267750 Accelerated Aging in Midlife Predicts Early Mortality

Tuesday, October 30, 2012 : 3:15 PM - 3:30 PM

Morgan Levine, BA , Gerontology, University of Southern California, Los Angeles, CA
Eileen Crimmins, PhD , Gerontology, University of Southern California, Los Angeles, CA
Age is often an indicator of the body's rate of entropy or “wear and tear”, and Is associated with a physiological breakdown of the organism. However, while the risk of morbidity and mortality increase over the lifespan, individual differences exist in the age of onset of physiological change. The aim of our study is to examine links between physiological dysregulation and chronological age to assess whether we can develop an index of “accelerated aging” and link this index to mortality. The sample consisted of 11,444 persons from NHANES III. Twelve biomarkers were regressed on age using sex-stratified models to generate an equation then used to calculate an expected physiological age. Differences between chronological age and physiological age were then used to create three categories—accelerated aging, typical aging, and decelerated aging. Finally, the probability of and relative risks of mortality over 18 years were calculated by sex and age cohort for aging rate groups. Results showed that subjects who had accelerated age were, on average, more than twice as likely to die as those with decelerated aging. Furthermore, accelerating aging subjects who were 30-39 at baseline were found to have a higher mortality risk than slower aging subjects who were on average ten years older—aged 40-49. Due to variations in aging rates, identifying at-risk individuals in middle-age is essential to improving efficacy in preventative medicine. Furthermore, generating a construct that predicts mortality risk and, unlike chronological age, possesses plasticity, will facilitate the development of preventative interventions to impact longevity.

Learning Areas:
Biostatistics, economics
Chronic disease management and prevention
Epidemiology
Public health biology
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
1. Analyze links between physiological dysregulation and chronological age. 2. Develop an index of “accelerated aging” and link this index to mortality. 3. Identify middle-aged subjects at increased risk of early mortality. 4. Define a construct that predicts mortality risk, which unlike chronological age possesses plasticity, facilitating the development of preventative interventions to impact longevity.

Keywords: Aging, Biostatistics

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a second year doctoral student with training and experience in biostatistics and biodemography research of aging. Furthermore, I am also a recipient of the Multidisciplinary Research Training Grant in Gerontology. My current research interests pertain to investigating variations in aging rates among humans, to examine causes and outcomes of accelerated aging.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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