The Tripartite Model of body image dissatisfaction postulates that three factors (peers, parents, and media) affect body image dissatisfaction and disordered eating through thin-ideal internalization and appearance comparison.
Thin-ideal internalization is the extent to which one accepts or “buys into” socioculturally defined beauty standards of thinness. The idea is that the more someone internalizes these standards, the more likely they are to engage in behaviours to achieve their “ideal”, and the more likely they are to develop an eating disorder.
A growing number of of studies have been done evaluating the validity of this model. Although I’m not well-read on the subject, it does seem like there is a growing number of studies showing an association between thin-ideal internalization and disordered eating practices.
But is the picture complete? Are peers, parents, and media the only or even the main factors that influence the extent of thin-ideal internalization?
One factor that’s curiously missing from the research is genetics. Can genetics play a role in explaining why some individuals are more prone to internalizing the thin-ideal …
Today I thought I’d take the time to do an overview of what researchers know about the genetics of eating disorders and try to clear up some common misconceptions. The bulk of the content in this blog post comes from a very nice review paper published in 2011 by Drs. Stephanie Zerwas and Cynthia Bulik on the genetics and epigenetics of eating disorders. In an effort to keep blog posts short, this will be a multi-part mini-series.
When it comes to the genetics of eating disorders, there are two main questions that research ask: What is the relative contribution of genetic factors to eating disorder behaviours? And what are those genetic factors? I’ll talk about research attempting to answer the first question in this post and the second question in my next post.
In order to understand the role that genetics plays in influencing eating disorder behaviours, researchers use family, twin, and to a lesser extent, adoption studies.
In family studies, researchers are typically asking What is the probability that a relative of someone with an eating disorder …
Eating disorders typically begin in adolescence. One common explanation for this is that during adolescence females are increasingly exposed to the media, thin models, and dieting. While this is probably true to some extent, it doesn’t explain why the rates of eating disorders are quite low despite the high levels of exposure to thin models in the media. Out of 100 girls, only a handful develop eating disorders, yet all of them are exposed to the same magazines and TV shows.
This means there must be some other factors that differ between this group of girls. One hypothesis is that hormonal changes during puberty may modulate the genetic risk factors for eating disorders. These changes may “turn on” genes that predispose individuals to eating disorders. Previous research has shown that genetic factors modulate disordered eating (eating disorders have a high heritability), but how? What are the mechanisms of this modulation?
Exploring this idea, Dr. Kelly Klump and colleagues sought to focus on the role of estradiol–the predominant estrogen during reproductive years in females. Estradiol (and other hormones, …
Six month of blogging and I have yet to do a proper post on the prevalence of eating disorders. I think it is about time. I see all sorts of numbers thrown around, often depending on the purpose of the article and the author’s bias. Is it 1 in 1000, 1 in 100, 1 in 20 or maybe even 1 in 2? Who is right?
Well, it is a tricky question to answer.
The number depends on how the particular study was conducted. Here are some factors that may influence the final rates: the population being studied, the sample size, the definition of eating disorder, the methods used by researchers to identify and screen for individuals with eating disorders, the number of years over which data is collected, and so on. In other words, a lot! That’s why in order to get a better sense of the true numbers, I prefer to look at review articles summarizing several years worth of epidemiological studies.
For this post, I picked a relatively recent review, published in May 2012, by Smink, van …