Modeling multisystem biological risk in young adults: The Coronary Artery Risk Development in Young Adults Study.
Although 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 multisystems view of health risks. How best to operationalize allostatic load, however, remains the subject of some debate. We sought to test a hypothesized metafactor model of allostatic load composed of a number of biological system factors, and to investigate model invariance across sex and ethnicity. 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 15exam 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). A "metafactor" model of AL as an aggregate measure of six underlying latent biological subfactors was found to fit the data, with the metafactor structure capturing 84% of variance of all pairwise associations among biological subsystems. There was little evidence of model variance across sex and/or ethnicity. These analyses extend work operationalizing AL as a multisystems index of biological dysregulation, providing initial support for a model of AL as a metaconstruct of inter-relationships among multiple biological regulatory systems, that varies little across sex or ethnicity.
Seeman
Teresa
T
Division of Geriatrics, David Geffen School of Medicine at UCLA, Los Angeles, California 90095-1687, USA. tseeman@mednet.ucla.edu
Gruenewald
Tara
T
Karlamangla
Arun
A
Sidney
Steve
S
Liu
Kiang
K
McEwen
Bruce
B
Schwartz
Joseph
J
D000328:Adult; D052636:Allostasis; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D002097:C-Reactive Protein / Q000032:analysis; D002140:California; D003327:Coronary Disease / Q000453:epidemiology*; D004837:Epinephrine / Q000652:urine; D005260:Female; D005340:Fibrinogen / Q000032:analysis; D006305:Health Status Indicators; D006339:Heart Rate; D006801:Humans; D006854:Hydrocortisone / Q000032:analysis; D007087:Illinois / Q000453:epidemiology; D007328:Insulin / Q000097:blood; D015850:Interleukin-6 / Q000097:blood; D008055:Lipids / Q000097:blood; D008297:Male; D008875:Middle Aged; D009638:Norepinephrine / Q000652:urine; D011446:Prospective Studies; D012463:Saliva / Q000737:chemistry; D055105:Waist Circumference
D001786:Blood Glucose; D007328:Insulin; D015850:Interleukin-6; D008055:Lipids; D005340:Fibrinogen; D002097:C-Reactive Protein; D006854:Hydrocortisone; D009638:Norepinephrine; D004837:Epinephrine