Biological correlates of adult cognition: Midlife in the United States (MIDUS)

Abstract

Multiple biological processes are related to cognitive impairment in older adults, but their combined impact on cognition in midlife is not known. Using an array of measurements across key regulatory physiological systems and a state-of-the-art cognition battery that is sensitive to early changes, on a large, national sample of middle-aged and older adults, we examined the associations of individual biological systems and a combined, multi-system index, allostatic load, with cognitive performance. Allostatic load was strongly inversely associated with performance in both episodic memory and executive function. Of seven biological systems, only the cardiovascular system was associated inversely with both; inflammation was associated inversely with episodic memory only, and glucose metabolism with executive function only. The associations of allostatic load with cognition were not different by age, suggesting that the implications of high allostatic load on cognitive functioning are not restricted to older adults. Findings suggest that a multi-system score, like allostatic load, may assist in the identification of adults at increased risk for cognitive impairment at en early age.

Allostatic load and biological anthropology

“…Cut-points defined by quartiles Seeman et al (1997Seeman et al ( , 2001Seeman et al ( , 2002, Seeman, Crimmins, et al (2004), Seeman, Glei, et al (2004), Kubzansky et al (1999), Karlamangla et al (2002Karlamangla et al ( , 2014, Schnorpfeil et al (2003), Weinstein et al (2003), Hampson et al (2009), Lipowicz et al (2014, Riva et al (2014), Barboza Solís et al (2015), Gale et al (2015), Horan and Widom (2015), McClure et al (2015), Zilioli et al (2015), Hansen et al (2016), Kusano et al (2016), and Robertson and Watts (2016) Cut-points defined by deciles Goldman et al (2005), Glei et al (2007), and Hwang et al (2014) Cut-points defined using clinical criteria Seeman et al (2008), Hampson et al (2009), Bird et al (2010 and Rosenberg et al (2014) Cut-points defined using a combination of clinical criteria and either deciles or quartiles (2015), Gale et al (2015), and Robertson and Watts (2016) Use of two-tailed cut-points Hampson et al (2009) and Hwang et al (2014) Use of recursive partitioning to calculate allostatic load Gruenewald et al (2006) Allostatic load scored by system rather than by biomarkers Karlamangla et al (2014), Seeman et al (2014), Gay et al (2015), and Zilioli et al (2015) Calculated allostatic...…”

Allostatic Load and Personality

“…This cumulative biological dysregulation has pervasive consequences for physical and mental health. Individuals with higher allostatic load, for example, have more disability and functional limitations (2–4), lower bone strength (5), more cognitive impairment (6), and greater risk of major depression (7). Higher allostatic load also predicts a range of adverse health outcomes, including cardiovascular disease (8) and all-cause mortality (9).…”

“…Higher allostatic load also predicts a range of adverse health outcomes, including cardiovascular disease (8) and all-cause mortality (9). This multi-system physiological dysregulation tends to be stronger than any single biological system indicator in predicting health outcomes (6, 10). In this study, we examine whether allostatic load is associated with changes in personality —i.e.…”

The Role of Stress in Periodontal Disease Progression in Older Adults

“…More complex scoring algorithms have been recently developed to expand the range of physiological measurements and account for unequal weighting, although no “gold standard” approach has yet been accepted. Nevertheless, even with a cruder summative scoring approach, cross-sectional and longitudinal studies of older adults have shown that allostatic load is a strong independent predictor of incident cardiovascular disease (Seeman et al 1997), declines in cognitive and physical functioning (Karlamangla et al 2002, Wikby et al 2005, Gruenewald et al 2009, Karlamangla et al 2013), and all-cause mortality (Seeman et al 2004, Gruenewald et al 2006, Karlamangla et al 2006, Borrell et al 2010). …”