Journal
PSYCHONEUROENDOCRINOLOGY
Volume 139, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.psyneuen.2022.105689
Keywords
Allostatic load; Patterns; Disparities; Life course
Categories
Funding
- National Institute for Child Health and Development, USA (NICHD) [R01HD058515, T32-ES02377]
- National Institute of Environmental Health Sciences, USA (NIEHS)
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This study compares the effects of different operationalizations on allostatic load (AL) and examines the expected disparities in AL by race, socioeconomic status (SES), and sex. The results demonstrate that different constructions of AL yield expected disparities by race and SES, while sex differences depend on whether sex-specific quartiles are used to construct the AL score.
Since its conceptualization, there has been a lack of consensus on the best way to operationalize allostatic load (AL). As a marker of the cumulative, physiological wear and tear on the body resulting from chronic exposure to stressors, it follows that AL should be higher among people who have faced more stressful life experiences. Thus, the purpose of this study was to construct AL scores using different operationalizations and, as a measure of construct validity, compare whether each construction produced expected disparities in AL by race and a composite socioeconomic status (SES) variable which accounts for measures over the life course; we also explored differences by sex. We conducted the study in a sample of 45-52-year-old offspring from the Child Health and Development Studies, a longitudinal birth cohort established in the early 1960s. AL scores were constructed in 6 different ways and included 10 biomarkers from inflammatory, neuroendocrine, cardiovascular, and metabolic systems. Our main approach to constructing AL was to sum across high-risk biomarker quartiles, correct for medication use, and use sex-specific high-risk quartiles for specific biomarkers. Alternative constructions did not use sex-specific quartiles and/or weighted biomarkers within subsystems and/or did not correct for medication use. We estimated differences in AL scores by race, SES, sex and their pairwise interactions. All constructions of AL, including the main approach, produced expected disparities by race (higher scores for Black vs. non-Black participants) and life course SES (higher scores for low vs. high SES participants). However, disparities by sex only emerged when the AL score was constructed via approaches that did not use sex-specific high-risk quartiles; for these alternative constructions, overall, female participants had higher AL scores than male participants and Black female participants had the highest AL scores in the sample. For most constructions, the pairwise interaction between sex and SES, showed a stronger disparity in AL scores between low and high-SES female compared with low- and high-SES male participants; this suggests that, in terms of lowering AL, high life course SES may be more important for female than male participants. In conclusion, our results suggest that the basic AL concept is consistently expressed in different operationalizations, making it an especially useful and robust tool for understanding disparities by race and SES.
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