Evidence map›Paper›PMID 26446764›Full record

ArticleAging cell2016

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

William B Zhang, Zachary Pincus

Abstract read
In one paragraph

Article in Aging cell, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Frailty and blood pressure in older adults: rethinking risk and treatment strategies.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Low birth weight trends: possible impacts on the prevalences of hypertension and chronic kidney disease.Hypertension research : official journal of the Japanese Society of Hypertension · 2020
    Review
  13. Article
  14. Review
  15. Article
  16. Blood Pressure Management: Beyond the Guidelines.Hypertension (Dallas, Tex. : 1979) · 2018
    Article
  17. Article
  18. Heterogeneity of Human Aging and Its Assessment.The journals of gerontology. Series A, Biological sciences and medical sciences · 2017
    Article
  19. The Longitudinal Study of Aging in Human Young Adults: Knowledge Gaps and Research Agenda.The journals of gerontology. Series A, Biological sciences and medical sciences · 2017
    Article
  20. Dynamics of biomarkers in relation to aging and mortality.Mechanisms of ageing and development · 2016
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

William B ZhangDepartment of Genetics, Washington University in St. Louis, St. Louis, MO, 63130, USA.
Zachary PincusDepartment of Genetics, Washington University in St. Louis, St. Louis, MO, 63130, USA.

Funding

NATIONAL RESEARCH SERVICE AWARD-MEDICAL SCIENTISTT32GM007200 · NIGMS · WASHINGTON UNIVERSITY · PI YOKOYAMA, WAYNE M. · 1985 to 2024
$59.8M
Discover determinants of individual longevity and health in C. elegansR00AG042487 · NIA · WASHINGTON UNIVERSITY · PI PINCUS, ZACHARY · 2014 to 2016
$740k
NIA NIH HHS R00 AG042487NIGMS NIH HHS 5T32 GM07200
6 · The paper itself

Abstract

Using longitudinal data from a cohort of 1349 participants in the Framingham Heart Study, we show that as early as 28-38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Specifically, we found diastolic and systolic blood pressure, blood glucose, weight, and body mass index (BMI) to be relevant to lifespan. These and similar parameters have been well-characterized as risk factors in the relatively narrow context of cardiovascular disease and mortality in middle to old age. In contrast, we demonstrate here that such measures can be used to predict all-cause mortality from mid-adulthood onward. Further, we find that different clinical measurements are predictive of lifespan in different age regimes. Specifically, blood pressure and BMI are predictive of all-cause mortality from ages 35 to 60, while blood glucose is predictive from ages 57 to 73. Moreover, we find that several of these parameters are best considered as measures of a rate of 'damage accrual', such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack-years of cigarette smoking). In short, we show that simple physiological measurements have broader lifespan-predictive value than indicated by previous work and that incorporating information from multiple time points can significantly increase that predictive capacity. In general, our results apply equally to both men and women, although some differences exist.

Indexed as

Body Mass IndexAdultAgedBlood PressureBody WeightCardiovascular DiseasesFemaleHumansMaleMiddle AgedObesityPredictive Value of TestsRisk Factorsagingbiodemographycumulative riskmortalityphysiologyrisk prediction

Identifiers

PMID26446764
PMCPMC4717277

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.