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Cited by 483Health disparities and outcomesFrailty in Older AdultsChronic Disease Management Strategies

Allostatic load as a predictor of functional decline

Karlamangla, Arun S, Singer, Burton H, McEwen, Bruce S, Rowe, John W, Seeman, Teresa E·2002·Journal of Clinical Epidemiology
DOI 10.1016/s0895-4356(02)00399-2
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Abstract

Allostatic load has been proposed as a cumulative measure of dysregulation across multiple physiological systems, and has been postulated to impact health risks. In the allostatic load model, increased risk is hypothesized to result not only from large and clinically significant dysregulation in individual systems, but also from more modest dysregulation, if present in multiple systems. Our objective was to construct an allostatic load score by optimally combining several physiologic measurements, and to examine its association with future functional decline. We analyzed data from a 7-year longitudinal study of a community-based cohort, whose age at baseline was between 70 and 79 years. Canonical correlation analysis was used to study the association of 10 biological measurements representing allostatic load with declines in scores on five tests each of physical and cognitive function over two follow-up periods: 1998-1991 and 1991-1995. We used bootstrapping to evaluate the stability of the canonical correlation and canonical weights. The canonical correlation between allostatic load and the 20 decline scores was 0.43 (P =.03) and the [25th, 75th] percentile interval of its distribution over 200 bootstrapped subsamples of the cohort was [0.48, 0.53]. These findings were not substantially affected by adjusting for covariates and cardiovascular disease. We conclude that a summary measure of physiologic dysregulation, such as allostatic load, is an independent predictor of functional decline in elderly men and women.

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  • Associations between allostatic load and outcomes are replicated when alternative scoring methods, including canonical correlation analyses, grade-of-membership, and recursive partitioning, are used to create allostatic load indices.

    “Subsequent work has shown that these associations are repli-cated when a variety of alternative scoring methods that incorporate more complex and detailed scoring algorithms are used to create indices of AL, including canonical correlation analyses, 169 grade-ofmembership 166,167,182 and recursive partitioning.168”

    From Socio‐economic differentials in peripheral biology: Cumulative allostatic load (2010) · cites this paper as [169]

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Authors
Karlamangla, A. S., Singer, B. H., McEwen, B. S., Rowe, J. W., & Seeman, T. E.
Affiliations
  • University of California, Los Angeles (US)
  • Princeton University (US)
  • Rockefeller University (US)
  • Aetna (United States) (US)
ORCID
Venue
Journal of Clinical Epidemiology
Publisher
Elsevier BV
Published
2002-07
Volume
55
Issue
7
Pages
696-710
ISSN
0895-4356 (ISSN-L)
DOI
10.1016/s0895-4356(02)00399-2
OpenAlex
W1991627437
Cited by
483
References
88
Citations by year
2026: 12 · 2025: 12 · 2024: 14 · 2023: 18 · 2022: 16 · 2021: 27 · 2020: 21 · 2019: 21 · 2018: 27 · 2017: 24 · 2016: 24 · 2015: 32 · 2014: 27 · 2013: 22 · 2012: 18
FWCI
15.57
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Journal of Clinical Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • John D. and Catherine T. MacArthur Foundation
  • National Institutes of Health (5r01ag017056-03)
  • National Institute on Aging (1K12AG01004, AG17265, K12AG001004, P30AG017265, AG 17056)
Topics
  • Social Sciences › Health › Health disparities and outcomes
  • Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
  • Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
Keywords
allostatic load, functional decline, physiological dysregulation, older adults, physical function, cognitive function, biomarkers, cumulative risk
MeSH terms
Adaptation, Physiological, Aged, Aging, Female, Health Status Indicators, Humans, Longitudinal Studies, Male, Predictive Value of Tests, Cohort Studies, Geriatric Assessment

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