A factor analytic investigation of allostatic load and associations with cognitive performance
Date
2026
Authors
McDowell, Cynthia
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Abstract
Introduction: Allostatic load (AL) reflects the cumulative physiological burden resulting from long-term chronic stress and has been linked to a range of adverse health outcomes, including cognitive impairment. However, operationalizing and measuring AL – requiring the integration of heterogeneous biomarkers across distinct physiological systems into a single unified construct – remains a significant methodological challenge. Research applying latent factor modeling to examine the underlying structure of AL is particularly limited, especially in older adults, despite AL being conceptualized as a cumulative, multisystem, and protracted process.
Objectives: The present dissertation addressed two primary research questions: (1) Which latent factor structure best indexes AL in older adulthood? and (2) Is this AL latent factor model associated with individual differences in cognitive performance? Methods: Seventeen biomarkers spanning four physiological systems (cardiovascular, anthropometric, metabolic, and inflammatory) were analyzed in a large sample (N = 12,646) of community-dwelling adults aged 65 and older (Mage = 73.10 years; 50.13% Males). Four distinct AL measurement models were tested and compared using confirmatory factor analysis to identify the model of best fit for males and females separately. Structural equation modeling was then used to examine whether the final latent AL factor was associated with six cognitive tasks spanning executive functioning, memory, and psychomotor processing speed domains, while adjusting for age, education, and total medication use.
Results: A bifactor model with relaxed orthogonality constraints emerged as the best-fitting structure for both sexes, whereby biomarkers loaded onto both a general AL factor and system-specific latent factors. In males, tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6) were the strongest contributors to the general AL factor, highlighting the central role of inflammatory processes in males. In females, triglycerides and high-density lipoprotein (HDL) cholesterol were the strongest indicators of AL, suggesting that lipid dysregulation may be more salient in the expression of AL among aging females. Using this bifactor model structure, the general AL factor was significantly associated with individual differences in performance across all three cognitive domains in both sexes, even after adjusting for covariates.
Conclusion: This dissertation provides an empirically rigorous and theory-informed modeling approach that advances both the conceptual and methodological foundations of AL research. The findings highlight the value of a latent AL factor for capturing individual differences in cognitive health and provide key insights for measuring multisystem dysregulation, understanding sex-specific biological differences, and enhancing early identification of cognitive vulnerabilities linked to chronic stress in older adults.
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Keywords
allostatic load, chronic stress, cognitive performance, structural equation modeling, older adulthood