Wearable-derived heart rate variability responses to a mind-body exercise intervention in older people from high southern latitudes (Chilean Patagonia, ~53°S)

Vollständiger Abstract

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Background High southern latitudes expose older adults to chronic cold and marked seasonal light variability, potentially challenging physiological resilience. Yet, few interventions have examined stress-related autonomic regulation in these geographically extreme contexts, and wearable-derived heart rate variability (HRV) frameworks remain insufficiently tested. Objective To evaluate a wearable-derived HRV framework, including signal quality control and Bayesian multivariate modeling, to characterize resting and exercise-evoked autonomic responses before and after a low-dose mind–body exercise (MBE) program in older adults living at high southern latitude. Methods Community-dwelling older adults completed a 24-week MBE intervention. RR intervals were continuously recorded using a chest-worn wearable device. HRV features were extracted from quality-controlled 5-minute segments at rest and after a standardized functional exercise bout. Intervention effects and potential moderators, including age, sex, body composition, and educational level, were estimated using multivariate Bayesian models to characterize individual variability and generate probabilistic estimates in a small sample. Results The intervention did not produce uniform resting HRV changes (RMSSD: β = −0.14, 95% CI [−1.41, 1.06]). Instead, modeling revealed a reorganization of exercise-evoked autonomic responses, including changes in sympathetic modulation (SNS index: β = −1.63, 95% CI [−3.05, −0.24]), alongside marked inter-individual heterogeneity. Age, sex, and adiposity-related measures consistently moderated autonomic response patterns. Conclusion In older adults living at high southern latitudes, a low-dose MBE program was associated with changes in cardiac autonomic regulation, particularly in acute exercise-evoked reactivity rather than resting HRV. This framework supports future longitudinal real-life monitoring integrating environmental covariates to improve individualized risk and response profiling.