Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Predicting all-cause mortality from basic physiology in the Framingham Heart Study.

William B Zhang1,2, Zachary Pincus1,2

  • 1Department of Genetics, Washington University in St. Louis, St. Louis, MO, 63130, USA.

Aging Cell
|October 9, 2015
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Parallel Selection for Longevity in Mammals and Birds.

bioRxiv : the preprint server for biology·2025
Same author

Six Drivers of Aging Identified Among Genes Differentially Expressed With Age.

Aging cell·2025
Same author

Similarities and differences in the gene expression signatures of physiological age versus future lifespan.

Aging cell·2024
Same author

Six drivers of aging identified among genes differentially expressed with age.

bioRxiv : the preprint server for biology·2024
Same author

Functional trajectories during innate spinal cord repair.

Frontiers in molecular neuroscience·2023
Same author

Looking at IGF-1 through the hourglass.

Aging·2022
Same journal

A Non-Canonical Role for Hepatocyte MLKL in Promoting Mitochondrial Dysfunction and Senescence in the Aging Liver.

Aging cell·2026
Same journal

EGR1 Mediates Ursodeoxycholic Acid-Promoted Mitophagy to Prevent Postovulatory Aging of Porcine Oocytes.

Aging cell·2026
Same journal

Interplay of the ENS and Microbiota With Murine Gut Epithelium-Derived Organoids in Aging.

Aging cell·2026
Same journal

Age-Associated Senescence of Decidual Macrophages: A Key Mediator of Adverse Pregnancy Outcomes in Advanced Maternal Age.

Aging cell·2026
Same journal

Correction to "Telomerase Knockout in Myeloid Cells Predisposes Mice to Foam Cell Formation, Dyslipidemia, Lung Fibrosis, and Cardiac Dysfunction".

Aging cell·2026
Same journal

Bidirectional Relationship and Shared Mechanisms Between Sarcopenia and Osteoporosis: An Observational Study Integrating Genomic, Proteomic, and Metabolomic Data.

Aging cell·2026
See all related articles

Simple clinical measurements like blood pressure and glucose can predict future lifespan as early as mid-adulthood. Tracking these health indicators over time offers valuable insights into longevity and all-cause mortality risk.

Area of Science:

  • Gerontology
  • Epidemiology
  • Biostatistics

Background:

  • Cardiovascular disease risk factors are well-established for middle to old age.
  • Predicting all-cause mortality from mid-adulthood using clinical parameters is less explored.

Purpose of the Study:

  • To investigate the predictive value of simple clinical parameters for future lifespan.
  • To determine if these parameters can predict all-cause mortality from mid-adulthood.
  • To explore age-specific predictive power of different clinical measurements.

Main Methods:

  • Longitudinal data analysis of 1349 participants from the Framingham Heart Study.
  • Statistical modeling to assess the relationship between clinical parameters and lifespan.
  • Examination of predictive accuracy across different age ranges.
Keywords:
agingbiodemographycumulative riskmortalityphysiologyrisk prediction

Related Experiment Videos

Main Results:

  • Approximately 10% of lifespan variation is predictable by clinical parameters (blood pressure, glucose, weight, BMI) from ages 28-38.
  • Blood pressure and BMI predict mortality from ages 35-60; blood glucose predicts from ages 57-73.
  • Cumulative exposure to parameters, akin to 'damage accrual,' is more predictive than current values.

Conclusions:

  • Simple clinical measurements possess significant lifespan-predictive value beyond cardiovascular risk.
  • Incorporating longitudinal data enhances the predictive capacity for all-cause mortality.
  • Clinical parameters offer a broader utility in predicting longevity across the adult lifespan.