The effects of anti-doping measures on sports performance in weightlifting

Eduard Bezuglov^1,2, Georgiy Malyakin^1,2, Danila Telyshev¹_,Ryland Morgans¹, Artemii Lazarev³, Elizaveta Kapralova^1,2, Olga Sadkovaya⁴, Oleg Talibov⁵

¹ Department of Sports Medicine and Medical Rehabilitation, Sechenov First Moscow State Medical University, Russia,

² High performance sports laboratory, Sechenov First Moscow State Medical University, Russia

³ Department of Internal Medicine, Mount Sinai Hospital, Chicago, Illinois, USA,

⁴ N.A. Semashko Public Health and Healthcare Department, F.F. Erisman Institute of Public Health, Sechenov First Moscow State Medical University, Moscow, Russia

⁵ Department of Therapy, Clinical Pharmacology and Ambulance Care, Moscow Medical University of Medicine and Dentistry, Russia

Corresponding author: Georgiy Malyakin, e-mail: manuljke@gmail.com

Abstract

Background

Evaluating anti-doping measures is essential to optimize their effectiveness. Comparing performance results in sports with a higher doping prevalence, such as weightlifting, before and after the implementation of anti-doping measures may serve as an effectiveness indicator.

Methods

The results of the most successful weightlifters of both sexes in two time periods, 2009-2015 and 2016-2022 were analyzed. The Sinclair Total (ST) to compare the relative strength of weightlifters from different weight categories was calculated.

Results

A significant decrease in the ST during 2016-2022 (p<0.001) in athletes of all ages and both sexes overall was reported. When analyzed by age, there was a decrease in ST in juniors and seniors of both sexes (p=0.010 and p<0.001, respectively), but not in youth. There was a decrease in the ST in senior men (p<0.001), junior women (p<0.001) and senior women (p<0.001).

Conclusion

In elite weightlifting, the results among adult athletes became worseduring the period 2016-2022, which may partly be explained by the implementation of new detection protocols of long-term anabolic androgenic steroid metabolites as well as other policies.  This may indicate the effectiveness of this method both in the prevention and detection of anti-doping rule violations.

Keywords: Anabolic androgenic steroid, Olympic weightlifting, doping in sports, weightlifting, long-term metabolites

Introduction

          Doping is one of the most pressing and prevalent issues in the sports world. Some athletes use various doping methods to improve performance results, while World Anti-Doping Agency (WADA) constantly increase their efforts to combat doping use. These efforts include increasing the total number of doping samples, conducting targeted testing, storing samples for ten years for further analysis, forming testing pools, as well as developing and introducing new methods of direct and indirect determination of prohibited substance use [1]. Moreover, WADA implemented anti-doping education as one of their strategic priorities in both the 2015-2019 and 2020-2024 strategic plans [2, 3]. Additionally, it has increased the severity of punishment for anabolic androgenic steroids (AAS) use since 2015, extending disqualification periods from 2 to 4 years [4]. Most likely, there remains a discrepancy between the number of prohibited substances and the metabolites found in samples and their actual use. Thus, the number of samples containing prohibited substances in athletics does not exceed 2%, however, in a study by Ulrich et al. it was demonstrated that the actual athlete use can be much higher and reach 43-57% [5]. This existing discrepancy indicates that WADA, and leading sports organizations, need to further develop to achieve maximum effectiveness in the fight against doping.

To optimize anti-doping measures, their effectiveness must be evaluated. One way to accomplish this is to compare performance results in sports with a high doping prevalence before and after the implementation of anti-doping measures. This approach has been previously used to assess the influence of the implementation of the Athlete Biological Passport (ABP) in elite female runners and the introduction of new methods for detecting AAS in female athletics [6, 7]. These athletes have historically had a high prevalence of doping and less subjective scoring of competition results, thus highlighting them suitable candidates for such examinations.

Weightlifting is another sport with a high doping prevalence. It is conducted indoors, with minimal influence from environmental factors, and the final result is based on the sum of best attempts in snatch and clean & jerk, with no significant rule changes in recent decades. Weightlifting as a sport has recently gained notoriety for doping prevalence to the extent that its exclusion from the Olympics was considered [8]. Adverse analytical findings in weightlifting over the last decade account for 1.28 to 3.36% (one of the highest percentages among Olympic sports) of cases with AAS being the most common cause [1]. According to Kolliari-Turner et al. there were 565 anti-doping sanctions in weightlifting between 2008 and 2019, with 82% related to AAS [9]. This widespread of violation because of AAS usage should not be surprising. The positive effect of AAS on muscle hypertrophy and strength has been previously convincingly proven, explaining the main reason for their inclusion on the World Anti-Doping Agency Prohibited List [10].

Tighter doping control can be achieved by increasing the number of doping samples and introducing new AAS detection methods, leading to increased detection and subsequent decreased AAS use, which may potentially result in decreased performance. Examples of such methods include the identification of long-term AAS metabolites and the use of highly sensitive chromatographic/mass spectrometric techniques, which enable AAS detection for a longer period and at lower concentrations of the substance in the sample [6, 11]. Additionally, the implementation of the ABP steroidal module enables AAS detection even after the drug has been eliminated from the body [12-14].

Thus, the aim of our study was to compare performance results in weightlifting before and following the implementation of anti-doping measures and increased sample collection. We hypothesized that there would be a decrease in performance results. Furthermore, the most significant decrease should occur among adult weightlifters, since an age group analysis of 565 weightlifter disqualifications from 2009 to 2022 showed that 69.6% (396 people) were adult, 20.04% (114 people) were junior and only 9.67% (55 people) were youth [15].

Methods

          Using competition protocols obtained from the official website of the International Weightlifting Federation (IWF), an analysis of the results achieved by the most successful male and female weightlifters from various age groups during two distinct time periods, 2009-2015 and 2016-2022 was conducted [16]. The 2017 World Senior Championship was excluded from the analysis as athletes from China, Kazakhstan, Russia, Armenia, Azerbaijan, Moldova, Turkey, Ukraine, and Belarus did not compete due to numerous anti-doping rule violations [17].

For the purposes of this study, we defined "most successful athletes" as those who achieved a place within the top 10 in the largest international competitions for their respective age groups, which included the World Weightlifting Championships for youth (age 13-17), juniors (age 15-20), and seniors (older than 15 years old), as well as the Olympics for seniors [18]. The final analysis included the results obtained from a total of 10 World Youth Championships, 13 World Junior Championships, 10 World Senior Championships, and 3 Olympic Games held between 2009 and 2022.

The athletes belonged to the age and weight class in which they were at the time of a particular competition.

In olympic weightlifting, the comparison of athletes from different weight categories is often carried out using the Sinclair coefficient, where Sinclair coefficient is multiplied by the athlete's actual total to produce the Sinclair Total (ST). The Sinclair coefficient allows for standardization of athlete’s results, and is calculated based on the world record holder’s body weight in the heaviest weight class and their corresponding result. The Sinclair coefficient is updated for each Olympic Cycle to account for the most recent records and is calculated using the formula

The mean ST was compared between weight groups, as per the classification previously described by Gottwald et al. and adjusted to the new weight categories implemented by the IWF in 2018 [22]. (Table 1)

Table 1. Breakdown of weight groups and categories.

Number of doping samples and taken in weightlifting between 2009 and 2021 was taken from WADA Anti-Doping Testing Figures Report for analysis of changes between researched periods. [1]

Statistical analysis

For statistical analysis, Jamovi 2.2.5 software, which is an internationally developed open-source project was used. The ST using mean, standard deviation, minimum, and maximum values in a normal distribution were described. The normality of data distribution using the Shapiro-Wilk test was checked. Student's T-test to compare differences between two groups with normal distribution of ST was used. Age categories were analyzed separately and the T-test was applied in these categories for independent variables (Sinclair Total and number of taken samples). If significant, Cohen mean difference and effect size were reported. For non-normal distribution, Mann-Whitney test were used, and the mean difference and rank biserial correlation if significant were reported. Finally, ANOVA was used to compare three or more groups, followed by Tukey's pairwise analysis. The results were considered statistically significant at p<0.05.

Results

A total of 5703 performance results from 3014 weightlifters (including both sexes, youth, juniors, and adults) were analyzed from 2009 to 2022. The first period accounted for 2823 results of 1619 weightlifters, while the second period accounted for 2880 results of 1395 weightlifters.

Change in the ST among weightlifters from both sexes

A significant decrease in ST was found between 2016-2022 and 2009-2015 (average difference: -8.8 (4.9-12.7), effect size: 0.12 (0.06-0.17), p<0.001). Sub-dividing all participants from both sexes by age group showed a statistically significant decrease in juniors and seniors (p=0.010 and p<0.001, respectively), but not in youth (p=0.39) athletes from both sexes.

Change in the ST in male and female weightlifters with and without weight consideration

The analysis of overall ST for all age groups revealed a decrease in 2016-2022 compared to 2009-2015 for both men and women (p=0.015 and p<0.001, respectively) (Figure 1). Furthermore, there was a decrease in ST in senior men (p<0.001), junior women (p<0.001), and senior women (p<0.001) when analyzed separately.

Figure1. Change in ST in male and female weightlifters in respective time periods

Change in the ST in male and female youth weightlifters

There was no significant difference in ST in youth male (p=0.33, p=0.54, p=0.97 in light, middle and heavy weight groups respectively) and female (p=0.91, p=0.99, p=0.65 for the same groups) weightlifters at the analyzed time periods.

Change in the ST in male and female junior weightlifters

The ST decreased among male junior weightlifters from the lightweight category (p=0.010, mean difference –7.3), and female middleweight (p=0.037, mean difference 5.3, rank biserial correlation 0.14) and heavyweight (p=0.049, mean difference 6.0, rank biserial correlation 0.13) groups. However, there was no ST decrease observed in other junior weightlifting groups (Figures 2 and 3).

Figure2. ST comparison among male junior weightlifters

Figure3. ST comparison among female junior weightlifters

Change in the ST in male and female senior weightlifters

When analyzing male senior weightlifters, a decrease in ST was found in light and middleweight groups (p=0.018, mean difference 11.0, effect size 0.69 and p<0.001, mean difference 6.8, rank biserial correlation 0.25. respectively), but not in the heavyweight group (Figure 4). In female senior weightlifters, a decrease in ST was found in the light (p<0.001, mean difference 10.8, effect size 0.53), middle (p<0.001, mean difference 12.5, biserial rank correlation 0.37), and heavyweight groups (p<0.001, mean difference 11.7, rank biserial correlation 0.27) (Figure 5).

Figure 4. ST comparison among male senior weightlifters

Figure5. ST comparison among female senior weightlifters

An analysis of WADA anti-doping testing figures reports shows a statistically significant increase in the total number of doping samples collected in weightlifting in recent years, with an average of 8,543 samples taken between 2009 and 2015 and 10,622 samples taken between 2016 and 2021, despite a sharp decrease in samples collected in 2020 due to the COVID-19 pandemic (p=0.026) (Figure 6) [1].

Figure6. Number of doping samples taken in weightlifting between 2009 and 2021

Discussion

Our analysis showed a significant decrease in the indicator of relative strength among weightlifters from various groups during 2016-2022 compared to 2009-2015. This decrease was observed in both male and female weightlifters. Further analysis by weight category and gender revealed a decrease in relative strength in five of the six weight groups in senior weightlifters. Among juniors, the decrease of results during 2016-2022 occurred among male juniors from the lightweight group and female juniors from the middle and heavyweight groups, (i.e. from three categories out of six). Results of youth athletes showed no significant decrease. Therefore, our findings demonstrate a decline in the relative strength of weightlifters, especially among senior athletes.

The beginning of the first time period (2009) was selected as it coincided with the First World Youth Weightlifting Championship. Publications that described in detail new methods for detecting long-term metabolites of anabolic steroids and endogenous testosterone derivatives appeared in 2014. [12] The start of the second time period (2016) was selected due to the time lag in obtaining information from advanced scientific research to most coaches and athletes. Thus, it can be assumed that 2015 may be the last year when the use of anabolic steroids and endogenous testosterone derivatives in sports was widespread. It should also be noted that the Olympic Games were held in 2016, before and during which the number of samples is traditionally higher than in other periods, while the samples are stored for up to 10 years to preserve the possibility of further analysis. This may also contribute to the lower use of the most banned substances in weightlifting than in previous years. 

Previous studies have investigated the relationship between performance results analysis and anti-doping measures [23]. Iljukov et al. conducted a dedicated review of the influence of novel anti-doping measures on performance results, focusing on the implementation of the ABP in elite female runners from a country with a known high prevalence of doping. The study showed a clear decrease in the performance results of female runners in multiple distances associated with the use of ABP [6].

Our study is the first of its kind to focus on weightlifters. Doping, particularly the use of AAS, has been prevalent in weightlifting, potentially leading to exclusion from the Summer Olympics [8]. The countries whose athletes were most often disqualified for doping were not allowed to participate in the World Weightlifting Championships (for example, Russia, Kazakhstan, Armenia, China and Egypt) [17, 24]. Thus, the widespread use of AAS in weightlifting, primarily exogenous anabolic steroids and endogenous testosterone derivation, should come as no surprise. The positive effect of these substances on the hypertrophy of muscle fibers and the growth of strength indicators has been convincingly proven in several studies conducted both with the participation of humans and animals [25, 26].

In the present study, it may be reasonable to speculate that a combination of increased doping sample collection and implementation of novel methods led to a decrease in weightlifting performance. There is a statistically significant increase in the total number of doping samples collected in weightlifting in recent years as it showed in results section.

Another possible explanation for the observed decrease in performance results in our study is the implementation of novel anti-doping methods, such as long-term AAS metabolite identification and highly sensitive chromatographic/mass spectrometric techniques, and ABP steroidal module implementation [12-14]. As previously mentioned, these methods have enabled anti-doping authorities to identify usage at lower concentrations for longer periods, or indirectly, even after elimination from the body. The existing scientific literature has previously described these methods, although it has shown that a certain amount of time is required for full implementation, including testing protocols, disciplinary actions, and athlete behavior change [7, 12, 27]. The percentage decrease of AAS-positive ADRVs from 65% in 2009-2015 to 58% in 2016-2021 may support the notion of athletes changing their practices due to increased knowledge of new detection methods. The absence of a decline in performance results in the group of youth athletes may partly be explained by the low number of ADRV cases in this group (55 over 14 years), which may be due to the low prevalence of prohibited substance use [1]. 

It is important to note that the analysis of our results was conducted only using the official IWF website, without including the results of athletes who were disqualified for doping. Additionally, a significant number of disqualifications of athletes from major competitions occurred following a retrospective analysis of stored samples up to 10 years later. This was demonstrated by a study by Kolliari-Turner et al. that re-tested weightlifters' samples from the 2008 and 2012 Olympic Games and identified 94 positive samples, with AAS accounting for the majority of cases [9]. Therefore, it is possible that some of the weightlifters included in the present study analysis may have their results cancelled, potentially contributing to an even greater decrease in the ST. 

Furthermore, the number of doping tests required to obtain data for biological passports in the second analyzed time period does not increase. In 2015 there were 495 samples (130 blood samples and 365 urine samples), while in 2020 and 2021 there were 281 such samples (41 blood samples and 240 urine samples) and 385 (86 blood samples and 299 urine samples), respectively [1]. Thus, an increase in thenumber of samples used to compile biological passports cannot be regarded as a factor causing a decrease in sporting results. It is important to note that the total number of Athlete Biological Passport (ABP) samples in weightlifting is very low compared to other Olympic sports, at only 80 samples per year from 2010 to 2021 [1].

When analyzing the possible reasons for the decline in the relative strength of weightlifters, it is important to consider other factors that may have contributed. These factors may include a decrease in the number of participants, restrictions and suspensions of leading weightlifting countries, or the banning of certain techniques or technologies (known as technical doping). The official IWF website showed an increase in the number of participants in junior and senior categories but a decrease in the youth category, although there was no observed ST decrease in youth athletes in the present study [16]. Secondly, restrictions were considered during the methodology planning phase, as the results of the 2017 World Weightlifting Championships were not included due to many previously successful athletes from nine different countries being banned from participating. No evidence was found regarding the prohibition of techniques or technologies, such as the clap skate in ice skating or racer swimsuits in swimming. Therefore, it may be assumed that the anti-doping measures were the main reason for the performance results decrease in weightlifting during the studied periods.

There are some limitations to our study that should be noted. First, there were two Olympic Games held during the second period (2016 and 2021), while only one was held in the first period (2012). As more samples are traditionally collected before and during the Olympics, athletes may be less likely to use doping during these periods due to a greater risk of detection and the world media surrounding such a prestigious competition. Second, different age categories are tested disproportionately, favoring older and higher-tier athletes. This results in a higher number of ADRVs in these more elite athletes, who tend to be older. Therefore, this could create a sample bias and does not fully provide a solid basis for making claims about differences in doping use by age.

Future studies should investigate the impact of anti-doping measures on performance in other sports.

Conclusion

Overall, our study highlights the importance of ongoing monitoring and analysis of the impact of anti-doping measures on athletic performance to ensure fairness and integrity in sporting competitions. The decrease in results in elite weightlifting may be partly due to the introduction of new methods for detecting prohibited substances, as well as the tightening of athlete monitoring procedures and many other policies.  The effectiveness of anti-doping measures may be assessed via the results comparison before and after their implementation.

References

Anti-Doping Testing Figures Report, https://www.wada-ama.org/en/resources/anti-doping-stats/anti-doping-testing-figures-report (Access date: 25.03.2023)

World Anti-Doping Agency Strategic plan 2015-2019, https://www.wada-ama.org/sites/default/files/wada-strategic_plan-2015-en.pdf (Access date: 26.02.2024)

World Anti-Doping Agency Strategic plan 2020-2024: https://www.wada-ama.org/en/whowe-are/strategy (Access date: 26.02.2024)

World Anti-Doping Code, https://www.wada-ama.org/sites/default/files/resources/files/wada-2015-world-anti-doping-code.pdf (Access date: 26.02.2024)

Ulrich R, Pope HG Jr, Cléret L, Petróczi A, Nepusz T, Schaffer J, Kanayama G, Comstock RD, Simon P. Doping in Two Elite Athletics Competitions Assessed by Randomized-Response Surveys. Sports Med. 2018 Jan;48(1):211-219.

Iljukov S, Kauppi JP, Uusitalo ALT, Peltonen JE, Schumacher YO. Association Between Implementation of the Athlete Biological Passport and Female Elite Runners' Performance. Int J Sports Physiol Perform. 2020, 15(9):1231-1236.

Bezuglov E, Talibov O, Lazarev A, Waśkiewicz Z, Iljukov S. Effects of new anti-doping measures on sports performance in elite female athletes [published online ahead of print, 2023 Apr 17]. Drug Test Anal. 2023;10.1002/dta.3484. doi:10.1002/dta.3484

LA28 Initial Sports Programme to be put forward to the IOC Session, https://olympics.com/ioc/news/la28-initial-sports-programme-to-be-put-forward-to-the-ioc-session (Access date: 10.03.2023)

Kolliari-Turner A, Oliver B, Lima G, et al. Doping practices in international weightlifting: analysis of sanctioned athletes/support personnel from 2008 to 2019 and retesting of samples from the 2008 and 2012 Olympic Games. Sports Med Open. 2021;7(1):4

10. Handelsman DJ, Hirschberg AL, Bermon S. Circulating Testosterone as the Hormonal Basis of Sex Differences in Athletic Performance. Endocr Rev. 2018 Oct 1;39(5):803-829.

11. Kolliari-Turner A, Lima G, Hamilton B, Pitsiladis Y, Guppy FM. Analysis of Anti-Doping Rule Violations That Have Impacted Medal Results at the Summer Olympic Games 1968-2012. Sports Med. 2021;51(10):2221-2229.

12. Geyer H, Schänzer W, Thevis M. Anabolic agents: recent strategies for their detection and protection from inadvertent doping. Br J Sports Med. 2014 May;48(10):820-6.

13. Vernec AR. The Athlete Biological Passport: an integral element of innovative strategies in antidoping. Br J Sports Med. 2014 May;48(10):817-9.

14. Saugy M, Lundby C, Robinson N. Monitoring of biological markers indicative of doping: the athlete biological passport. Br J Sports Med. 2014 May;48(10):827-32.

15. Anti-doping sanctions list, https://iwf.sport/anti-doping/sanctions/ (Access date: 25.03.2023)

 IWF events results, https://iwf.sport/results/results-by-events/ (Access date: 15.02.2023)

 IWF Executive Board upholds decision related to Member Federations which have produced three or more retesting cases, https://iwf.sport/2017/09/30/iwf-executive-board-upholds-decision-related-to-member-federations-which-have-produced-three-or-more-retesting-cases/ (Access date: 10.03.2023)

 Weightlifting age groups, https://iwf.sport/weightlifting_/participants/ (Access date: 10.02.2023)

 Sinclair RG. Normalizing the performances of athletes in Olympic weightlifting. Can J Appl Sport Sci. 1985;10(2):94-98.

 IWF, Sinclair Coefficient, https://iwf.sport/weightlifting_/sinclair-coefficient/. (Access date: 10.02.2023)

 New Bodyweight Categories Approved by the IWF Executive Board, https://iwf.sport/2018/07/05/new-bodyweight-categories-approved-iwf-executive-board/. (Access date: 10.02.2023)

 Gottwald VM, Anderson Jr DN, Lawrence GP. Early Promise Versus Late Bloomers: A Longitudinal and Multidisciplinary Analysis of Relative Age Effects in an Elite Weightlifting Pathway. Journal of Expertise/Dectember. 2021;4(4):335-364.

 Seiler S, De Koning JJ, Foster C. The fall and rise of the gender difference in elite anaerobic performance 1952-2006. Med Sci Sports Exerc. 2007;39(3):534-540. doi:10.1249/01.mss.0000247005.17342.2b

 Weightlifting - Doping positives need not be a negative, says top official, https://www.reuters.com/article/uk-olympics-rio-weightlifting-idUKKCN10S0M9 (Access date: 10.03.2023)

 Andrews MA, Magee CD, Combest TM, Allard RJ, Douglas KM. Physical Effects of Anabolic-androgenic Steroids in Healthy Exercising Adults: A Systematic Review and Meta-analysis. Curr Sports Med Rep. 2018;17(7):232-241. doi:10.1249/JSR.0000000000000500.

 Skoupá K, Šťastný K, Sládek Z. Anabolic Steroids in Fattening Food-Producing Animals-A Review. Animals (Basel). 2022;12(16):2115. Published 2022 Aug 18. doi:10.3390/ani12162115.

 Pitsiladis Y, Ferriani I, Geistlinger M, de Hon O, Bosch A, Pigozzi F. A Holistic Antidoping Approach for a Fairer Future for Sport. Curr Sports Med Rep. 2017;16(4):222-224. doi:10.1249/JSR.0000000000000384.

Disclosures and declarations

Ethics approval and consent to participate:

Local ethics committee approval was not required since publicly available data was utilized. The study was conducted according to the Helsinki declaration. The data were obtained from open access sources, therefore no informed consent for study participation was necessary.

Data availability

The datasets generated during and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Consent for publication not applicable.

Availability of data and materials:

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Funding:

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Conflict of interest

Eduard Bezuglov, Georgiy Malyakin, Danila Telyshev, Artemii Lazarev, Ryland Morgans, Elizaveta Kapralova, Olga Sadkovaya and Oleg Talibov declare that they have no conflict of interest.

Author Contributions:

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Georgiy Malyakin, Danila Telyshev and Eduard Bezuglov. The first draft of the manuscript was written by Eduard Bezuglov and Georgiy Malyakin. Critical revision was done by Oleg Talibov, Artemii Lazarev, Elizaveta Kapralova, Olga Sadkovaya and Ryland Morgans. The figures were created by Elizaveta Kapralova and Olga Sadkovaya. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Acknowledgments: none.