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Modeling multisystem biological risk in later life: Allostatic load in the lothian birth cohort study 1936

Authors

  • Tom Booth,

    Corresponding author
    1. Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
    2. Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
    • Correspondence to: Tom Booth, Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom. E-mail: tom.booth@ed.ac.uk

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  • John M. Starr,

    1. Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
    2. Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, United Kingdom
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  • Ian Deary

    1. Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
    2. Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
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Abstract

Objectives

To investigate and replicate a multisystem model of biological risk, or allostatic load, in a sample of generally healthy older adults.

Methods

Multigroup confirmatory factor analysis (MG-CFA) was applied to data from the Lothian Birth Cohort 1936 (n = 726). Blood samples were taken at a physical examination. Three markers of inflammation (fibrinogen, interleukin-6, and C-reactive protein), five metabolic markers (high- and low-density lipoprotein, body mass index, glycated hemoglobin, and triglyceride), and blood pressure (mean sitting systolic and diastolic blood pressure) were used to estimate a second-order CFA model of allostatic load. Our sample was split into those taking antihypertensive, anti-inflammatory, lipid-lowering, and diabetes medications (n = 470), and those who were not (n = 256), in order to test the stability of the CFA model across groups.

Results

In the nonmedicated sample, a second-order allostatic load model showed good fit to the data. However, the second-order model failed to estimate in the medicated group. The factor correlations between blood pressure and inflammation and metabolism were smaller in magnitude in the medicated group. Invariance analysis on the first-order measurement model suggested significant differences across groups in the associations of low-density lipoprotein and HbA1c with metabolism.

Conclusions

Reliable measurement of allostatic load is possible in ageing samples free of medications but is complicated in the presence of medications. MG-CFA represents a highly versatile method for the analysis of allostatic load. Am. J. Hum. Biol. 25:538–543, 2013. © 2013 Wiley Periodicals, Inc.

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