Diagnosing obesity — time to move beyond BMIs?

Obesity has more than doubled globally since 1990, with more than 2.5 billion adults aged 18 and older found to be overweight in 2022, according to data from the World Health Organization.

As health systems around the world work towards tackling obesity and improving population health, two new research papers from the US reflect on advantages and disadvantages of relying on body mass index (BMI) as a measure of obesity and how this influences perceptions and patient care.

Tackling disparities

Researchers from Harvard Medical School, Massachusetts General Hospital and MGH Weight Center argue that as obesity manifests differently in different populations, the implications of universal thresholds to define obesity may results in health disparities.

The need for different BMI thresholds to define obesity in Asian populations offer lessons that may help to address existing disparities in health care, the researchers said. “In 2004, the World Health Organization (WHO) suggested a lower BMI cut-off for many Asian populations because of their higher tendency toward central adiposity and risk for type 2 diabetes. While these changes were clinically important, Asian populations are not monolithic and organisations should acknowledge these BMI thresholds as only temporary placeholders until when we can establish whether even more specific thresholds are needed to define obesity across different Asian ethnic subpopulations.”

The authors suggested that with recent pushes towards disaggregated data and personalised medicine, increasing granularity for Asian Americans could potentially pave the way for similar efforts among all racial and ethnic groups, making diagnosis of obesity more accurate, tailored and equitable.

Avoiding unintended consequences

An accompanying editorial from Annals of Internal Medicine notes that consensus on how obesity should be defined remains elusive and argues that beyond diagnostic challenges, focusing on obesity exclusively as a disease rather than a broader, more inclusive construct may have unintended consequences — including reinforcing the weight bias in our current healthcare reimbursement system.

The healthcare community takes treating similar health risk factors including hypertension and high cholesterol seriously even before these result in disease complications, but health insurers, including Medicare, apply a higher bar when it comes to covering obesity treatment, according to the authors. Because obesity has multiple genetic, social, cultural, environmental and behavioural contributors, addressing obesity requires that clinicians have the time and space to get to know their patients as people.

This is particularly imperative now for many reasons, including because of the increasing demand for new highly effective weight loss agents. Equitable dissemination of these treatments will require clinicians to be able to make nuanced clinical decisions based on contributors to an individual patient’s obesity and the health risk it poses, and not just whether it meets a panel’s definition of ‘disease’. The author suggests that obesity should be recognised as a serious health threat and ‘pandemic’, and as such, clinical education about obesity needs to be a priority in medical school and residency training.

BMI and other risks

Authors from New York University School of Global Public Health suggest that BMI (weight in kilograms divided by the square of height in metres) remains useful for identifying obesity. While clinical decisions can be enhanced with additional measures, such as waist circumference and weight changes over time, BMI is strongly associated with indicators of cardiovascular risk, is low cost and is easy to measure in the clinical encounter. And among healthy persons who do not smoke, studies also show that the relationship between BMI and mortality is nearly identical among Black persons, White persons and Asian Americans in relative terms — and because BMI data are readily available across populations and time, it provides a useful metric by which to comprehend and quantify the ramifications of structural racism and discrimination for population health. This enables researchers to gain deeper insights into the influence of systemic factors — including inequities in resource allocation, educational access, housing security, dietary options and health care quality — on health outcomes and to develop efficacious interventions to mitigate health disparities.

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