body dissatisfaction and disordered eating than their normal weight peers (Weinberger, Kersting, Riedel-Heller, & Luck-Sikorski, 2016; Nagata, Garber, Tabler, Murray, & Bibbins-Domingo, 2018), it is possible that those prescribed stimulants for weight purposes experience increased levels of eating disorder symptomatology. In a clinical setting, binge eating disorder (BED) often goes undiagnosed (Kornstein, Kunovac, Herman, & Culpepper, 2016) and physicians prescribing stimulants for weight loss may be unaware of a patient’s disordered eating attitudes and behaviors. In part, this may be because BED was only recently recognized as formal eating disorder diagnosis in the fifth edition to the Diagnostic and Statistical Manual of Mental Disorders.

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However, physicians who are aware of a patient’s binge eating behaviors whether or not they are diagnosed may

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also prescribe stimulants in an effort to regulate appetite and pathological eating. In 2015, the US Food and Drug Administration approved the first pharmacologic agent for the treatment of moderate to severe BED in adults:

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lisdexamfetamine dimesylate, a stimulant commonly marketed for the treatment of ADHD (Guerdjikova, Mori, Casuto, & McElroy, 2016; Ward & Citrome, 2018). However, the exact relationship between disordered eating

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symptoms and medical use of prescription stimulants remains unclear.

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4.2 Limitations

While the present study is the largest investigation of the association between disordered eating and non-

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medical use of prescription stimulants to date, there are limitations. First, classification of nonmedical use, medical use, and disordered eating was derived using self-report measures, introducing the potential for misclassification and recall bias. Low sensitivity of the SCOFF questionnaire may contribute to students falsely screening negative for disordered eating. Future epidemiological investigation will be necessary to validate

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estimates of the prevalence of disordered eating among individuals using prescription stimulants non-medically and those using for medical purposes. Additionally, covariates included in this analysis were self-reported and recall bias cannot be ruled out. For example, both weight perception and “actual” weight and height are likely to be biased, especially among those with eating disorder symptoms. However, while individuals with some eating disorders may overestimate their weight (those with anorexia), those with binge eating and purging behaviors may be more likely to underestimate their weight (McCabe, McFarlane, Polivy, & Olmsted, 2001; Meyer,

Arcelus, & Wright, 2009). In a sample of this size, the Central Limit Theorem would argue that these opposing biases would contribute to a normalized distribution and thus influence overall findings to the null. Despite our best efforts to explore the influence of demographic, psychiatric, and behavioral factors on the observed association, additional factors, such as the use of alcohol or other illicit substances, were not evaluated. Further, academic factors explored in this study (e.g. GPA) are likely influenced by unmeasured covariates such as academic year. For example, those reporting NMUPS are more likely to be younger students, whose GPA is less likely to be stable compared to older students who have completed more coursework. Careful

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interpretation of these covariates is necessary. Lastly, this is a cross-sectional study and we are unable to

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determine temporality. 4.3 Conclusions

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The risk for non-medical use of prescription stimulants increases with disordered eating symptomology, suggesting the need to query for NMUPS among college students presenting with disordered eating. Evaluation

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and management of non-medical use among individuals with disordered eating is likely essential to

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individualizing treatment goals and improving outcomes. Further, though we were unable to explore specific patterns of misuse among those using prescription stimulants medically, it may be beneficial for physicians

eating.

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prescribing stimulants to consider the potential for misuse among individuals at increased risk for disordered

Contributors: Authors SN, CM, and CW conceptualized the present work. Author SN conducted data analysis

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and wrote the initial draft of the manuscript. Authors CM and CS assisted in manuscript revision and provided project oversight. All authors approved the final manuscript as submitted.

Role of the Funding Source: Nothing declared Declarations of interest: None

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Figure 1: United States colleges and universities participating in the Healthy Minds Study between Fall 2015 and Spring 2018

Table 1: Demographic, behavioral, and psychiatric characteristics of study sample, a national sample of college students (n=87,296), by use of prescription stimulants NMUPS N=2,435 (%)

Rx Only N=3,545 (%)

Non-users N=81,316 (%)

Gender

p <0.0001

961 (39.5) 1474 (60.5)

1063 (30.0) 2482 (70.0)

23478 (29.2) 57,568 (70.8)

1767 (72.6)N, Rx 58 (2.4) 134 (5.5) 89 (3.7) 387 (15.9)

2743 (77.4)N 72 (2.0) 140 (4.0) 115 (3.3) 475 (13.4)

51419 (63.2) 3976 (4.9) 10914 (13.4) 4184 (5.2) 10823 (13.3)

1883 (77.3)N, Rx 481 (19.8) 71 (2.9)

2127 (60.0)N 1045 (29.5) 373 (10.5)

51662 (63.5) 21424 (23.6) 8230 (10.1)

2045 (84.0)N, Rx 390 (16.0) 471 (19.3)N 161 (6.6)N

2606 (73.5)N 939 (26.5) 602 (17.0)N 255 (7.2)N

822 (33.8)N 1543 (63.4) 70 (2.9)

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57954 (71.3) 23,362 (28.7) 19227 (23.6) 9414 (11.6)

<0.0001

<0.0001

<0.0001 <0.0001

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<0.0001

29613 (36.4) 48911 (60.2) 2792 (3.4)

2776 (78.3) 769 (21.7)

62878 (77.3) 18438 (22.7)

1034 (42.5)N, Rx 1090 (44.8) 199 (8.2) 112 (4.6) 1684 (69.2)N,Rx 601 (24.5)N,Rx 231 (9.5) 989 (40.6)N,Rx 1789 (73.5)N,Rx

1566 (44.2)N 1319 (37.2) 352 (9.9) 308 (8.7) 2154 (60.8) 469 (13.2)N 319 (9.0) 602 (17.0)N 1213 (34.2)N

46261 (56.9) 24904 (30.6) 4066 (5.0) 6085 (7.5) 50993 (62.7) 7395 (9.1) 7609 (9.4) 6875 (8.5) 14317 (17.6)

<0.0001

1855 (76.2)N 580 (23.8)

2713 (76.5)N 832 (23.5)

72028 (88.6) 9288 (11.4)

<0.0001

1513 (62.1)N 922 (37.9)

2155 (60.8)N 1390 (39.2)

61665 (75.8) 19651 (24.1)

<0.0001

681 (28.0)N,Rx 745 (30.6)N,Rx 283 (11.6)N,Rx 98 (4.0)N,Rx 48 (50.0) 50 (51.0)

1814 (51.2)N 1958 (55.2)N 2483 (70.0)N 102 (2.9)N 48 (47.1) 54 (52.9)

15089 (18.6) 17236 (21.2) 2540 (3.1) 758 (0.9) 397 (52.4) 361 (47.6)

<0.0001 <0.0001 <0.0001 <0.0001 0.5256

1173 (33.1)N 2254 (63.6) 118 (3.3)

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1957 (80.4)N 478 (19.6)

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Male Female Race/ethnicity White African American Asian/Asian American Hispanic/Latino/a Other/Mixed Age 18-22 23-30 31+ Degree Program Undergraduate Graduate International Student First Generation College Student Housing On-campus Off-campus Other Financial Situation Sometimes-Always Stressful Never-Rarely Stressful GPA A B C or below Unknown Participation 1+ school activities Fraternity/Sorority Member Varsity/club Athlete Tobacco Use Marijuana Use Depression symptomatology Mild-Moderate Moderately Severe-Severe Anxiety symptomatology None-Mild Moderate-Severe Lifetime History: Depression Anxiety Attention/Learning Disorder Substance Use Disorder Alcohol Use Disorder Other/Don’t Know

N, Rx

<0.0001

0.0009

<0.0001 <0.0001 0.7505 <0.0001 <0.0001

Lifetime use of Counseling or Therapy Past Year Visit to a Medical Provider

1245 (51.1)N,Rx

2618 (73.9)N

31322 (38.5)

<0.0001

1960 (80.5)Rx

3240 (91.4)N

63838 (78.5)

<0.0001

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N: Bivariate analysis indicates significant difference compared to Non-users Rx: Bivariate analysis indicates significant difference compared to Rx Only

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Table 2: Disordered eating behaviors of study sample, a national sample of college students (n=87,296), by use of prescription stimulants NMUPS Rx Only Non-users p N=2435 (%) N=3545 (%) N=81,316 (%) Reported 2+ Disordered Eating 828 (34.0)N 979 (27.6)N 18318 (22.5) <0.0001 R Attitudes/Behaviors (SCOFF  2) Make yourself sick because you 585 (24.0)N,Rx 587 (16.6)N 11084 (13.6) <0.0001 R* feel uncomfortably full Worry that you have lost control 935 (38.4)N 1282 (36.2)N 24303 (29.9) <0.0001 R* over how much you eat Recently lost more than 15 pounds 336 (13.8)N 447 (12.6)N 5795 (7.1) <0.0001 R* in a 3-month period Believe yourself to be fat when 491 (20.2)N,Rx 545 (15.4)N 11746 (14.4) <0.0001 R* others say you are too thin Believe food dominates lifeR* 498 (20.5)N,Rx 621 (17.5)N 12656 (15.6) <0.0001 Perceived Bodyweight Underweight 304 (12.5)N,Rx 346 (9.8) 7422 (9.1) <0.0001 Normal weight 1184 (48.6) 1585 (44.7) 38405 (47.2) Overweight 947 (38.9) 1614 (45.5) 35489 (43.6) BMI <0.0001 N,Rx Underweight 226 (9.3) 262 (7.4) 6936 (8.5) Normal weight 1414 (58.1) 1859 (52.4) 43006 (52.9) Overweight/Obese 795 (32.7) 1424 (40.2) 31374 (38.6) Lifetime ED Diagnosis 170 (7.0)N 280 (7.9)N 2482 (3.1) <0.0001 Ref (R): Reported less than 2 disordered eating attitudes or behaviors (SCOFF < 2) Ref (R*): Response of “No” on the SCOFF N: Bivariate analysis indicates significant difference compared to Non-users Rx: Bivariate analysis indicates significant difference compared to Rx Only

Table 3: Logistic regression models of non-medical use and medical use of prescription stimulants among a national sample of college students (n=87,296)* Non-medical use Medical Use AOR 95% CI AOR 95% CI (1.23,1.49)

0.94

(0.85, 1.04)

1.46

(1.31, 1.62)

1.01

(0.89, 1.15)

1.22

(1.10, 1.34)

1.02

(0.92, 1.12)

1.39

(1.22, 1.59)

1.25

(1.09, 1.44)

1.22

(1.09, 1.37)

0.90

(0.80, 1.02)

1.20

(1.07, 1.34)

2.35 2.07 1.38 1.39 1.22

(1.54, 3.59) (1.66, 2.58) (1.17, 1.63) (1.22, 1.57) (1.10, 1.37)

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2+ Disordered Eating Attitudes/Behaviors (SCOFF  2) Do you ever make yourself sick because you feel uncomfortably full? Do you worry that you have lost control over how much you eat? Have you recently lost more than 15 pounds in a 3-month period? Do you believe yourself to be fat when others say you are too thin? Would you say that food dominates your life? # ED Symptoms (SCOFF) 5 vs. 0 4 vs. 0 3 vs. 0 2 vs. 0 1 vs. 0

2.08 1.00 0.96 0.95 1.10

(0.84, 1.07)

(1.25, 3.45) (0.76, 1.31) (0.82, 1.14) (0.83, 1.08) (0.99, 1.22)

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*Separate logistic regression models using non-medical and medical use of prescription stimulants as the outcome variable and various ED characteristics as separate predictor variables. Models are adjusted for various demographic (gender, race, age, housing, financial status, GPA, fraternity/sorority membership, and BMI) and psychiatric/behavioral characteristics (tobacco use, marijuana use, lifetime use of therapy/counseling, past year visit to medical provider, current symptoms of anxiety or depression, and lifetime diagnosis of depression, anxiety, attention/learning or substance use disorders). Ref=Non-user