For decades, BMI has served as the most familiar measure of obesity. Calculated by dividing body weight in kilograms by height in metres squared, BMI is useful for identifying population-level patterns, but it is an indirect indicator. It does not distinguish fat from muscle, reveal where fat is stored, or show whether excess adiposity is already impairing a person’s health. Two people with the same BMI can have very different proportions of body fat, metabolic profiles and physical abilities. Conversely, an individual with a lower BMI may still carry clinically important visceral fat, the metabolically active tissue surrounding internal organs. The Commission’s framework attempts to address these limitations by combining anthropometric measures, direct adiposity assessments and evidence of functional or disease-related effects.

The distinction between preclinical and clinical obesity is central to that framework. Preclinical obesity refers to excess adiposity that has not yet produced clear limitations in physical function or established obesity-related illness. Clinical obesity, by contrast, involves measurable consequences, such as impaired mobility, reduced ability to perform everyday activities or medical conditions linked to excessive adipose tissue. This distinction is intended to separate biological risk from current disease burden without suggesting that preclinical obesity is harmless. It may represent a window in which prevention, weight management and treatment of associated risk factors could delay or prevent the emergence of more serious complications.

Yao, Dardari, Zahid and their colleagues address a question that has remained unanswered since the new terminology was proposed: how frequently do adults with preclinical obesity progress to clinical obesity? Their analysis of US adults is designed to estimate the incidence of that transition and identify characteristics associated with a higher probability of progression. In epidemiological research, incidence refers to the occurrence of new cases within a population over a defined period, rather than the total number of people who already have a condition. Measuring incidence is essential because it can reveal whether preclinical obesity is a stable state, a temporary stage or a common pathway toward functional impairment and disease.

The study’s importance extends beyond terminology. If preclinical obesity frequently advances to clinical obesity, healthcare systems may need to identify affected adults before symptoms become disabling. Earlier recognition could support interventions aimed at improving diet, physical activity, sleep, cardiometabolic health and body composition. It could also encourage clinicians to assess strength, mobility and daily functioning rather than relying exclusively on a patient’s BMI. On the other hand, if progression varies substantially according to age, existing health conditions, sex, adiposity distribution or other characteristics, prevention strategies could be directed toward people at greatest risk instead of treating all individuals with elevated body weight as though they faced identical outcomes.

The concept also challenges a common assumption that obesity becomes clinically meaningful only after a diagnosis such as type 2 diabetes, cardiovascular disease or osteoarthritis has appeared. Adipose tissue is an active endocrine organ, not merely an inert energy store. Enlarged fat cells and dysfunctional adipose tissue can alter the release of hormones and inflammatory molecules, contribute to insulin resistance and influence lipid metabolism. Visceral and ectopic fat—fat deposited in organs such as the liver, pancreas or skeletal muscle—may be particularly relevant to metabolic disease. At the same time, excess weight can increase mechanical stress on joints and make movement more difficult. These biological and physical pathways can develop gradually, making the boundary between preclinical and clinical disease a process rather than a single moment.

The researchers’ focus on risk factors is therefore crucial. A transition to clinical obesity is unlikely to be determined by body size alone. Ageing can reduce muscle mass and physical reserve, while chronic illness may limit activity and accelerate loss of function. Changes in body composition, rather than weight alone, may alter the relationship between adiposity and mobility. Social and environmental conditions—including access to nutritious food, safe places to exercise, healthcare, transportation and stable housing—can also influence both obesity progression and the ability to respond to it. By examining determinants alongside incidence, the study may help clarify which biological and social patterns accompany the shift from excess adiposity without evident impairment to obesity with measurable clinical consequences.

The findings could influence how obesity is recorded in medical research and addressed in public health. A BMI-based category treats obesity as a relatively uniform exposure, while the Commission’s model describes a spectrum with different levels of risk and current impact. This may improve clinical communication by allowing doctors to distinguish between preventing future complications and treating present disease. It could also affect eligibility for interventions, the design of clinical trials and the way health authorities estimate the burden of obesity. However, the framework will require careful implementation. Direct adiposity measurements are not equally available in every clinic, and assessments of physical function must be reliable, culturally appropriate and sensitive to disability, ageing and other conditions that may not be caused by adiposity.

The study arrives as obesity rates remain a major concern in the United States and worldwide, but its broader message is more nuanced than any simple weight-loss headline. The transition from preclinical to clinical obesity cannot be understood by a number on a scale alone. It involves the interaction of fat quantity and distribution, metabolic biology, musculoskeletal function, existing disease and the conditions in which people live. By measuring how often that transition occurs and identifying those most vulnerable to it, Yao and colleagues provide evidence for a more precise approach to obesity care. The emerging scientific question is no longer only how many people meet a BMI threshold, but how many are developing functional and health consequences—and how early those consequences can be prevented.

Subject of Research: The progression from preclinical obesity to clinical obesity among US adults, including its incidence and associated risk factors.

Article Title: Transition from preclinical obesity to clinical obesity among US adults: incidences and risk factors

Article References: Yao, Z., Dardari, Z.A., Zahid, S. et al. “Transition from preclinical obesity to clinical obesity among US adults: incidences and risk factors.” International Journal of Obesity (2026). https://doi.org/10.1038/s41366-026-02199-9

Image Credits: AI Generated

DOI: 10.1038/s41366-026-02199-9

Keywords: obesity, preclinical obesity, clinical obesity, adiposity, body mass index, BMI, physical function, public health, epidemiology, risk factors

Type 2 diabetes, a global health crisis affecting approximately 400 million people, has traditionally been diagnosed based on elevated blood glucose levels. However, the period leading up to the manifestation of overt diabetes—known as prediabetes—is characterized by subtle yet critical metabolic changes, including insulin resistance and hyperinsulinemia, which can precede definitive diagnosis by 10 to 20 years. Recognizing the necessity for earlier detection, the UBC research team focused on measuring hyperinsulinemia, a condition marked by elevated insulin concentrations that signals an increased risk of developing diabetes, cardiovascular disease, and obesity.

Dr. Jonathan Little, a professor at UBC Okanagan’s School of Health and Exercise Sciences and lead investigator of the study, explains that while current metabolic screening involves blood draws and invasive procedures, saliva insulin measurement offers a painless, accessible alternative. The team conducted a randomized controlled clinical trial encompassing 94 participants with varying body compositions, who after fasting consumed a standardized meal-replacement shake. Subsequent saliva samples and finger-prick blood tests were collected at intervals to compare saliva insulin concentrations with blood glucose levels.

The results were striking: individuals with obesity exhibited significantly higher saliva insulin levels compared to their overweight or normal-weight counterparts, despite showing similar blood glucose readings. This finding suggests that saliva insulin concentrations can act as a sentinel biomarker, revealing heightened metabolic risk before traditional glucose markers indicate diabetes onset. Such insight carries profound implications for public health, as early identification can facilitate timely lifestyle modifications and therapeutic interventions aimed at halting or reversing disease progression.

Further intriguing was the observation that some lean participants demonstrated pronounced spikes in saliva insulin following the meal challenge, despite having normal blood glucose levels. This unexpected finding challenges the prevailing paradigm that excess weight is the primary driver of metabolic risk, revealing that lean individuals may harbor metabolic vulnerabilities undetectable by conventional measures. Hence, saliva insulin testing could redefine risk stratification by transcending simplistic metrics like BMI and waist circumference.

Co-author Dr. Hossein Rafiei highlights the dynamic nature of saliva insulin responses, emphasizing that their prior research had shown a strong correlation between plasma and saliva insulin throughout the day, even when comparing high- and low-carbohydrate meals. This study extends those findings by revealing temporal insulin fluctuations within saliva after a standardized mixed meal, capturing metabolic nuances that could be invaluable for clinical assessment.

Notably, the research also underscores waist circumference as the anthropometric measure most closely associated with saliva insulin levels. This aligns with growing evidence that central adiposity drives metabolic dysfunction, rather than total body weight alone. By integrating saliva insulin testing with waist measurements, clinicians may gain a sophisticated yet practical approach to metabolic risk screening.

Mechanistically, elevated insulin levels in saliva likely reflect pancreatic beta-cell hyperactivity and peripheral insulin resistance. Early hyperinsulinemia ramps up insulin secretion to compensate for decreased tissue sensitivity, a compensatory state that, if persistent, contributes to systemic metabolic derangements. Saliva sampling captures this phenomenon in a user-friendly manner, opening new vistas for research into pathophysiological mechanisms and personalized medicine.

Importantly, the adoption of saliva insulin testing could democratize access to metabolic health evaluation, especially in resource-limited settings or among populations with aversion to needles and blood draws. This could facilitate broader screening efforts and reduce disparities in diabetes prevention and management.

While the technology and techniques for accurately quantifying saliva insulin require further refinement and validation in larger diverse cohorts, this study lays compelling groundwork for the future. Continued research could also explore integrating this biomarker with other salivary analytes to develop multiplexed non-invasive assays, propelling metabolic diagnostics into a new era.

In summary, this innovative study from UBC Okanagan propels saliva insulin testing to the forefront of metabolic research, offering a simple yet powerful method to detect early metabolic disruptions before the onset of Type 2 diabetes and obesity. By capturing physiological alterations that traditional blood glucose tests may miss, this approach holds the potential to revolutionize preventive healthcare strategies and improve outcomes for millions worldwide.

Subject of Research: People

Article Title: Saliva insulin concentration following ingestion of a standardized mixed meal tolerance test: influence of obesity status

News Publication Date: 16-May-2025

Web References: http://dx.doi.org/10.1139/apnm-2024-0532

References: Applied Physiology Nutrition and Metabolism, DOI: 10.1139/apnm-2024-0532

Image Credits: UBC Okanagan

Keywords: Health care, Diseases and disorders, Human health, Epidemiology