Open Access

The age-gender-status profile of high performing athletes in the UK taking nutritional supplements: Lessons for the future

Journal of the International Society of Sports Nutrition20085:2

DOI: 10.1186/1550-2783-5-2

Received: 27 September 2007

Accepted: 10 January 2008

Published: 10 January 2008

Abstract

Background

Owing to the mechanics of anti-doping regulation via the World Anti-Doping Agency's Prohibited List, nutritional supplement use received little attention in comparison to the prevalence of doping. The aims of this study were to investigate supplement use, identify groups of athletes with high levels of supplement use and the prevalence of concomitant use of supplements.

Methods

Survey data from 847 high-performing athletes in the UK were analysed using descriptive statistics. The survey, conducted by UK Sport, consisted of questions regarding knowledge of the prohibited substances, testing procedure, nutritional supplement use and perceptions of the doping problem. The proportion of supplement users and the relative use of each supplement were compared by age, gender and professional status.

Results

Among 874 high-performing athletes in the UK sample, 58.8% of them reported the use of at least one nutritional supplement. Among supplement users, 82.6% used more than one and 11.5% reported use of more than five nutritional supplements. Of the 9 supplements listed, multivitamins (72.6%) and vitamin C (70.7%) were used most, followed by creatine (36.1%), whey protein (31.7%), echinacea (30.9%), iron (29.9%) and caffeine (23.7%). Less than 11% reported the use of magnesium or ginseng. Creatine use was typically associated with males regardless of status and across all ages, whereas iron was characteristically used by females. A 'typical' supplement user is male, between 24 and 29 years of age, involved in professional sport and using a combination of supplements. Male professional players between age 30 and 34 years, and female non-professional athletes between 24 and 29 years of age also represented a considerable proportion of supplement users. Athletes older than 40 years of age were practically non-users. Concomitant use of supplements is characteristic of male users more than females.

Conclusion

As supplement use has been previously shown to increase the probability of prohibited substance use, groups exhibiting high use of nutritional supplements should be monitored. Future research should incorporate a wide range of supplements and enquire about the daily amount ingested. In addition to tutoring, preventive measures should incorporate offering acceptable and healthy alternatives for assisted performance enhancement.

Background

Owing to the mechanics of the anti-doping regulation via the World Anti-Doping Agency's Prohibited List, nutritional supplement use has received little attention in the past in comparison to the prevalence of doping despite a growing body of evidence, which supports the assumption that performance enhancing supplement use positively correlates with the probability of prohibited performance enhancing substance use [13]. Supplement taking has also been used as a proxy for attitude toward prohibited substances [4]. A noticeable positive association was found between supplement use and i) a perception that doping is a problem and ii) knowledge of doping testing procedure. The interpretation of such findings may be that supplement users have the need or desire to assist their performance but wish to do so by legal means, or alternatively, supplement use is the first step in their 'pharmacological training' [5].

Another reason that underscores the importance of research into supplement use is the pressure for constant enhancement of sport performance and the need for control of performance enhancement. In the UK, the Science and Technology Committee of the UK Parliament House of Commons conducted an extensive investigation into human performance enhancement in sport [6]. Among the recommendations, all stakeholders were urged to increase their research effort aiming to find acceptable legal alternatives for performance enhancements. One of these legal alternatives is the confidence in nutritional supplements with proven ergogenic effects. However, certain nutritional supplements can also be detrimental to health; hence their use should be closely monitored.

Vitamins A (retinol), D, E, and K are stored in the liver and in body fat stores hence they do not need to be taken every day. Some are toxic if an excess amount is consumed. For example, evidence was found that beta-carotene supplements and retinol supplements may increase the risk of lung cancer and there is suggestive evidence that links selenium to skin cancer [7]. In a recent meta-analysis of primary and secondary treatment with antioxidant supplements, beta-carotene, vitamin A and E were also found to increase mortality but there was no convincing evidence for harmful effects of selenium or vitamin C [8]. Despite the fact that water-soluble vitamins (i.e. C, B) are excreted in the urine rather than stored in the body, there is evidence suggesting that vitamin C, especially in combination with iron [9] can cause damage to the gastrointestinal tract (GI) and initiate or aggravate symptoms associated with chronic GI disorders. A high intake of iron, especially in combination with manganese doubles the risk for Parkinson's disease [10]. Unnecessary cobalt ingestion results in enhanced oxidative stress leading to organ damage and dysfunction in liver and kidney, and also impairs thyroid activity and myocardial function [11]. In addition to the potential hazard of positive doping tests [12, 13], contamination may also pose health risks such as lead contamination in calcium products [14].

In this study, we provide a nutritional supplement users' profile of UK high-performance athletes to inform policy makers and researchers. The aims of this report were to: i) describe the profile of supplement users by age, gender and professional status and ii) describe the prevalence of supplement use and multiple supplement use among high-performing athletes.

Methods

Data

Data were collected by the UK Sport for the 2005 Drug Free Sport [15] report among high performing athletes in the UK, aged 18 years and over. At the start of the project, 2995 surveys were sent to randomly selected athletes via the respective Sports councils or Professional bodies. As the participation was voluntary with no selection criteria, all athletes had an equal chance of being included in the sample. The survey data of 874 athletes were re-analysed to identify athlete groups with extensive supplement use. In the overall sample European football was represented with 17.4%, followed by badminton (14.7%), athletics (11.3%), cricket (7.2%), rugby (6.6%), swimming (6.4%) and cycling (6.2%). The remaining 36.7% comprised 30 different sports [15], each contributing less than 3.5%. Professional athletes (n = 272) were from football (52.9%), cricket (12.5%), rugby union (21.3%), tennis (5.5%), ice hockey (4.1%) and basketball (3.7%). Non-professionals were lottery-funded athletes from 34 sports (some with disability variations). Sports represented in the full and supplement user samples are listed in Table 1.
Table 1

The distribution of lottery funded athletes in the full and supplement user samples by sports and gender

Sport

Full sample n = 874 (100%)

Supplement users n = 520 (100%)

 

Male

Female

Male

Female

Archery

4 (< 1%)

2 (< 1%)

1 (< 1%)

1 (< 1%)

Athletics a

53 (6.1%)

44 (5.0%)

26 (5.0%)

35 (6.7%)

Badminton

30 (3.4%)

34 (3.9%)

8 (1.5%)

18 (3.5%)

Boccia

1 (< 1%)

0

0

0

Boxing

10 (1.1%)

0

4 (< 1%)

0

Canoeing

16 (1.8%)

8 (< 1%)

9 (1.7%)

8 (1.5%)

Cricket

14 (1.6%)

15 (1.7%)

3 (< 1%)

7 (1.4%)

Cycling

39 (4.5%)

19 (3.6%)

29 (5.6%)

16 (3.1%)

Diving

1 (< 1%)

3 (< 1%)

0

3 (< 1%)

Equestrian

0

7 (< 1%)

0

1 (< 1%)

Fencing b

1 (< 1%)

0

0

0

Football (European)

0

8 (< 1%)

0

5 (1.0%)

Golf

9 (1.0%)

11 (1.2%)

1 (< 1%)

5 (1.0%)

Gymnastics

12 (1.3%)

8 (< 1%)

5 (1.0%)

3 (< 1%)

Hockey

11 (1.2%)

7 (< 1%)

5 (1.0%)

4 (< 1%)

Ice skating

1 (< 1%)

3 (< 1%)

1 (< 1%)

1 (< 1%)

Judo

4 (< 1%)

7 (< 1%)

4 (< 1%)

4 (< 1%)

Karate

1 (< 1%)

1 (< 1%)

1 (< 1%)

0

Modern Pentathlon

2 (< 1%)

8 (< 1%)

1 (< 1%)

6 (1.1%)

Netball

0

8 (< 1%)

0

2 (< 1%)

Powerlifting

1 (< 1%)

1 (< 1%)

0

0

Rowing

14 (1.6%)

10 (1.1%)

12 (2.3%)

8 (1.5%)

Sailing

9 (1.0%)

6 (< 1%)

4 (< 1%)

0

Shooting a

10 (1.1%)

9 (1.0%)

3 (< 1%)

1 (< 1%)

Squash

8 (< 1%)

5 (< 1%)

5 (1.0%)

5 (1.0%)

Swimming a

27 (3.1%)

29 (3.3%)

17 (3.3%)

19 (3.6%)

Table tennis a

3 (< 1%)

5 (< 1%)

0

4 (< 1%)

Taekwondo

0

2 (< 1%)

0

1 (< 1%)

Triathlon

1 (< 1%)

7 (< 1%)

0

6 (1.1%)

Tennis a

0

3 (< 1%)

0

2 (< 1%)

Waterskiing

2 (< 1%)

0

0

0

Wheelchair basketball b

54 (6.2%)

1 (< 1%)

2 (< 1%)

1 (< 1%)

Wheelchair rugby b

5 (< 1%)

1 (< 1%)

3 (< 1%)

1 (< 1%)

Wheelchair tennis b

2 (< 1%)

0

1 (< 1%)

1 (< 1%)

Missing data on sport

285 (32.6%)

15 (1.7%)

193 (37.1%)

8 (1.5%)

Missing data on gender

5 (< 1%)

   

Total

580 (66.4%)

289 (33.1%)

338 (65.0%)

182 (35.0%)

Percentages to full sample and supplement user sample are in parentheses.

a Includes disability sport.

b Disability sport only

Statistical analyses

Results are presented as descriptive statistics summarised in tables and charts. For the relative use of each supplement by athlete groups, the number of users of a given supplement was divided by the total number of supplement users in the respective age-gender-status group. The use of each supplement per sub-group is shown as a proportion of the 100% for the given supplement. Chi-square goodness of fit statistics test was used to establish significant differences between the proportion of each age-gender-status group in the full sample and among supplement users. Chi-square statistics test was performed under the assumption that the proportion of each subgroup in the supplement user sample does not differ from the proportion of each subgroup observed in the random sample (H0: expected frequency = observed frequency). If sufficient evidence is found to reject the null hypothesis, it suggests that the proportion of a given subgroup among supplement users in the population is higher or lower than it could be expected by random chance. The statistically significant difference, however, does not necessarily manifest in a large difference in the sample.

Results

Of the 2995 questionnaires distributed, 874 were returned and 520 met the criteria for further analysis for supplement use (346 indicated no use of nutritional supplements and 8 were excluded because of missing data).

The supplement user athlete sample comprised of 191 professional (186 male and 5 female) and 329 lottery-funded (152 male and 177 female) athletes from 31 sports (Table 1). The most dominant age group among male supplement user athletes was the 24 – 29 years of age group (31.6%), whereas the largest proportion (34.6%) of females supplement users was the 19 – 23 years age group (Figure 1).
Figure 1

Age distribution of male and female supplement user athletes (n = 520).

Among the supplements, the use of multivitamins and vitamin C were reported by 72.6% and 70.7%, respectively. Creatine was used by 36.1%, followed by whey protein (31.7%), echinacea (30.9%), iron (29.9%), caffeine (23.7%) and magnesium or ginseng with less than 11%.

User profile

Overall, the supplement user sample (n = 520) did not differ significantly from the entire cohort, but for three sub-groups (Figure 2). The supplement user proportion of the 24–29 years old male professional athletes who reported supplement use was increased by 3% (χ2 = 4.46, p = .035), from 10% (proportion of the 24–29 years old professional male athletes in the total sample) to 13% (proportion of the 24–29 years old professional male athletes who reported supplement use in the total supplement user sample). Similarly, the proportion of the 24–29 years old female lottery funded athletes has increased from 7% to 10% (χ2 = 5.18, p = .023) in the supplement user cohort relative to the full sample. The proportion of the under-18 years old male lottery-funded athletes slightly decreased from 12% in the full sample to 8% in the supplement user cohort (χ2 = 9.18, p = .002). Although the change in the sample appears to be small (3 – 4%), it suggests that the characteristics of the identified groups (a combination of gender, age and status) related to supplement use in the athlete population. Athletes over 40 years of age represented 4.1% of the athletes in the full sample and only 1.7% in the supplement user sample (Figures 1 and 2).
Figure 2

Comparison of relative percentage (Y-axis) of athlete subgroups in the full sample (n = 874) and supplement user sample (n = 520).

The most dominant group among supplement users appears to be the male, professional in the 24–34 years age group (Figure 2). This resonates with the literature where male athletes were found to be more likely to use performance enhancements [2, 3, 1618]. Observed supplement use was also comparably high among female athletes between age 24 and 29 years (Figure 2).

Figures 3 and 4 show concomitant use of nutritional supplements by age and status groups for both genders. The use of each supplement itself represents 100% (which is the case if all supplement user athletes reported the use of a given supplement) and the reported usage of each supplement by age and status groups are stacked to facilitate comparison between the subgroups. From the graphs it is apparent that a fairly balanced multiple use of supplements is a characteristic of the male athlete supplement user population (Figure 3). Female supplement users reported taking fewer supplements in combinations and their choices appeared to be dominated by health maintenance with multivitamin and vitamin C (Figure 4).
Figure 3

Relative use of nutritional supplements by age and status among male supplement users (n = 520).

Figure 4

Relative use of nutritional supplements by age and status among female supplement users (n = 520).

Multivitamins and vitamin C were equally the most ingested supplement by athletes from both genders (Figure 5) but the proportion of female users was less than the proportion of male users. Creatine was predominantly used by male athletes whereas the use of iron was relatively high among female athletes.
Figure 5

Relative percentage of each supplement used by gender (n = 520).

Supplement use

The average number of supplements used by athletes in the users' sample was 3.22 (1674 instances with 520 athletes), indicating that supplements are used in combinations. Of the 520 supplement users, 82.6% reported the use of more than one supplement (Table 2). Among them, 23.7% used two and a further 21.6% used three supplements. This is congruent with the analysis of the declaration report used during drug testing at the 2000 Sydney Olympics [19], where alarmingly high overuses of vitamins were found among 2758 athletes. Concomitant use of nutritional supplements is typical in general population as well with a wider range of supplements ingested daily. Multiple supplement users tend to take a combination of multivitamin, B-complex, vitamin C, E, D, carotenoids, calcium, omega-3 fatty acids, flavonoids, lecithin, alfalfa, coenzyme Q10, glucosamine and herbal immune supplements daily [20]. In the UK sport sample, the list of nutritional supplements was limited to nine supplements plus the 'other' category. Even so, 11.5% reported using more than 5 supplements with dosage unknown. Higher than average (> 3.22) number of supplements used were reported in the following groups: 24–29 years old male athlete (4.03), 19–23 years old female professional (4.00), 29–29 years old male professional (3.84), 35–39 years old female athlete (3.67), 19–23 years old male professional (3.52), 35–39 years old male professional (3.47).
Table 2

Prevalence of multiple supplements use in the full sample (n = 874) and among supplement users (n = 520)

Number of supplements reported

% of all athletes

% of all supplement users

None

40.2

 

1 supplement

10.4

17.4

2 supplements

14.2

23.7

3 supplements

12.9

21.6

4 supplements

9.8

16.4

5 supplements

5.6

9.4

6 supplements

3.2

5.4

7 supplements

1.8

3.1

8 supplements

1.0

1.7

9 supplements

0.8

1.3

Conclusion

The results deserve attention for multiple reasons: i) nutritional supplements obtained from unknown sources may be contaminated and pose an involuntary doping offence [13], ii) a combination of supplements can potentially be dangerous [21], and iii) most importantly, supplement use increases the probability of prohibited substance use [2].

Assisting sports performance by allowable means is an acceptable behaviour to most athletes who are involved in competitive sport. Physiological, biomechanical, medical, psychological and nutritional supports are routinely provided to high performing athletes and during the natural course of the athlete development, athletes are accustomed to technologies and methods for human performance enhancement. According to the life-cycle model of performance enhancement doping practices likely to grow out of habitual engagement in a range of acceptable performance enhancement practices [22].

Therefore, the results of this paper have strong practical applications. Groups exhibiting high use of nutritional supplements should be given attention to prevent transgression toward prohibited methods. Research is urgently needed to identify risk factors, inform anti-doping deterrence and foster targeted interventions. As athletes are more likely to be honest about using supplements rather than reporting on prohibited substances, self-reported supplement use may be successfully applied as a proxy for the perceived need for assisted performance enhancement and is easily used as a screening tool. Future studies should incorporate a wide range of supplements and investigate the daily amount ingested. Groups exhibiting high use of nutritional supplements should be given attention to prevent transgression toward prohibited methods. Preventive measures should incorporate offering alternatives for assisted performance enhancement.

Declarations

Acknowledgements

The authors thank Allison Holloway and Jerry Bingham from UK Sport for providing the data and their support for this paper.

Authors’ Affiliations

(1)
School of Life Sciences, Faculty of Science, Kingston upon Thames, Kingston University

References

  1. Goldberg L, MacKinnon DP, Elliot DL, Moe EL, Clarke G, Cheong J: The adolescents training and learning to avoid steroids program: preventing drug use and promoting health behaviours. Arch Pediatr Adolesc Med. 2000, 154: 332-338.View ArticlePubMedGoogle Scholar
  2. Papadopoulos FC, Skalkidis I, Parkkari J, Petridou E, "Sports Injuries" European Union Group: Doping use among tertiary education students in six developed countries. Eu J Epidemiol. 2006, 21: 307-313. 10.1007/s10654-006-0018-6.View ArticleGoogle Scholar
  3. Yussman SM, Wilson KM, Klein JD: Herbal products and their association with substance use in adolescents. J Adolesc Health. 2006, 38: 395-400. 10.1016/j.jadohealth.2004.10.015.View ArticlePubMedGoogle Scholar
  4. Mazanov J, Petróczi A, Bingham J, Holloway A: Towards an empirical model of performance enhancing supplement use: A pilot study among high performance UK athletes. J Sci Med Sport. 2007Google Scholar
  5. Brissonneau C: Deviant Careers: The case of cycling. WADA International Conference "Ethics and Social Science Research in Anti-Doping". Larnaca, Cyprus, 2006 April 13–14
  6. UK Parliament, The House of Commons, Science and Technology Committee: Human enhancement technologies in sport. HC 67. 2007, London: The Stationary Office Limited, [http://www.publications.parliament.uk/pa/cm200607/cmselect/cmsctech/67/67.pdf]Google Scholar
  7. World Cancer Research Fund/American Institute for Cancer Research: Food, nutrition, physical activity, and the prevention of cancer: a global perspective. 2007, Washington DC: AICR, [http://www.dietandcancerreport.org/downloads/Second_Expert_Report.pdf?JServSessionIdr012=h72yup5vx1.app44a]Google Scholar
  8. Bjelakovic G, Nikolova D, Gluud LL, Simonetti RG, Gluud C: Mortality in randomised trials of antioxidant supplements for primary and secondary prevention. JAMA. 2007, 297: 842-857. 10.1001/jama.297.8.842.View ArticlePubMedGoogle Scholar
  9. Fisher AEO, Naughton DP: Iron supplements: the quick fix with long-term consequences. Nutr J. 2004, 3: 2-10.1186/1475-2891-3-2.PubMed CentralView ArticlePubMedGoogle Scholar
  10. Powers KM, Smith-Weller T, Franklin GM, Longstreth WT, Swanson PD, Checkoway H: Parkinson's disease risks associated with dietary iron, manganese, and other nutrient intakes. Neurology. 2003, 60: 1761-1766.View ArticlePubMedGoogle Scholar
  11. Lippi G, Franchini M, Guidi GC: Blood doping by cobalt. Should we measure cobalt in athletes?. J Occupational Med Toxicol. 2006, 1: 18-10.1186/1745-6673-1-18.View ArticleGoogle Scholar
  12. Kamber M, Baume N, Saugy M, Rivier L: Nutritional supplements as a source for positive doping cases?. Int J Sport Nutr Exerc Metab. 2001, 11: 258-263.PubMedGoogle Scholar
  13. Maughan RJ: Contamination of dietary supplements and positive drug tests in sport. J Sports Sci. 2005, 23: 883-889. 10.1080/02640410400023258.View ArticlePubMedGoogle Scholar
  14. Scelfo GM, Flegal AR: Lead in Calcium Supplements. Environmental Health Perspectives. 2000, 108: 309-313. 10.2307/3454348.PubMed CentralView ArticlePubMedGoogle Scholar
  15. UK Sport 2005 Drug Free Survey. [http://www.uksport.gov.uk/assets/File/Generic_Template_Documents/Publications/Drug_Free_Sport/2005%20Drug-Free%20Sport%20Survey.pdf]
  16. Wichstrom L: Predictors of Future Anabolic Androgenic Steroid Use. Med Sci Sport Exerc. 2006, 38: 1578-1583. 10.1249/01.mss.0000227541.66540.2f.View ArticleGoogle Scholar
  17. Schofield DE, Unruh S: Dietary supplement use among adolescent athletes in Central Nebraska and their sources of information. J Strength Cond Res. 2006, 20: 452-455. 10.1519/R-16984.1.Google Scholar
  18. Ronsen O, Sundgot-Borgen J, Maehlum S: Supplement use and nutritional habits in Norwegian elite athletes. Scand J Med Sci Sports. 1999, 9: 28-35.View ArticlePubMedGoogle Scholar
  19. Corrigan B, Kazlauskas R: Medication use in athletes selected for doping control at the Sydney Olympics (2000). Clin J Sports Med. 2003, 13 (1): 33-40. 10.1097/00042752-200301000-00007.View ArticleGoogle Scholar
  20. Block G, Jensen CD, Norkus CD, Dalvi TB, Wong LG, McManus JF, Hudes ML: Usage patterns, health, and nutritional status of long-term multiple dietary supplement users: a cross sectional study. Nutr J. 2007, 6: 30-10.1186/1475-2891-6-30.PubMed CentralView ArticlePubMedGoogle Scholar
  21. Petróczi A, Naughton DP: Supplement use in sport: is there a potentially dangerous incongruence between rationale and practice?. J Occup Med Toxicol. 2007, 2: 4-10.1186/1745-6673-2-4.PubMed CentralView ArticlePubMedGoogle Scholar
  22. Petróczi A, Aidman E: Psychological drivers in doping: a developmental vulnerability model. 5th Play the Game Conference. Reykjavik, Iceland, 2007 October 28 – November 2

Copyright

© Petroczi and Naughton; licensee BioMed Central Ltd. 2008

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.