Eating Disorders in Type 1 Diabetes

Jacqueline Allan, PhD candidate and Associate Lecturer in Psychology, at Birkbeck discusses the little known but extremely dangerous prevalence of eating disorders in Type 1 Diabetics, and her charity Diabetics with Eating Disorders.

In 2014 I was lucky enough to be granted a Bloomsbury scholarship to undertake a PhD focussing on Eating Disorders in Type 1 Diabetes, including one known as ‘Diabulimia’, at Birkbeck. I’ve worked in this area since 2009 when I founded the registered charity Diabetics with Eating Disorders.

First, let me explain what Type 1 Diabetes is.

Type 1 Diabetes is an autoimmune disorder where the insulin-producing beta cells of the pancreas are mistakenly destroyed, making sugar in the body impossible to process. Insulin is one of the most vital hormones in the body – it ferries energy we consume in the form of carbohydrates to our muscles, organs and brain, so it is essential for every bodily function. For this reason, those with Type 1 must check their blood sugar every few hours and administer synthetic insulin to keep themselves safe. There are two main ways for administering insulin – Multiple Daily Injections using both long acting and short acting insulin, or Subcutaneous Infusion using an insulin pump.

Most of us utilise a carbohydrate-counting approach, whereby we know how many insulin units we need for every 10 grams of carbohydrate consumed and what our general background levels should be. If it sounds like a simple equation, it’s not.  Everything affects blood sugar – not just the obvious stuff like sports, illness or alcohol but stress, the weather, sleep, menstruation – its educated guesswork.

When it goes wrong, we are in immediate danger of death. Too much insulin and we can’t think as there is not enough fuel in the cells of the body. We shake, seize, our bodies have a fight or flight reaction and if not treated with sugar in a timely manner we risk falling into a coma and/or dying. Too little insulin and the body has to find other ways to get rid of sugar and provide energy for itself; sugar escapes into the bloodstream and is excreted in the urine while the body starts burning fat and muscle for fuel. The calories consumed can’t be processed and are not utilised, so the body is forced to cannibalise itself for energy. This process is called Diabetic Ketoacidosis – it is a life-threatening condition and the main symptom is massive weight loss. In this sense, we are borne into a world where everything is about food, injections, the looming threat of complications, hospitals and numbers with the knowledge that ignoring it all results in a substantial reduction in body size.

For decades, research has shown that those with Type 1 Diabetes have higher levels of eating disorders that their non-Diabetic counterparts. Anorexia, Bulimia and eating disorders not otherwise specified (EDNOS) are twice as prevalent, and insulin omission is present in around 40% of female patients. The statistics for men are not as clear but levels have been rising steadily since the early 90s.

My research looks at risk factors for the development of Eating Disorders in Type 1 Diabetes. I started my PhD in 2014 and found that there is a psychological vulnerability which, when combined with Diabetes-specific distress predicts higher eating disorder symptomology and higher levels of blood sugar. Having modelled these risks, I developed a multidisciplinary intervention delivered online to address them. I am in the process of writing them up at the moment, but initial results are positive.

I am also looking at another important question – are we measuring the right thing? One common feature of standard eating disorder questionnaires is that they ask questions which could directly relate to diabetes regimen, rather than eating disorder symptomology – for example, questions like ‘do you avoid specific food groups?’ Many Type 1 Diabetics deliberately avoid carbohydrates in order to control blood sugar as a lifestyle choice rather than an eating disorder. Similarly, many people investigate this population by asking these standard questions that are fundamentally flawed, without acknowledging the issue that insulin omission leads to weight loss.

We have made substantial inroads into treating Eating Disorders in Type 1 Diabetes and it has been a privilege to be involved centrally with that research. The National Institute for Health and Care Excellence (NICE) guidelines published earlier this year marked a watershed in recognising the issue, as did the documentary and radio piece with the BBC. There are now two NHS Trust programmes that deal with diabulimia which is more than when I founded the charity in 2009. We still have a long way to go.

The next big hurdle is recognising that Eating Disorders in Type 1 Diabetes is fundamentally different due to the nature of the illness itself and that insulin omission and diabulimia are unique. Hopefully, my research will help with that.

Watch: Diabulimia: The World’s Most Dangerous Eating Disorder

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What’s in a face? Birkbeck researchers delve into what facial expressions reveal

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Birkbeck scientists in residence at the Science Museum have recently run a live experiment with members of the public, to discover how much we understand about people simply by looking at their faces. Two members of the team report on their experiences.  

Ines Mares, postdoctoral research assistant in the Department of Psychological Sciences: As humans, we possess the remarkable ability to extract a wealth of information from even a brief glance at a face: we can identify people, judge the emotion they are feeling, assign character traits (rightly or wrongly), and in doing so, continue to thrive as a social species. Because faces are so interesting and processing them well is so important to us as humans, they made an ideal topic to explore in the context of the Science Museum’s ‘Live Science’ initiative.

In the Science Museum we ran a series of experiments to understand what factors make faces more rewarding or appealing – such as how attractive they were, the emotions they were displaying or how old the faces were. We were especially interested to see how these judgements related to our ability to recognise faces, and to see how our results would change for younger and older participants (our experiments tested children from five years of age to adults of almost 90!).

Dr Ines Mares explains the experiment to a participant.

Dr Ines Mares explains the experiment to a participant. 

“This was a great opportunity for us to engage directly with people and discuss the type of research we do and the questions that motivate us. It is also a unique chance to reach out and test a much more diverse set of people than we are conventionally able to do, with anyone aged from five to 105 invited to take part in our studies.”

Dr Marie Smith, Senior Lecturer, Lead Scientist with Dr Louise Ewing (UEA) and Professor Anne Richards (Birkbeck)

Conducting this type of study, in which we focused so closely on individual differences with such a broad audience was outstanding.  It was a unique opportunity to interact with people from very different backgrounds and ages – something that can be challenging to do in the university labs.

To begin with, we were concerned about people’s willingness to take part in our experiments, but after the first day at the museum we understood that people were interested in being involved and actually wanted to know more about our hypothesis and what motivated us to do this type of work. It was an amazing chance to discuss these topics with members of the public and get feedback on our work directly from them. Initially this idea seemed quite daunting to me, but I ended up loving it, since the majority of people who took part in our experiments (and we had almost 2500 participants) were really motivated and interested to know more – not only about face processing, but also about other aspects of science in general.

Being part of a team running experiments in the Science Museum was an amazing opportunity.  Without a doubt, I would repeat this experience, not only because of the amazing breadth of data we were able to collect, but also because of the opportunity it gave us as researchers to disseminate our work and discuss science in general.

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Professor Anne Richards explains the purpose of our study to an interested volunteer. 

Michael Papasavva, PhD student in the Department of Psychological SciencesEven when working in a hub-science such as psychology, lab life can become monotonous. Surrounded by friends and colleagues who share similar views and challenges, it’s very easy to lose yourself in the bubble of academia.

Michael Papasavva signs up another keen volunteer!

Michael Papasavva signs up another keen volunteer! 

I was thrilled when presented with the opportunity to get out of the lab and be a scientist in residence at the London Science Museum. This prospect invoked childhood memories of navigating this huge and stimulating environment on school trips and family days out; I knew that the experience was going to be awesome (in the nerdiest way possible).

Working as part of a team of 12 researchers, we ran experiments in the ‘Who Am I? Gallery.’ This is perhaps one of the more interesting areas of the museum; the space houses visiting scientists from various disciplines and facilitates their research. Members of the public are free to wander over and volunteer to participate in experiments (or query the location of the toilets or dinosaurs). Our team conducted a range of different face processing experiments that examined the role of development and individual difference on face memory and emotion processing. By the end of the residency, almost 2500 people had participated (832 children, 1487 adults), creating masses of data for us to explore once we were back in the lab.

In addition to generating novel information, it’s the responsibility of a scientist to disseminate that knowledge to the wider public. Our residency provided us with an opportunity to engage with a very wide demographic. I must admit, it was heart-warming to see our younger participants having so much fun with the masks and games we had set up to help draw in the crowds and that so many of our  older participants chose to stay back to discuss our project with us. People genuinely enjoyed giving back to science.

I would strongly recommend the Live Science project.

Photo credits: Science Museum Group Collection

The full science museum team: Dr Marie Smith (Senior Lecturer, Birkbeck), Professor Anne Richards (Birkbeck), Dr Louise Ewing (Lecturer, University of East Anglia), Dr Ines Mares (Post-doc, Birkbeck), Michael Papasavva (PhD Student, Birkbeck), Alex Hartigan (PhD Student, Birkbeck), Gurmukh Panesar (PhD Student, Birkbeck), Laura Lennuyeux-Comnene (RA, Birkbeck), Michaela Rae (RA, Goldsmiths College), Kathryn Bates (MSc student, Birkbeck), Susan Scrimgeour (MSc student, Birkbeck), Jay White (Intern, UCL Institute of Education).

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The Myth of the Optimism Bias?

This article was originally posted by ‘Neuroskeptic’ on DiscoverMagazine.com on 3 June 2016. The article discusses research on optimism bias, as carried out by a team of psychological researchers including Birkbeck’s Professor Ulrike Hahn.

OptimismAre humans natural, irrational optimists? According to many psychologists, humans show a fundamental optimism bias, a tendency to underestimate our chances of suffering negative events. It’s said that when thinking about harmful events, such as contracting cancer, most people believe that their risk is lower than that of ‘the average person’. So, on average, people rate themselves as safer than the average. Moreover, people are also said to show biased belief updating. Faced with evidence that the risk of a negative outcome is higher than they believed, people don’t increase their personal risk estimates properly.

But now a group of researchers, led by first author Punit Shah of London, hascriticized the theory of biased belief updating and, by extension, the whole optimism bias model. Shah et al. say that optimism bias may be a mere statistical artifact, a product of the psychological test paradigms used to assess it. They argue that even perfectly rational, unbiased individuals would seem ‘optimistic’ in these tests. Specifically, the authors say that the apparent optimism is driven by the fact that negative events tend to be uncommon.

The new work builds on a 2011 paper by Adam J. L. Harris and Ulrike Hahn, also authors of the present paper. The 2011 article criticized the claim that people show an optimism bias by rating themselves as safer than the average. The new paper takes aim at biased belief updating. Here’s how Shah et al. describe their argument:

New studies have now claimed that unrealistic optimism emerges as a result of biased belief updating with distinctive neural correlates in the brain. On a behavioral level, these studies suggest that, for negative events, desirable information is incorporated into personal risk estimates to a greater degree than undesirable information (resulting in a more optimistic outlook).

 

However, using task analyses, simulations and experiments we demonstrate that this pattern of results is a statistical artifact. In contrast with previous work, we examined participants’ use of new information with reference to the normative, Bayesian standard.

 

Simulations reveal the fundamental difficulties that would need to be overcome by any robust test of optimistic updating. No such test presently exists, so that the best one can presently do is perform analyses with a number of techniques, all of which have important weaknesses. Applying these analyses to five experiments shows no evidence of optimistic updating. These results clarify the difficulties involved in studying human ‘bias’ and cast additional doubt over the status of optimism as a fundamental characteristic of healthy cognition.

I asked Shah and his colleagues to explain the case against the optimism bias in belief updating in a nutshell. They said

All risk estimates have to fit into a scale between 0% and 100%; you can’t have a chance of getting a heart attack at some point in your life of less than 0% or greater than 100%. The problems for the update method arise from the fact that the same ‘movement’ in percentage terms means different things in different parts of the scale.

 

Someone whose risk decreases from 45% to 30% has seen their risk cut by 1/3, whereas someone whose risk increases from 15% to 30% has seen their risk double -much bigger change. So the same 15% difference means something quite different if you have to revise your beliefs about your individual risk downwards (good news!) or upwards (bad news!) toward the same percentage value. The moment people’s risk estimates are influenced by individual risk factors (a family history of heart attack increases your personal risk by a factor of about 1.6), people should change their beliefs to different amounts, depending on the direction of the change. The update method falsely equates the 15% in both cases.

 

If the difference in belief change simply reflects these mathematical properties of risk estimates then one should see systematic differences between those increasing and those decreasing their risk estimates regardless of whether they happen to be estimating a negative or a positive event. But in the first case, this will look like ‘optimism’, in the second case it will look like ‘pessimism’. This is the pattern our experiments find…

 

The evidence base thus seems far less stable than previously considered. There is, using various paradigms, plenty of evidence for optimism in various real-world settings such as sports fans predictions and political predictions, but these just show that certain people might be optimistic in certain situations, not that there is a general optimistic tendency across situations that would be required to say people are optimistically biased. It is also important to note that because this belief updating paradigm has been used in so many neuroscience studies, it means those neuroscience data are also uninterpretable.

Read the original article on DiscoverMagazine.com

Read the original article on DiscoverMagazine.com

In my view, Shah et al. make a strong case that the evidence for optimism bias needs to be reexamined. Their argument makes a crucial prediction: that people should show a ‘pessimistic’ bias (the counterpart of the optimism bias) when asked to rate their chance of experiencing rare, positive events. In the new paper, the authors report finding such a pessimistic bias in a series of experiments. But perhaps they should team up with proponents of the optimism bias and run an adversarial collaboration to convince the believers.

  • Punit Shah, Adam J. L. Harris, Geoffrey Bird, Caroline Catmur, & Ulrike Hahn (2016). A Pessimistic View of Optimistic Belief Updating Cognitive Psychology
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