image: Figure 9. Mean function and eigenfunctions for longitudinal behavioral data. The estimated mean function μ^ and the first three estimated spherical eigenfunctions ϕ^1, ϕ^2, ϕ^3 for the behavioral fly data using spherical functional principal component analysis. The first three eigenfunctions explain 96.54% of the total variation, with the individual components explaining 80.55%, 12.23% and 3.76%, respectively.
Credit: 2024 Iao et al.
“We specifically demonstrate the methodology with data on activity monitoring for Mediterranean fruit flies.”
BUFFALO, NY- September 18, 2024 – A new research perspective was published in Aging (listed by MEDLINE/PubMed as “Aging (Albany NY)” and “Aging-US” by Web of Science), Volume 16, Issue 17 on September 9, 2024, entitled, “Longitudinal activity monitoring and lifespan: quantifying the interface.”
As highlighted in the abstract of this perspective, understanding the relationship between lifelong activity and longevity is a crucial aspect of aging research.
Researchers Su I Iao, Poorbita Kundu, Han Chen, James R. Carey, and Hans-Georg Müller from the Departments of Statistics and Entomology at the University of California, Davis, present a comprehensive framework for analyzing longitudinal activity and behavior. Their study examines how these factors relate to age-at-death on an individual level, emphasizing the importance of advanced statistical methods in aging research.
While the authors demonstrate their methodology using lifetime monitoring data from Mediterranean fruit flies, they emphasize that it can be adapted to other species, including humans. Advanced statistical techniques, such as functional principal component analysis, concurrent regression, Fréchet regression, and point processes, are employed to explore the relationship between activity and age-at-death. Although the study focuses on linking movement, reproduction, behavior, and nutrition data in Mediterranean fruit flies to age-at-death, the same methodologies are applicable across different species.
“We provide an overview of advanced statistical methodologies that are particularly well-suited for analyzing such data, with a focus on understanding the complex relationships between age-at-death and activity, reproduction and diet at the individual level.”
Continue reading: DOI: https://doi.org/10.18632/aging.206106
Corresponding author: Hans-Georg Müller – hgmueller@ucdavis.edu
Video short: https://www.youtube.com/watch?v=NLB3vl7Jih8
Keywords: aging, age-at-death, force of mortality, functional data analysis, longitudinal data, mediterranean fruit fly
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About Aging:
The journal Aging aims to promote 1) treatment of age-related diseases by slowing down aging, 2) validation of anti-aging drugs by treating age-related diseases, and 3) prevention of cancer by inhibiting aging. (Cancer and COVID-19 are age-related diseases.)
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Journal
Aging-US
Method of Research
News article
Subject of Research
Not applicable
Article Title
Longitudinal activity monitoring and lifespan: quantifying the interface
Article Publication Date
9-Sep-2024
COI Statement
The authors declare no conflicts of interest related to this study.