DIET QUALITY OF COLLEGIATE ATHLETESK elly W ebber, PhD, RD.docx

DIET QUALITY OF COLLEGIATE ATHLETES
K elly W ebber, PhD, RD, LD
University o f Kentucky
A manda Ireland Stoess, M .S ., RD, LD
H azel F orsythe, PhD,RD
Janet K urzynske, PhD, RD
C orresponding A uthors: Joy Ann Vaught, M S , R D , LD
Bailey Adams, M S, R D , L D
Abstract
Background/Objectives: Collegiate athletes generally appear
healthy
according to weight for height and body fat standards. Despite
the fact
that there are well known connections between
athletic performance and nutrition, little is known about the
diets o f
collegiate athletes. The objective o f this study was to determine
the
diet quality o f 138 collegiate athletes.

Subjects and Methods: Data were collected in the laboratory and
via survey. Anthropometries were assessed using a free standing
sta-
diometer and the BodPod® for body fat assessment. The Block
2005
Food Frequency Questionnaire© was used to assess diet. The
Healthy
Eating Index (HEI) 2005 was used to calculate diet quality
scores.
Results: The average BM1 was 23.2 + 2.3 kg/m2 and the
average body
fat was 17.8 % ± 6.5. The average HEI score was 51.2 + 8.8 out
o f
100 possible. Higher HEI scores were correlated with higher
body fat
percentages in this sample. Diets were adequate in calcium,
iron, and
vitamin C. Diets were inadequate in fiber, fruits and vegetables.
The
athletes had excessive intakes o f sodium and percent fat.
Conclusion: These findings demonstrate the need for and
potential
benefit o f nutrition education for collegiate athletes.
Keywords: Diet quality, collegiate athletes, Healthy Eating
Index 2005,
Block 2005 Food Frequency Questionnaire, Nutrition
Knowledge
251

252 / College Student Journal
Introduction
College athletes spend hours a day train-
ing for their sport. While physical achieve-
ments require training, more emphasis
may be needed on the diet quality of these
athletes. An athletes’ macronutrient and mi-
cronutrient intake have an influence on the
athletes physical output (Bonci, 2011). Nu-
tritional needs for athletes vary based on the
type of sport, hours spent training, season,
weather conditions, gender, and body mass
index. Nutritional needs also vary between
training days and competition days. Athletes
who consume a balanced diet tend to per-
form better than those who have poor diet
quality (Bonci, 2011).
Depending on the sport, physical appear-
ance is often important to the coach and the
athlete. Some athletes and coaches tend to
be more concerned about physical appear-
ance than nutritional intake. Collegiate ath-
letes may be pressured by their coaches and
strength staff to have a specific body size
because of performance expectations and
comparison with other competitors (Hoogen-
boom et al 2009). While body size can play an
important role in performance, the nutritional
status of an athlete also plays an important
role (Rodriguez, DiMarco, & Langley, 2009).
Athletes receive most of their nutrition
knowledge from the coaches, strength and

conditioning staff, and athletic training staff;
however, the accuracy of the information they
receive may be questionable (Torres-McGe-
hee et al 2012). These athletic professionals
may have some general knowledge of nutri-
tion; however, they are not licensed nutrition
professionals. Some colleges provide their
athletes with access to nutrition professionals
but many do not.
It is important for athletes to consume
adequate nutrients for both short-term per-
formance goals and long-term health. Many
athletes have health issues after their careers
are concluded because nutritional care of
their bodies’ was not a priority during their
athletic careers. Some of the health concerns
that female athletes face later in life are
high risks of arthritis, infertility and obesi-
ty (Manore 1999) while male athletes face
risks for orthopedic problems in addition to
arthritis and obesity. Athletes have also been
found to have more degenerative joint and
spine problems compared to a control popu-
lation (Kujala et al 2003).
The purpose of this study was to assess
the diet quality and body composition of
male and female collegiate athletes. Overall
diet quality, as well as food groups, macro
and micronutrients, and total calories were
assessed. Body composition was assessed
using body mass index and body fat percent-
age. The relationship between diet quality
and body composition was also assessed.

This is one of the few studies to assess colle-
giate athlete diet quality and its’ relationship
to body composition.
Subjects and Methods
Study Design
The study was a cross-sectional study
and data were collected between September
2010 and January 2012 on collegiate athletes
who volunteered. This study was based at a
university and approved by the university
Institutional Review Board (IRB). All ath-
letes signed consent forms for participation.
Data were taken from the first measurement
of an individual athlete when more than one
assessment was conducted during the study
period. The athletes’ height and weight were
measured and his/her body composition was
determined using air displacement plethys-
mography with the BodPod® (Fields, Hunter
and Goran, 2000). The athletes’ demographics
were also collected by a questionnaire at the
initial assessment. The athletes completed a
Block 2005 Food Frequency Questionnaire©
and a diet quality score was calculated using
the Healthy Eating Index 2005.
Diet Quality Of Collegiate Athletes / 253
Participants
Participants were drawn from college ath-
letes involved in various sports. A total o f 138

male and female athletes signed consent forms
and completed data at the time of data analy-
sis. All participants were 18+ years o f age and
were on the active roster for their team.
Food Frequency Questionnaire
The Block 2005 Food Frequency Ques-
tionnaire© was used to assess the athletes’
diets (Block et al., 1986). The question-
naire contains questions on over 100 foods
and includes portion size and frequency of
consumption. The validity (r = 0.59) and
reliability (r = 0.75) o f the Block FFQ was
confirmed among a sample o f Canadian
women (Boucher et al., 2006). The analysis
o f the questionnaires was conducted at Nutri-
tionQuest (Berkeley, CA, USA). The intake
o f macronutrients, micronutrients and food
group servings were obtained from the anal-
ysis. The intake from supplements was not
included in the dietary data. All analyses were
performed using SPSS, version 19.0 (SPSS
Inc., Chicago, IL, USA).
The Healthy Eating Index 2005
The Flealthy Eating Index (HEI) 2005
was used to determine diet quality. This
measure assesses diet quality that conforms
to the United States (U.S.) federal dietary
guidance and recommendations published in
the 2005 Dietary Guidelines for Americans.
The components on the HEI 2005 index and
the scoring standards are shown in Table
I (Guenther, Krebs-Smith, Reedy, Britten,

Juan, Lino, Carlson, Hiza & Basiotis, 2005).
The HEI is a valuable tool in that it meets the
least restrictive o f food-group recommenda-
tions for diets expressed on a per 1000 kcal
basis-and receives maximum scores for the
nine adequacy components o f the index.
Lesser amounts were prorated linearly. The
following three components measuring mod-
eration and population probability densities
were examined when setting the standards
for minimum and maximum scores for these
components: (i) Saturated Fat, (ii) Sodium
and (iii) Calories from Solid Fats, Alcoholic
Beverages and Added Sugars (SoFFAS).
SoFFAS is a proxy for the discretionary cal-
orie allowance (Guenther et al., 2008a). The
HEI-2005 measure was previously shown to
be valid for assessing diet quality (Guenther
et al., 2008). The HEI-2005 score is highly
associated with plasma biomarkers including:
vitamin C (r = 0.41), a-carotene (r = 0.28),
P-carotene (r = 0.28), P-cryptoxanthin
(r = 0 .4 1 ) and lutein (r = 0.23) (Hann et al.,
2001). See Table I.
Results
There were a total o f 138 participants in
the study. The sample was 65.2% female and
89.1% Caucasian. The average age o f all the
participants was 19.4 years old. There were
five sports represented in this study. The lean
sports included gymnastics, and swimmers
and divers. The ball sports included soccer,
basketball and volleyball. Those in their first

year o f school made up 42.8% o f the study.
The mean body mass index for all o f the
participants was 23.2 (2.3) kg/m2. The male
participants had a mean body mass index of
23.6 (2.4) kg/m2. The females had a mean
body mass index o f 22.9 (2.2) kg/m2 (P=0.07).
All o f the participants had an average body
fat o f 17.8 (6.5%). The male participants had
a body fat o f 11.1(3.9%), females were 24.1
(4.5%) (PO.OOl).
The HEI scores for males and females
differed significantly (Males= 47.7 + 7.9
and Females= 53.1 + 8.6, p<0.001). Calorie
intakes were significantly different for males
and females also (p<0.001). Females reported
consuming fewer than recommended calories
(1866.9 + 976.8) and males reported con-
suming more than the recommended calories
(3615.8 ± 2238.4). See Table II for detailed
dietary intake.
Overall, there was a positive correlation
between diet score and percent body fat (r=
0.30; P<0.001) and no correlation between
BMI and diet score, r=0.03; P=0.72. When
grouping the participants by lean vs. ball
sports, there was a significant difference in
HEI scores in males (lean= 45.4, ball= 50.6,
p=0.02). For females there was no difference

in HEI score in lean vs. ball sports (lean=
54.7, ball= 52.0, p=0.14).
Discussion
The purpose o f this study was to determine
the diet quality o f collegiate athletes and to
determine which groups o f athletes might be
most at risk for nutritional deficiencies. In this
study, athletes with lower body fat had lower
HEI scores. Females had better diet quality
than males and males in the ball sports had
better diet quality than males in sports that
require a leaner body type. Cumulatively, the
participants had diets that were high in solid
fats, alcohol, and added sugar (SoFAS). Their
diets were also high in sodium and lacked in
fiber and fruit.
Previous studies have found that diet qual-
ity in collegiate athletes affects performance.
Both malnourishment and over-nourishment
can have a negative impact on an athletes’
performance (Quatromoni, 2008). According
to Quatromoni, there is a need for nutrition
education for athletes because meal skipping,
limited finances and limited cooking skills
are common issues for athletes. It is also very
common for athletes to have misconceptions
about the types and amount o f food that they
should be eating (Quatromoni, 2008).
Skinner, Kopeck, Seburg, Roth and Lew-
is developed a medical nutrition therapy
protocol for female athletes because female

athletes tend to be at the highest risk for
suboptimal caloric intake, stress fractures,
and eating disorders (Skinner et al, 2001).
According to these authors, there needs to be
Table I. Healthy Eating Index 2005
Component
Maximum
Points
Standard for Maximum Score
Standard for minimum
score of zero
Total Fruit (includes 100% juice) 5 >0.8 cups equiv. per 1,000
Calorie No Fruit
Whole Fruit (not juice) 5 >0.4 cups equiv. per 1,000 Calorie No
Whole Fruit
Total Vegetables 5 >1.1 cups equiv. per 1,000 Calorie No
Vegetables
Dark Green and Orange Vegeta-
bles and Legumes
5 >0.4 cups equiv. per 1,000 Calorie
No Dark Green or Orange
Vegetables or Legumes
Total Grains 5 >3.0 cups equiv. per 1,000 Calorie No Grains
Whole Grains 5 >1.5 cups equiv. per 1,000 Calorie No Whole
Grains

Milk 10 >1.3 cups equiv. per 1,000 Calorie No Milk
Meat and beans 10 >2.5oz equiv. per 1,000 Calorie No Meat or
Beans
Oils 10 >12 grams equiv. per 1,000 Calorie No Oil
Saturated Fat 10 <7% o f energy >15% o f energy
Sodium 10 >0.7 grams equiv. per 1,000Calorie
>2.0 grams o f 1,000
Caloric
Calories from Solid Fats,
Alcoholic beverages, and added
sugars (SoFAS)
20 <20% o f energy >50% o f energy
Diet Quality Of Collegiate Athletes / 255
a consistent MNT for collegiate athletes in
order to prevent health issues that are caused
by inadequate nutrition. Four nutrition re-
lated issues were highlighted: amenorrhea,
decreased bone density, hydration and iron
status Nutrition education and intervention
are key to preventing these health issues that
can have long term negative effects (Skinner
et al 2001).
In a study by Shriver, Betts, and Wol-
lenberg, the diets of female college athletes

were assessed using a 3-day food record, 24
hour dietary recall, a nutrition questionnaire
and anthropometric data. The diets of these
athletes were compared to minimum recom-
mendations for athletes. Only 9 percent of
the athletes met their energy needs, 25% met
their carbohydrate needs and 16% monitored
their hydration status. This study speaks to
the need for both nutrition intervention and
nutrition education (Shriver, Betts and Wol-
lenberg, 2013).
While female athletes have a higher
rate of disordered eating than male athletes
(Thrash and Anderson, 2003), male athletes
are certainly not immune to disordered eating
patterns that cause long term metabolic dis-
turbances (Chatterton and Petrie, 2013). In
a survey of 732 male collegiate athletes the
most common form of weight control was
dieting and males that participated in weight
controlled sports had the highest rates of
dieting (Chatterton and Petrie, 2013). While
dieting can aid in weight loss, it is important
that athletes consume all required nutrients to
prevent long term health effects. If an athlete
is not educated on proper nutrition than nutri-
tional deficiencies can be caused by dieting
(Chatterton and Petrie, 2013).
The strengths and limitations of this study
are related to variation in the types of sport.
One limitation may be the composition of the
pool of athletes studied. The small numbers of
male and female athletes in each sport make

it hard to generalize this to a larger popula-
tion. In order to gather a large enough pool
of both male and female athletes in one sport
would require a larger longitudinal study to
build a statistically relevant pool. However,
the study is strengthened by the diversity of
participants. There was a large enough sample
size to see differences in groups and start to
pinpoint which athletes might be at greatest
risk for malnutrition and benefit most of a
nutritional intervention.
The practice implications of these find-
ings suggest that college athletic staff should
include nutrition care for their athletes’ that
Table II. Dietary Intake
Fem ale In tak e
Fem ale
Recom m endation
M ale Intake
Male
R ecom m endation
Calories 1867 2400 3616 3000
Fruits
(cups/day)
1.6 2 1.8 2
Vegetables
(cups/day)

2.0 2.5 3.1 2.5
Fiber
(gm)
9 per 1000 calories
14 per 1000
calories
8 per 1000
calories 14 per 1000 calories
SoFAS
Calories
965 per 2000 calorics 267 per 2000 calories 1020 per 2000
calorics 267 per 2000 calories
Sodium
(mg)
2875 2300 5803 2300
supports the long term health o f the athlete.
While arthritis, orthopedic disorders, and
infertility may not be widespread disorders,
they pose issues that cannot be ignored in
terms o f individual wellbeing and health care
costs. The serious nature o f nutrition care
should be noted as obesity and nutrition relat-
ed diseases become more endemic in the pop-

ulation. Athletes’ risks for obesity and other
health issues should not be ignored. Athletic
staff should be proactive when considering
the nutritional health o f their athletes for both
athletic performance and future health.
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Vogel et al. Journal of the International Society of Sports
Nutrition (2015) 12:12
DOI 10.1186/s12970-015-0074-y
RESEARCH ARTICLE Open Access
Safety of a dose-escalated pre-workout
supplement in recreationally active females
Roxanne M Vogel1,2, Jordan M Joy1, Paul H Falcone1, Matt M
Mosman1, Michael P Kim1 and Jordan R Moon1,3*
Abstract

Background: Pre-workout supplements (PWS) have increased in
popularity among athletic populations for their
purported ergogenic benefits. Most PWS contain a “proprietary
blend” of several ingredients, such as caffeine,
beta-alanine, and nitrate in undisclosed dosages. Currently,
little research exists on the safety and potential side
effects of chronic consumption of PWS, and even less so
involving female populations. Therefore, the purpose of
the present study was to examine the safety of consuming a
dose-escalated PWS over a 28-day period among
active adult females.
Methods: 34 recreationally active, adult females (27.1 ± 5.4
years, 165.2 ± 5.7 cm, 68.2 ± 16.0 kg) participated in this
study. Participants were randomly assigned to consume either 1
(G1) or 2 (G2) servings of a PWS daily or remain
unsupplemented (CRL) for a period of 28 days. All were
instructed to maintain their habitual dietary and exercise
routines for the duration of the study. Fasting blood samples, as
well as resting blood pressure and heart rate, were
taken prior to and following the supplementation period.
Samples were analyzed for hematological and clinical
chemistry panels, including lipids.
Results: Significant (p < 0.05) group by time interactions were
present for absolute monocytes (CRL −0.10 ± 0.10;
G1 + 0.03 ± 0.13; G2 + 0.01 ± 0.12×10E3/uL), MCH (CRL
−0.13 ± 0.46; G1 + 0.36 ± 0.52; G2 -0.19 ± 0.39 pg), creatinine
(CRL 0.00 ± 0.05; G1 -0.06 ± 0.13; G2 -0.14 ± 0.08 mg/dL),
eGFR (CRL −0.69 ± 5.97; G1 + 6.10 ± 15.89; G2 + 14.63 ±
7.11 mL/min/1.73), and total cholesterol (CRL −2.44 ± 13.63;
G1 + 14.40 ± 27.32; G2 -10.38 ± 15.39 mg/dL). Each of
these variables remained within the accepted physiological
range. No other variables had significant interactions.
Conclusion: The present study confirms the hypothesis that a

PWS containing caffeine, beta-alanine, and nitrate
will not cause abnormal changes in hematological markers or
resting vital signs among adult females. Although
there were statistically significant (p < 0.05) group by time
interactions for absolute monocytes, MCH, creatinine,
eGFR, and total cholesterol, all of the results remained well
within accepted physiological ranges and were not
clinically significant. In sum, it appears as though daily
supplementation with up to 2 servings of the PWS under
investigation, over an interval of 28 days, did not adversely
affect markers of clinical safety among active adult females.
Keywords: Pre-workout, Safety, Health, Female
Background
Nutrient timing refers to the methodical, timed ingestion
of carbohydrate, protein, fat and other dietary supple-
ments either before, during, or after physical activity [1].
Supplementation during the period immediately preced-
ing physical activity has become an increasingly popular
* Correspondence: [email protected]
1MusclePharm Sports Science Institute, MusclePharm Corp.,
4721 Ironton St.
Building A, Denver, CO 80239, USA
3Department of Sports Exercise Science, United States Sports
Academy,
Daphne, AL, USA
Full list of author information is available at the end of the
article
© 2015 Vogel et al. ; licensee BioMed Central.
Commons Attribution License (http://creativec
reproduction in any medium, provided the or
Dedication waiver (http://creativecommons.or
unless otherwise stated.
strategy among competitive and recreational athletes
alike as a means of improving performance [2]. In re-

sponse to this trend, manufacturers have developed pre-
workout supplements (PWS), which typically combine
caffeine with any number of purported ergogenic sub-
stances, such as beta-alanine, nitrate, and amino acids.
As the number of PWS available on the market grows,
each containing their own “proprietary blend” of active
ingredients, it must be determined which, if any, are safe
for chronic consumption. This becomes particularly im-
portant as concerns have arisen over the concept of
This is an Open Access article distributed under the terms of the
Creative
ommons.org/licenses/by/4.0), which permits unrestricted use,
distribution, and
iginal work is properly credited. The Creative Commons Public
Domain
g/publicdomain/zero/1.0/) applies to the data made available in
this article,
mailto:[email protected]
http://creativecommons.org/licenses/by/4.0
http://creativecommons.org/publicdomain/zero/1.0/
Nutrition (2015) 12:12 Page 2 of 6
proprietary blends, namely the fact that the Food and
Drug Administration does not monitor the amounts of
ingredients used in these blends or the accuracy of prod-
uct labeling by manufacturers [2].
Caffeine is one of the most commonly found ingredi-
ents in PWS. An extensive amount of scientific literature
exists on the ergogenic properties of caffeine [3-5]. Ac-
cording to the International Society of Sports Nutrition’s
position stand on caffeine and performance, it is most
effective when consumed in low to moderate doses,

about 3–6 mg per kilogram bodyweight, 30–60 minutes
prior to exercise [4]. Caffeine has been shown to im-
prove performance in endurance events and time-trials,
improve cognitive function and alertness, and delay the
onset of fatigue during exhaustive exercise [3,5]. More-
over, caffeine anhydrous, which is frequently used in PWS,
has been shown to have greater ergogenic effects than caf-
feine ingested in the form of coffee, tea, or cola [4].
Beta-alanine (BA), another common ingredient in
PWS, is an amino acid which serves as a rate-limiting
precursor to carnosine in skeletal muscle [6]. Carnosine’s
suggested mechanism of action may be to buffer hydro-
gen ions during exercise, thereby influencing intracellu-
lar muscle pH, and ultimately increasing work capacity
[7]. In a recent review of the literature by Quesnele et al.
[8], the authors concluded that although there is evi-
dence to suggest that BA supplementation enhances ath-
letic performance, the safety of its use remains unclear,
and there is a general under-reporting of its side effects
in the literature.
Despite the existing literature pertaining to individual
ingredients contained in PWS and the growing number
of studies that address multi-ingredient PWS specifically,
we are unaware of any published reports examining the
safety of PWS in a solely female population. Therefore,
the purpose of the present study was to examine the
safety of chronic consumption of a PWS over a 28 day
period among active adult females. We hypothesized
that daily PWS supplementation would not produce ab-
normal changes in hematological or metabolic safety
markers or resting vital signs.
Methods
Experimental design

In a dose-escalated, simple randomized design, 34 sub-
jects were randomly assigned to control (CRL, n = 16;
27.1 ± 5.9 y, 166.2 ± 4.0 cm, 65.2 ± 12.9 kg), 1 serving (G1,
n = 10; 24.9 ± 3.9 y, 164.7 ± 5.8 cm, 72.4 ± 23.3 kg), or 2
serving (G2, n = 8; 29.6 ± 5.8 y, 163.8 ± 8.8 cm, 69.0 ±
11.6 kg) groups via random number generation by the
investigators and asked to remain unsupplemented, or
consume either 1 or 2 servings, respectively, of a pre-
workout formula (Fitmiss Ignite™, MusclePharm Corp.,
Denver, CO) every day for 28 days. The pre-workout
formula contained 1 g of carbohydrate, 23 mg of Cal-
cium, and 5,700 mg of a proprietary blend consisting of
beta-alanine, choline bitartrate, L-tyrosine, glycine, tau-
rine, L-carnitine, beetroot extract, hawthorn berry pow-
der, agmatine sulfate, caffeine anhydrous, and huperzine
A. The supplement was analyzed by a third party (Euro-
fins Supplement Analysis Center, Petaluma, CA) and
verified to contain all of the ingredients on the label.
Subjects were instructed to consume 1–2 level scoop(s)
of the supplement with 12 oz water per scoop either
30 minutes prior to exercise or at the same time of day
on rest days. Compliance was monitored using supple-
ment consumption logs, as well as by weighing supple-
ment containers before and after the supplementation
period. A total of 38 subjects were initially recruited for
this study. From G1, one subject discontinued the study
due to noncompliance, and from G2, three subjects dis-
continued due to noncompliance. The CRL group con-
tained more total participants, as CRL group data was
added from a previously conducted study which fea-
tured a design exactly identical to the present study.
Participants completed the study with an average sup-
plementation compliance of 94.6% for G1 and 100% for
G2. Blood draws were taken prior to and following the
supplementation period. Approval for the human sub-
ject protocol was obtained from MusclePharm Sports

Science Institute’s IRB, and subjects were provided with
written informed consent documents prior to participa-
tion in the study.
Participants
34 recreationally active female adults (27.1 ± 5.4 years,
165 ± 5.7 cm, 68.2 ± 16.0 kg) participated in the study.
Recreationally active was defined as habitually participat-
ing in moderate to vigorous physical activity on three or
more days a week for a duration of thirty minutes or
more. Subjects were required to be non-smokers, free of
any disease or disorder which may have produced con-
founding effects, and have abstained from taking any
other pre-workout supplements for one month prior to
the beginning of the study. Exclusion criteria included
having a significant history or current presence of a
treated condition, such as high blood pressure
(≥140 mmHg systolic and/or ≥90 mmHg diastolic),
tachyarrhythmia, or heart, kidney, or liver disease, or
any contraindication to physical activity. Also excluded
from the study were participants whose willingness or
ability to comply with the study protocol was uncertain.
Eligibility was determined upon evaluation of pre-
participation health history, exercise, and supplementa-
tion screening questionnaires. A caffeine usage question-
naire was given as part of the pre-participating screening
process, with average self-reported caffeine consumption
prior to study being 131 mg/day for G1 and 269 mg/day
for G2. Subjects were instructed to maintain their habit-
ual dietary and exercise routines, and to not take any
additional supplements during their participation in the

study.
Measurements
All measurements were taken prior to and following the
28-day supplementation period in a quiet, temperature
controlled private office. Upon arrival at the office, sub-
jects were instructed to remain seated quietly for 15 mi-
nutes before resting vital signs, height, and weight were
taken. Subjects then submitted a blood sample in the
fasted state. All blood draws were performed in the
morning to prevent diurnal variations by a trained phle-
botomist via venipuncture. Samples were analyzed for
comprehensive metabolic panels, complete blood counts
and lipid profiles by an external laboratory (Laboratory
Corporation of America, Denver, CO). Variables re-
corded from blood analysis consisted of white blood cell
count (WBC), red blood cell count (RBC), hemoglobin,
hematocrit, mean corpuscular volume (MCV), mean
corpuscular hemoglobin (MCH), mean corpuscular
hemoglobin concentration (MCHC), red blood cell dis-
tribution width (RDW), platelets (absolute), neutrophils
(percent and absolute), lymphocytes (percent and abso-
lute), monocytes (percent and absolute), eosinophils
(percent and absolute), basophils (percent and absolute),
serum glucose, blood urea nitrogen (BUN), creatinine,
estimated glomerular filtration rate (eGFR), BUN:cre-
atinine, sodium, potassium, chloride, carbon dioxide, cal-
cium, protein, albumin, globulin, albumin:globulin,
bilirubin, alkaline phosphatase, aspartate aminotransfer-
ase (AST), alanine aminotransferase (ALT), total choles-
terol, triglycerides, high density lipoprotein (HDL)
cholesterol, and low density lipoprotein (LDL) choles-
terol. Inter-test reliability results from 12 men and
women measured up to one week apart at the aforemen-
tioned laboratory resulted in no significant differences
for any of the variables noted above from day-to-day
(p > 0.05) and an average inter-test Coefficient of Vari-

ation (CV) of 6.9%.
Statistical analyses
Data was analyzed using a 3×2 repeated measures
ANOVA model for all group, time, and group by time in-
teractions. A Bonferroni post-hoc analysis was used to lo-
cate differences. Shapiro-Wilk tests were used to
determine normality of the data. The Minimal Difference
(MD) needed to be considered real was determined using
the method previously described by Weir [9]. Data are
presented as means ± standard deviation. All data were
analyzed using Statistica software (Statsoft, Version 10).
Results
Significant group by time interactions were present for ab-
solute monocytes (p < 0.05), wherein CRL decreased rela-
tive to G1 and G2. Absolute monocytes had a normal
distribution at baseline (p = 0.07), yet the distribution was
positively skewed (p < 0.05) after the supplementation
period. Significant group by time interactions were ob-
served with MCH (p < 0.05), with G1 increasing relative to
CRL and G2. Significant group by time interactions were
detected for creatinine (p < 0.05), with G2 decreasing rela-
tive to CRL. Significant group by time interactions were
noted for eGFR (p < 0.05), with G2 increasing relative to
control. Significant group by time interactions were also
present for total cholesterol (p < 0.05), G1 increasing
relative to CRL and G2. Total cholesterol was positively
skewed at baseline (p < 0.05), and at post-supplementation,
it became normally distributed (p = 0.99). MCH and eGFR
were normally distributed (p > 0.05) at both time points,
and creatinine was positively skewed (p < 0.05) at both time
points. All variables remained within the accepted physio-
logical range at baseline and post supplementation. No
other variables had significant group by time interactions.
Data are presented in Additional file 1 as means ± standard
deviation. Tolerability data collected from participants
reported no serious adverse events. The most common re-

ported side effects were a tingling sensation (n = 6), itchi-
ness (n = 2), and nausea (n = 2). Other reported side effects
included dizziness, lightheadedness, dry mouth, headache,
a burning sensation, and diarrhea (all n = 1). Most of these
effects occurred within the first several days of supplemen-
tation and subsided over time.
Discussion
The results of the present study suggest that daily sup-
plementation with the PWS under investigation does not
appear to cause any abnormal changes in hematological
and clinical chemistry/metabolic safety markers or rest-
ing vital signs in female subjects. While significant group
by time interactions (p < 0.05) were observed for abso-
lute monocytes, MCH, creatinine, eGFR, and total chol-
esterol, all group values remained well within the
accepted physiological range and were not clinically sig-
nificant. While remaining within range, unusual effects
were observed between groups. For instance, the CRL
group decreased relative to G1 and G2 for absolute
monocytes, and for MCH and total cholesterol, G1 in-
creased relative to both CRL and G2. Similar to total
cholesterol, although not reaching significance (p > 0.05),
both LDL and HDL increased in G1 but decreased in
G2 over time. These findings are somewhat discrepant,
since intuitively, one would think that if a lower dose in-
creases a given parameter compared to control, then a
higher dose should amplify this effect. This, however,
was not the case. Such results suggest a natural variation
in these clinical markers, and may not necessarily be re-
lated to supplementation. Additionally, the control

group (n = 16) was larger than either of the experimental
groups (G1, n = 10; G2, n = 8), so individual variations
within the experimental groups had greater impact on
the group mean values.
Variables that were significantly different at the group
level were evaluated at the individual level to determine
clinical significance. Analysis of clinical significance at
the individual level was conducted using the MD statis-
tic, which calculates the magnitude of the inter-test dif-
ference (between baseline and post-supplementation)
needed to be exceeded in order for a single measure-
ment to be considered real, as described by Weir [9].
The MD is calculated using the standard error of meas-
urement (SEM), which is considered an absolute index
of the reliability of a given test/measurement, not rela-
tive to the characteristics of the sample or population
from which values were obtained. Unlike other reliability
measures, such as the CV, the SEM and thus the MD,
are not affected by between-subject variability [9]. If a
subject’s measured values exceeded the MD, the change
was considered a true change. Clinical significance at the
individual level was reached when a score that exceeded
the MD crossed the upper or lower limits of the ac-
cepted physiological range for each variable. For creatin-
ine, this occurred in three subjects, one from G1 and
two from G2, wherein values decreased pre to post,
bringing them within the clinical reference range. For
total cholesterol, changes observed in two subjects from
G1 and one from G2 exceeded the MD. Specifically, the
two subjects from G1 increased over time, moving from
within range to out of range, while the subject from G2
decreased pre to post, entering the accepted reference
range. Also worth noting is the fact that three individ-
uals from the CRL group experienced changes in total
cholesterol values that both exceeded the MD and

moved in or out of range. In this case, one subject in-
creased over time to leave the accepted range, one
started outside of the range and remained out of range,
and one decreased pre to post, entering back into range.
All subjects remained within 3 standard deviations of
the mean and exceeded the MD. Collectively, individual
analysis supports the present hypothesis and also sup-
ports the notion of intra-subject diurnal variability. Fur-
thermore, absolute monocytes and total cholesterol were
distributed differently pre to post, increasing the prob-
ability for a type 1 statistical error [10].
These findings generally agree with previous literature.
Aside from the research pertaining to PWS effects on
performance [11-16], only a limited number of studies
have also examined the clinical safety of PWS. Kedia
et al. [17] looked at the effects of a multi-ingredient
PWS containing caffeine, betaine, and dendrobium
extract on body composition, performance measures,
and hematological markers of clinical safety in healthy,
young men and women undergoing concurrent resist-
ance training for six weeks. While the investigators did
not see an improvement in objective assessments of ex-
ercise performance or body composition with supple-
mentation, they found the PWS to be well tolerated with
no significant changes in clinical laboratory safety
markers at the end of six weeks.
Similarly, Shelmadine et al. [18] examined the effects
of 28 days consuming a commercially available PWS,
NO-Shotgun®, combined with heavy resistance exercise
on body composition, muscle strength and mass, myofi-
brillar protein content, markers of satellite cell activa-
tion, and clinical safety markers in male subjects. They
found no negative side effects or abnormal impact on
clinical safety markers after 28 days of supplementation.

In a follow up study of the same nature, this time with a
post-workout supplement added (NO-Synthesize®), Spil-
lane et al. [19] again found no detrimental effects on
clinical safety markers following 28 days supplementa-
tion and resistance training with NO-Shotgun®.
Farney et al. [20] investigated hemodynamic and
hematological effects of two supplements containing caf-
feine and 1,3- dimethylamylamine (a constituent of gera-
nium) after 14 days of supplementation in men and
women, and found only a significant change in blood
glucose for one of the supplements (Jack3d™) over this
time period. A follow up to this study conducted by
Whitehead et al. [21] supplemented with the same prod-
uct containing caffeine and 1,3- dimethylamylamine
(Jack3d™) over a 10-week period in healthy males and
also found it did not negatively impact hematological
markers of health when consumed daily.
Kendall et al. [22] investigated the safety and efficacy
of a PWS containing caffeine, creatine, beta-alanine,
amino acids and B-vitamins in recreationally trained,
college-age men over an identical period of 28 days. In
that study, no adverse effects were observed for renal or
hepatic clinical blood markers or resting vital signs. Re-
searchers concluded that PWS with similar ingredients
in similar doses should be safe for ingestion periods up
to 28 days in healthy males. More recently, Joy et al. [23]
found that supplementation with a PWS containing caf-
feine, nitrate, and amino acids in healthy, recreationally
active men and women was apparently safe when taken
within recommended dosage guidelines for 28 days.
To our knowledge, this is the first study assessing the
clinical safety of a PWS in an all-female population.
Female-specific recommendations for sports nutrition

and supplementation is an area that warrants more
attention. A review article by Volek, Forsythe, and Kraemer
[24], for instance, identifies the subtle, yet important differ-
ences in exercise metabolism between male and female
athletes. The authors suggest that nutritional strategies, in-
cluding nutrient timing and supplement use, should be tai-
lored to meet the sex-specific needs of female athletes. In
another review article addressing gender differences in
sports nutrition, Tarnopolsky [25] similarly concluded that
future studies in nutrition and metabolism should exam-
ine and consider sex differences in response to supple-
mentation and exercise. It therefore seems prudent for
future research to continue to address sports nutrition
supplementation in females to evaluate both safety and ef-
ficacy in this population as compared to males.
Limitations
The present study included a short duration supplemen-
tation period and small sample size. Future studies
should examine the effects of supplementation for lon-
ger than 28 days among more subjects, especially given
the fact that statistically significant interactions did take
place over time in the present study. Again, while none
of the significant variables left the accepted physiological
range, the possibility that these could be the beginnings
of adverse trends cannot be ruled out. This leaves long-
term safety of PWS supplementation, at least greater
than 28 days, still open to question.
Conclusion
This study supports the hypothesis that a PWS contain-

ing caffeine, beta-alanine, and nitrate will not cause ab-
normal changes in hematological or clinical chemistry/
metabolic markers, or resting vital signs among recre-
ationally active females. Although there were statistically
significant (p < 0.05) group by time interactions for abso-
lute monocytes, MCH, creatinine, eGFR, and total chol-
esterol, all of the results remained well within accepted
physiological ranges and were not clinically significant.
In sum, it appears as though daily supplementation with
up to 2 servings of the PWS used in this investigation,
over a period of 28 days, had no adverse impact on
markers of clinical safety among active adult females.
Additional file
Additional file 1: Data collected pre and post supplementation.
Abbreviations
PWS: Pre-workout supplement(s); BA: Beta-alanine; WBC:
White blood cell;
RBC: Red blood cell; MCV: Mean corpuscular volume; MCH:
Mean corpuscular
hemoglobin; MCHC: Mean corpuscular hemoglobin
concentration; RDW: Red
blood cell distribution width; BUN: Blood urea nitrogen; eGFR:
Estimated
glomerular filtration rate; AST: Aspartate aminotransferase;
ALT: Alanine
aminotransferase; CV: Coefficient of variation; MD: Minimum
difference;
SEM: Standard error of measurement.
Competing interests
RV, JJ, PF, MM, MK and JM are employees of the funding
source,
MusclePharm Corporation. However, this publication should not

be viewed
as endorsement by the investigators, Metropolitan State
University of
Denver, the United States Sports Academy, or MusclePharm
Corporation.
Authors’ contributions
RV, JJ, and PF participated in data collection for this
investigation. All authors
contributed to the conception of the experimental design,
drafting of the
manuscript, and interpretation of data. All authors have read
and approved
the final manuscript.
Acknowledgements
We would like to thank all of the participants as well as
MusclePharm
Corporation for supplying product and funding the
investigation.
Author details
1MusclePharm Sports Science Institute, MusclePharm Corp.,
4721 Ironton St.
Building A, Denver, CO 80239, USA. 2Metropolitan State
University, Denver,
CO, USA. 3Department of Sports Exercise Science, United
States Sports
Academy, Daphne, AL, USA.
Received: 19 December 2014 Accepted: 16 February 2015
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AbstractBackgroundMethodsResultsConclusionBackgroundMeth
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analysesResultsDiscussionLimitationsConclusionAdditional
fileAbbreviationsCompeting interestsAuthors’
contributionsAcknowledgementsAuthor detailsReferences
A 41-year-old woman came to the Emergency
Department in January, 1998. She had awoken that
morning in severe pain and had taken ibuprofen without
improvement. The previous day, she had walked 4
miles. Examination showed a temperature of 36·9°C,
pulse 86 beats per min, and blood pressure 118/56 mm
Hg. She weighed 72 kg and her height was 158 cm. She
had diffuse muscle tenderness in her thighs and biceps.
No neurological deficits were noted. She was diagnosed
as having musculoskeletal pain and given a prescription
for paracetamol with codeine. 2 days later, she returned
to the Emergency Department complaining of
continued muscle pain, now accompanied by
symmetrical muscle weakness. Examination again
showed diffuse muscle tenderness in her arms and legs,

with normal muscle tone and symmetrical, proximal,
and distal muscle weakness (power 4/5). Laboratory
investigations showed a sodium of 141 mmol/L,
potassium of 1·1 mmol/L, chloride of 98 mmol/L,
bicarbonate of 33 mmol/L, blood urea nitrogen of 3·9
mmol/L, creatinine of 106 �mol/L, and a glucose of 5·8
mmol/L. Her haemoglobin was 11·9 g/dL (mean
corpuscular volume 77·0 fL), albumin 3·5 g/dL, calcium
1·9 mmol/L, magnesium 0·57 mmol/L, and phosphate
0·94 mmol/L. She had high concentrations of lactate
dehydrogenase (748 U/L), aspartate aminotransferase
(244 U/L), and creatine kinase (CK; 13 182 U/L). Her
urine was positive for myoglobin. She was admitted to
hospital with a diagnosis of rhabdomyolysis and
hypokalaemia. She was treated with intravenous
hydration and electrolyte replacement. Her CK peaked
at 21 072 U/L. Her creatinine remained normal.
Further investigation of her hypokalaemia included
urine chemistry (random urine potassium 3·8 m m o l / L ;
normal 10–160 mmol/L), a negative screen for diuretics,
and normal corticotropin and renin concentrations.
We discovered from the patient’s husband that her
diet consisted mostly of cheese sandwiches. She did not
eat any fruits, vegetables, or meat products. No history
of purging was discovered. A psychiatric consultation
was arranged, but no definitive evidence for a primary
eating disorder (anorexia or bulimia nervosa) was found.
She received nutritional advice and was discharged. She
came back to the Emergency Depratment in August,
1998, with a 1-day history of weakness. Her potassium
was 1·1 mmol/L with a normal CK. An
electrocardiogram showed first-degree atrioventricular
block and probable TU wave fusion (figure). A h i s t o r y
of purging and laxative abuse was obtained. After

medical treatment she was transferred to the psychiatric
service for management of her bulimia nervosa. She was
last seen in January, 1999. She had maintained more
normal eating pattterns and a normal serum potassium,
but had not attended for psychiatric follow-up.
Rhabdomyolysis is associated with both traumatic,
(crush syndrome)1 and non-traumatic causes.
Rhabdomyolisis secondary to hypokalaemia is a well-
described non-traumatic cause2 and has been associated
with several medical conditions including use of
diuretics, eating liquorice, coeliac disease, infectious
diarrhoea, anorexia nervosa/bulimia, and abuse of
laxatives. Rhabdomyolysis can be a life-threatening
disorder, with acute renal failure being one of the most
serious complications.3 Although this patient did not
develop renal failure, that consequence has been
associated with rhabdomyolysis secondary to laxative
abuse and induced hypokalaemia.4 The primary
mechanism of rhabdomyolysis secondary to
hypokalaemia appears to be that potassium is released
from normal contracting muscle cells resulting in a
vasodilatory response of the surrounding arterioles.5
Failure of this potassium-mediated arteriolar dilation
may lead to muscle ischaemia. This case demonstrates
the need to include hypokalaemia in a differential
diagnosis of rhabdomyolysis, and the importance of
screening for eating disorders in patients with
hypokalaemia associated with a low urinary potassium.
Other clues in the initial presentation suggesting an
underlying eating disorder include the hint of excessive
exercise, her very restricted eating patterns, and the
laboratory abnormalities that point to malnutrition (eg,
microcytic anaemia and low calcium, magnesium,
potassium, and phosphate concentrations).

R e f e r e n c e s
1 Bywater EGL, Beall D. Crush injuries with impairment of
renal
function. BMJ 1941; i: 4 2 7 – 3 2 .
2 Singhal PC, Abramovici M, Venkatesan J, Mattana J.
Hypokalemia
and rhabdomyolysis. Miner Electrolyte Metab 1991; 17: 3 3 5 –
3 9 .
3 Zager RA. Rhabdomyolysis and myohemoglobinuric acute
renal
failure. Kidney Int 1996; 49: 3 1 4 – 2 6 .
4 Copeland PM. Renal failure associated with laxative abuse.
Psychother Psychosom 1994; 62: 2 0 0 – 0 2 .
5 Knochel PL, Schlein EM. On the mechanism of
rhabdomyolysis in
potassium depletion. J Clin Invest 1972; 51: 1 7 5 0 – 5 8 .
Muscle pain after exerc i s e
Craig Nielsen, Peter Mazzone
1062 THE LANCET • Vol 353 • March 27, 1999
Case report
Lancet 1999; 353: 1062
Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA
(C Nielsen MD, P Mazzone MD)
Correspondence to: Dr Craig Nielsen

Patient’s electrocardiogram
Muscle pain after exerciseReferences

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