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Observational Study
. 2023 Aug 1;6(8):e2327584.
doi: 10.1001/jamanetworkopen.2023.27584.

Aging-Related Comorbidity Burden Among Women and Men With or At-Risk for HIV in the US, 2008-2019

Lauren F Collins  1   2 , Frank J Palella Jr  3 , C Christina Mehta  1 , JaNae Holloway  4 , Valentina Stosor  3 , Jordan E Lake  5 , Todd T Brown  6 , Elizabeth F Topper  7 , Susanna Naggie  8 , Kathryn Anastos  9 , Tonya N Taylor  10 , Seble Kassaye  11 , Audrey L French  12 , Adaora A Adimora  13 , Margaret A Fischl  14 , Mirjam-Colette Kempf  15 , Susan L Koletar  16 , Phyllis C Tien  17   18 , Ighovwerha Ofotokun  1   2 , Anandi N Sheth  1   2
Affiliations
Observational Study

Aging-Related Comorbidity Burden Among Women and Men With or At-Risk for HIV in the US, 2008-2019

Lauren F Collins et al. JAMA Netw Open. .

Abstract

Importance: Despite aging-related comorbidities representing a growing threat to quality-of-life and mortality among persons with HIV (PWH), clinical guidance for comorbidity screening and prevention is lacking. Understanding comorbidity distribution and severity by sex and gender is essential to informing guidelines for promoting healthy aging in adults with HIV.

Objective: To assess the association of human immunodeficiency virus on the burden of aging-related comorbidities among US adults in the modern treatment era.

Design, setting, and participants: This cross-sectional analysis included data from US multisite observational cohort studies of women (Women's Interagency HIV Study) and men (Multicenter AIDS Cohort Study) with HIV and sociodemographically comparable HIV-seronegative individuals. Participants were prospectively followed from 2008 for men and 2009 for women (when more than 80% of participants with HIV reported antiretroviral therapy use) through last observation up until March 2019, at which point outcomes were assessed. Data were analyzed from July 2020 to April 2021.

Exposures: HIV, age, sex.

Main outcomes and measures: Comorbidity burden (the number of total comorbidities out of 10 assessed) per participant; secondary outcomes included individual comorbidity prevalence. Linear regression assessed the association of HIV status, age, and sex with comorbidity burden.

Results: A total of 5929 individuals were included (median [IQR] age, 54 [46-61] years; 3238 women [55%]; 2787 Black [47%], 1153 Hispanic or other [19%], 1989 White [34%]). Overall, unadjusted mean comorbidity burden was higher among women vs men (3.4 [2.1] vs 3.2 [1.8]; P = .02). Comorbidity prevalence differed by sex for hypertension (2188 of 3238 women [68%] vs 2026 of 2691 men [75%]), psychiatric illness (1771 women [55%] vs 1565 men [58%]), dyslipidemia (1312 women [41%] vs 1728 men [64%]), liver (1093 women [34%] vs 1032 men [38%]), bone disease (1364 women [42%] vs 512 men [19%]), lung disease (1245 women [38%] vs 259 men [10%]), diabetes (763 women [24%] vs 470 men [17%]), cardiovascular (493 women [15%] vs 407 men [15%]), kidney (444 women [14%] vs 404 men [15%]) disease, and cancer (219 women [7%] vs 321 men [12%]). In an unadjusted model, the estimated mean difference in comorbidity burden among women vs men was significantly greater in every age strata among PWH: age under 40 years, 0.33 (95% CI, 0.03-0.63); ages 40 to 49 years, 0.37 (95% CI, 0.12-0.61); ages 50 to 59 years, 0.38 (95% CI, 0.20-0.56); ages 60 to 69 years, 0.66 (95% CI, 0.42-0.90); ages 70 years and older, 0.62 (95% CI, 0.07-1.17). However, the difference between sexes varied by age strata among persons without HIV: age under 40 years, 0.52 (95% CI, 0.13 to 0.92); ages 40 to 49 years, -0.07 (95% CI, -0.45 to 0.31); ages 50 to 59 years, 0.88 (95% CI, 0.62 to 1.14); ages 60 to 69 years, 1.39 (95% CI, 1.06 to 1.72); ages 70 years and older, 0.33 (95% CI, -0.53 to 1.19) (P for interaction = .001). In the covariate-adjusted model, findings were slightly attenuated but retained statistical significance.

Conclusions and relevance: In this cross-sectional study, the overall burden of aging-related comorbidities was higher in women vs men, particularly among PWH, and the distribution of comorbidity prevalence differed by sex. Comorbidity screening and prevention strategies tailored by HIV serostatus and sex or gender may be needed.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Collins reported receiving honoraria from Curio Sciences during the conduct of the study. Dr Palella reported receiving personal fees from ViiV, Janssen, and Gilead outside the submitted work. Dr Stosor reported grants from National Institutes of Health (NIH) during the conduct of the study; grants from Eli Lilly & Company and personal fees from DiaSorin, S.p.A. outside the submitted work. Dr Lake reported receiving grants from Gilead Sciences and personal fees from Theratechnologies outside the submitted work. Dr Brown reported personal fees from Merck, Gilead, Janssen, and ViiV Healthcare outside the submitted work. Dr Topper reported grants from NIH during the conduct of the study. Dr Naggie reported receiving grants from Gilead Sciences Research and AbbVie Research funding to institution paid to her institution, consulting fees from Pardes Biosciences, advisor fees from Vir Biotechnology, stock options and personal fees from Personal Health Insights, Inc DSMB, and personal fees for event adjudication committee work from Bristol Myers Squibb/PRA Health Sciences outside the submitted work. Dr Anastos reported receiving grants from NIH outside the submitted work. Dr French reported receiving grants from NIH paid to her institution during the conduct of the study. Dr Adimora reported receiving grants from NIH during the conduct of the study; she reported receiving grants and personal fees from Merck and Gilead outside the submitted work. Dr Fischl reported receiving grants from Grant during the conduct of the study. Dr Kempf reported receiving grants from NIH during the conduct of the study. Dr Koletar reported receiving grants from NIH National Institute of Allergy and Infectious Diseases during the conduct of the study; grants from NIH National Heart, Lung, and Blood Institute outside the submitted work. Dr Tien reported grants from NIH during the conduct of the study; she reported receiving grants from Merck outside the submitted work. Dr Sheth reported grants from NIH during the conduct of the study; she reported receiving grants from NIH outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Distribution of Prevalent Non-AIDS Comorbidity (NACM) Burden by HIV Serostatus, Sex, and Age Group
The burden of comorbidities was associated with increasing age; with persons living with vs without HIV; and with women, regardless of HIV serostatus.
Figure 2.
Figure 2.. Estimated Mean Number of Non-AIDS Comorbidities (NACM) Among Persons With and Without HIV Stratified by Sex and Age Group
Participants were enrolled in the Women’s Interagency HIV Study (for women) or the Multicenter AIDS Cohort Study (men), stratified by sex and age group. Adjusted linear regression (model 2) was performed with the following covariates included: race and ethnicity, body mass index, socioeconomic status, cigarette use, alcohol use, crack or cocaine use, in addition to HIV serostatus, age, sex, and all interaction terms (HIV × age × sex, P for interaction = .04).
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