IPM Take
Obesity policy is still built around a number that is easy to calculate and easy to ration: BMI. But cardiometabolic risk does not respect that simplicity. Visceral fat, epicardial fat and inflammatory fat biology may explain why some people develop diabetes, heart failure or coronary disease at lower BMI thresholds, while others with higher BMI do not show the same risk pattern. Personalised prevention cannot keep using a population shortcut as if it were a precision tool. The next policy fight will be whether health systems use better risk stratification to improve access, or simply use BMI to deny care.
Executive Summary
A Nature Reviews Cardiology review argues that adipose tissue should be understood as an active immunological and metabolic organ, not passive stored weight. The authors highlight that regional fat depots, including visceral, subcutaneous and epicardial adipose tissue, communicate with the vasculature and myocardium through endocrine, paracrine, vasocrine and neural pathways that can mediate cardiovascular inflammation and remodelling.
The review’s most policy-relevant message is simple: total body weight is not the whole story. The distribution, quality, density and inflammatory biology of adipose tissue may shape cardiometabolic risk more directly than BMI alone.
This matters globally because obesity is rising across regions, while risk is not distributed equally. WHO reports that 2.5 billion adults were overweight in 2022, including 890 million living with obesity, and that more than 390 million children and adolescents aged 5-19 were overweight. At the same time, South and East Asian populations can carry higher visceral and epicardial adipose tissue burden at lower BMI thresholds than white populations, meaning BMI-based policy can miss risk in some groups and overgeneralise risk in others.
The policy implication is uncomfortable: obesity care, cardiovascular prevention and access to new therapies may need to move toward risk stratification based on body composition, central adiposity, ethnicity, sex, imaging and cardiometabolic phenotype, not BMI alone.
Why it matters
- Policymakers and public authorities: Need to update obesity and cardiovascular prevention strategies so that BMI remains a practical screening tool, not the final gatekeeper for prevention, treatment or reimbursement.
- HTA bodies and payers: Will increasingly need to decide whether obesity therapies, imaging tools and AI-based risk stratification should be assessed by cardiometabolic risk reduction, not only weight loss.
- Clinicians and providers: Need practical pathways that combine BMI with waist-to-height ratio, waist circumference, cardiometabolic markers and, where clinically justified, imaging-based risk assessment.
- Data / AI leaders: AI-enabled adipose tissue measurement could turn routine scans into cardiometabolic risk tools, but validation, bias testing and governance are essential before deployment.
- Patients and advocates: Moving beyond BMI could reduce stigma and improve access for people whose cardiometabolic risk is underestimated by weight-based thresholds, but only if better tools are accessible outside elite centres.
Obesity policy has a measurement problem.
For decades, BMI has been the dominant gatekeeper. It is cheap, fast and simple. That is why policymakers like it. That is also why it is dangerous when used as the whole story.
A new Nature Reviews Cardiology review makes the case for a deeper model of cardiometabolic risk. Adipose tissue is not just excess weight. It is an active metabolic and immunological organ made up of different depots, including visceral, subcutaneous and epicardial fat. These depots do not behave the same way. They communicate with the heart and blood vessels, influence inflammation, and may help drive cardiovascular remodelling.
That matters because two people with the same BMI can carry very different cardiometabolic risk. One may have more subcutaneous fat, another may have more visceral or epicardial fat. One may have relatively low inflammatory activity, another may have adipose tissue biology that is already pushing the heart, liver, kidneys and blood vessels toward disease.
This is where the politics starts.
Health systems still use BMI because it is administratively convenient. It can determine who qualifies for treatment, who enters a weight-management pathway, who receives reimbursement, and who is told to wait. But the new science is making that convenience harder to defend.
The Nature review argues that regional adiposity and its biology, rather than total adipose tissue mass alone, are central determinants of cardiometabolic risk. It also highlights advances in cardiac CT, MRI, DXA and artificial intelligence that can measure adipose tissue volume, quality, density and radiomic features with increasing reproducibility. In other words, the field is moving from “how heavy is this person?” to “what kind of fat biology is driving risk?”
The global implications are huge. WHO estimates that in 2022, 2.5 billion adults were overweight, including 890 million living with obesity. More than 390 million children and adolescents aged 5-19 were overweight, including 160 million living with obesity. A crude system based only on BMI is not prepared for that scale, especially when access to obesity care, cardiology, diabetes prevention and imaging is already unequal.
The equity issue is sharper across ethnicity. The Nature review notes that South and East Asian individuals can have higher visceral and epicardial adipose tissue burden at lower BMI thresholds than white individuals. This is not an academic detail. It means a person may look “not obese enough” under standard BMI policy while carrying a high cardiometabolic risk burden. If reimbursement and referral pathways rely too heavily on BMI, some high-risk populations will be missed before disease becomes visible.
NICE already reflects part of this shift. Its obesity guidance says BMI should be interpreted with caution because it is not a direct measure of central adiposity. For children and young people aged five and over, NICE recommends considering waist circumference and waist-to-height ratio to predict health risks linked to central adiposity. It also advises explaining that waist should be kept to less than half of height.
The 2025 Lancet Diabetes & Endocrinology Commission went further, arguing that excess adiposity should be confirmed either by direct body-fat measurement where available, or by at least one anthropometric criterion such as waist circumference, waist-to-hip ratio or waist-to-height ratio in addition to BMI, except in people with very high BMI. That is a direct challenge to obesity policy built on BMI alone.
The same logic will hit cardiovascular prevention. Epicardial adipose tissue surrounds the heart and sits close to the coronary arteries and myocardium. It may contribute to atrial fibrillation, coronary artery disease and heart failure pathways through local inflammatory and metabolic effects. AI-enabled imaging studies are already exploring whether epicardial fat measurements from routine cardiovascular imaging can improve risk prediction.
But this should not become a new toy for wealthy hospitals only.
Advanced imaging is expensive. AI tools are not neutral. Data used to train algorithms may underrepresent populations already underserved by cardiometabolic care. If epicardial fat imaging becomes a premium risk tool available mainly in high-income health systems, the precision gap will widen. Better measurement will help the people already closest to care, while those at highest structural risk remain invisible.
That is the central policy challenge. Moving beyond BMI cannot mean replacing one blunt tool with one expensive tool. It means building a layered approach.
At population level, BMI, waist circumference and waist-to-height ratio remain practical. At primary care level, risk stratification should include blood pressure, lipids, glucose, HbA1c, liver markers, kidney function, family history and ethnicity-aware interpretation. At specialist level, imaging-derived adiposity markers may help identify people at higher residual cardiovascular risk, especially when routine CT or cardiac imaging has already been performed.
This also matters for GLP-1 and incretin-based therapy policy. These medicines are often discussed through the politics of weight loss, but their cardiometabolic value may depend partly on how they modify visceral and ectopic fat depots, inflammation and organ-level risk. If HTA bodies assess obesity medicines only through kilograms lost, they may miss the more important question: which patients achieve meaningful risk reduction?
That question will become unavoidable as payers face rising demand. BMI-based eligibility is easy to administer, but it may be clinically crude. A risk-based model could prioritise patients with high cardiometabolic vulnerability, including those with central adiposity, diabetes risk, fatty liver disease, heart failure risk or high-risk adipose phenotypes. Done well, this could make access more rational. Done badly, it could become another bureaucratic barrier.
The future of obesity policy should not be a war between BMI and imaging. BMI still has public health value. The problem is pretending it is precision medicine.
Cardiometabolic disease is not driven by weight alone. It is driven by biology, distribution, inflammation, environment, ethnicity, sex, age and access to care. The science is moving toward that complexity. Policy is still catching up.
The next phase of personalised cardiometabolic prevention will not simply ask whether someone has obesity.
It will ask where the risk is hiding.
