Because combination antiretroviral therapy (cART) has been used to treat HIV, HIV-related morbidity and mortality have decreased, and people living with HIV (PLWH) are living longer [1,2]. As PLWH age, their risk of developing age-related comorbidities increases, and there is evidence that PLWH experience illnesses associated with aging 5 or more years earlier, and/or in a more severe form, than those living without HIV [1–8]. This increased number of comorbidities often results in a greater number of medications. Consequently, the risk of polypharmacy and the potential for drug–drug interactions with cART is increased among PLWH [2,5]. Comorbid conditions and concomitant medication use have been previously described in PLWH, and the commonly seen chronic conditions include cardiovascular disease, hypertension, hyperlipidemia, kidney disease, metabolic syndrome, and diabetes [5,6]. However, the participants of these studies have been mostly men [1,3,6,7,9–12].
Women living with HIV (WLWH) represent 50% of PLWH worldwide  and close to 25% of PLWH in Canada . Women experience many socio-structural factors that act as barriers to accessing health care, including economic, social, and cultural factors, which can contribute to higher disease burden . Furthermore, women of lower social and economic status are not only more vulnerable to acquiring HIV, they are also less likely to be reached by health promotion strategies or to access healthcare facilities for support . Although women in the general population have a longer life expectancy than men, in the Canadian population, women have been shown to have higher rates of multimorbid chronic disease burden [16,17]. At all ages above 35 years, women have a higher prevalence of arthritis and mood/anxiety disorders than men – the two most common chronic diseases in the Canadian population in 2017 . In PLWH, mortality is higher among women, who also have a substantially shorter life expectancy (7 years) compared to men living with HIV . Men in the general Canadian population develop cardiovascular disease, hypertension, metabolic syndrome, and diabetes earlier in life than women, and men living with HIV develop these conditions at comparatively earlier ages [19–21]. It is unclear if this is also the case among WLWH. We therefore aimed to describe the type and burden of comorbidities of WLWH and the associated treatments, as this knowledge is essential to optimize care.
In this study, we assessed the prevalence and types of chronic comorbidities WLWH have developed in comparison to their HIV-negative peers enrolled in the Children and Women: Antiretrovirals and Markers of Aging (CARMA) cohort in British Columbia (BC), Canada. Pharmacological treatment of these comorbidities, alongside concomitant cART use, was also assessed.
Study design and population
We analyzed baseline data from all WLWH and HIV-negative women aged at least 19 years, enrolled in the prospective CARMA cohort in Vancouver, BC, Canada, between December 2008 and October 2017. WLWH were recruited during routine visits at the Oak Tree Clinic in Vancouver. This clinic employs a multidisciplinary care model to provide specialized HIV care to women, children, and families living with or affected by HIV in BC. HIV-negative controls were recruited through strategically placed advertisements, and efforts were made to recruit participants with similar socio-demographic characteristics to the WLWH, particularly from 2013 onward, when increased efforts were made to match the two groups with respect to age and ethnicity.
Self-reported demographic, chronic medical condition, medication, vitamin, and substance exposure data were collected at baseline CARMA study visits. Participants were asked to bring a list of their medications and vitamins to the study visit. For medical condition data, participants were given specific categories of diagnoses and asked to list conditions they have that fall within each category. For WLWH, self-reported medical condition data were verified by chart review, though no additional diagnoses were added. As for other diagnoses, history of hepatitis C viral infection (HCV) and treatment was self-reported; PCR data were not used. The list of all diagnoses included can be found in Supplemental Table 1 (http://links.lww.com/QAD/B524). Some diagnoses were combined due to potential overlap. We assessed rate of therapy for the 13 most common conditions by considering conditions to be ‘treated’ if the participants were on medication used to treat the condition. For HCV, we considered the participant to be ‘treated’ if they had ever received treatment for their HCV. However, we did not evaluate treatment effectiveness or adherence for any condition.
Wilcoxon rank-sum and Fisher's exact tests were used to compare continuous and categorical variables between WLWH and HIV-negative women.
We compared the number of diagnoses (excluding HIV), number of prescribed medications (excluding cART), use of vitamins (yes/no) including calcium, vitamin D, vitamin B12, and iron, and the prevalence of depression/anxiety/panic disorder (D/A/P) diagnosis between WLWH and HIV-negative women using negative binomial regressions for count variables, and logistic regressions for binary variables. To examine the relationship between HIV status and the outcomes further, we adjusted the models for potential confounders including age, BMI, tobacco smoking (current, past, never), and income (<$15 000 vs. ≥$15 000 per year). We also examined potential nonlinear (quadratic) relationships between age or BMI and the outcomes. Finally, the interaction between age and HIV status was included to allow different relationships between the groups and age. If the interaction was nonsignificant (P > 0.05), it was removed to ease model interpretation. Raw and adjusted regression results are available in Supplemental Tables 2, 3, and 4 (http://links.lww.com/QAD/B524). As a sensitivity analysis, we subdivided the WLWH into categories of suppressed HIV plasma viral load (<200 copies/ml) vs. unsuppressed HIV plasma viral load (≥200 copies/ml).
We then used Fisher's exact tests to compare the prevalence among WLWH and HIV-negative women of each of the 13 most common conditions in our cohort: D/A/P (combined into one item due to significant overlap in the diagnoses), HCV infection, osteoporosis/osteopenia/low bone mass, anemia, asthma, gastroesophageal reflux disease, and/or peptic ulcer disease (GERD/PUD), osteoarthritis, hypertension, hypothyroidism, dyslipidemia, diabetes, B12 deficiency, and chronic obstructive pulmonary disease (COPD). We also compared the proportion of WLWH and HIV-negative women being treated for each diagnosis and for WLWH, and assessed the presence or absence of potential cART interactions with the treatment of specific conditions in WLWH. Drug–drug interactions between cART medications and comorbid illness treatment were based on the University of Liverpool's HIV Drug Interaction website .
Data were available for 267 WLWH and 276 HIV-negative women. WLWH were younger [median, interquartile range (IQR) 39.9, 33.6–46.9 years] than HIV-negative women (43.6, 31.8–54.6 years; P = 0.01). WLWH in this cohort had attained lower education, with 41% having attended college or university in comparison to 70% of the HIV-negative group (P < 0.0001). WLWH were more likely to currently smoke tobacco (48 vs. 32%; P < 0.0001), but intravenous drug use was similar between groups (16 vs. 18%; P = 0.98) (Table 1).
Within the WLWH, five (2%) acquired HIV perinatally. For women not infected perinatally, the median age of HIV acquisition was 29 [IQR (range) 24–36 (0.6–74)]. At the baseline visit, 77 (29%) had unsuppressed HIV plasma viral load (<200 copies/ml), and the median (IQR) CD4+ nadir was 190 cells/μl (100–300 cells/μl), and median CD4+ was 465 cells/μl (310–660 cells/μl). Of all WLWH, 99 (37%) were taking tenofovir as part of their regimen's backbone, and as a third drug, 5 (2%) were on an integrase inhibitor, 145 (54%) a protease inhibitor, and 53 (20%) a non-nucleoside reserve-transcriptase inhibitor.
Number of diagnoses
There were significantly more diagnoses of comorbid illness among WLWH compared to HIV-negative women [incidence rate ratio (IRR), 95% CI 1.58, 1.38–1.81; P < 0.001]. After adjustment, there was a significant interaction between HIV status and age, with WLWH accruing diagnoses faster with age than HIV-negative women (Fig. 1a and b). Income less than $15 000/year (Fig. 1a) and tobacco smoking (Fig. 1b) were significantly independently associated with a greater number of diagnoses (Fig. 1, Supplemental Table 2, http://links.lww.com/QAD/B524). Number of diagnoses by decade of age is shown in Fig. 2, and illustrates that a larger proportion of WLWH have multiple diagnoses, and that these increase with age faster than for HIV-negative women. There was also a significant quadratic relationship between the number of diagnoses and BMI, with rates of diagnoses increasing faster at higher BMI (Fig. 1c and d). The negative binomial model suggested that WLWH and HIV-negative women would have two diagnoses on average by the age of 30 and 60, respectively, for someone with average BMI (26.3), whereas for someone with a BMI of 35, these ages were lowered to 27 and 48.
Overall, women with income above $15 000/year had, on average, 18% lower rate of multiple diagnosis than those with lower incomes (IRR 0.82, 0.71–0.95; P = 0.01), after controlling for age, BMI, and HIV status. Among WLWH and average BMI, those with income below $15 000/year were predicted to have two diagnoses by age 28, whereas this age was predicted to be 36 for someone with income less than 15 000/year (Fig. 1a). Finally, tobacco smoking was significantly associated with number of diagnoses after controlling for age, BMI, HIV status, and income, with past smokers having a 38% higher rate of diagnoses (IRR 1.38, 1.13–1.67; P = 0.001; Fig. 1b), and current smokers having a 45% higher rate of diagnoses in comparison to participants who had never smoked (IRR 1.45, 1.20–1.75; P < 0.001; Fig. 1b).
The sensitivity analysis showed no significant difference in the relationship between age and the number of diagnoses between WLWH with unsuppressed vs. suppressed HIV viral load (P = 0.82), therefore we combined them for all reported analyses.
Type of diagnoses
Among the 13 most common diagnoses in our cohort, WLWH had significantly higher rates of D/A/P (42 vs. 27%; P = 0.04), HCV infection (40 vs. 18%; P = 0.001), and osteoporosis/osteopenia/low bone mass (21 vs. 3%; P < 0.001). Rates of these and other diagnoses are shown in Fig. 3, whereas rates of the five most common diagnoses by age grouping are shown in Supplemental Fig. 1 (http://links.lww.com/QAD/B524).
After adjustment for age, income, and current tobacco smoking, rates of D/A/P remained higher in WLWH than HIV-negative women [odds ratio (OR) (95% CI) 1.86 (1.22–2.83); P = 0.004], with neither age, BMI, nor income predicting a diagnosis of D/A/P. HIV status and age were not significantly associated with a diagnosis of D/A/P. However, current tobacco smoking and having a diagnosis of D/A/P were significantly associated [OR 1.77 (1.03–3.02); P = 0.04; Supplemental Table 3, http://links.lww.com/QAD/B524).
Number of medications
Overall, and without adjustment, WLWH and HIV-negative women used a similar number of medications [IRR 1.23 (0.98–1.54); mean (SD) in WLWH = 1.6 (2.1), HIV-negative women = 1.3 (1.7); P = 0.07]. However, there was a significant interaction between age and HIV status (P = 0.03) on the number of medications after adjusting for BMI, current or past tobacco smoking, and income (Fig. 4a and b). The interaction between age and HIV status is similar to that for number of diagnoses, with the difference between WLWH and HIV-negative women becoming more pronounced with age. Among all women, there was a strong relationship with income, whereby women with income at least $15 000/year used 28% fewer medications than those with income below $15 000/year [IRR 0.72 (0.56–0.93); P = 0.01]. WLWH with income below $15 000/year and at least $15 000/year were predicted to be taking two medications by the ages of 44 and 52, respectively (Fig. 4a). Current smokers were using 85% more medications [IRR 1.85 (1.36–2.51); P < 0.001], and past smokers were using 55% more medications than participants who had never smoked [IRR 1.55 (1.13–2.13); P = 0.007; Fig. 4b).
Number of vitamins
Women living with HIV had significantly higher odds of using vitamins than HIV-negative women [OR 1.41 (1.00–1.99); P = 0.05]. Among all women, older age was associated with increased vitamin use up to approximately 40 years where it began to level off or slightly decline (Fig. 4c). Current smokers had 52% lower odds of using vitamins than never-smokers [OR 0.48 (0.29–0.82); P = 0.007; Supplemental Table 4, http://links.lww.com/QAD/B524].
Number of participants being treated for the common diagnoses
For the 13 most common conditions in our cohort, similar proportions of WLWH (47%) and HIV-negative women (52%) were prescribed pharmacological treatment for their diagnosed comorbidities. However, fewer WLWH than HIV-negative women were on treatment for osteoporosis/osteopenia/low bone mass (67 vs. 100%; P < 0.001), asthma (34 vs. 59%; P < 0.001), GERD/PUD (23 vs. 47%; P < 0.001), diabetes (45 vs. 80%; P < 0.001), and COPD (27 vs. 50%; P = 0.001) (Fig. 3).
Combination antiretroviral therapy interactions
The treatments for seven of the 13 comorbidities evaluated have potential for cART drug–drug interactions (Supplemental Table 5, http://links.lww.com/QAD/B524). In WLWH, there were 14 cases in which the medication currently used to treat a participants’ comorbidity had a known interaction with one or more components of her cART regimen. Among those who were not currently being treated for one of their comorbidities, 23 were receiving HIV cART that included at least one antiretroviral with a known interaction with the recommended treatment for that condition. Of the 27 participants diagnosed with both HIV and osteoarthritis, two (7%) were taking both NSAIDs and tenofovir, which are known to interact, and six (22%) were not on NSAIDs or any other medication to manage their osteoarthritis. but were taking tenofovir. Of the 46 WLWH diagnosed with either COPD or asthma, nine (20%) were not being treated for their COPD/asthma, but were concurrently taking a protease inhibitor boosted with ritonavir, which has a known interaction with inhaled corticosteroids (Supplemental Table 5, http://links.lww.com/QAD/B524).
Comorbid conditions and concomitant medication use in the aging population of PLWH has been described primarily in male cohorts. This study describes these conditions in WLWH, and how they are being managed with concomitant cART use.
After controlling for socio-demographic factors, WLWH have an increased number of diagnoses, and this difference becomes larger with age. It has previously been described that PLWH develop age-related comorbidities 5–15 years earlier than the HIV-negative population [6,7]. When examining a wider variety of comorbidities in our cohort, we see a more dramatic trend, with the multivariable model predicting that WLWH would develop on average two comorbidities 30 years earlier than their HIV-negative peers. The key pathological mechanisms that have been hypothesized to explain this include higher levels of chronic systemic inflammation, hypercoagulability, and immune senescence with chronic HIV infection [7,8,23]. While the commonly described conditions in previous studies among aging PLWH include cardiovascular disease, hypertension, kidney disease, and diabetes, our participants demonstrated relatively low rates of these conditions [5,6]. This may be due to the fact that the median age of our population was approximately 10 years younger (40 years) than most other populations described (>50 years) [3,5,6]. However, in our cohort, WLWH had higher rates of D/A/P, HCV, and osteoporosis/osteopenia/low bone mass than their HIV-negative peers. Additional research with an older population of WLWH is necessary to further determine the effects of aging on the prevalence of comorbidities among older WLWH specifically.
After controlling for key socio-demographic factors, WLWH were taking more medications and nearly two times more likely to be taking certain vitamins (calcium, vitamin D, vitamin B12, and iron) than their HIV-negative peers. This is likely due to the higher number of comorbid diagnoses among WLWH. However, it may also be related to increased rates of certain conditions among PLWH requiring vitamins and medications, including dyslipidemia, B12 deficiency, anemia, and osteoporosis/osteopenia/low bone mass [24–27]. Additionally, WLWH receiving care at the Oak Tree Clinic regularly attend health check-ups where they receive guideline-based screening and treatment of common conditions. Therefore, diagnosis rates may be higher among WLWH, and thus prescription rates of medications and vitamins to WLWH may also be higher than their HIV-negative peers who may not regularly be followed by a healthcare professional. Regarding access to vitamins for PLWH, however, in BC, there is no difference in coverage of the studied vitamins between PLWH and HIV-negative persons.
We also saw that among all women, those with higher income (≥$15 000) were taking 28% fewer medications, independent of HIV status. This may be due, in part, to the disparity in income between WLWH and their HIV-negative peers, with a larger proportion of WLWH having lower income and more comorbid illness. Given that income is a key social determinant of health, with lower income being linked to poorer health, those in the higher income group may have better overall health with fewer diagnoses and therefore require fewer medications . It is also possible the increased number of medications among women with lower income is related to access to monetary support for medications through programs such as Pharmacare in BC, which would not be available to those with slightly higher income . The latter may thus experience nonadherence to prescription medication related to the cost of the medication .
Present and past tobacco smoking was independently associated with an increased number of diagnoses and medications in comparison to never-smokers. It is well established that tobacco smoking is not only associated with higher rates of heart disease and COPD, it is also associated with aging at the cellular level, which may contribute to the higher number of comorbid conditions, in turn, leading to more medication use [31–36]. WLWH were more likely to have smoked tobacco at some point in their lives (67%) when compared to their HIV-negative peers (53%). A focus on smoking cessation is thus important in the management of health outcomes among WLWH.
Women living with HIV were twice as likely to have a diagnosis of D/A/P than HIV-negative women. This is consistent with other studies, reporting a two to four-fold increase in depression, and an overall increase in anxiety among PLWH in comparison to the general population [37–40]. The higher levels of D/A/P in WLWH may also be due to a discrepancy of reporting between WLWH and HIV-negative groups, with the HIV-negative group more likely to under-report rates of D/A/P, given that HIV-negative women were not receiving their care from the clinic. They may also be underdiagnosed, if they are seen by their physician less regularly. However, according to the 2012 Canadian Community Health Survey, 15% of Canadian females aged at least 15 years had been diagnosed with a mood disorder at one point in their life, 14% had a major depressive episode, and 11% had been diagnosed with generalized anxiety disorder . Therefore, the levels of D/A/P in our HIV-negative population are higher than that of the general Canadian population, which might indicate that our groups are well matched, or that the HIV-negative participants felt safe to discuss their mental health diagnoses with their care providers and our study team. Depression leads to poorer health outcomes and decreased quality of life, and it has been described that identification and treatment of depression in PLWH enhances cART adherence [42–44]. Therefore, one aspect of optimizing care for WLWH includes screening and appropriate management of mood and anxiety disorders, particularly in a population of aging individuals with increased morbidity.
We acknowledge several limitations of our study. First, given that diagnostic data were self-reported, it is possible that underdiagnosis, underscreening, or under-reporting took place. For HCV infection specifically, we did not use PCR data, therefore we do not know if HCV infections were active at baseline. Because WLWH were patients of the Oak Tree Clinic, some medical condition data were verified with medical charts; this was not done for HIV-negative matched peers. Second, it is possible that some participants were managing chronic conditions with lifestyle intervention only, and therefore rate of treatment for these conditions, including diabetes and hypertension, might appear lower than they were in both groups. Next, given the known increased prevalence of osteoporosis and rates of fractures among WLWH, care providers at Oak Tree Clinic regularly screen for changes in bone mass, which may contribute to the increased diagnoses of osteoporosis/osteopenia/low bone mass in WLWH compared to HIV-negative controls. Additionally, it is possible that WLWH experienced lower treatment rates due to factors such as pill fatigue or patient choice affecting whether a recommended treatment for a given ailment was adhered to. We would also like to acknowledge that while we are modeling longitudinal risk of disease in a population of WLWH, we are using cross-sectional data to do so. Longitudinal data from a prospective cohort would be stronger.
Despite the fact that they were younger, WLWH in our cohort experienced an increased number of comorbidities compared with their HIV-negative peers and were more likely to experience negative social-structural factors such as low income, exacerbating this disparity. WLWH also experienced high rates of depression/anxiety/panic disorder – a predictor of negative clinical outcomes. Moreover, these results were found in a cohort that receives thorough care from an interdisciplinary team specializing in care of WLWH and their families . Addressing the social determinants of health and mental health of WLWH at any age, alongside their HIV, is required to improve health outcomes among WLWH.
We would like to thank the CARMA cohort participants, the CARMA team, and the Oak Tree Clinic research staff.
Author contributions: Study conception: A.Y.A., H.C.F.C., and M.C.M.M.; funding acquisition: H.C.F.C., M.C.M.M., and N.P.; study design: A.R.C., A.Y.A., M.A.D., and M.C.M.M.; participant recruitment: A.N., A.R.C., E.J.M., N.P.; data collection: A.N., A.R.C., E.J.M., M.A.D., and M.B.; data analysis: A.Y.A. and M.A.D.; database management: A.N., A.R.C., E.J.M., and M.B.; writing: M.A.D.; editing: A.N., A.R.C., A.Y.A., E.J.M., H.C.F.C., M.A.D., M.B., M.C.M.M., and N.P.
Funding: This work was supported by the Canadian Institutes of Health Research (CIHR) and the Canadian HIV Trials Network (CTN). This study was supported by the following grants: Canadian Institutes of Health Sciences Grant numbers HET-85515 and TCO-125269.
Conflicts of interest
The authors report no conflicts of interest related to this work.
Data was presented previously at the Canadian Conference on HIV/AIDS Research (CAHR) 2019 in Saskatoon, Saskatchewan, and published as an abstract in the 28th Annual Canadian Conference on HIV/AIDS Research Abstract Book as abstract number CS3.05.
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