Check your subscription status, update your details and more. Using data from more than 800,000 people, researchers have tested a system that can identify those with obesity who would benefit from treatment, and those who don't require intervention Body mass index (BMI), which divides a person’s weight by their height squared, comes with fundamental and well-acknowledged problems for diagnosing obesity. It can’t distinguish fat from muscle, tell us where fat is distributed in the body or determine whether excess body fat is actually affecting someone’s health.
Now, a very large international study suggests that a more-nuanced approach could substantially improve obesity diagnosis, identify people at elevated risk of illness and mortality, and help clinicians determine who needs treatment – and how much. The study tested a framework proposed by a 2025 Lancet Commission00004-X/fulltext). It combines measurements of abdominal fat with assessments of organ function to distinguish between people who are harmed by obesity and those who aren’t. (The health effects of obesity vary among people for reasons not yet known.) Receive a weekly dose of discovery in your inbox.
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