Eating disorders are on the rise. GLP-1s could make things worse.

This is the available feed excerpt, which may be shortened or in the publisher’s original language.

GLP-1 weight-loss drugs are one of the biggest biotech breakthroughs of the last decade. But to some clinical psychologists, they can represent something more sinister—a potential trigger for eating disorders. A new report suggests that the global incidence of anorexia nervosa and bulimia nervosa shot up between 1990 and 2023—by a whopping 71%. By 2023, there were an estimated 18.1 million people living with one of these two disorders. What’s worse is that the number is likely to be much higher than that once we factor in other eating disorders. And, disturbingly, those in the field are already starting to see GLP-1 weight-loss drugs exacerbating the issue. Cheri Levinson is a clinical psychologist at the University of Louisville in Kentucky who has specialized in eating disorders for almost 20 years. She says she’s now seeing more patients with more severe symptoms than at any other time in her career, and that many of them are misusing GLP-1s. “This is the worst I’ve seen things,” she says. Eating disorders are mental health conditions in which people’s eating behaviors impact their health. They include anorexia nervosa (defined by a fear of weight gain), bulimia nervosa (in which people binge and purge), binge eating disorder, and others. It’s thought that some people have a genetic predisposition to certain eating disorders, but that some external factor is what triggers their onset. That might be stress, or social pressure to be skinny. Often, simply restricting food intake can trigger an eating disorder, says Levinson. Eating disorders—along with the pressure to look thin—were already prevalent in the 1990s (the heroin chic era springs to mind). To find out how things might have changed since then, Ruhai Bai at the Children’s Hospital of Nanjing Medical University in China and his colleagues pulled together data from studies and surveys conducted on populations around the world. The team used statistical models to fill in any data gaps. That research al