Modeling multisystem physiological dysregulation

Journal article


Wiley, Joshua F., Gruenewald, Tara L., Karlamangha, Arun S. and Seeman, Teresa E.. (2016). Modeling multisystem physiological dysregulation. Psychosomatic Medicine. 78(3), pp. 290-301. https://doi.org/10.1097/PSY.0000000000000288
AuthorsWiley, Joshua F., Gruenewald, Tara L., Karlamangha, Arun S. and Seeman, Teresa E.
Abstract

Objectives
The purposes of this study were to compare the relative fit of two alternative factor models of allostatic load (AL) and physiological systems, and to test factor invariance across age and sex.

Methods
Data were from the Midlife in the United States II Biomarker Project, a large (n = 1255) multisite study of adults aged 34 to 84 years (56.8% women). Specifically, 23 biomarkers were included, representing seven physiological systems: metabolic lipids, metabolic glucose, blood pressure, parasympathetic nervous system, sympathetic nervous system, hypothalamic-pituitary-adrenal axis, and inflammation. For factor invariance tests, age was categorized into three groups (≤45, 45–60, and >60 years).

Results
A bifactor model where biomarkers simultaneously load onto a common AL factor and seven unique system-specific factors provided the best fit to the biomarker data (comparative fit index = 0.967, root mean square error of approximation = 0.043, standardized root mean square residual = 0.028). Results from the bifactor model were consistent with invariance across age groups and sex.

Conclusions
These results support the theory that represents and operationalizes AL as multisystem physiological dysregulation and operationalizing AL as the shared variance across biomarkers. Results also demonstrate that in addition to the variance in biomarkers accounted for by AL, individual physiological systems account for unique variance in system-specific biomarkers. A bifactor model allows researchers greater precision to examine both AL and the unique effects of specific systems.

Keywordsphysiological dysregulation; allostatic load; biomarkers; Midlife in the United States
Year2016
JournalPsychosomatic Medicine
Journal citation78 (3), pp. 290-301
PublisherLippincott Williams & Wilkins
ISSN0033-3174
Digital Object Identifier (DOI)https://doi.org/10.1097/PSY.0000000000000288
PubMed ID26734956
Scopus EID2-s2.0-84953309368
PubMed Central IDPMC4844860
Open accessPublished as green open access
Page range290-301
FunderJohn D. and Catherine T. MacArthur Foundation
National Institute on Aging (NIA), National Institutes of Health
Georgetown University
General Clinical Research Centers Program
National Center for Advancing Translational Sciences (NCATS), National Institutes of Health
National Institute of General Medical Sciences (NIGMS), National Institutes of Health
Research GroupMary MacKillop Institute for Health Research
Author's accepted manuscript
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Open
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All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Online2016
Grant IDP01-AG020166
M01- RR023942
M01-RR00865
UL1TR000427
T32GM084903
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