Psych Intro

ORIGINAL PAPER

The Consumption of Energy Drinks Among a Sample of College Students and College Student Athletes

Andrew R. Gallucci1 • Ryan J. Martin2 • Grant B. Morgan3

Published online: 9 August 2015

� Springer Science+Business Media New York 2015

Abstract To assess energy drink (ED) consumption,

potential ED correlates, and ED-related motivations among

a sample of college students to determine differences based

on athlete status (student athlete vs. non-athlete). Six

hundred and ninety-two college students completed sur-

veys at a large private university in the United States.

Participants completed a paper based questionnaire

assessing ED and ED-related variables. Over thirty-six

percent (197 non-athletes, 58 student athletes) of partici-

pants reported ED consumption in the preceding 30 days.

Multivariately, there was no difference in ED consumption

based on athlete status. Heavy episodic drinking and pre-

scription stimulant misuse were both correlated with

increased ED consumption. ED motivations differed based

on the frequency of ED consumption. ED use was common

among student athletes and non-athletes in our sample. It is

important to be aware of the correlation between heavy

episodic drinking, prescription stimulant misuse, and ED

consumption among college student populations because of

the adverse consequences associated with these behaviors.

Keywords Energy drink � College students � Athletes

Introduction

Energy drinks (ED) are a type of dietary supplement that

claim to enhance athletic performance and assist with

weight loss [1]. However, research suggests that the

majority of the benefits from the consumption of EDs are

derived from their caffeine content [1]. Caffeine is a central

nervous stimulant that has been shown to increase motor

activity, reduce the sensation of fatigue, and increase

alertness [1, 2]. However, the use of energy drinks and

associated caffeine content for sports performance has been

linked to unintended consequences such as cardiac events,

anxiety, seizures, tremors, vomiting, and death [3–5].

Because caffeine has the potential to enhance sports

performance and cause adverse health reaction, its con-

sumption among student-athletes is monitored by the

National Collegiate Athletic Association (NCAA) [6–8].

Student athletes testing positive for excessive caffeine

concentrations could receive punishments ranging from

disqualification from a game/event to a loss of athletic

eligibility for multiple offenses [9]. Despite the conse-

quences, the potential ability of EDs to increase mental

acuity and motor activity makes their use attractive to both

college student athletes and non-athletes.

Energy Drink Use Among College Students

Studies estimating past year ED use among college student

populations have found rates that vary from 22.6 to 65.6 %

[4, 10, 11]. Some research among college students has

found that males are more likely to consume EDs [11–13];

however, another study found higher rates of use among

females [4]. Similarly, the association between ED use and

race is conflicted. Some studies indicate that Caucasian

students are more likely to use EDs [13, 14], while another

& Andrew R. Gallucci [email protected]

1 Department of Health, Human Performance and Recreation,

Baylor University, One Bear Place #97313, Waco, TX 76798,

USA

2 Department of Health Education and Promotion, East

Carolina University, 2206 Carol Belk Building, Greenville,

NC 27858, USA

3 Department of Educational Psychology, Baylor University,

Waco, TX 76798, USA

123

J Community Health (2016) 41:109–118

DOI 10.1007/s10900-015-0075-4

failed to identify an association [11]. Involvement with

Greek organizations (i.e. fraternities, sororities) has been

associated with the use of EDs among college students [11,

14]. In addition, research has found that ED consumption is

correlated with other adverse health behaviors including

tobacco use [11, 13], frequent heavy episodic drinking [14,

15] and the misuse of prescription stimulants (MPS) [11,

16].

With regard to motivations associated with ED con-

sumption, college students have reported a need to com-

plete a major assignment, feel less tired, and decrease

fatigue [4, 12, 17]. Additionally, students have reported

being motivated to use EDs to drive long distances, mix

with alcohol, increase physical performance, and to

become more involved with friends [4, 12, 17]. Although

motivations for ED consumption have been explored

among the general undergraduate student population, a

comparison of motivations between student athletes and

student non-athletes has not been reported in the peer-re-

viewed literature.

Associations between health behaviors and college stu-

dent athletic status (student athlete vs. non-athlete) vary.

Studies have found higher rates of alcohol use [18, 19] and

performance enhancing drug use [20–22] among college

student athletes compared to non-athletes. Conversely,

athletic participation has been identified as a protective

factor against the use of illicit drugs [18, 23] and tobacco

use [24, 25] in the college student population.

There are few examinations of ED consumption (in-

cluding the prevalence and motivations) among college

student athletes. The NCAA reported that 44.5 % (of

20,474) collegiate athletes indicated that they consumed

EDs while in college [6]. In an examination of the use of

prescription drugs and EDs for performance enhancement,

Hoyte et al. [21] found that 89.4 % of athletes (i.e., col-

legiate, semiprofessional, club) in their sample had used

an ED in the past year to improve athletic performance.

However, the study failed to examine other motivations

that may have been associated with the consumption of

EDs among those athletes. Woolsey et al. [26] examined

ED use and ED combined with alcohol use among a

sample of student athletes. Of the 401 athletes in the

sample, 194 (48.4 %) had used EDs in the past year and

150 (37.4 %) had combined EDs with alcohol. However,

the sample of athletes was not compared to student non-

athletes to examine potential differences. Identifying if

differences in ED consumption exist based on athletic

status is important because student athletes are subject to

penalties (e.g. NCAA penalties) and benefits (e.g.

enhanced sports performance) for excessive consumption

in ways that are distinctly different from their non-athlete

counterparts.

Purpose

There were two purposes of this study: (1) to examine

whether there were differences in ED consumption and

ED-related motivations based on athletic status (student

athlete vs. non-athlete); and (2) to identify other potential

ED correlates (i.e. gender, race, year in school, Greek

affiliation, past-year MPS, current tobacco use, heavy

episodic drinking) in a sample of college students.

Methods

Procedure

This study received Institutional Review Board approval

and the data was collected from a sample of college student

athletes and non-athletes at a large, private Southwestern

university in spring 2014. To obtain class time to recruit

participants, we first identified athletic trainers associated

with the university and course instructors responsible for

teaching general education courses required to fulfill the

universities’ degree requirements. This review identified 32

instructors responsible teaching these general education

courses and 17 athletic trainers working in the athletic

department. We then sent emails to these instructors and

athletic trainers to request time during class or practice to

recruit participants to complete a paper-and-pencil survey.

This email explained the purpose of the study and stated

that the instructor or athletic trainer was not obligated to

donate their time for this study. From the instructors that

we contacted, 25 allowed us to collect data in a total of 34

classes. Fifteen of the 17 athletic trainers donated time for

participants to complete the survey.

Prior to distributing the surveys to potential participants,

we explained the study’s purpose, selection criteria (i.e.,

18–25 years old; undergraduate status) and indicated that

students would not be asked to provide any identifiable

information linking them to the responses provided. It was

also explained that participants could discontinue the sur-

vey at any time and were free to skip any question in the

survey. To reduce coercion and increase the likelihood of

honest responses, varsity athletes completed the survey

away from coaches and instructors were asked to leave the

room while surveys were being completed. Students par-

ticipating in the study were issued a $5 gift certificate.

A review of class roles revealed that 77.3 % of students

enrolled in the courses used for recruitment were in

attendance on the day that data was collected. Ten student

athletes declined to participate in the study, six completed a

survey in class, and one did not complete a survey in class

because they had previously participated at practice. Also,

110 J Community Health (2016) 41:109–118

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three non-athletes declined to participate and six had

already participated in another class and did not complete

the survey a subsequent time. We received a total of 490

(99.4 %) surveys from the 493 college student non-athletes

that were recruited for participation. A total of 207

(95.4 %) completed surveys were received from the 217

student-athletes that were recruited for participation. Of

note, to complete the analyses needed for this study (i.e.,

examining differences based on athletic status), we pur-

posefully oversampled student athletes. Overall, 697

(98.1 %) of the 710 students that were recruited completed

the survey.

An initial review of the 697 completed surveys identi-

fied and removed two subjects for failing to meet the study

selection criteria (i.e., older than 25). Three students were

removed because they did not respond to the question

assessing ED use. Removing these participants resulted in a

sample of 692 to be used for analyses (205 student athletes

and 487 student non-athletes).

Measures

Survey Development

Questions examining ED consumption and associated

behaviors were adapted and modified from items included

in previous surveys [4, 10, 12, 16, 27, 28]. To increase the

face validity and readability, an, initial version of the

survey was reviewed by content and survey design experts.

This review identified several minor errors (e.g., formatting

issues, typographical errors) that were subsequently

revised. Then the instrument was pilot tested among a

small sample of college students. This process identified

potential confusion with the wording of some questions and

confirmed a student’s ability to complete the survey in the

desired time frame. Revisions were made based on the

feedback received and the final version of the survey was

submitted for IRB approval.

Survey Overview

We assessed ED use, ED-related motivations, and potential

correlates (i.e. athletic status, gender, race, year in school,

Greek affiliation, past-year MPS, current tobacco use,

heavy episodic drinking) of increased ED consumption

among college students using a 68-question survey. The

paper-and-pencil survey was distributed during class time

or practice time at the institution where the research was

conducted. The survey included questions assessing a

plethora of health-related behaviors (e.g., sleep, gambling).

The portions of the survey that are relevant to the present

study are discussed below.

ED Use

Participants were asked to report the number of occasions

they had consumed an ED or ED shot in the previous

30 days. For purposes of this study, an ‘‘occasion’’ was

defined as the consumption of one energy drink or shot at

one point in time. This question was modeled from a

question assessing MPS used by McCabe and Teter [29]

(On how many occasions during the previous 30 days have

you consumed an energy drink or energy shot?). Respon-

dents were provided examples of common energy drink

brands (e.g., Red Bull, Monster, Venom, Amp, NOS) as a

point of reference. Items on the response scale were: (0)

none, (1) 1–2 occasions, (2) 3-5 occasions, (3) 6–9 occa-

sions, (4) 10–19 occasions, (5) 20–39 occasions, and (6) 40

or more occasions.

Demographics

Participants responded to questions that assessed their age,

gender, year in school, race, and Greek status (i.e., member

of a fraternity or sorority).

Athlete Status

We assessed whether respondents participated in organized

college athletics during the previous 12 months. This was a

‘select all that apply’ question and response options

included varsity (division I) sports, club sports, intramural

sports, recreational sports, and no sports participation.

Respondents reporting participation in varsity (division I)

sports were considered students athletes and all other par-

ticipants were considered student non-athletes (0 = student

non-athlete; 1 = student athlete).

The Misuse of Prescription Stimulants (MPS)

We assessed MPS via one question: On how many occa-

sions in the previous 12 months have you used someone

else’s prescription stimulant or your own medication in

excess or for a purpose other than what the medication was

prescribed for? As part of this question, we provided the

following examples for common stimulant brand name

medications: Vyvanse, Adderall, Ritalin, Concerta, Dexe-

drine, and Provigil. Response options were identical to

those used in a previous study [29] and included: none, 1–2

occasions, 3–5 occasions, 6–9 occasions, 10–19 occasions,

20–39 occasions, and 40 or more occasions. To better

group the responses provided, we conducted a cluster

analysis (k-means procedure) to determine logical seg-

ments in the level of MPS reported. Results indicated that

this variable should be dichotomized into two groups:

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Those indicating no MPS use and those indicating any

MPS use (0 = no use; 1 = MPS).

Tobacco Use

We assessed the number of times in the previous 30 days

that participants had used a tobacco product, including the

use of cigars, cigarettes, e-cigarettes, and smokeless

tobacco. Response options included: Never, 1–2, 3–5, 6–9,

10–19, 20–29 days, and every day. Because of the limited

number of students reporting greater than 19 days of

tobacco use, we again conducted a cluster analysis (k-

means procedure) as we did for MPS. This procedure

indicated three separate cluster groups: No use, low use

(using between 1 and 5 days), and high use (using for 6 or

more days).

Heavy Episodic Drinking

We assessed heavy episodic drinking frequency by having

participants estimate the number of times they had five or

more standard drinks for males or four or more standard

drinks for females on one occasion. The question included

a visual display of common standard drinks. Response

options included: Never, less than monthly, monthly,

weekly, and daily or almost daily. Respondents who

reported heavy drinking never or less than monthly were

classified as a none/infrequent heavy episodic drinker and

those engaging in behavior at least once a month were

classified as frequent heavy episodic drinkers (0 = none/

infrequent heavy episodes; 1 = frequent heavy episodes).

Motivations for ED Consumption

ED users were asked to indicate all of the motivations for

consuming an ED in the previous 30 days. Because recent

findings [10, 16] have identified a relationship between ED

consumption and MPS, a list of possible motivations were

compiled based on research examining MPS-related moti-

vations [27, 28] and ED-related motivations [4, 12].

Response options included: (1) To concentrate better in

class, (2) to concentrate better while studying, (3) to study

longer/complete major assignments, (4) feel lest restless in

class/while studying, (5) to improve mental focus/alertness,

need for more energy, (6) to drive for a long period of time,

(7) prolong the effects alcohol or other substances, (8) lose

weight, (9) to exercise longer, (10) to improve my athletic

performance, (11) because I am addicted, and (12) not

getting enough sleep. Respondents were also provided an

open text box in which they could provide ‘‘other’’ moti-

vations for the behavior.

A review of the data found that multiple levels of con-

sumption (i.e., 10–19 occasions, 20–39 occasions, 40 or

more occasions) did not contain enough cases to statisti-

cally evaluate motivations between student athletes and

non-athletes. To facilitate the statistical analyses of the

motivations associated with varying levels of ED con-

sumption based on athletic participation, we conducted a

cluster analysis (k-means procedure) in the same manner

described with tobacco use and MPS. Results suggested

clustering ED consumption into two levels: Low use (one

to nine occasions of ED consumption), and high use (10 or

more occasions of ED consumption).

Data Analysis

We entered the data from 692 completed surveys into SPSS

20.0. First, we calculated descriptive statistics for ED

consumption and all of our independent variables of

interest: Athlete status, gender, race, year in school, Greek

affiliation, past-30 day ED, past-year MPS, past-30 day

tobacco use, heavy episodic drinking. Next, we examined

each independent variable with ED consumption bivari-

ately via Cramer’s V tests. Then, we examined the Akaike

information criteria (AIC) and Bayesian information cri-

teria (BIC) for both Poisson and negative binomial (nb)

distributions to determine which type of multiple regres-

sion analysis was most appropriate to examine the rela-

tionship between the significant independent variables and

increased ED consumption (i.e., none, 1–2 occasions, 3–5

occasions, 6–9 occasions, 10–19 occasions, 20–39 occa-

sions, 40? occasions). To evaluate differences in ED-re-

lated motivations based on athlete status, we grouped

participants into a low ED use (one to nine occasions of ED

consumption) or a high ED use (ten or more occasions of

ED consumption) category. Then, we used Chi square

analyses to determine differences in ED motivations

between student athletes and non-athletes in each group.

Results

The final sample was comprised of 692 undergraduate

college students between the ages of 18 and 25 (participant

demographics and behaviors are listed in Table 1). Our

sample was comprised of 397 females (57.4 %), 205 stu-

dent athletes (29.7 %), and had a mean age of 20.4 years

(SD = 1.42). The majority of the sample was Caucasian

(64.6 %) and 172 (24.9 %) were affiliated with a Greek

organization. The sample demographics used were similar

to the entire student body at the university this research was

conducted with regards to gender, year in school, and

Greek affiliation. With regard to race, the sample had an

overrepresentation of African-American students (12.2 vs.

7.3 %), and an underrepresentation of Hispanic students

(8.7 vs. 13.1 %). Because student athletes were purposely

112 J Community Health (2016) 41:109–118

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oversampled, they were overrepresented (29.7 % of the

sample).

ED Consumption

A total of 252 (36.4 %) participants indicated consuming at

least one ED in the preceding 30 days. Of those, 122 (90

non-athletes, 32 athletes) consumed an ED on 1–2 occa-

sions, 61 (51 non-athletes, 10 athletes) on 3–5 occasions,

23 (20 non-athletes, 3 athletes) on 6–9 occasions, 28 (21

non-athletes, 7 athletes) on 10–19 occasions, 14 (8 non-

athletes, 6 athletes) on 20–39 occasions, and 4 (4 non-

athletes, 0 athletes) on 40 or more occasions.

Bivariate Analyses

Independent Cramer’s V analyses found that non-athletes

had significantly higher rates of ED consumption

(U = 0.148, p \ .05). In addition, these analyses found significant associations existed between increased ED use

Table 1 Demographic characteristics of the sample by

athletic status

Non-athletes Student-athletes Total

n = 487 % n = 205 % n = 692 %

Gender

Male 213 43.8 82 40.0 295 42.6

Female 274 56.2 123 60.0 397 57.4

Race

Caucasian 306 62.9 140 68.6 446 64.6

African-American 41 8.5 43 21.1 84 12.2

Hispanic 56 11.5 4 2.0 60 8.7

Asian 53 10.9 3 1.5 56 8.1

Multiracial 27 5.6 10 4.9 37 5.4

Other 3 0.6 4 2.0 7 1.0

Year of undergraduate education

1st year 76 15.6 51 25.0 127 18.4

2nd year 113 23.2 55 27.0 168 24.3

3rd year 129 26.5 49 24.0 178 25.8

4th year 147 30.2 39 19.1 186 26.9

5th year 22 4.5 10 4.9 32 4.6

Greek affiliation

Greek 150 30.8 22 10.7 172 24.9

Non-Greek 337 69.2 183 89.3 520 75.1

Energy drink use frequency (categorical)

None 292 60.1 147 71.7 439 63.5

1–2 Occasions 90 18.5 32 15.6 122 17.7

3–5 Occasions 51 10.5 10 4.9 61 8.8

6–9 Occasions 20 4.1 3 1.5 23 3.3

10-19 Occasions 21 4.3 7 3.4 28 4.1

20–39 Occasions 8 1.6 6 2.9 14 2.0

40? Occasions 4 0.8 0 0.0 4 0.6

Current tobacco use

None 390 80.4 185 90.2 575 83.3

Low use (1–5 days) 68 14.0 14 6.8 82 11.9

High use (6\ days) 27 5.6 6 3.0 33 4.8 Heavy alcohol consumption frequency

Less than monthly 373 76.7 173 85.6 546 79.4

Monthly or more 113 23.3 29 14.4 142 20.6

Past-year prescription stimulant misuse

No 403 82.8 185 93.0 588 86.2

Yes 80 16.4 14 7.0 94 13.8

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and the following independent variables: male gender

(U = 0.134, p \ .05), Greek affiliation (U = 0.163, p \ .01), current tobacco use (U = 0.163, p \ .01), fre- quent heavy episodic drinking (U = 0.245, p \ .001), and past-year MPS (U = .203, p \ .001). Bivariate analyses did not find significant associations between increased ED

consumption and the following variables: race (U = 0.110, p = .100) and the student’s year in school (U = 0.106, p = .147).

Multivariate Analyses

A review of the AIC and BIC values indicated that the

negative binomial distribution provided the best multi-

variate analysis because the predicted values were much

closer to actual reported frequencies of ED consumption.

Specifically, the AIC and BIC values for the Poisson model

were 1761.4 and 1797.6, respectively. The AIC and BIC

values for the negative binomial model were 1587.0 and

1622.8, respectively. Relatively lower values of AIC and

BIC indicate better model fit. The negative binomial model

was the better approximating model according to AIC and

BIC also; consequently, we chose to interpret the negative

binomial model.

Based on these results, we conducted a negative bino-

mial regression analysis with ED consumption (0 = None,

1 = 1–2 occasions, 2 = 3–5 occasions, 3 = 6–9 occa-

sions, 4 = 10–19 occasions, 5 = 20–39 occasions, 6 = 40

or more occasions) as the outcome variable. The predictor

variables included all those found to be significant in the

preceding bivariate analyses (i.e., athletic status, gender,

Greek affiliation, frequent heavy episodic drinking, past-

year MPS, current tobacco use). In the model (See

Table 2), increased ED consumption was positively asso-

ciated with frequent heavy episodic drinking (IRR = 1.65,

CI = 1.18–2.32, p = .003) and MPS (IRR = 1.62,

CI = 1.12–2.34, p = .01). The model indicated that ED

consumption was lower for athletes than non-athletes

(IRR = .75), but that difference was not statistically sig-

nificant. However, based on the confidence interval for

athlete status, we can conclude with 95 % confidence that

rate of ED use among athletes is at most the same as non-

athletes (i.e., CIupper = 1.03).

Motivations for Energy Drink Consumption

We examined ED-related motivations between two groups

of ED users: Low use (one to nine occasions of ED con-

sumption), and high use (10 or more occasions of ED

consumption). Of those classified in the low use group, 182

participants (141 non-athletes; 42 athletes) identified a total

of 486 motivations for ED consumption (see Table 3).

Low Use

Non-athletes in the low use group most commonly cited the

need for more energy (64.5 %), and a desire to study longer

(47.5 %) as reasons for ED consumption. Of note, nine

students (6.4 %) reported the desire to prolong the effects

of alcohol or other substances while seven reported ‘‘other’’

as a motivation. However, only one student non-athlete

provided an alternative motivation, which was ‘‘the taste’’.

Low ED use student athletes most commonly identified a

need for more energy (61.5 %), and in order to drive for

Table 2 A negative binomial regression analysis to predict

increased energy drink

consumption among a sample of

college students (N = 692)

B S.E. Z IRR 95 % C.I.

Gender

Male 0.231 0.144 1.608 1.260 0.950 1.67

Greek affiliation

Yes -0.003 0.158 -0.019 1.000 0.730 1.360

Athletic participation

Varsity athlete -0.283 0.159 -1.782 0.750 0.550 1.030

Heavy episodic drinking**

Frequent heavy episodes 0.503 0.159 2.921 1.650 1.180 2.320

Past-year stimulant misuse*

1 or More occasions 0.481 0.189 2.538 1.620 1.12 2.340

Current tobacco use

Low use 0.160 0.208 0.770 1.174 0.780 1.765

High use 0.064 0.309 0.206 1.066 0.581 1.955

Akaike information criteria = 1587.0; Bayesian information criteria = 1622.8

IRR incident rate ratio

* p \ .01; ** p \ .001

114 J Community Health (2016) 41:109–118

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long periods of time (29.3 %). No low ED use student

athletes reported a desire to lose weight or to prolong the

effects of alcohol or other substances.

A series of Chi square analyses were completed to

compare motivations for ED consumption between low use

student athletes and low use student non-athletes. Results

indicated that a greater proportion of low use student non-

athletes identified a desire to concentrate better while

studying (v2 = 10.8, p \ .01), to study longer/complete major assignments (v2 = 10.3, p \ .01), improve mental focus/awareness (v2 = 4.6, p \ .05), and a need for more energy (v2 = 4.4, p \ .05) as a motivation for consump- tion. In contrast, low use student athletes were significantly

more likely to report ‘‘other’’ (v2 = 5.9, p \ .05) as a motivation.

High Use

Sixty-nine participants (53 non-athletes; 16 athletes) in the

high ED use group reported a total of 315 motivations.

Student non-athletes most commonly cited a lack of sleep

(71.7 %), and the need for more energy (66.0 %). Student

athletes most commonly identified a need for more energy

(62.5 %), and improving mental focus (50.0 %). Seven

(43.8 %) student athletes also reported a desire to improve

athletic performance. No high use student athletes reported

a desire to prolong the effects of alcohol or other sub-

stances. Chi square analyses revealed that a greater pro-

portion of high ED use student non-athletes identified a

lack of sleep (v2 = 4.2, p \ .05) and a desire to drive for a long period of time (v2 = 6.3, p \ .05) as a motivation for the behavior. A greater proportion of high ED use student

athletes reported a desire to improve athletic performance

(v2 = 5.9, p \ .05) as a motivation.

Discussion

The role of college sports participation has a varying

association with substance use. In the use of alcohol and

performance enhancing drugs, sports participation is asso-

ciated with increased use [18, 19, 23, 25]. Conversely,

sports participation is associated with decreased use of

tobacco products and other illicit drugs [18, 23]. This

investigation extends this work by examining the differ-

ences in ED consumption based on sports participation.

Over a third (36.5 %) of the study sample had consumed

at least one ED in the previous 30 days. The rate of ED

consumption among the sample was consistent with other

college student samples in the literature [13, 15], but we

did not detect a difference in ED consumption based on

athletic status when controlling for other variables. It is

Table 3 Comparison of reported motivations for energy drink consumption by frequency of use

Motivations Low use High use

Non-athlete

n = 141 (%) a

Varsity athlete

42 (%) b

Non-athlete

n = 53 (%) c

Varsity athlete

n = 16 (%) d

I needed more energy 91 (64.5) 19 (46.3) 35 (66.0) 10 (62.5)

In order to study longer/complete major assignments 67 (47.5) 8 (19.5) 34 (64.2) 6 (37.5)

I did not get enough sleep 49 (34.8) 8 (19.5) 38 (71.7) 7 (43.8)

To concentrate better while studying 56 (39.7) 5 (12.2) 28 (52.8) 7 (43.8)

To improve mental focus/alertness 40 (28.4) 5 (12.2) 26 (49.1) 8 (50.0)

To concentrate better in class 20 (14.2) 3 (7.3) 18 (34.0) 7 (43.8)

To feel less restless in class/while studying 23 (16.3) 2 (4.9) 14 (26.4) 5 (31.2)

To drive for a long period of time 35. (24.8) 12 (29.3) 16 (30.2) *

To improve my athletic performance 6 (4.3) 4 (9.8) 8 (15.1) 7 (43.8)

To exercise longer 7 (5.0) 2 (4.9) 10 (18.9) 5 (31.2)

To feel good or get high 1 (0.7) 1 (2.4) 7 (13.2) *

To prolong the effects of alcohol or other substances 9 (6.4) * 6 (11.3) *

Other 4 (2.8) 5 (12.7) 3 (5.7) 1 (6.2)

To lose weight 1 (0.7) * 4 (7.5) 2 (12.5)

Because I am addicted 2 (1.4) 1 (2.4) 3 (5.7) 1 (6.2)

* Not identified as a motivation a 411 Motivations were reported

b 75 Motivations were reported

c 250 Motivations were reported

d 65 Motivations were reported

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possible that there was no difference in ED use between

these groups because beverage companies have purpose-

fully marketed these drinks to active college aged popu-

lations [8]. In addition, both athletes and non-athletes who

consume these beverages might share common personality

traits, such as competitiveness [8]. For instance, Woolsey

[26] stated that ED consumers are more likely to have a

‘‘jock identity’’. The lack of significance based on sport

participation could also be an artifact of a low prevalence

of heavy episodic drinking among athletes in the sample

(14.4 % among athletes, 23.3 % among non-athletes).

Studies have linked ED consumption with heavy episodic

drinking among student non-athletes [19] and student ath-

letes [26]. Since alcohol consumption among student ath-

letes typically exceeds that of student non-athletes [18, 19],

it is possible that a sample of athletes consuming more

alcohol might also display higher rates of ED consumption.

Results also supported existing research in that frequent

heavy episodic drinking [13–15] and MPS [11, 16] were

significantly associated with increased ED consumption. It

is plausible that these associations along with the reported

motivations (e.g. study longer, not enough sleep) in the

sample suggest that students are using stimulants to com-

pensate for lifestyles (e.g. partying frequently) that are not

congruous with high academic achievement. In fact,

examinations of these behaviors found that students use

EDs and prescription stimulants in an effort to make up for

infrequent class attendance and a lack of sleep [4, 11]. ED

consumption has also been linked to concurrent use of

other substances (e.g. marijuana) [13, 17]. Therefore, these

relationships might exist among students struggling with

substance use and dependence issues. Contrary to the lit-

erature [11, 14], we did not identify a significant associa-

tion between ED consumption and current tobacco use

when controlling for other variables.

We also did not identify significant differences in ED

use based on race. This finding is consistent with some ED-

related research [11] but not with other research that found

that Caucasians were more likely to consume EDs [13, 14].

We also did not identify differences in ED consumption

based on Greek affiliation, which is not consistent with

previous findings [11, 14]. Finally, we did not find a sig-

nificant difference based on gender. Previous studies [11–

13] have found that males were more likely to consume

EDs while another [4] found that females were more likely

to consume EDs. It is possible that the consumption of EDs

is becoming more popular among all college students and

differences in consumption patterns based on gender and

race are becoming less pronounced. It is also possible that

the lack of significance is a byproduct of a sample with a

disproportionately high number of females (57.3 %) and

Caucasians (64.6 %).

Concerning ED-related motivations, consistent with

other investigations [4, 12], the desire for more energy and

a lack of sleep were the most commonly reported moti-

vations for ED consumption among all students. However,

analyses identified differences in the motivations between

student athletes and student non-athletes in low use (1-9

occasions) and high use (10 or more occasions) ED groups.

Low ED use student non-athletes were more likely to

report a need for more energy and motivations related to

academics (e.g. concentrate better while studying to study

longer/complete major assignments, improve mental focus/

awareness). Of note, low use student athlete motivations

were more dispersive. No single motivation was identified

by at least half of this group. Reasons as to why low ED

use student-athletes might not have a prevailing motivation

should be explored further.

Among high ED use participants, a greater proportion of

non-athletes identified a lack of sleep and a desire to drive

for a long period of time while a higher proportion of

student athletes reported a desire to improve athletic per-

formance. Almost as many student non-athletes among the

high ED use group reported a lack of sleep as those in the

low use group. Thus, it is possible that lifestyle choices

(e.g. staying up late, partying) can lead to increased con-

sumption. Finding that student athletes are using EDs to

improve athletic performance is consistent with a previous

study [21]. Hoyte et al. [21] also suggested that those using

EDs to improve performance consume EDs more fre-

quently. This is of concern because the consumption of

EDs to enhance athletic performance has been known to

cause insomnia, nausea, tachycardia and seizures [5].

Finally, despite the findings of others [13, 15] and our

findings that link increased ED consumption with heavy

episodic drinking, students in both high and low use groups

did not commonly report a desire to prolong the effects of

alcohol or other substances. In fact, no student athlete

reported this as a motivation.

Limitations

A strength of our study is that it is compares ED use and

ED-related motivations between student athletes and stu-

dent non-athletes, and differences between these groups

have not been examined in the peer reviewed literature.

However, there are important methodological limitations to

note when interpreting the results. Participants of this study

only included a convenience sample of college students at

one large private university in the US. Therefore, this

sample might not be representative of other populations of

college students or college athletes at other institutions

throughout the country.

116 J Community Health (2016) 41:109–118

123

The study is also limited because students self-reported

their behavior. Students may have underreported behaviors

and provided more socially acceptable responses to some

survey items. The cross-sectional design of the study also

limited the inferences that can be drawn, as this study

design does not allow for us to establish causal relation-

ships between ED use and ED correlates. In addition,

participants did not indicate the sport they participated in.

Based on the limited number of athletes on some teams,

having participants identify their sport would have made

individual identification possible. As a result, we were not

able to examine differences based on participation in dif-

ferent sport-types. Finally, we only asked participants to

report the consumption of an ED. The questions presented

to students did not account for the different types of EDs,

varying levels of caffeine in each ED, or the consumption

of other caffeinated beverages (e.g., coffee, soda).

Conclusion

EDs are popular among college students as they provide an

avenue to increase alertness, decrease fatigue, and increase

motor activity. The consumption of EDs was prevalent in

our sample; however, we did not find significant differ-

ences in consumption based on athletic participation.

Concerning motivations for ED consumption, both student

athletes and student non-athletes most commonly reported

a need for energy as a motivation for the behavior. Com-

pared to high use student non-athletes, a greater proportion

of high use student athletes reported the desire to increase

athletic performance as a motivation for ED consumption.

As a result, college health professionals attempting to

prevent increased ED consumption among student athletes

might consider highlighting the adverse health risks asso-

ciated with high levels of stimulants and physical activity.

Future studies should consider exploring potential changes

of ED consumption and related motivations over time. For

instance, it is possible that ED consumption among student

athletes can change based on the time of year (i.e. offsea-

son vs. in season). Finally, examinations of ED consump-

tion among specific athletes are needed. It is plausible that

athletes participating in sports requiring heightened cog-

nitive abilities (e.g. baseball, softball, sprinting) display

higher rates of consumption than other athletes.

References

1. Ballard, S. L., Wellborn-Kim, J. J., & Clauson, K. A. (2010).

Effects of commercial energy drink consumption on athletic

performance and body composition. Physician and Sports-

medicine, 38(1), 107–117.

2. Astorino, T. A., & Roberson, D. W. (2010). Efficacy of acute

caffeine ingestion for short-term high-intensity exercise perfor-

mance: A systematic review. Journal of Strength and Condi-

tioning Research, 24(1), 257–265. doi:10.1519/JSC.0b013e318

1c1f88a.

3. Iyadurai, S. J. P., & Chung, S. S. (2007). New-onset seizures in

adults: Possible association with consumption of popular energy

drinks. Epilepsy & Behavior, 10(3), 504–508.

4. Malinauskas, B. M., Aeby, V. G., Overton, R. F., Carpenter-

Aeby, T., & Barber-Heidal, K. (2007). A survey of energy drink

consumption patterns among college students. Nutrition Journal,

6(1), 35–41.

5. Heneghan, C., Gill, P., O’Neill, B., Lasserson, D., Thake, M., &

Thompson, M. (2012). Mythbusting sports and exercise products.

BMJ (Clinical Research Ed.), 345, e4848. doi:10.1136/bmj.

e4848.

6. Bracken, N. M. (2012). National study of substance use trends

among NCAA college student-athletes. Indianapolis, IN: National

Collegiate Athletic Association.

7. Deventer, K., Roels, K., Delbeke, F., & Van Eenoo, P. (2011).

Prevalence of legal and illegal stimulating agents in sports. An-

alytical and Bioanalytical Chemistry, 401(2), 421–432.

8. Rosenbloom, C. (2014). Energy drinks, caffeine, and athletes.

Nutrition Today, 49(2), 49–54.

9. National Collegiate Athletic Association. (2011). NCAA banned

drug list. http://www.ncaa.org/wps/wcm/connect/public/NCAA/

Health?and?Safety/Drug?Testing/Resources/.

10. Arria, A. M., Caldeira, K. M., Kasperski, S. J., Vincent, K. B.,

Griffiths, R. R., & O’Grady, K. E. (2011). Energy drink con-

sumption and increased risk for alcohol dependence. Alcoholism,

Clinical and Experimental Research, 35(2), 365–375.

11. Arria, A. M., Caldeira, K. M., Kasperski, S. J., O’Grady, K. E.,

Vincent, K. B., Griffiths, R. R., & Wish, E. D. (2010). Increased

alcohol consumption, nonmedical prescription drug use, and

illicit drug use are associated with energy drink consumption

among college students. Journal of Addiction Medicine, 4(2),

74–80. doi:10.1097/ADM.0b013e3181aa8dd4.

12. Bulut, B., Beyhun, N. E., Topbaş, M., & Çan, G. (2014). Energy

drink use in university students and associated factors. Journal of

Community Health, 39(5), 1004–1011.

13. Miller, K. E. (2008). Energy drinks, race, and problem behaviors

among college students. Journal of Adolescent Health, 43(5),

490–497.

14. O’Brien, M. C., McCoy, T. P., Rhodes, S. D., Wagoner, A., &

Wolfson, M. (2008). Caffeinated cocktails: Energy drink con-

sumption, high-risk drinking, and alcohol-related consequences

among college students. Academic Emergency Medicine, 15(5),

453–460.

15. Velazquez, C. E., Poulos, N. S., Latimer, L. A., & Pasch, K. E.

(2012). Associations between energy drink consumption and

alcohol use behaviors among college students. Drug and Alcohol

Dependence, 123(1), 167–172.

16. Woolsey, C. L., Barnes, L. B., Jacobson, B. H., Kensinger, W. S.,

Barry, A. E., Beck, N. C., & Evans, M. W., Jr. (2014). Frequency

of energy drink use predicts illicit prescription stimulant use.

Substance Abuse, 35(1), 96–103.

17. Spierer, D. K., Blanding, N., & Santella, A. (2014). Energy drink

consumption and associated health behaviors among university

students in an urban setting. Journal of Community Health, 39(1),

132–138. 18. Kwan, M., Bobko, S., Faulkner, G., Donnelly, P., & Cairney, J.

(2014). Sport participation and alcohol and illicit drug use in

adolescents and young adults: A systematic review of longitu-

dinal studies. Addictive Behaviors, 39(3), 497–506.

19. Martens, M. P., Dams-O’Connor, K., & Beck, N. C. (2006). A

systematic review of college student-athlete drinking: Prevalence

J Community Health (2016) 41:109–118 117

123

rates, sport-related factors, and interventions. Journal of Sub-

stance Abuse Treatment, 31(3), 305–316.

20. Ford, J. A. (2008). Nonmedical prescription drug use among

college students: A comparison between athletes and nonathletes.

Journal of American College Health, 57(2), 211–220.

21. Hoyte, C. O., Albert, D., & Heard, K. J. (2013). The use of energy

drinks, dietary supplements, and prescription medications by

United States college students to enhance athletic performance.

Journal of Community Health, 38(3), 575–580.

22. Yusko, D. A., Buckman, J. F., White, H. R., & Pandina, R. J.

(2008). Alcohol, tobacco, illicit drugs, and performance enhan-

cers: A comparison of use by college student athletes and

nonathletes. Journal of American College Health, 57(3),

281–290.

23. Ford, J. A. (2007). Substance use among college athletes: A

comparison based on sport/team affiliation. Journal of American

College Health, 55(6), 367–373.

24. Primack, B. A., Fertman, C. I., Rice, K. R., Adachi-Mejia, A. M.,

& Fine, M. J. (2010). Waterpipe and cigarette smoking among

college athletes in the United States. Journal of Adolescent

Health, 46(1), 45–51.

25. Lisha, N. E., & Sussman, S. (2010). Relationship of high school

and college sports participation with alcohol, tobacco, and illicit

drug use: A review. Addictive Behaviors, 35(5), 399–407.

26. Woolsey, C., Waigandt, A., & Beck, N. C. (2010). Athletes and

energy drinks: Reported risk-taking and consequences from the

combined use of alcohol and energy drinks. Journal of Applied

Sport Psychology, 22(1), 65–71.

27. Rabiner, D. L., Anastopoulos, A. D., Costello, E. J., Hoyle, R. H.,

McCabe, S. E., & Swartzwelder, H. S. (2009). Motives and

perceived consequences of nonmedical ADHD medication use by

college students: Are students treating themselves for attention

problems?. Journal of Attention Disorders, 13(3), 259–270.

28. Gallucci, A. R., Usdan, S. L., Martin, R. J., & Bolland, K. A.

(2014). Pill popping problems: The non-medical use of stimulant

medications in an undergraduate sample. Drugs: Education,

Prevention and Policy, 21(3), 181–188.

29. McCabe, S. E., & Teter, C. J. (2007). Drug use related problems

among nonmedical users of prescription stimulants: A web-based

survey of college students from a midwestern university. Drug

and Alcohol Dependence, 91(1), 69–76.

118 J Community Health (2016) 41:109–118

123

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