Integrated heart rate variability and physiological profiling reveals autonomic phenotypes in older adults from a high-southern-latitude population

Abstract

Heart rate variability (HRV) is widely used to assess autonomic regulation, but its interpretation in older adults is influenced by age, sex, body composition, and hemodynamic status, particularly in underrepresented populations living in geographically extreme environments. We analyzed 530 community-dwelling older adults from the Magallanes region in southern Chile using an integrated framework that combined HRV indices with demographic, anthropometric, and cardiovascular descriptors. After quality-controlled preprocessing, we characterized the distribution and association structure of autonomic and physiological variables and then performed a large-scale unsupervised clustering benchmark across multiple feature spaces, dimensionality-reduction strategies, and clustering algorithms. Conventional descriptors explained only a limited proportion of HRV variability, whereas integrated multivariate analysis revealed a structured continuum of autonomic heterogeneity. A six-cluster solution provided the best compromise between separation, balance, and physiological interpretability, identifying profiles that differed in HRV magnitude, blood pressure burden, body composition, sex distribution, and age structure. These findings indicate that autonomic regulation in older adults cannot be adequately summarized by isolated descriptors such as age, body mass index, or blood pressure alone. Instead, it is better represented as a multidimensional physiological organization that supports future hypothesis generation for risk stratification and longitudinal monitoring in aging populations.