IPM Take
BMI remains one of medicine’s cheapest measurements. That is also part of the problem.
Two people can occupy the same BMI category while carrying very different metabolic and organ-level risk. In this study, researchers divided 570 older men into six groups according to BMI and metabolic health, then compared visceral fat thickness, liver stiffness, carotid intima-media thickness and several calculated metabolic indices. The measures did not tell the same story.
Visceral fat thickness, liver stiffness and body adiposity index primarily distinguished differences in obesity status. The triglyceride-glucose index and visceral adiposity index were better at distinguishing metabolically healthy from unhealthy participants within similar weight categories. Lipid accumulation product, calculated from waist circumference and triglycerides, differentiated across both dimensions.
That does not make BMI obsolete. It makes BMI insufficient when health systems use it as though kilograms per square metre were a complete biological diagnosis.
The more important policy question is whether better stratification requires expensive technology. This study suggests that part of the answer may already sit inside routine blood tests and a tape measure.
Executive Summary
The study used baseline data from the PolyIran-Liver cohort, nested within the Golestan Cohort Study in northern Iran. Researchers analysed 570 men aged 50 to 80 and classified them as metabolically healthy or unhealthy within normal-weight, overweight and obesity categories.
They then compared multiple measures designed to capture different dimensions of adiposity and metabolic health. Visceral fat thickness and liver stiffness were assessed with ultrasound-based methods, while the researchers calculated the visceral adiposity index, lipid accumulation product, body adiposity index and triglyceride-glucose index from anthropometric and laboratory measurements.
The key finding was that different tools appeared to capture different biological dimensions. Visceral fat thickness, liver stiffness and body adiposity index varied between obesity groups with similar metabolic status. TyG and visceral adiposity index differentiated metabolically healthy and unhealthy participants within comparable weight categories. Lipid accumulation product differentiated across both obesity and metabolic categories.
Elevated liver stiffness was significantly more likely in metabolically unhealthy participants with obesity or overweight and, importantly, also in the metabolically healthy obesity group compared with the healthy reference phenotype. This suggests that apparently favourable metabolic status did not necessarily mean absence of organ-level abnormalities.
By contrast, carotid intima-media thickness did not differ significantly across the six phenotypes, showing that these metabolic distinctions did not translate into detectable differences in this marker of subclinical atherosclerosis within this cohort.
Why it matters
- HTA bodies: Obesity technologies and medicines are increasingly being assessed in populations defined by BMI thresholds. If metabolic dysfunction and organ involvement vary substantially within the same BMI category, future evaluations may need to consider whether phenotype or complication burden identifies patients more likely to derive value from treatment.
- Payers: More sophisticated risk stratification does not automatically require costly imaging. Indices based on waist circumference, glucose, triglycerides and HDL cholesterol could potentially support more targeted care using information already collected in routine practice, although prospective evidence of clinical utility is still needed.
- Industry / innovation partners: As obesity treatment becomes more crowded, BMI alone may become an increasingly weak enrichment strategy for clinical trials. Combining anthropometric measures with metabolic phenotype, visceral adiposity and organ-level markers could help identify biologically distinct populations, but only if those distinctions predict treatment response or outcomes.
Obesity medicine is becoming more precise, but one of its most important clinical tools remains remarkably crude.
BMI divides weight by height. It does not distinguish fat from lean mass, show where adipose tissue is stored, reveal insulin resistance or tell a clinician whether the liver is already showing signs of damage.
The Iranian study makes that limitation visible by placing different measurements side by side.
Researchers created six phenotypes, ranging from metabolically healthy normal weight to metabolically unhealthy obesity. Instead of asking which measure was “best,” they examined what each measure appeared to capture.
Visceral fat thickness and body adiposity index tracked obesity-related differences. TyG and visceral adiposity index were more informative about metabolic health within similar BMI categories. Lipid accumulation product was unusual because it separated participants on both axes.
That matters because a person classified as normal weight can still have metabolic dysfunction, while a person meeting a BMI definition of obesity may have a relatively favourable metabolic profile.
But the study also complicates the idea of “metabolically healthy obesity.”
Men classified as metabolically healthy with obesity still had significantly increased odds of elevated liver stiffness compared with the healthy reference group. The finding does not prove that these men will progress to liver disease, because the analysis was cross-sectional, but it suggests that apparently normal metabolic markers may not capture all obesity-related organ effects.
Cheap measurements could become more valuable than another BMI cut-off
The most practical finding may be lipid accumulation product.
LAP combines waist circumference and fasting triglycerides, two measurements that are already widely available. Visceral adiposity index similarly incorporates waist circumference, BMI, triglycerides and HDL cholesterol.
Neither requires an MRI scanner or expensive molecular test.
That gives these tools an obvious appeal for health systems trying to identify higher-risk patients without dramatically expanding diagnostic spending. The authors conclude that LAP and VAI may be practical, low-cost tools for metabolic risk stratification.
The evidence is not strong enough to turn those indices into universal screening rules.
The analysis was cross-sectional, so it cannot show which measures predict future cardiovascular events, diabetes or liver disease progression. All participants were men aged 50 to 80, and the authors explicitly warn against extrapolating the findings directly to women or younger populations.
There is another important negative result. Carotid intima-media thickness did not differ significantly among the phenotypes. If the metabolic indices truly capture clinically important risk, prospective studies will still have to demonstrate that they predict hard outcomes rather than simply producing more detailed categories.
That distinction matters in an obesity market increasingly shaped by powerful medicines and pressure to decide who should receive them.
Better measurement can improve precision.
But a more sophisticated score is valuable only if it changes a decision that improves a patient’s health.
The scale may be too simple. The answer is not automatically to replace it with complexity, but to measure the biology that actually matters.
