RED-S

Science for dance performance

Professional dancers are like elite athletes

This web site is about using science to improve performance. Although my focus has generally been on sport, science can also help artistic performance. Professional dancers face many of the same challenges as elite athletes, but a cultural divide separates the two communities. A recent paper helps to bridge this gap, by showing that scientific advances in managing relative energy deficiency in sport (RED-S) may be of great benefit in the dance world.

Dance and sport

Professional dancers spend many hours a day training in order to deliver top level performances in high pressure situations. On stage, they are quite literally under the spotlight. They also start young, developing bodies that are able to meet the high level of technical demands required to reach the top. In spite of the similarities with the lives of those in elite sport, artistic performance is viewed differently from athletic performance. A prima ballerina would not consider herself an athlete any more than a sprinter would consider herself a dancer. Strictly Ballroom is dance, whereas figure skating is sport. This separations stretches from the individual participants up to the level of governing bodies.

Athletes in many sports adapt their body composition to gain an advantage, often seeking to achieve “race weight” ahead of competition. In many ways, the situation is more extreme for dancers, particularly those pursuing classic forms such as ballet, who aim for a body shape that meets aesthetic ideals, while maintaining the strength and flexibility to perform.

Relative energy deficiency in dance

In the paper, dancers were invited to complete an online survey that had been based on previous studies of athletes who were potentially at risk of low energy availability, specifically RED-S. Responses included anthropomorphic data, training and performance hours, injuries and illness, indicators of hormone status and attitudes to eating and weight control.

A RED-S risk score was derived from each dancer’s responses. Of the 247 participants, 57% of females and 29% of males had negative scores, consistent with low energy availability.

Psychological factors proved to be important. Many dancers felt anxious about missing class or rehearsals, in a similar way to athletes who suffer from exercise addiction. These dancers also tended to be more obsessive about controlling their weight and what they eat. Most considered the chances of gaining a leading role to be higher if they lost weight. These kinds of attitudes were observed in an earlier study of male cyclists.

Among the female dancers, some interesting correlations showed up between these mental attitudes and both physical and physiological factors. The more obsessive individuals tended to have a lower body mass index (BMI) particularly when calculated using their lowest weight for their current height. They also tended to have experienced various forms of menstrual disfunction, indicating a disruption to normal hormonal function that has been observed in female athletes in low energy availability.

The large majority of dancers had not heard of Relative Energy Deficiency in Sport, probably because they do not self-identify as sportsmen/sportswomen. Yet the peer pressure of dance schools and dance companies, combined with ever present social media, can lead some dancers to restrict energy intake to levels that are insufficient to meet the high demands of training and performance.

Fit to dance

The authors hope that the publication of this study will help raise awareness in the dance community of the importance of fuelling for the work required. The fact that physical outcomes are connected, via hormones, to mental attitudes is particularly relevant during the COVD crisis, which has impacted the dance world in such a tragic way. The hope is that dancers will be fully fit and healthy to return to the stage, when the theatres eventually open.

References

Indicators and correlates of low energy availability in male and female dancers
Nicola Keay, AusDancers Overseas, Gavin Francis

Energy Availability: Concept, Control and Consequences in relative energy deficiency in sport (RED-S)

Low energy availability assessed by a sport-specific questionnaire and clinical interview indicative of bone health, endocrine profile and cycling performance in competitive male cyclists, Nicola Keay, Gavin Francis, Karen Hind

Relative Energy Deficit in Sport (RED-S)

EnergyBalance

Unfortunately an increasing proportion of the population of western society has fallen into the habit consuming far more calories than required, resulting an a huge increase in obesity, with all the associated negative health consequences. At the opposite end of the spectrum, a smaller but important group experiences problems stemming from insufficient energy intake. This group includes certain competitive athletes, especially those involved in sports or dance, where a low body weight confers a performance advantage. A new infographic draws attention to this problem and highlights the fact that the individuals have control over the factors that can put them on the path to optimal health and performance.

The human body requires a certain amount of energy to perform normal metabolic functions, including, maintaining homeostasis, cardiac and brain activity. The daily requirement is around 2,000 kcal for women and 2,500 kcal for men. Additional energy intake is required to balance the energy requirements any physical activities performed.

Athletes and dancers need to eat more than sedentary people, but they can fall into an energy deficit in two ways.

Reducing energy intake, while maintaining the same training load. This is typically an intentional decision, in order to lose weight, in the belief that this might improve performance. It can also arise unintentionally, perhaps due to failing to calculate energy demands of the training programme.
Increasing training load, while maintaining the same energy intake. This can often occur unintentionally, as a result of a more intensive training session or a shift into a higher training phase. Some athletes or dancers perform extra training sessions while deliberately failing to eat more, in the hope, once again, that this might improve performance.

While most of the population would benefit from a period of moderate energy deficit. High level athletes and dancers tend to be very lean, to the extent that losing further weight compromises health and performance. The reason is that the endocrine system is forced to react to an energy deficit by scaling back or shutting down key metabolic systems. For example, levels of the sex hormones testosterone and oestrogen can fall, leading to, among other things, reductions in bone density. Unlike men, women have a warning sign, in the form of an interruption or cessation of menstruation. Both men and women with RED-S are likely to suffer from a failure to achieve their peak athletic performance.

Achieving peak performance

Fortunately athletes have control over the levers that lead to peak performance. These are nutrition, training load and, of course, recovery. Consistently fuelling for the energy required, whilst ensuring that the body has adequate time to recover, allows the endocrine system to trigger the genes that lead to the beneficial outcomes of exercise, such as improved cardiovascular efficiency, effective muscular development, optimal body composition, healthy bones and a fully functional immune system. These are the changes required to reach the highest levels of performance.

Screenshot 2019-04-08 at 12.19.45

Don’t ride your bike like an astronaut

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Astronauts return from the International Space Station with weak bones, due to the lack of gravitational forces. It is surprising to learn that competitive cyclists can experience similar losses in bone density over the period of a race season.

The problem is called Relative Energy Deficiency is Sport (RED-S). This occurs when lean athletes reach a tipping point where the benefits of losing weight become overwhelmed by negative impacts on health. When deprived of sufficient energy intake to match training load, certain metabolic systems become impaired or shut down.

Colleagues from Durham University and I recently published a study investigating what cyclists at risk of RED-S can do to improve their health and performance. It is freely available and written in an accessible way, without the requirement for specialist expertise.

Race performance

Race performance was measured by the number of British Cycling points accumulated over the season. This was correlated with power (FTP and FTP/kg) and training load. However, changes in energy availability proved to be an important factor. After adjusting for FTP, cyclists who improved their fuelling (green triangles) gained, on average, 95 points more than those who made no change. In contrast, those who restricted their nutrition (red crosses) accumulated 95 fewer points and reported fatigue, illness and injury.

Figure2 600 — Race Performance versus FTP and changes in Energy Availability (EA)

The nutritional advice included recommendations on adequate fuelling before, during and after rides. Also see my previous article on fuelling for the work required.

Bone health

Competitive road cyclists can fall into an energy deficit due to the long hours of training they complete. Although an initial loss of excess body weight can lead to performance improvements, athletes need to maintain a healthy body mass. The lumbar spine is particularly sensitive to deficiencies of energy availability.

In cyclists, the lower back also fails to benefit from the gravitational stresses of weight-bearing sports. This is why, in addition to nutritional advice, study participants were recommended some basic skeletal loading exercises (yes, that is me in the pictures).

The cyclists fell into three general groups: those who made positive changes to nutrition and skeletal loading, those who made negative changes and the remainder. The resulting changes in bone mineral density over a six month period were striking, with highly statistically significant differences observed between the groups.

Those making positive changes (green triangles) saw significant gains in bone mineral density, while those making negative changes (red crosses) saw equally significant negative losses in bone density. Any individual observation outside the band of the least significant change (LSC) is indicative of a material change in bone health.

Figure1 600 — Changes in Lumbar Bone Mineral Density versus Behaviour Changes

Conclusions

The study provided strong evidence of the benefits of positive changes and the costs of negative changes in nutrition and skeletal loading exercises. It was noted that certain cyclists found it hard to overcome psychological barriers preventing them from deviating from their current routines. It is hoped that such strong statistical results will help these vulnerable athletes make beneficial behavioural changes

References

Clinical evaluation of education relating to nutrition and skeletal loading in competitive male road cyclists at risk of relative energy deficiency in sports (RED-S): 6-month randomised controlled trial, Nicola Keay, Gavin Francis, Ian Entwistle, Karen Hind. BMJ Open Sport and Exercise Medicine Journal, Volume 5, Issue 1. http://dx.doi.org/10.1136/bmjsem-2019-000523

Machine learning for a medical study of cyclists

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This blog provides a technical explanation of the analysis underlying the medical paper about male cyclists described previously. Part of the skill of a data scientist is to choose from the arsenal of machine learning techniques the tools that are appropriate for the problem at hand. In the study of male cyclists, I was asked to identify significant features of a medical data set. This article describes how the problem was tackled.

Data

Fifty road racing cyclists, riding at the equivalent of British Cycling 2nd category or above, were asked to complete a questionnaire, provide a blood sample and undergo a DXA scan – a low intensity X-ray used to measure bone density and body composition. I used Python to load and clean up the data, so that all the information could be represented in Pandas DataFrames. As expected this time-consuming, but essential step required careful attention and cross-checking, combined with the perseverance that is always necessary to be sure of working with a clean data set.

The questionnaire included numerical data and text relating to cycling performance, training, nutrition and medical history. As a result of interviewing each cyclist, a specialist sports endocrinologist identified a number of individuals who were at risk of low energy availability (EA), due to a mismatch between nutrition and training load.

Bone density was measured throughout the body, but the key site of interest was the lumbar spine (L1-L4). Since bone density varies with age and between males and females, it was logical to use the male, age-adjusted Z-score, expressing values in standard deviations above or below the comparable population mean.

The measured blood markers were provided in the relevant units, alongside the normal range. Since the normal range is defined to cover 95% of the population, I assumed that the population could be modelled by a gaussian distribution in order to convert each blood result into a Z-score. This aligned the scale of the blood results with the bone density measures.

Analysis

I decided to use the Orange machine learning and data visualisation toolkit for this project. It was straightforward to load the data set of 46 features for each of the 50 cyclists. The two target variables were lumbar spine Z-score (bone health) and 60 minute FTP watts per kilo (performance). The statistics confirmed the researchers’ suspicion that the lumbar spine bone density of the cyclists would be below average, partly due to the non-weight-bearing nature of the sport. Some of the readings were extremely low (verging on osteoporosis) and the question was why.

Given the relatively small size of the data set (a sample of 50), the most straightforward approach for identifying the key explanatory variables was to search for an optimal Decision Tree. Interestingly, low EA turned out to be the most important variable in explaining lumbar spine bone density, followed by prior participation in a weight-bearing sport and levels of vitamin D (which was, in most cases, below the ideal level of athletes). Since I had used all the data to generate the tree, I made use of Orange’s data sampler to confirm that these results were highly robust. This had some similarities with the Random Forest approach. Although Orange produces some simple graphical tools like the following, I use Python to generate my own versions for the final publication.

Decision Tree from Orange

Published Decision Tree

Finding a robust decision tree is one thing, but it was essential to verify whether the decision variables were statistically significant. For this, Orange provides box plots for discrete variables. For my own peace of mind, I recalculated all of the Student’s T-statistics to confirm that they were correct and significant. The charts below show an example of an Orange box plot and the final graphic used in the publication.

Orange Box Plot

Final Box Plots

The Orange toolkit includes other nice data visualisation tools. I particularly liked the flexibility available to make scatter plots. This inspired the third figure in the publication, which showed the most important variable explaining performance. This chart highlights a cluster of three cyclists with low EA, whose FTP watts/kg were lower than expected, based on their high training load. I independently checked the T-statistics of the regression coefficients to identify relationships that were significant, like training load, or insignificant, like percentage body fat.

Orange Scatter Plot

Published Scatter Plot

Conclusions

The Orange toolkit turned out to be extremely helpful in identifying relationships that fed directly into the conclusions of an important medical paper highlighting potential health risks and performance drivers for high level cyclists. Restricting nutrition through diet or fasted rides can lead to low energy availability, that can cause endocrine responses in the body that reduce lumbar spine bone density, resulting in vulnerability to fracture and slow recovery. This is know as Relative Energy Deficiency in Sport (RED-S). Despite the obsession of many cyclists to reduce body fat, the key variable explaining functional threshold power watts/kg was weekly training load.

References

Relative Energy Deficiency in Sport, British Association of Sports and Exercise Medicine

Synergistic interactions of steroid hormones, British Journal of Sports Medicine

Cyclists: Make No Bones About It, British Journal of Sports Medicine

Male Cyclists: bones, body composition, nutrition, performance, British Journal of Sports Medicine

Fuelling for Cycling Performance

Some commentators were skeptical of Team Sky’s explanation for Chris Froome’s 80km tour-winning attack on stage 19 of the Giro. His success was put down to the detailed planning of nutrition throughout the ride, with staff positioned at strategic refuelling points along the entire route. If you consider how skeletal the riders look after two and a half weeks of relentless competition, along with the limits on what can be physically absorbed between stages, the nutrition story makes a lot of sense. Did Yates, Pinot and Aru dramatically fall by the wayside simply because they ran out of energy?

The best performing cyclists have excellent balancing skills. This includes the ability to match energy intake with energy demand. The pros benefit from teams of support staff monitoring every aspect of their nutrition and performance. However, many serious club-level cyclists pick up fads and snippets of information from social media or the cycling press that lead them to try out all kinds ideas, in an unscientific manner, in the hope of achieving an improvement in performance. Some of these activities have potentially harmful effects on the body.

Competitive riders can become obsessed with losing weight and sticking to extremely tough training schedules, leading to both short-term and long-term energy deficits that are detrimental to both health and performance. One of the physiological consequences can be a reduction in bone density, which is particularly significant for cyclists, who do not benefit from gravitational stress on bones, due to the non-weight-bearing nature of the sport. In a recent paper, colleagues at Durham University and I describe an approach for identifying male cyclists at risk of Relative Energy Deficit in Sport (RED-S).

You need a certain amount of energy simply to maintain normal life processes, but an athlete can force the body into a deficit in two ways: by intentionally or unintentionally restricting energy intake below the level required to meet demand or by increasing training load without a corresponding increase in fuelling.

EnergyBalance

Our bodies have a range of ways to deal with an energy deficit. For the average, slightly overweight casual cyclist, burning some fat is not a bad thing. However, most competitive cyclists are already very lean, making the physiological consequences of an energy deficit more serious. Changes arise in the endocrine system that controls the body’s hormones. Certain processes can shut down, such as female menstruation, and males can experience a reduction in testosterone. Sex steroids are important for maintaining healthy bones. In our study of 50 male competitive cyclists, the average bone density in the lumbar spine, measured by DXA scan, was significantly below normal. Some relatively young cyclists had the bones of a 70 year old man!

The key variable associated with poor bone health was low energy availability, i.e. male cyclists exhibiting RED-S. These riders were identified using a questionnaire followed by an interview with a Sports Endocrinologist. The purpose of the interview was to go through the responses in more detail, as most people have a tendency to put a positive spin on their answers. There were two important warning signs.

Long-term energy deficit: a prolonged significant weight reduction to achieve “race weight”
Short-term energy deficit: one or more fasted rides per week

Among riders with low energy availability, bone density was not so bad for those who had previously engaged in a weight-bearing sport, such as running. For cyclists with adequate energy availability, those with vey low levels of vitamin D had weaker bones. Across the 50 cyclists, most had vitamin D levels below the level of 90 nmol/L recommended for athletes, including some who were taking vitamin D supplements, but clearly not enough. Studies have shown that the advantages of athletes taking vitamin D supplements include better bone health, improved immunity and stronger muscles, so why wouldn’t you?

In terms of performance, British Cycling race category was positively related with a rider’s power to weight ratio, evaluated by 60 minute FTP per kg (FTP60/kg). Out of all the measured variables, including questionnaire responses, blood tests, bone density and body composition, the strongest association with FTP60/kg was the number of weekly training hours. There was no significant relationship between percentage body fat and FTP60/kg. So if you want to improve performance, rather than starving yourself in the hope of losing body fat, you are better off getting on your bike and training with adequate fuelling.

Cyclists using power meters have the advantage of knowing exactly how many calories they have used on every ride. In addition to taking on fuel during the ride, especially when racing, the greatest benefits accrue from having a recovery drink and some food immediately after completing rides of more than one hour.

For those wishing to know more about RED-S, the British Association of Sports and Exercise Medicine has provided a web resource.

A related blog will explore the machine learning and statistical techniques used to analyse the data for this study.

References

Relative Energy Deficiency in Sport, British Association of Sports and Exercise Medicine

Synergistic interactions of steroid hormones, British Journal of Sports Medicine

Cyclists: Make No Bones About It, British Journal of Sports Medicine

Male Cyclists: bones, body composition, nutrition, performance, British Journal of Sports Medicine