Key result
Allostatic load shows moderate-to-high overlap with multimorbidity, particularly for cardiometabolic phenotypes.
Why the study?
Heterogeneity in allostatic load specifications raises concerns about capturing distinct physiological dysregulation, leaving unresolved questions regarding its conceptual and analytic overlap with multimorbidity.
How do methodological choices in defining allostatic load affect its relationship with multimorbidity outcomes?
Systematic Review (n=428)
How do methodological choices in defining allostatic load affect its relationship with multimorbidity outcomes?
Allostatic load shows moderate-to-high overlap with multimorbidity, particularly cardiometabolic phenotypes, highlighting the need for more transparent and theoretically coherent operationalizations.
Answers are grounded in this paper and cite their sources.
Measurement inconsistencies warrant clinical caution in allostatic load interpretation; challenges its reliability as a distinct biomarker and leaves open standardization.
Background Allostatic load is conceptualised as a sub-clinical construct reflecting cumulative physiological wear associated with chronic environmental and psychosocial stress. However, marked heterogeneity in biomarker composition, threshold definition, and medication handling raises concerns about whether different specifications consistently capture a distinct subclinical signal of physiological dysregulation. Unresolved questions remain regarding conceptual and analytic overlap with multimorbidity and related health constructs, particularly when medication use is included in its specification. Objective To summarise how population-based studies define and calculate allostatic load, and to assess how these methodological choices affect its relationship with multimorbidity outcomes. Methods We conducted a PRISMA-guided systematic review of population-based studies indexed in Web of Science, PsycINFO, MEDLINE, and CINAHL Ultimate in 2022, using the terms “allostasis” and “allostatic load” in post-2010 papers. We then analysed data from four population-based studies to characterise the association between alternative allostatic load specifications and general,cardiometabolic and immune multimorbidity using C-statistic–based measures. Results Among 428 studies, we found substantial heterogeneity in operationalisation, particularly regarding biomarker composition, systems, threshold definitions, and medication handling. Empirical analyses showed moderate-to-high overlap between allostatic load and multimorbidity (C-statistics 0.64–0.86), with higher values for cardiometabolic and lower for immune phenotypes and following medication adjustment. Using different threshold definitions for allostatic load produced minimal changes in these associations. Conclusions Allostatic load usefully captures multisystem dysregulation, but current operationalisations insufficiently reflect allostatic dynamics and blur subclinical-clinical boundaries. Future research should prioritise longitudinal designs, broader biomarker coverage, and theoretically coherent, transparent approaches to threshold definition and medication adjustment.
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Booker et al. (2026) conducted a systematic review in Allostatic load and multimorbidity (n=428). Allostatic load was evaluated on Overlap between allostatic load and multimorbidity (C-statistics 0.64-0.86). Allostatic load showed moderate-to-high overlap with multimorbidity, with higher values for cardiometabolic and lower for immune phenotypes.
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