Predicting Mortality from Profiles of Biological Risk and Performance Measures of Functioning

  • Sarinnapha VasunilashornEmail author
  • Latrica E. Best
  • Jung Ki Kim
  • Eileen M. Crimmins
Part of the European Studies of Population book series (ESPO, volume 18)


While high-risk levels of individual biological and functioning indicators are predictive of adverse health outcomes, the use of measures that incorporate multiple measures is often a better indicator of current health and a better predictor of health outcomes than any single marker. Using the latent class approach and multiple markers indicating functioning across several physiological systems, this study groups individuals into risk classes for mortality. Participants age 60+ from the US National Health and Nutrition Examination Survey III (1988–1994) were included (N = 3,120), and logistic regression models were used to determine the relationship between the latent risk classes and 5-year mortality. The indicators examined included a number of biomarkers and measures of physiological and mental conditions. With the ten physiological indicators and five functioning/frailty indicators, individuals were categorized into four latent classes termed: no high-risk, high inflammation, high blood pressure, and high frailty. Compared to the no high-risk class, participants in the high inflammation and high frailty classes were 2.6 and 2.8 times as likely to die within 5-years of the initial exam (respectively); people in the high blood pressure class were 1.8 times as likely to die relative to the no high-risk class. Based on the ability of the latent class approach to predict 5-year mortality, we suggest that this approach to classifying individuals based on their biological and functioning indicators is an appropriate method for grouping people into classes indicating their risk of death.


Biomarkers Latent classes Performance indicators Risk factors United States 



This work was supported in part by the US National Institute on Aging Grants T32AG0037 and P30 AG17265. Merril Silverstein and Wonho Lee provided helpful suggestions on a previous draft of this manuscript.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sarinnapha Vasunilashorn
    • 1
    Email author
  • Latrica E. Best
    • 2
  • Jung Ki Kim
    • 3
  • Eileen M. Crimmins
    • 3
  1. 1.Division of General Medicine and Primary CareBeth Israel Deaconess Medical Center, Harvard Medical SchoolBrooklineUSA
  2. 2.Department of Pan-African Studies and Department of SociologyUniversity of LouisvilleLouisvilleUSA
  3. 3.Andrus Gerontology CenterUniversity of Southern CaliforniaLos AngelesUSA

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