A wearable-based aging clock associates with disease and behavior.

Aging biomarkers play a vital role in understanding longevity, with the potential to improve clinical decisions and interventions. Existing aging clocks typically use blood, vitals, or imaging collected in a clinical setting. Wearables, in contrast, can make frequent and inexpensive measurements throughout daily living. Here we develop PpgAge, an aging clock using photoplethysmography at the wrist from a consumer wearable. Using the Apple Heart & Movement Study (n = 213,593 participants; >149 million participant-days), our observational analysis shows that this non-invasive and passively collected aging clock accurately predicts chronological age and captures signs of healthy aging. Participants with an elevated PpgAge gap (i.e., predicted age greater than chronological age) have significantly higher diagnosis rates of heart disease, heart failure, and diabetes. Elevated PpgAge gap is also a significant predictor of incident heart disease events (and new diagnoses) when controlling for relevant risk factors. PpgAge also associates with behavior, including smoking, exercise, and sleep. Longitudinally, PpgAge exhibits a sharp increase during pregnancy and concurrent with certain types of cardiac events.

Duke Scholars

Author Guillermo Sapiro Electrical and Computer Engineering