Exploring Allostatic Load as an Objective Measure of Stress Among U.S. Women With and Without HIV: A Pilot Study.

Background: Stress has been found to be linked to adverse health outcomes. Having an objective measure of stress to complement validated self-reported stress measures is helpful for assessing the impact of interventions aimed at reducing stress and measuring its associations with health outcomes. Allostatic load is an objective measure that summarizes stress's impact on multiple physiological systems. However, inconsistent combinations of indicators in an allostatic load index (ALI) are found in literature. The purpose was to (1) explore the ability to identify a set of indicators for inclusion in an ALI related to perceived stress and (2) explore the ability of the calculated ALI to identify an association between ALI and Perceived Stress Scale (PSS) score category among a small sample of women with HIV and comparable women without HIV. Materials and Methods: Data were from participants of the Women's Interagency HIV Study in the United States during 2014-2019 whose PSS score on the PSS-10 questionnaire were in the highest (n = 103) and lowest (n = 103) quartiles for the cohort. The pilot study explored an ALI based on a combination of 15 indicators selected from a literature review. Stepwise regression and logistic regression were used to perform the preliminary analysis. Results: Stepwise regression models identified five indicators for an ALI based on PSS scores. A positive association was found where the ALI predicted membership in the higher stress group (odds ratio = 1.62; 95% confidence interval: 1.11, 2.37; p = 0.012). Conclusion: This pilot study identified a concise set of ALI indicators that may be useful for future stress research and practice. Although preliminary, the identification of an ALI for operationalizing stress may provide a cost-effective and straightforward tool for future research. With further refinement, this measure could offer a method for researchers studying chronic stress, with potential for future clinical application for managing stress-related health outcomes.