Beyond BMI: how to capture influences from body composition in health surveys

Peeters, A., Tanamas, S., Gearon, E., Al-Gindan, Y. and Lean, M. E.J. (2016) Beyond BMI: how to capture influences from body composition in health surveys. Current Nutrition Reports, 5(4), pp. 286-294. (doi: 10.1007/s13668-016-0183-5)

Full text not currently available from Enlighten.


Population monitoring of health risks is critical for resource allocation and planning of health services and preventive interventions. It also enables identification of population groups and regional areas where need may be greater. To support these functions, population monitoring needs to be accurate and reliable over time. With increasing prevalence of obesity over time, the need to monitor high risk adiposity is recognised internationally. Body composition is regularly monitored in population health surveys globally, primarily to identify high risk adiposity as an important contributor to future disease burden. Body mass index, a composite of height and weight, is the most commonly used population indicator of high risk adiposity, but its correlation with body fat is relatively poor. Many population surveys also collect waist and hip circumference, with a minority collecting further indicators such as skinfold thickness, bioelectrical impedance and dual-energy X-ray absorptiometry. Here, we review the advantages and disadvantages of the body composition indicators currently used in population health surveys and reflect on how the information from such indicators could be optimised. Our focus is on the use of indicators to identify those at increased metabolic health risk associated with excess body fat. We conclude that while most current indicators have reasonable correlation with body fat when tested, they have only been validated in small, specific samples that cannot be compared and are likely to have limited use over time as populations change demographically and in their body composition. Future population monitoring of high risk adiposity requires a more systematic analysis of which combined indicators from population health surveys will provide the best estimation of excess body fat and future cardio-metabolic risk across all adult ages, both sexes and a wide range of ethnicities.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Lean, Professor Michael
Authors: Peeters, A., Tanamas, S., Gearon, E., Al-Gindan, Y., and Lean, M. E.J.
College/School:College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
Journal Name:Current Nutrition Reports
ISSN (Online):2161-3311
Published Online:17 October 2016

University Staff: Request a correction | Enlighten Editors: Update this record