Obesity is a major risk factor for diseases ranging from diabetes, heart conditions and even cancers. However, it is also well established that it is not only the amount of fat in the body that confers risk for various diseases but where the fat is distributed. There are a number of ways adiposity and body composition can be measured, but it is an ongoing area of research as to what measures are best for understanding the risk of disease and the genetic underpinnings of why this happens.
Body mass index (BMI) is a measure of body size but is a crude indicator of body composition, taking into account only a height-weight ratio. The gold standards to measure specific adipose tissue distribution and body composition involve either MRI, which is costly, or CT imaging, which requires unnecessary exposure to ionising radiation. 3D imaging is a non-invasive, cost-effective method of capturing surface geometry. Whole-body 3D scans can provide a detailed, geometrically accurate representation of body morphology and physical composition. We propose to analyse 3D body scan data collected as part of the ALSPAC study to examine how body shapes can be used to investigate genetics and the risk of cardiometabolic diseases.