A Wearable-Derived Autonomic Component Is Associated with Cardiovascular Health in Community-Dwelling Adults: A...

Background/Objectives: Wearable devices provide multidimensional measures of cardiometabolic health. We aimed to derive latent physiological dimensions from ECG and motion variables collected by a wearable device and evaluate their associations with the individual health metrics of the Longevity Check-Up 8+ (LC8+) programme. Methods: Community-dwelling adults voluntarily participating in four Longevity Check-Up 8+ (LC8+) events underwent 24-h multiparameter recording using a wearable device. Eight wearable-derived variables were entered into principal component analysis (PCA) to derive latent physiological dimensions. Component scores were subsequently evaluated for associations with overall LC8+ health, while exploratory analyses examined associations with individual health metric domains. Results: Ninety-seven participants (mean age 51.3 ± 13.4 years; 36% female) were enrolled. Among the 96 participants with complete data for the PCA, three latent physiological components were identified, explaining 70.1% of the total variance. PC1, which was characterised by high SDNN, high RMSSD, and low nocturnal heart rate, was independently associated with overall LC8+ health (LM: B = +0.402, 95% CI [+0.103, +0.700], p = 0.009). Among the eight LC8+ domains, only the association between PC1 and glycaemic health remained statistically significant after Benjamini-Hochberg correction in the primary fixed-effects analysis (95% CI [1.32, 4.62], adjusted p = 0.039). Conclusions: A wearable-derived autonomic component was associated with overall cardiometabolic health in community-dwelling adults. Among the individual LC8+ domains, the strongest association was observed for glycaemic health. These preliminary findings support further investigation of wearable device monitoring as a complementary tool for cardiovascular health assessment in preventive medicine.