J Galen Buckwalter
Allostatic load as a complex clinical construct: a case-based computational modeling approach
Galen Buckwalter, J; Castellani, Brian; Mcewen, Bruce; Karlamangla, Arun S; Rizzo, Albert A; John, Bruce; O'donnell, Kyle; Seeman, Teresa
Authors
Professor Brian Castellani brian.c.castellani@durham.ac.uk
Professor
Bruce Mcewen
Arun S Karlamangla
Albert A Rizzo
Bruce John
Kyle O'donnell
Teresa Seeman
Abstract
Allostatic load (AL) is a complex clinical construct, providing a unique window into the cumulative impact of stress. However, due to its inherent complexity, AL presents two major measurement challenges to conventional statistical modeling (the field's dominant methodology): it is comprised of a complex causal network of bioallostatic systems, represented by an even larger set of dynamic biomarkers; and, it is situated within a web of antecedent socioecological systems, linking AL to differences in health outcomes and disparities. To address these challenges, we employed case‐based computational modeling (CBM), which allowed us to make four advances: (1) we developed a multisystem, 7‐factor (20 biomarker) model of AL's network of allostatic systems; (2) used it to create a catalog of nine different clinical AL profiles (causal pathways); (3) linked each clinical profile to a typology of 23 health outcomes; and (4) explored our results (post hoc) as a function of gender, a key socioecological factor. In terms of highlights, (a) the Healthy clinical profile had few health risks; (b) the pro‐inflammatory profile linked to high blood pressure and diabetes; (c) Low Stress Hormones linked to heart disease, TIA/Stroke, diabetes, and circulation problems; and (d) high stress hormones linked to heart disease and high blood pressure. Post hoc analyses also found that males were overrepresented on the High Blood Pressure (61.2%), Metabolic Syndrome (63.2%), High Stress Hormones (66.4%), and High Blood Sugar (57.1%); while females were overrepresented on the Healthy (81.9%), Low Stress Hormones (66.3%), and Low Stress Antagonists (stress buffers) (95.4%) profiles.
Citation
Galen Buckwalter, J., Castellani, B., Mcewen, B., Karlamangla, A. S., Rizzo, A. A., John, B., O'donnell, K., & Seeman, T. (2016). Allostatic load as a complex clinical construct: a case-based computational modeling approach. Complexity, 21(S1), 291-306. https://doi.org/10.1002/cplx.21743
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 25, 2015 |
Online Publication Date | Dec 23, 2015 |
Publication Date | 2016-09 |
Deposit Date | Sep 24, 2018 |
Journal | Complexity |
Print ISSN | 1076-2787 |
Publisher | Hindawi |
Peer Reviewed | Peer Reviewed |
Volume | 21 |
Issue | S1 |
Pages | 291-306 |
DOI | https://doi.org/10.1002/cplx.21743 |
Public URL | https://durham-repository.worktribe.com/output/1318823 |
Related Public URLs | http://europepmc.org/abstract/MED/28190951 |
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