original research

74               SAJSM  vol 23  No. 3  2011

Introduction
Body composition is a very important aspect of an athlete’s perfor-
mance. According to the American Dietetic Association: ‘body weight 
can influence an athlete’s speed, endurance and power, whereas 
body composition can affect an athlete’s strength, agility and appear-
ance.’

1
 Determining optimal body weight and body composition for 

each individual according to age, sex, genetics and type of sport 
definitely has been shown to correlate well with race time and in-
creased exercise performance.

2

Assessment of body composition can be done via various ways. 
Prediction equations with the use of a combination of anthropometric 
measurements and bioelectrical impedance analysis measurements 
have been compared and validated with the criterion methods.

3,4

Nutrition is known to play a key role in exercise performance and 
endurance during extensive periods of exercise. In all sport, the main 
goal of nutritional strategies is to target and eliminate  factors that  
impair exercise performance; these factors include fatigue, thirst, 
muscle glycogen depletion and gastro-intestinal disturbances.

5
 

Nutrition is an important modifiable factor towards achieving the 
optimal body composition as well as providing fuel for increased 
levels of training. Adequate energy should come from a wide variety 
of available foods which provide carbohydrate, protein, fat and 
micronutrients.

1
 Marginal vitamin and mineral deficiencies have 

been found to be present in some elite athletes, due to either an 
inadequate diet, reduced absorption by the gastro-intestinal tract, 
increased excretion in sweat, urine and faeces, increased turnover 
and the consequent biochemical adaptation to physical activity.

6
 

Most athletes believe that supplements are necessary in order for an 
endurance athlete to reach their increased nutritional requirements. 
They also believe that supplements can promote changes due to 
activity, provide more consistent training sessions, improve recovery 
of muscle tissue between sessions, reduce the prevalence of 
injury or infection and enhance their competitive performance.

7
 

A triathlete has to ensure that his/her dietary intake, including the 
use of supplements, body composition and general immune health, 
are in harmony, not only for groups of athletes, but also specifically 
tailor made for the individual according to age, gender, ethnicity 
and genetics. In Southern Africa, to our knowledge, no study has 
investigated these aspects in triathletes competing in Olympic and 
Ironman distance events; therefore, the main aim of this study was 
to determine the body composition, dietary intake and supplement 
use amongst triathletes residing in the Western Cape region. A 
secondary aim was to determine and compare percentage body 
fat measured via anthropometry and multi-frequency bioelectrical 
impedance analysis. 

Methods
The study design was descriptive and cross-sectional with an ana-
lytical component. A convenient sample was selected from both the 

Abstract
objective. The aim of this study was to determine body composi-
tion, dietary intake and supplement use among Olympic and Iron-
man distance triathletes residing in the Western Cape.
Methods. A descriptive, analytical, cross-sectional study design 
was conducted in Western Cape Province. Twenty-six triathletes 
registered with Triathlon South Africa were included. Percentage 
body fat was measured via multi-frequency bio-electrical imped-
ance analysis and anthropometry. Dietary intake and supplement 
use were measured with an estimated 3-day food record and 
questionnaire.
Results. The mean age of the men and women was 38±7 and 
38±10 years respectively. The mean amount of training per week 
for men and women respectively was 15±4 and 15±5 hours. The 
percentage body fat (%BF) of men and women was 13±4% and 
21±6%, respectively. The mean dietary macronutrient intake 
for men and women respectively was for total energy intake  
14 535±4 510 kJ and 9 004±2 369 kJ, carbohydrate intake 
5.3±1.9 g/kg and 3.5±1.0 g/kg, protein intake 2.0±0.5 g/kg and 
1.2±0.2 g/kg and fat intake 35±10% and 30±6% of total energy 
intake. Seventy-three per cent of the triathletes used over-the-
counter dietary supplements. 
Conclusion. Percentage body fat of the men and women was at 
the upper end of the range associated with elite athletes. Overall 
the athletes had a fairly good intake of macro- and micronutri-
ents. Inadequate habitual carbohydrate intake was attenuated by 
the vast majority of the triathletes  taking additional carbohydrate 
supplementation. Various supplements were used widely among 
the athletes.

Sunita Potgieter (Master of Nutrition)1

Demetre labadarios (PhD Nutrition, MB ChB)2

Irene labuschagne (BSc Dietetics)1

1
Department of Interdisciplinary Health Sciences, Division Human Nutrition, Stellenbosch University

2
Population Health, Health Systems and Innovation, Human Sciences Research Council,

 Cape Town

Correspondence to: Sunita Potgieter (sunita@sun.ac.za)

Body composition, dietary intake and supplement use 
among triathletes residing in the Western Cape



SAJSM  vol 23  No. 3  2011                                                                                                                                75

2007 and 2008 Western Province Triathlon (WPTA) team. Twenty-
six of these 91 (29% response rate) athletes were recruited by send-
ing out an e-mail to all registered triathletes using the WPTA data-
base and the placement of an advertisement on the WPTA website 
(http://www.wptriathlon.org). A reminder notice to participation was 
sent out midway during data collection to achieve maximum possible 
voluntary participation. The investigator also distributed pamphlets 
at most of the triathlon races during the 2007/2008 season. Male 
or female triathletes aged 18 - 70 years, triathletes on the WPTA 
team of 2007 and 2008 and who were training more than 10 hours 
per week (swimming, cycling and running) or triathletes who com-
pleted an Ironman distance event 6 months prior to data collection 
and training more than 10 hours per week were included. The data 
collection phase was during the South African Triathlon season from 
June 2007 to March 2008.

The height and weight of the subjects were measured using a 
Seca 767 Column Scale with height meter according to specifications 
from the literature.

8
 The bicep, tricep, sub-scapular, supra-iliac, 

abdominal, chest, mid-axilla, thigh and calf skinfold thickness were 
measured with a Dial Gauge Harpenden Skinfold Caliper. Three 
skinfold measurements were taken at each individual site and the 
mean calculated for use in data analysis. All the anatomical sites 
were found as indicated for each individual skinfold thickness 
according to standard protocol.

8
 Body composition of the subjects 

was measured using a Bodystat Quadscan 4000SN (5 kHz, 50 kHz, 
100 kHz and 200 kHz) Isle of Mann, 2000 multi-frequency bioelectrical 
impedance (MF-BIA) meter. Subjects were asked to adhere to the 
pretest conditions before BIA measurement was taken. Subjects 
were asked to remove all jewellery, watches and belts and instructed 
to remove the right shoe and sock as well as clear the hand and 
wrist area. Subjects had fasted for 3 - 4 hours and abstained from 
exercising for 12 hours prior to the measurement. They were asked 
not to consume any alcohol or caffeine for 24 hours prior to the 
measurement. Subjects were asked to lie in the supine position on 

a plinth for approximately 5 minutes before the measurements were 
taken. All the measurements were taken inside a building at normal 
room temperature and calibration and placement of the electrodes 
were as described by the manufacturer in the instruction manual. 

Dietary intake was measured using a 3-day estimated food 
record. The food record also contained a section where the subjects 
were instructed to record daily supplement use. The subjects were 
asked to write down their food and beverage intake as accurately as 
possible and they signed a declaration stating that the information 
given was an accurate reflection of their dietary intake. They were 
instructed to record two weekdays and one weekend day on the food 
record. They were also asked to record their training on the days the 
food record was kept. An additional questionnaire was completed 

TABlE 1. Mean (SD) demographic and training characteristics of the triathletes by gender

Athletes characteristics

Male 
Mean± SD
(N = 13)

Female
Mean±SD
(N = 13) t-test; p-value

Demographic characteristics
Age (years) 37.9±6.8 37.5±9.6 t= 0.1; p=0.050

Anthropometric characteristics
Height (m) 1.8±0.1 1.7± 0.1 t= 3.9; p=0.001

Body weight (kg) 78.9±12.9 63.9±10.3 t=3.3; p=0.003

Body mass index (kg/m
2
) 24.5±3.2 22.6±2.8 t=1.6; p=0.100

Training characteristics (N=12)*
Total hours training per week 15.1±4.1 15.3±4.7 t=-0.1; p=0.900

Swimming (hours per week) 3.5±2.1 4.2±2.5 t=-0.7; p=0.500

Bicycling (hours per week) 6.5±2.1 6.4±2.5 t= 0.1; p=0.900

Running (hours per week) 4.2±2.4 4.3±1.7 t=-0.1; p=0.900

Gym/resistance training 0.9±1.1 0.5±0.9 t=1.1; p=0.300

(hours per week)

Swimming (km per week) 6.4± 2.6 10.2±5.9 t=2.1; p=0.010

Bicycling (km per week) 173.8 ± 8.1 188.9 ±88.5 t=0.5; p=0.600

Running (km per week) 39.6±17.9 41.5±16.6 t=-0.3; p=0.800

*One male subject neglected to complete the training characteristics questionnaire and did not respond to correspondence requesting its completion.

Fig. 1. Mean (SD) of percentage body fat of triathletes by gender 
(male N=12, female N=9); prediction equations could not be de-
termined from subjects due to SKF measurements not obtained 
from subjects due to variation in skin compressibility and an 
increased muscle mass, making the skinfold thickness difficult 
and inaccurate to measure.



76               SAJSM  vol 23  No. 2  2011

by the subjects indicating general supplement use and reasons for 
taking the supplements as well as their general training regimen.

All triathletes gave informed written consent and the study was 
approved by the Health Research Ethics Committee of Stellenbosch 
University (Reference number: N07/03/07).

Data analysis 
A registered dietitian edited and analysed the dietary intake data 
using the Food Finder III computer software program (http://www.
wamsys.co.za) and prediction equations were used to calculate per-
centage body fat from anthropometrical measurements.

9-12

Statistical analysis
Data were entered into a spreadsheet on Microsoft Excel and trans-
ferred to Statistica 8.0 for statistical analysis in consultation with 
a statistician. Due to the descriptive and informative nature of the 
study, mostly descriptive statistics in the form of mean and standard 
deviation (SD) for nominal data and percentages of the total popula-
tion for ordinal data were calculated to determine the central ten-
dency. When repeated measures were compared with one another, 
repeated measures analysis of variance (ANOVA) was used. The 
technique of bootstrapping was applied to estimate sample distribu-
tions for data from a bivariate normal distribution and the post hoc 
Bonferroni test was applied to determine the significant differences 
between group means during analysis of variance (p<0.01).

Results
Twenty-six triathletes were included of whom 13 were male and 13 
female. All the athletes were Caucasian, except for one male par-
ticipant who was of mixed ancestry. The demographic and training 
characteristics of the triathletes are summarised in Table I.

Body composition
The different %BF values for men and women respectively differed 
significantly irrespective of the method used and are portrayed 
against gender-specific reference values in  Fig. 1.

When comparing the measurements, no significant difference 
was found with the men’s results when using analysis of variance 
and applying the Bonferroni correction between the %BF from the 
MF-BIA (12.6±4.2), %BF from the equation using 7 SKF sites from 
Evans et al. 2005

9
 (12.6±4.4) (p=1.00), the %BF  from the 4 SKF 

site equation from Jackson and Pollock 1985
10

 (12.1±4.9) (p=1.00), 
the %BF from the 3 SKF site equation from Jackson and Pollock 
1985

10
 (12.5±4.9) (p=1.00) and the %BF from the Body Bite nutrition 

software program
11

 (11.7± 5.2) (p=1.00). A significant difference was 
found between %BF measured from MF-BIA and the 4 SKF site 
equation from Durnin and Womersley

12
 (17.5±5.5) (p<0.05) and the 

%BF from the 3 SKF site equation from Evans et al. 2005
9
 (9.4±2.9) 

(p=0.01).  

The %BF from the women’s results showed no significant 
differences in the %BF from MF-BIA (22.3±6.3) and the %BF 
from the 7 SKF site equation from Evans et al. 2005

9
 (24.2±6.1) 

(p=1.00), the %BF from the 3 SKF site equation from Evans et al. 
2005

9
 (22.9±6.6) (p=1.00) and the %BF from the Body bite nutrition 

software program
11 

(23.4±9.0) (p=1.00). There was however a 
statistically significant difference between the %BF from MF-BIA and 
the %BF from the 4 SKF site equation from Durnin and Womersley

12
 

(30.0±7.2) (p<0.05) and the 4 SKF site equation from Jackson and 
Pollock 1985

10
 (32.40±8.95) (p<0.05).

Dietary intake and supplement use
The total number of completed food records received was 18 out 
of a possible 26 food records (69% response rate), of which 9 were  

Fig. 3. Mean (SD) of micronutrient intake expressed as a per-
centage of the dietary reference intakes (DRIs) of the triathletes 
by gender. Due to the limited reference values available for the 
interpretation of micronutrient intake in groups, the recom-
mended daily allowance (RDA) values were used. Where avail-
able the adequate intake (AI) and the estimated average require-
ment (EAR) values were used.

Fig. 2. Mean (SD) of carbohydrate and protein intake of triath-
letes by gender (N=18)* (top) and mean (SD) of fat intake of tri-
athletes by gender (N=18)* (bottom).*Only 9 females and 9 males 
were included in the analysis of dietary intake because only 18 
of the 26 subjects returned their completed food record. Rec-
ommended protein intake is 1.2 - 1.7 g/kg body weight/day, rec-
ommended carbohydrate intake is 6 - 8 g/kg body weight/day, 
recommended fat intake (percentage of total energy) is 25%, 
SFA=10%, MUFA=10%, PUFA=10%, TFA <2% of TE.



SAJSM  vol 23  No. 3  2011                                                                                                                                77

males and 9  females. The food records were handed out and the 
subjects were given a pre-paid postage envelope to mail it back to 
the researcher. However, not all the subjects sent the completed 
food records back or responded to follow-up reminders. 
Dietary intake from diet does not include intake from additional sup-
plements. This approach was adopted because it proved impractical 
to quantify the amounts consumed from the supplements used cor-
rectly. The total energy intake of the athletes for men and women 
respectively were 14 535±4 510 kJ and 9 004±369 kJ. Upon calcu-
lating energy availability, the men and women had a mean energy 
availability of 162±58 kJ/kg fat free mass (FFM) and 144±56 kJ/kg/
FFM respectively. The results from the men and women differed sig-
nificantly (t=3.3; p=0.05). The macronutrient intake is summarised 
in Fig. 2.

The intake of most of the micronutrients fell within 67 - 133% 
of the dietary reference intakes (DRIs).

13
 The micronutrients with 

an intake below 67% of the DRIs for men included iodine 44% and 
fluoride 49% and for women, chloride 61%, iodine 31% and fluoride 
52%. Most of the micronutrients from dietary intake alone above 
133% of the DRI were still below the tolerable upper limit and not 
too excessive. The men’s intake of sodium, manganese and niacin 
was above the upper limit at 213%, 162% and 228% of the DRI 
respectively. Only the manganese intake of the women, 174% of the 
DRIs, fell above the upper limit. The micronutrients expressed as a 
percentage of the DRIs are shown in Fig. 3. 

Provision has been made in the Food Finder database for 
145 nutrients. Information is not yet available on all the nutrients. 
There may be a significant number of missing values for nutrients 
and micronutrient intake should be interpreted keeping in mind the 
limitations of the database.

A separate questionnaire was given to the subjects to report 
supplement and reasons for supplement use (N=26). Seventy-three 
per cent (N=19) of the triathletes used over-the-counter dietary 
supplements (chi-square; p=1.0). Supplement use is summarised in 
Table II. The athletes took supplements daily (35%) (N=9) several 
times a week (19%) (N=5) or during specific times, i.e. increased 
training or racing on consecutive weekends (19%) (N=5). Reasons 
why the triathletes were  taking the supplements are summarised in 
Fig. 4.

Discussion
This is the first study of its type in South Africa using triathletes as 
study population. The findings of this study contribute to the body of 
current knowledge on endurance athletes like runners and cyclists, 

TABlE II. Prevalence of supplement use among the triathletes

Supplement category Supplements Percentage triathletes (N=26)
Chi-square;
p-value

Increased muscle growth and repair Protein 100% (N=26) No value

Amino acids 27%   (N=7) p=0.7

Increased energy supply Carbohydrate 81%   (N=21) p=0.1

Creatine 12%   (N=3) p=0.5

Increased immune function Antioxidants 54%   (N=14) p=1.0

Glutamine 4%     (N=1) p=0.3

Increased joint health Glucosamine sulphate 4%     (N=1) p=0.3

CNS stimulants Caffeine 4%     (N=1) p=0.3

Fat reduction Carnitine 4%     (N=1) p=0.3

Electrolytes Salt tablets 19%   (N=5) p=0.6

General health Multivitamin and mineral 81%   (N=21) p=0.6

Vitamin B12 65%   (N=17) p=0.7

Single minerals 58%   (N=15) p=0.7

Iron 4%     (N=1) p=0.3

Calcium 4%     (N=1) p=0.3

Magnesium 27%   (N=7) p=0.2

Essential fatty acids 8%     (N=2) p=1.0

Herbal supplements* 42%   (N=11) p=0.7

Probiotics 4%     (N = 1) p=0.3

*Herbal supplements include ginseng, Echinacea, inositol, guarana and green tea extract.

Fig. 4. Reasons given by triathletes for taking supplements.



78               SAJSM  vol 23  No. 3  2011

but gives new insight on the nutritional status of triathletes. The key 
findings of the present study were that percentage body fat calculat-
ed from skinfold prediction equations generally correlated well with 
percentage body fat measured with MF-BIA. The percentage body 
fat of the men and women was at the upper end of the range as-
sociated with elite athletes and related more to the percentage body 
fat of amateur athletes. The athletes had a good dietary intake of 
micronutrients. The triathletes consumed less than optimal amounts 
of dietary carbohydrate and supplements were used widely, includ-
ing carbohydrate and protein supplementation even though dietary 
protein intake was adequate for both men and women. Fat intake 
was higher than the recommendation in both groups. 

Body composition
Percentage body fat calculated from skinfold prediction equations 
generally correlated well with percentage body fat measured with 
MF-BIA. Significant associations in both and men women were ob-
tained between percentage body fat calculated from skinfold meas-
urements and MF-BIA. The findings of this study support those de-
scribed by  Ostojic et al. 2005, who found that %BF from skinfold 
measurements and %BF from BIA correlated well in male athletes.

14
 

Dietary intake and supplement use
An athlete’s habitual dietary intake is very important to ensure that 
he or she meets the increased energy requirements of triathlon. The 
body’s ability to adapt to the stress of intense daily exercise depends 
on the adequacy of the athlete’s diet.

15
 The World Health Organiza-

tion defines energy requirement as ‘the level of energy intake from 
food that will balance energy expenditure when the individual has a 
body size and composition, and level of physical activity, consistent 
with long-term good health; and that will allow for the maintenance 
of economically necessary and socially desirable physical activity.’

16
 

The International Olympic Committee (IOC) recommends in its posi-
tion statement on nutrition for athletes that energy availability, rather 
than total energy requirements, should be calculated (135 kJ/kg/
FFM).

17
 They concluded that if energy availability is below the rec-

ommendation, that there can be changes in metabolic and hormonal 
function, which can affect sport performance and health in general. 
This is especially true for females where a reduced energy avail-
ability can influence reproductive health.

17
 The male and female ath-

letes in the present study had a higher than recommended energy 
availability. The women also had a higher than anticipated percent-
age body fat and a normal body mass index (BMI) and none of the 
women reported weight loss in the preceding months, which indi-
cates that the women are indeed in energy balance. The majority of 
the women also reported having regular monthly menses (77%). The 
women’s results for total energy intake also coincided with findings 
of Worme et al. (1990),

18
 who found the mean total energy intake of 

21 recreational female triathletes to be 9 058 kJ. They also reported 
the mean total energy intake for 50 male triathletes to be 11 591 kJ.

18

The evidence on importance of adequate carbohydrate intake for 
athletes has been described and concludes that muscle glycogen is 
the most important energy substrate during endurance exercise and 
a decreased intake can lead to less than optimal training, recovery 
post training and performance. A sub-optimal carbohydrate intake 
can also lead to  feeling fatigued, often not being able to finish training 
sessions due to a feeling of hitting the wall, lack of energy, heavy 
legs, slow rate of recovery, and loss of concentration, dizziness, 
irritability and fainting.

19
 The carbohydrate intake of 21 female and 

50 male recreational triathletes as reported by Worme et al. was 
5.1 g/kg body weight and 4.9 g/kg body weight for men and women 
respectively.

18
  Nogueira et al. (2004) also described the CHO intake 

of endurance athletes as 4.5 - 11.3 g/kg BW for males and 4.4 - 7.2 
g/kg BW for females.

20
 Frentsos et al. (1997) also reported that 6 

elite triathletes only had a carbohydrate intake of 4 g/kg BW before 
intervention.

21
 The male triathletes in the present study are meeting 

carbohydrate requirements and the female athletes are not meeting 
the recommended requirements, with an intake of 5.26 g/kg BW for 
men and 3.54 g/kg BW for women, respectively. Literature suggests 
that endurance athletes should have a carbohydrate intake of 5 - 7 g/
kg BW or 6 - 8 g/kg BW.

17,22
 However, the practical implementation of 

this recommendation should be taken into consideration, especially 
with the female athletes in the present study who have a higher than 
recommended percentage body fat and adequate energy availability. 
Most (81%) of the triathletes in our study group also consumed some 
form of a CHO supplementation and listed an increase in energy 
supply as one of the main reasons for taking supplements. This 
could make up for the inadequate dietary CHO intake; however 
quantifying the amount of CHO supplements taken in future studies 
is recommended.

The present study indicated that the dietary intake of protein for 
male triathletes was 1.95 g/kg BW and for female triathletes 1.20 g/
kg BW. Worme et al. reported the habitual protein intake of both male 
and female triathletes to be 1.4 g/kg body weight per day.

18
 Nogueira 

et al. reported a habitual dietary protein intake for endurance 
athletes as 1.2 - 2.0 g/kg body weight.

20
 Protein in combination with 

carbohydrate in an endurance athlete’s diet is especially important 
for recovery after training sessions and when carbohydrate intake 
after training is limited, such as a low appetite or short recovery 
periods. It is required to cover the increased losses of amino acids 
oxidised during exercise and to provide extra raw material to replace 
exercise-induced muscle damage.

23
 The requirements for protein in 

endurance athletes are higher than those of sedentary peers (1.2 - 
1.7 g/kg body weight v. 0.8 - 1.0 g/kg body weight)

22
 due to the fact 

that some amino acids (including the branched chain amino acids) 
are oxidised in larger amounts during exercise.

23
 All of the athletes 

in the present study also reported taking some form of protein 
supplementation, which is unnecessary as well as energy dense and 
can lead to weight gain.

Fat is a very important macronutrient for endurance athletes as 
it provides the training diet with essential fatty acids (EFAs) and 
fat-soluble vitamins. The male (35±10%) and female (30± 6.0%) 
triathletes in this study had a very high fat intake compared with 
the requirements of 25% of total energy intake.

1
 The distribution 

of the different types of fatty acids in this group was not according 
to prudent dietary guidelines and recommendations to increase 
sources of poly- and monounsaturated fatty acids while reducing 
saturated and total fat intake in the diet should be made. 

There are certain vitamin and mineral requirements that are 
increased during physical activity and according to the IOC, adequate 
intakes of iron, copper, manganese, magnesium, selenium, sodium, 
zinc, vitamin A, E, C, B6 and B12  necessary for optimal health 
and performance.

17
 It should be noted that supplementation of 

micronutrients are not required and that it only affects performance 
if the athlete has a deficiency of the nutrient.

7
 In the present study, 

the athletes had a good intake of micronutrients and most values 
fell within 67 - 133% of the DRIs. Micronutrients of which the intake 
was below 67%, such as iodine and fluoride, are not a concern as 
the athletes will take this in via iodated salt and toothpaste, which is 
not accounted for in the dietary analysis software programme. The 
micronutrient intake that fell above the 133% of the DRI is still below 
the tolerable upper level and not a concern. In a study by Striegel et 
al. (2006)

24
 on Master’s athletes, 61% of athletes were consuming 



SAJSM  vol 23  No. 3  2011                                                                                                                                 79

dietary supplements as compared with our study group in which 
73% took dietary supplements. The majority of the triathletes took 
a form of multivitamin supplementation which shows that they feel 
their diet is not providing adequate nutrition. They also indicated an 
inadequate diet or nutrient replacement as being a popular reason for 
using supplements. Other popular reasons for taking supplements 
included to provide an increased energy supply, optimise recovery, 
increase lean body mass and to support the immune function. 
According to the IOC, an athlete can take a multivitamin-mineral 
preparation to support a low energy or restricted diet, although in our 
study population this does not seem necessary.

17
  

Supplement use in athletes should be carefully monitored. 
Contamination of supplements and ingredients in supplements 
with no beneficial effect can harm athletes and the IOC has clear 
guidelines as to which supplements are recommended and which 
are banned.

25
 

Conclusion
In the present study we found that two of the popular field meth-
ods for determining percentage body fat in athletes do correlate well 
when the appropriate equations are used. Our dietary intake findings 
were that the triathletes had a high energy availability and consumed 
enough dietary carbohydrate and protein. The fat intake was higher 
than the recommendation in both groups. Supplements were also 
widely used among the athletes. Recommendations for future stud-
ies would be to include a larger study population as it would be bene-
ficial to have a large enough study population to divide the group into 
subgroups of elite and amateur athletes. Future studies can also go 
into more depth regarding quantifying the supplements used by the 
athletes and adding this to determine their habitual dietary intake. 
Timing of nutrient intake in relation to training would also provide 
valuable information in future studies.

References 
1. American Dietetic Association. Position of the American Dietetic Associa-

tion Dietitians of Canada and the American College of Sport: Nutrition and 
Athletic performance. J Am Diet Assoc 2009;109:509-527. 

2. Knechtle B, Wirth A, Baumann B, Knechtle P, Rosemann T and Senn 
O. Differential correlations between anthropometry, training volume, and 
performance in male and female Ironman athletes. J Strength Cond Res 
2010;24(10):2785-2793.

3. Garcia AL, Wagner K, Hothorn T, Koebnick C, Joachim H, Zunfit F, Trippo 
U. Improved prediction of body fat by measuring skinfold thickness, cir-
cumferences, and bone breadths. Obesity Research 2005;13(3):626-634.

4. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gomez JM, 
et al. Bioelectrical Impedance Analysis – part 1: Review of principles and 
methods. Clin Nutr. 2004;23:1226-1243.

5. Bentley D, Cox G, Green D, Laursen P. Maximising performance in tri-
athlon: Applied physiological and nutritional aspects of elite and non-elite 
competitions. J Sci Med Sport 2008;11(4):407-417.

6. Knez W, Peake J. The prevalence of vitamin supplementation in ultraen-
durance triathletes. Int J Sport Nutr Ex Met 2010;20(6):507-514.

7. Maughan RJ, Depiesse F, Geyer H. The use of dietary supplements by 
athletes. J Sport Sci 2007;25(SI):S103-S113.

8. Lee RD, Nieman DC. Nutritional Assessment. 3rd ed. 2003:63-215.
9. Evans EM, Rowe DA, Misic MM, et al. Skinfold prediction equation for 

athletes developed using a four-component model. Med Sci Sports Exerc 
2005;2006-2011.

10. Jackson AS, Pollock M. Practical assessment of body composition. Phys 
Sport Med 1985;13:76-90.

11. Body byte® Pro V3.20. Body and Nutrition Manager software program.
12. Durnin JVGA, Womersley J. Body fat assessed from total body density 

and its estimation from skinfold thickness: measurements on 481 men and 
women aged from 16-72 years. Br J Nutr 1974;34:77-97.

13. Dietary Reference Intakes. Nutrition Information Centre of the University of 
Stellenbosch. 2003. Adapted from: Dietary Reference Intakes. The essen-
tial guide to nutrient requirements. 2001. Institute of Medicine. Washington: 
The National Academic Press. 

14. Ostojic SM. Estimation of body fat in athletes: Skinfolds vs. bioelectrical 
impedance. J Sports Med Phys Fitness 2005;46(3):442-446.

15. Laursen PB, Rhodes EC. Factors affecting performance in an ultra-endur-
ance triathlon. Sports Med 2001;31(3):195-209.

16. World Health Organization website [Online] [access 2008, June]; Avail-
able: http://www.who.int/bmi/index

17. Burke LM. The IOC consensus on sport nutrition 2003: New guidelines for 
nutrition for athletes. 2003;13(4):549-52.

18. Worme JD, Doubt TJ, Singh A, et al. Dietary patterns, gastrointestinal com-
plaints, and nutrition knowledge of recreational triathletes. Am J Clin Nutr 
1990;51:690-697.

19. Ivy JL. Role of carbohydrate in physical activity. Clin Sports Med. 
1999;18(3):469-484

20. Noguiera JA, Da Costa TH. Nutrient intake and eating habits of triathletes 
on a Brazilian diet. Int J Sport Nutr Exerc Metab 2004;14(6):684-697.

21. Frentsos JA, Baer JT. Increased energy and nutrient intake during training 
and competition improves elite triathlete’s endurance performance. Int J 
Sport Nutr 1997;7:61-71.

22. Hawley JA, Burke LM. Peak performance: Training and nutritional strate-
gies for sport. Sydney: Allen and Unwin, 1998.

23. Tipton KD, Wolfe RR. Protein and amino acids for athletes. J Sport Sci 
2004;22(1):65-79.

24. Striegel H, Simon P, Wurster C. The use of nutritional supplements among 
master athletes. Int J Sports Med 2006;27:236-241.

25. The World Anti-doping Code. The 2010 prohibited list International Stand-
ard. 2010 [Online] [access 2010, September]; Available:http://www.wada-
ama.org/Documents/World_Anti-Doping_Program/WADP-Prohibited-list/
WADA_Prohibited_List_2010_EN.pdf.