Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes.
Bibliographical noteFunding Information:
This research was supported by Grants from the National Institute on Aging to the University of Michigan (U01 AG009740) and to the University of Southern California (R01 AG AG060110).
This analysis was supported by funds from the National Institutes of Health/National Institute on Aging R01 AG060110. The Health and Retirement Study is supported by NIH/NIA-U01-AG009740. SAS 9.4 and Stata 16 were used for the analysis.
This analysis was supported by funds from the National Institutes of Health/National Institute on Aging R01 AG060110. The Health and Retirement Study is supported by NIH/NIA-U01-AG009740.
© 2021, The Author(s).
- Biological age
- Phenotypic age
- TAME markers