Modeling Multi-System Biological Risk in Young Adults: The Coronary Artery Risk Development in Young Adults Study (CARDIA)

Abstract

Background: While much prior research has focused on identifying the roles of major regulatory systems in health risks, the concept of allostatic load (AL) focuses on the importance of a more multi-systems view of health risks. How best to operationalize allostatic load, however, remains the subject of some debate.
Aim: To test a hypothesized meta-factor model of allostatic load composed of a number of biological system factors, and to investigate model invariance across sex and ethnicity.
Subjects & Methods: Biological data from 782 men and women, aged 32-47, from the Oakland, CA and Chicago, IL sites of the Coronary Artery Risk Development in Young Adults Study (CARDIA) were collected as part of the Year 15 exam in 2000. These include measures of blood pressure, metabolic parameters (glucose, insulin, lipid profiles, and waist circumference), markers of inflammation (interleukin-6, C-reactive protein, and fibrinogen), heart rate variability, sympathetic nervous system activity (12 hr urinary norepinephrine and epinephrine) and hypothalamic-pituitary-adrenal axis activity (diurnal salivary free cortisol).
Results: A “meta-factor” model of AL as an aggregate measure of six underlying latent biological subfactors was found to fit the data, with the meta-factor structure capturing 84% of variance of all pairwise associations among biological subsystems. There was little evidence of model variance across sex and/or ethnicity.
Conclusions: These analyses extend work operationalizing AL as a multi-systems index of biological dysregulation, providing initial support for a model of AL as a meta4 construct of inter-relationships among multiple biological regulatory systems, that varies little across sex or ethnicity.