Quantitative Characterization of Biological Age and Frailty Based on Locomotor Activity Records
Timothy V. PyrkoviD, Evgeny Getmantsev, Boris Zhurov, Konstantin AvchacioviD, Mikhail A. PyatnitskiyiD, L. I. Men’shikov, Kristina Khodova, Andrei V. GudkoviD, Peter O. FedicheviD
Abstract
We performed a systematic evaluation of the relationships between locomotor activity and signatures of frailty, morbidity, and mortality risks using physical activity records from the 2003 - 2006 National Health and Nutrition Examination Survey (NHANES) and UK BioBank (UKB). We proposed a statistical description of the locomotor activity tracks and transformed the provided time series into vectors representing physiological states for each participant. The Principal Components Analysis of the transformed data revealed a winding trajectory with distinct segments corresponding to subsequent human development stages. The extended linear phase starts from 35 40 years old and is associated with the exponential increase of mortality risks according to the Gompertz mortality law. We characterized the distance traveled along the aging trajectory as a natural measure of biological age and demonstrated its significant association with frailty and hazardous lifestyles, along with the remaining lifespan and healthspan of an individual. The biological age explained most of the variance of the log-hazard ratio that was obtained by fitting directly to mortality and the incidence of chronic diseases. Our findings highlight the intimate relationship between the supervised and unsupervised signatures of the biological age and frailty, a consequence of the low intrinsic dimensionality of the aging dynamics.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 55
- FWCI
- 3.46
- Field percentile
- top 7%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Biological age is a universal marker of aging, stress, and frailty
Timothy V. Pyrkov, Peter O. Fedichev·Healthy ageing and longevityPeer-reviewed·Jan 1, 2019
- A mathematical model that predicts human biological age from physiological traits identifies environmental and genetic factors that influence aging
Sergiy Libert, Alex Chekholko, Cynthia J. Kenyon·eLifePeer-reviewed·Jun 11, 2025
- Analysis of the current state of frailty indexes and their implementation for aging intervention studies
Oliver G. Frost, Anna Barkovskaya, … Amit Sharma·AgingPeer-reviewed·Aug 26, 2025
- The AccelerAge framework: A new statistical approach to predict biological age based on time-to-event data
Marije H. Sluiskes, Jelle J. Goeman, … Mar Rodríguez‐Girondo·European Journal of EpidemiologyPeer-reviewed·Apr 6, 2024
- Extracting biological age from biomedical data via deep learning: too much of a good thing?
Timothy V. Pyrkov, Konstantin Slipensky, … Peter O. Fedichev·Scientific ReportsPeer-reviewed·Mar 26, 2018
- Longitudinal analysis of blood markers reveals progressive loss of resilience and predicts ultimate limit of human lifespan
Timothy V. Pyrkov, Konstantin Avchaciov, … Peter O. Fedichev·Nature CommunicationsPeer-reviewed·May 25, 2021