Body Composition Tech
Award Category
Insurtech
With chronic diseases such as type 2 diabetes and cardiovascular disease reaching epidemic proportions, insurers are seeking ways to manage and assess the associated risks, engage with policyholders and increase customer loyalty.
Body Composition Technologies (BCT) has developed a revolutionary digital solution to allow insurers to inexpensively and easily measure and monitor fat composition and body circumference measurements, key primary markers of future incidence of chronic disease and more direct measures of risk compared to BMI.
BCT can estimate body composition and body measurements simply by using photos of an individual taken with a smartphone and this technology can be easily embedded into an insurers existing platform either during onboarding or as part of wellness program using Software Development Kits (SDKs).
The user first takes a front and then a side photo using a smartphone application. The photos are processed using novel and advanced statistical methods, computer vision (CV), Machine learning (ML) and Artificial Intelligence (AI) approaches to capture these images and understand how they can provide information about body composition. The app then returns an avatar to the user with waist, hip, chest and thigh circumference measurements validated to 97%-98% accuracy and body composition estimates validated to 91% accuracy.
BCT has invested heavily in these patented, back-end ML and AI algorithms trained using large medical imaging datasets in order to achieve the speed and accuracy of our results. Medical images are collected by BCT in collaboration with Universities and medical institutions around the world who also validate the results of BCT’s algorithms.
The incidence of chronic disease, especially type 2 diabetes and cardiovascular disease, has been increasing rapidly over the past few decades driven by changes in diet and lifestyle and exacerbated by aging populations. 18 million people die each year from cardiovascular disease, the number one cause of death in the world. There are 425 million people globally with diabetes and 1.1 billion people estimated to be pre-diabetic. As the incidence of chronic disease increases, so do the costs associated with the treatment and management of those diseases.
BMI is a tool that insurers have traditionally used to estimate risk. However, research has shown that BMI can be misleading for a significant portion of the population as a measure of obesity and as a predictor of the future incidence of chronic disease. More direct measures of body composition such as DXA and MRI are expensive and time consuming.
This inaccessibility of diagnostic tools is evident in the large proportion of people who are affected by chronic disease, but don’t know it. For example, of the approximately 425 million people in the world who have diabetes, half of them are undiagnosed and of the 1.1 billion people in the world are estimated to be prediabetic, the reversible precursor to type 2 diabetes, approximately 90% of them are undiagnosed.
BCT’s solution allows an insurer to use body composition and body circumference estimates to better assess and price the insured party’s risk at the time of origination. An insurer can then engage with and monitor its policyholders during the life of the policy. With regular updates on its insured population’s health, an insurer can consistently monitor its risk and mitigate this risk by incentivizing its insured population to live healthier lifestyles, thereby reducing claims. What makes the technology unique is that we are capturing the key primary markers of chronic disease, instead of indirect and self-reported measures such as weight, BMI, steps, and other activity measures that insurers currently rely on.
BCT is also developing its technology further to provide additional estimates of body composition including:
Android fat: In both women and men, Android Fat is significantly associated with blood pressure, fasting plasma glucose, triglycerides, and decreased HDL cholesterol and with increased odds of hypertension, impaired fasting glucose, diabetes mellitus, and metabolic syndrome, irrespective of BMI.
Lean Muscle Mass: Lean Mass is an important measure for overall fitness and health. Estimating the amount of muscle in the body is a key measure when identifying problems such as sarcopenia - the loss of muscle mass with age and also frailty risk in older populations.
Visceral Fat: High levels of Visceral Fat are strongly correlated with type II diabetes and other chronic diseases, and for people who are not currently diabetic, it is an accurate predictor of future incidence of the disease. Estimating Visceral Adiposity is also essential to assessing Cardiometabolic Risk.