Longitudinal activity monitoring and lifespan: quantifying the interface

Understanding the relationship between activity over the entire lifespan and longevity is an important facet of aging research. We present a comprehensive framework for the statistical analysis of longitudinal activity and behavioral monitoring and their relationship with age-at-death at the individual level, highlighting the importance of advanced methodological approaches in aging research. The focus is on animal models, where continuous monitoring activity in terms of movement, reproduction and behaviors over the entire lifespan is feasible at the individual level. We specifically demonstrate the methodology with data on activity monitoring for Mediterranean fruit flies. Advanced statistical methodologies to explore the interface between activity and age-at-death include functional principal component analysis, concurrent regression, Fréchet regression and point processes. While the focus of this perspective is on relating age-at-death with data on movement, reproduction, behavior and nutrition of Mediterranean fruit flies, the methodology equally pertains to data from other species, including human data.

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Publication Details

Journal
Aging
Published
2024-09-09
DOI
https://doi.org/10.18632/aging.206106
Citations
1
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
article
Field-Weighted Citation Impact
0.23

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Longitudinal activity monitoring and lifespan: quantifying the interface

Hans‐Georg Müller, Su I Iao, Han Chen, Poorbita Kundu et al.
1 citations
Aging
Genetics, Aging, and Longevity in Model Organisms
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article

Longitudinal activity monitoring and lifespan: quantifying the interface

Hans‐Georg Müller, Su I Iao, Han Chen, Poorbita Kundu, James R. Carey
article en
1 citations

Abstract

Understanding the relationship between activity over the entire lifespan and longevity is an important facet of aging research. We present a comprehensive framework for the statistical analysis of longitudinal activity and behavioral monitoring and their relationship with age-at-death at the individual level, highlighting the importance of advanced methodological approaches in aging research. The focus is on animal models, where continuous monitoring activity in terms of movement, reproduction and behaviors over the entire lifespan is feasible at the individual level. We specifically demonstrate the methodology with data on activity monitoring for Mediterranean fruit flies. Advanced statistical methodologies to explore the interface between activity and age-at-death include functional principal component analysis, concurrent regression, Fréchet regression and point processes. While the focus of this perspective is on relating age-at-death with data on movement, reproduction, behavior and nutrition of Mediterranean fruit flies, the methodology equally pertains to data from other species, including human data.

AgingVol. 16(17)
University of California, Davis (US)
National Science Foundation, National Institutes of Health
Zero hunger
Openalex Percentile: Top 47%
Genetics, Aging, and Longevity in Model Organisms
0.23
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