Research conducted using the UK Biobank, has found that nontraditional risk factors – self-reported walking pace and wearable, measured step counts – demonstrate robust predictive power for mortality risk. UK Biobank is “a large-scale biomedical database and research resource, containing in-depth, de-identified genetic and health information from half a million UK participants.”
The research by the University of Leicester, analyzed by the Reinsurance Group of America (RGA), shows an association between self-reported walking pace and mortality risk in all UK Biobank male participants under 60, after controlling for traditional underwriting risk factors.
50 per cent lower risk
“Compared to individuals who typically walk at a slow pace, those with a steady average walking pace had a 40 per cent lower mortality risk, while those who usually walk briskly had a 50 per cent lower risk,” they write. “This robust relationship remained consistent across all data subsets.” They add that using self-reported walking pace in its base model increased the model’s predictive power for mortality risk by approximately two per cent, demonstrating the additional value this metric provides.”
During the research, analysts also swapped out systolic blood pressure and total cholesterol with self reported walking pace information instead, again resulting in the model more accurately predicting mortality risk. Model accuracy declined when body mass index (BMI) and smoker status were independently replaced with self-reported walking pace.
Step count
As for step counts, “those averaging approximately 5,000 steps per day had an approximately 1.5 times higher mortality risk compared to those with approximately 11,000 steps per day,” RGA’s analysts write in the note, Quantifying Wellbeing in Insurance: What are the keys to a longer life? “Conversely, individuals with approximately 15,000 steps per day had an approximately 30 per cent lower mortality risk compared to the median.” (The data, they say, comes from the largest objectively measured physical activity study in the world – 100,000 participants wore wrist-worn accelerometers over a period of one week for 24 hours a day.)
Again substituting step counts for traditional underwriting risk factors, they found the model’s ability to predict mortality risk also increased once total cholesterol, BMI and systolic blood pressure were independently replaced by step count information. Model accuracy decreased in this experiment when smoker status was replaced with step counts.
“Further research is needed before recommending broader underwriting changes,” they conclude. “As the industry’s interest in biometric data continues to grow, these insights have the potential to enhance underwriting and wellness strategies, while also helping applicants make informed decisions to improve their longevity.”
