| Title: | Body Composition (BC) Studies Collaboration (BCSC) Project |
| Lead Institution: | University College London |
| Principal investigator: | Dr Vivek Prasad |
Application 70816
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About
Globally, obesity levels have risen and account for 13% of the adult population based on World Health Organization data from 2016. Laterally, malnutrition remains to be a major public health problem that can be prevalent among the underweight, normal weight, overweight and obese individuals. Currently, obesity and underweight diagnostic criteria are primarily based on Body Mass Index (BMI). While BMI measurement is low cost and reduces measurement burden, it does not reflect an individual's body composition(BC) (that is, fat mass and fat-free mass) because it only accounts for height and weight. Accurate diagnosis of obesity and malnutrition is crucial for individuals to obtain proper treatment therefore, the methods for classifying obesity and underweight should be enhanced. Dual X-ray absorptiometry (DXA) is among the most accurate and convenient direct measures of BC and body fat (BF) distribution. There are discrepancies in the studies conducted using BMI as the measure of obesity. One example is: Obesity is associated with an increased risk of adverse health outcomes in the general population. However, studies that consisted exclusively of patients with chronic diseases suggest that overweight and obese patients may paradoxically have better outcomes than lean patients. Looking on to the discrepancies caused by the use of BMI, there is a need for a "BMI like" disease risk classification based on BF. Initial critical analysis using the UK Biobank will investigate the effects of different levels of BC parameters (fat mass, fat-free mass, visceral fat) and changes in these parameters on morbidities, obesity-related mortality and all-cause mortality. Then the UK biobank data will be merged with datasets consisting of DXA measured BC from other countries to construct a central dataset with a representative sample of the world's population. Reference values for BC parameters will be developed using the central dataset. The anticipated timeline for this project is 2-3 years. Our team and partners will work to make sure that the state-of-the-art study information generated is employed in developing awareness on the limitations BMI has as a diagnostic tool. The project will help spread the message that BF is more strongly associated with health outcomes compared to BMI while giving an insight into the public health importance of assessing the population's BC. Finally, the study will help in structuring a universal BF classification that will be developed using a representative sample of the world's population.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 16595 | Association Between Trunk Fat Mass Index and Diabetes in a Multinational Population | Chibueze Ogbonnaya (+11) | 2025 | Mayo Clinic Proceedings Innovations Quality & Outcomes |
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