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

William B. Zhang, Zachary Pincus

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


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.

Original languageEnglish
Pages (from-to)39-48
Number of pages10
JournalAging Cell
Issue number1
StatePublished - Feb 1 2016


  • Aging
  • Biodemography
  • Cumulative risk
  • Mortality
  • Physiology
  • Risk prediction


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