TY - JOUR
T1 - Predicting all-cause mortality from basic physiology in the Framingham Heart Study
AU - Zhang, William B.
AU - Pincus, Zachary
N1 - Funding Information:
ZP and WZ are supported by NIH grant R00 AG042487 and Longer Life Foundation grant 2015-008. WZ is additionally supported by NIH grant 5T32 GM07200.
Funding Information:
ZP and WZ are supported by NIH grant R00 AG042487 and Longer Life Foundation grant 2015-008. WZ is additionally supported by NIH grant 5T32 GM07200.
Publisher Copyright:
© 2016 The Anatomical Society and John Wiley & Sons Ltd.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - 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.
AB - 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.
KW - Aging
KW - Biodemography
KW - Cumulative risk
KW - Mortality
KW - Physiology
KW - Risk prediction
UR - http://www.scopus.com/inward/record.url?scp=84955215776&partnerID=8YFLogxK
U2 - 10.1111/acel.12408
DO - 10.1111/acel.12408
M3 - Article
C2 - 26446764
AN - SCOPUS:84955215776
SN - 1474-9718
VL - 15
SP - 39
EP - 48
JO - Aging Cell
JF - Aging Cell
IS - 1
ER -