by Carolyn Chu, MD, MSc, AAHIVS, AAHIVM Chief Medical Officer
June 21, 2022
This analysis of WIHS cohort data was undertaken to evaluate whether HIV modifies the effects of age and menopausal status on non-AIDS comorbidity burden. 2,716 women (1,931 living with HIV and 785 without HIV) aged 26-59 years with at least 2 study visits from 2009 through the end of March 2018 were included. Detailed assessment was undertaken at each study visit to gather medical history, perform physical examination, and collect biospecimens. Primary outcome was comorbidity burden, defined as the number of prevalent non-AIDS comorbidities (out of 10 total assessed: hypertension, dyslipidemia, diabetes, non-AIDS cancer, psychiatric illness, cardiovascular, kidney, lung, liver, and bone disease) and as indicated by participant-reported diagnosis or medication; clinical measurement; and/or laboratory evidence. Comparing women with HIV vs. without HIV, post-menopausal status was 10% vs. 6%, 34% vs. 21%, and 86% vs. 85% among women aged <40, 40-49, and 50-59 years, respectively. In covariate-adjusted analyses, menopausal status, age, and HIV were all independently associated with higher comorbidity burden. The estimated mean burden among pre-, peri-, and post-menopausal women overall was 2.26, 2.83, and 3.41, respectively, and was higher in successive age groups. Comparing women with vs. without HIV, the estimated mean difference in comorbidity burden stratified by age <40, 40-49, and 50-59 years was +0.22, +0.50, +0.52 among pre-menopausal women; +0.52, +0.43, +0.47 among peri-menopausal women; and -0.22, +0.25, +0.18 among post-menopausal women.
Author’s Commentary:
This study expands on previous investigations of aging-related comorbidity and suggests that the disproportionate burden of chronic disease among women with HIV may affect individuals experiencing pre- and peri-menopause more so than post-menopausal women. Importantly, authors note that: “in disentangling the effects of chronological vs. reproductive aging … it is important to consider that HIV-specific virologic, immunologic, and socio-behavioral factors likely influence both processes.” Additional research is needed to characterize the associations between these factors, and to determine whether similar results to this analysis are observed among other cohorts. Appropriate risk modification strategies and clinical interventions can then be identified and tailored to key populations to ensure optimal health outcomes.
The author has no conflicts of interest to disclose.
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