BACKGROUND
Despite an increase in female-only studies on HIV-associated neurocognitive impairment (NCI), few compare HIV+ women and men. Women are often [1–3], but not always [4,5], more likely to demonstrate NCI. This female-specific vulnerability may reflect a greater prevalence of psychosocial factors in women (e.g., low education, substance abuse, depression) that have biological effects on the brain (“biopsychosocial factors”) [6–8]. These factors or “syndemics” may additively or synergistically harm cognitive/brain health and lower cognitive reserve [9,10]. Biopsychosocial syndemics are associated with HIV acquisition [11], antiretroviral adherence [12], and may also contribute to NCI. In the Women’s Interagency HIV Study (WIHS), reading level, years of education, and income were more strongly associated with cognition than HIV-serostatus [13], and stress/anxiety increased risk of NCI among HIV+, but not HIV-, women [14]. While biopsychosocial factors may increase HIV-associated NCI, studies have not examined the role of biopsychosocial syndemics in sex differences in risks for HIV-associated NCI.
It is also unclear whether specific cognitive domains are more impaired in HIV+ women versus men. Memory impairment is highly prevalent in WIHS HIV+ women [15], whereas, in male-dominant cohorts (e.g., CHARTER), learning and executive function impairments are more common [16]. The primary studies examining sex differences in HIV-associated NCI were in the context of substance-dependence. Fogel et al. found a sex by serostatus effect on the number of completed learning trials, whereby HIV+ men successfully completed more learning trials than HIV+ women [17]. Other studies demonstrated that HIV-seropositivity was associated with visual memory [18] and decision-making [19]; however, associations were either female-specific [18] or stronger in women [19].
Further examination of sex differences in HIV-associated NCI is needed. We examined sex differences in the prevalence and profile of HIV-associated NCI and whether any differences were explained by sex differences in biopsychosocial factors. We hypothesized that HIV-associated NCI, specifically memory recall impairments, would be more prevalent in women than men. Among HIV+ and HIV- participants, the association between HIV-seropositivity and NCI would be stronger in women versus men because of lower “cognitive reserve” in HIV+ women. We further hypothesized that biopsychosocial risk factors would be more prevalent in HIV+ women than men. Thus, sex differences in HIV-associated NCI should diminish after adjustment for individual biopsychosocial factors, but we anticipated that the largest attenuation would result from adjustment for syndemic count (number of such factors present).
METHODS
Participants
Participants included 1,361 HIV+ (204 women) and 702 HIV- (214 women) enrolled in various NIH-funded research protocols at the University of California San Diego’s HIV Neurobehavioral Research Program (HNRP, https://hnrp.hivresearch.ucsd.edu/). Study details have been published [20]. Exclusion criteria for the parent studies included history of non-HIV-related neurological, medical or psychiatric disorders that affect brain function (e.g., diabetes), learning disabilities, dementia diagnosis and a first language that was not English. Our inclusion criterion was availability of all analytic study variables. Our exclusion criteria were positive urine toxicology for illicit drugs (except marijuana) or Breathalyzer test for alcohol during study visits.
Measures
UCSD’s Human Research Protections Program approved all study procedures, and all participants provided written informed consent. Participants completed comprehensive neuromedical and neurobehavioral assessments during study visits.
Neuropsychological Evaluation
Participants completed a standardized neurocognitive test battery of verbal fluency, working memory, processing speed, verbal and visual learning and delayed recall, executive function, and complex motor function. Specific tests are described elsewhere [21]. Raw test scores were transformed into age-, education-, sex-, and race/ethnicity-adjusted T-scores based on normative samples of HIV- participants [22,23]. T-scores were averaged across tests within a domain to generate domain summary T-scores. T-scores for each test were also converted into deficit scores that ranged from 0 (T-score≥40, no impairment) to 5 (T-score<20, severe impairment) and then averaged across all tests to obtain a Global Deficit Score (GDS) [20,24,25]. Based on a pre-established cut-point, NCI was defined as a GDS score≥0.50 [24].
Biopsychosocial Risk Factors
We examined any biopsychosocial variable that is associated with NCI in the literature and was available for enough participants to be adequately powered in analyses. Biopsychosocial risk factors included: 1) low education (<12 years), 2) low reading level (a proxy for cognitive reserve) based on the Wide Range Achievement Test-4 Reading subtest (WRAT-4 Reading) score<90 [26], 3) history of any substance use disorders (SUD) or a specific SUD based on the Composite International Diagnostic Interview (CIDI version 2.1) [27] using DSM–IV criteria for alcohol, amphetamine, cocaine, hallucinogen, inhalant, sedative, opioid, and PCP, 4) depressed mood indicated by either a Beck Depression Inventory-II (BDI-II) score>16 [28] and/or a current diagnosis of major depressive disorder based on the CIDI and 5) a syndemic count of all the biopsychosocial risk factors (low education, low reading level, any SUD, depressed mood) experienced by an individual (range=0–4). Cannabis abuse/dependence was not included in the SUD summary measure because of a potential protective role of cannabis on NCI owing to anti-inflammatory effects [29].
Potential Covariates
Demographics and clinical factors that impact cognition were considered as covariates including age, Hepatitis C infection and HIV disease characteristics (analyses in HIV+ group only).
Statistical Analysis
A chi-square test was used to examine sex differences in the prevalence of HIV-associated NCI, followed by stepwise logistic regressions to determine whether covariates (step one) and/or individual biopsychosocial factors (step two) attenuated (≥10% change in the odds ratio) the sex difference. Biopsychosocial factors were individually examined to avoid multicollinearity. Demographic or clinical factors outside of biopsychosocial factors were considered as covariates if they related to NCI and differed between sexes.
To determine sex differences in the profile of NCI, we examined domain T-scores among individuals who showed any NCI. We examined T-scores rather than domain-specific impairment because there was 100% impairment in the learning domain among White, HIV+ women with NCI. We conducted analyses of variance to examine sex differences in T-scores among HIV+ participants with NCI. Significant sex differences in these domain summary scores were followed by analyses of covariance adjusting for covariates and biopsychosocial factors. Lastly, among HIV+ and HIV- participants, we examined the moderating role of sex in the relationship between HIV-serostatus and the likelihood of NCI in two logistic regression approaches: 1) inclusion of an HIV-serostatus by sex interaction term and 2) examination of the HIV and NCI relationship in sex-stratified analyses. Significant effects were followed by stepwise logistic regressions adjusting for covariates (step one) and individual biopsychosocial factors (step two). Significance was set at p<.05. Analyses were performed using SPSS (v24.0, SPSS Inc., Chicago, Illinois). Given race/ethnicity differences in the prevalence of biopsychosocial factors and NCI, analyses were repeated within non-hispanic whites and blacks.
RESULTS
Irrespective of HIV-serostatus, women had fewer years of education and lower WRAT-4 scores, and these differences were stronger in HIV+ individuals (Table 1). Among HIV+ individuals, most men were white and most women were black. Among HIV- individuals, women had higher rates of Hepatitis C infection and lower rates of lifetime cannabis abuse/dependence than men. There were no sex differences in HIV-related characteristics. Demographic and clinical characteristics meeting criteria for covariates were lifetime cannabis abuse/dependence and race/ethnicity. Race/ethnicity was accounted for in race/ethnicity-stratified analyses. Examining the biopsychosocial factors within both HIV-serostatus groups, women had higher rates of low education, low reading level and depressed mood. As seen in the general population [30], women had lower rates of SUD than men regardless of serostatus. Because their prevalence rates in the overall sample were at-least 10%, we examined the individual SUDs of alcohol, cocaine, methamphetamine, and opiates. Regardless of HIV-serostatus, lifetime alcohol abuse/dependence was more prevalent in men versus women. Among HIV+ individuals, lifetime cocaine and methamphetamine abuse/dependence were more prevalent among men, whereas lifetime opiate abuse/dependence were more common among women. Mean syndemic count was higher in women versus men in the HIV+, but not HIV-, group suggesting that women experience a greater constellation of biopsychosocial factors in the context of HIV.
Table 1.
Sample characteristics, biopsychosocial risk factors and global NCI rates by HIV-serostatus and sex.
| HIV+ | HIV- | |||||
|---|---|---|---|---|---|---|
| Variables | Women (n=204) |
Men (n=1,157) |
Women vs. Men p-value (effect sizea) | Women (n=214) |
Men (n=488) |
Women vs. Men p-value (effect sizea) |
| Demographic/Clinical Factors | ||||||
| Age, M (SD) | 41.6 (10.0) | 42.81 (9.9) | ns | 41.0 (13.9) | 40.1 (12.2) | ns |
| Education yrs, M (SD) | 11.8 (2.5) | 13.4 (2.6) | <.001 (0.6) | 12.7 (2.5) | 13.1 (2.4) | .04 (0.2) |
| WRAT-4 Score, M (SD) | 87.1 (16.1) | 97.8 (14.8) | <.001 (0.7) | 97.7 (12.0) | 99.8 (12.6) | .04 (0.2) |
| Race/Ethnicity | ||||||
| % White | 29.4 | 56.9 | <.001 (0.2) | 58.4 | 64.9 | .10 (0.1) |
| % Black | 51.5 | 26.4 | <.001 (0.2) | 12.6 | 15.8 | ns |
| % Hispanic | 13.7 | 12.3 | ns | 18.2 | 15.0 | ns |
| % Asian | 1.5 | 1.3 | ns | 3.3 | 1.4 | ns |
| % Other | 3.9 | 3.1 | ns | 7.5 | 2.9 | ns |
| % LT Cannabis Abuse/Dependence |
24.0 | 29.2 | ns | 45.8 | 59.2 | .001 (−0.1) |
| Biopsychosocial Risk Factors | ||||||
| % Low Education (<12yrs) |
37.7 | 18.7 | <.001 (0.2) |
27.6 | 21.1 | .06 (0.1) |
| % Low Reading Level (WRAT-4<90) |
49.5 | 23.8 | <.001 (0.2) |
23.8 | 16.4 | .02 (0.1) |
| % LT SUD (% Abuse, % Dep)* |
52.0 (25.0, 42.2) |
68.6 (43.8, 46.8) |
<.001 (0.1) |
62.1 (38.3, 53.3) |
70.5 (48.4, 57.6) |
.02 (−0.1) |
| % Alcohol SUD (% Abuse, % Dep)* |
39.7 (15.7, 25.5) |
53.6 (30.7, 26.0) |
<.001 | 45.8 (26.6, 26.2) |
59.2 (36.3, 30.5) |
.001 |
| % Cocaine (% Abuse, % Dep)* |
27.9 (6.4, 22.5) |
24.9 (10.8, 14.5) |
ns | 20.1 (6.1, 14.5) |
25.8 (9.2, 18.6) |
ns |
| % Methamphetamine (% Abuse, % Dep)* |
14.2 (3.4, 10.8) |
34.1 (7.1, 28.8) |
<.001 | 41.6 (8.4, 36.9) |
47.7 (6.9, 44.7) |
ns |
| % Opiates (% Abuse, % Dep)* |
12.7 (2.0, 10.8) |
6.8 (3.5, 3.5) |
.004 | 15.4 (2.3, 13.5) |
12.1 (4.7, 7.6) |
ns |
| % Depressed Moodb | 43.6 | 36.8 | .07 (0.05) |
25.2 | 17.8 | .02 (.08) |
| Syndemics Count (range: 0–4), M (SD) |
1.8 (1.1) | 1.5 (1.0) | <.001 (0.3) |
1.4 (1.1) | 1.3 (1.0) | ns |
| Neurocognitive Status | ||||||
| Global NCI, N (%) | 106 (52.0) | 475 (41.1) | .004 (0.1) |
58 (27.1) |
125 (25.6) | ns |
| GDS, M (SD) | 0.7 (0.6) | 0.5 (0.5) | .005 (0.4) |
0.4 (0.4) | 0.4 (0.4) | ns |
| Disease Characteristics | ||||||
| Hepatitis C Virus (%) | 23.0 | 19.8 | ns | 34.6 | 21.1 | <.001 (0.1) |
| Nadir CD4 Count (cells/μl), M (SD) | 223.9 (219.6) |
236.43 (212.5) |
ns | - | - | - |
| Current CD4 Count (cells/μl), M (SD) | 527.8 (331.4) |
486.2 (303.1) |
ns | - | - | - |
| Plasma Viral Load (% detectable) | 48.2 | 54.7 | ns | - | - | - |
| Duration of HIV Infection, yrs, M (SD) | 8.3 (5.8) | 9.2 (7.3) | ns | - | - | - |
| ART Status (% prescribed) | 70.6 | 67.0 | ns | - | - | - |
Note.
Effect sizes for mean differences are Cohen’s d (0.2 = small, 0.5 = medium, 0.8 = large) and effect size for differences in proportions are a phi coefficient (0.1 = small, 0.3 = medium, 0.5 = large).
Criteria for depressed mood included current diagnosis of major depressive disorder and/or Beck Depression Inventory-II score > 16.
Overlap between participants with lifetime substance abuse and dependence occurs because participants may have a history of both an abuse and dependence substance use diagnosis. Univariate analyses of variance and chi-square tests were used to determine sex differences in continuous and categorical variables, respectively. WRAT-4= Wide Range Achievement Test 4h edition; SUD = substance use disorder; LT = lifetime; Dep = dependence; NCI = neurocognitive impairment; GDS = global deficit score. Undetectable=<48copies/ml; ART = antiretroviral therapy. Sex differences within serostatus groups were examine using analysis of variance for continuous variables and chi-square tests for categorical variables.
Sex differences in HIV-associated NCI
NCI prevalence was higher in HIV+ women versus men (52% vs. 41%) but similar between HIV- women and men (27% vs. 26%). After adjusting for covariates, the likelihood of HIV-associated NCI was 1.5 times higher in women versus men (Table 2). When adjusting for biopsychosocial factors, this difference was eliminated after adjusting for reading level but not any other factor.
Table 2.
Statistical results of stepwise regression analyses examining the association between sex and the odds of global NCI among HIV+ participants and the explanatory role of biopsychosocial risk factors.
| Model | Association between sex (women vs. men) and the odds of NCI | Association between biopsychosocial risk factors (with factor vs. without) and odds of NCI | ||
|---|---|---|---|---|
| OR (95% CI) | p-value | OR (95% CI) | p-value | |
| Step 1: Adjusted for relevant covariates | 1.53 (1.13–2.06) | .005 | - | - |
| Step 2: Adjusted for relevant covariates and individual biopsychosocial risk factors | ||||
| Low reading level | 1.19 (0.87–1.63) | .29 | 2.88 (2.23–3.70) | <.001 |
| Low education | 1.50 (1.11–2.03) | .009 | 1.10 (0.84–1.44) | .47 |
| Depressed mood | 1.49 (1.10–2.01) | .01 | 1.55 (1.24–1.94) | <.001 |
| LT SUD | 1.50 (1.11–2.02) | .009 | 0.86 (0.68–1.10) | .23 |
| Alcohol | 1.53 (1.13–2.07) | .005 | 0.91 (0.73–1.13) | .39 |
| Cocaine | 1.55 (1.15–2.09) | .004 | 0.94 (0.73–1.20) | .62 |
| Methamphetamine | 1.51(1.11–2.04) | .008 | 0.86 (0.68–1.10) | .23 |
| Opiates | 1.56 (1.16–2.11) | .004 | 0.88 (0.58–1.32) | .54 |
| Syndemics count | 1.38 (1.02–1.87) | .04 | 1.35 (1.21–1.50) | <.001 |
Note. OR = odds ratio. CI = confidence interval. NCI = neurocognitive disorder. SUD = substance use disorders. LT = lifetime. Results were generated from stepwise logistic regressions
Sex differences in the profile of HIV-Associated NCI
Among HIV+ NCI participants (475 men, 106 women), there were no sex differences in domain summary T-scores (Table 3).
Sex differences in the association between HIV and NCI
After adjusting for covariates, there was no HIV-serostatus by sex interaction for NCI (OR=1.48, 95%CI=0.92–2.36, p=.11). Rather, HIV+ participants were at greater odds of NCI regardless of sex (OR=2.16, 95%CI=1.76–2.66, p<.001). Female sex was associated with a greater odds of NCI regardless of HIV-serostatus (OR=1.31, 95%CI=1.04–1.65, p=.02). Although the HIV-serostatus by sex interaction was not significant, sex-stratified analyses showed a stronger association between HIV-serostatus and NCI in women versus men. Compared to their HIV- counterparts, the odds of NCI was higher in HIV+ women (OR=2.90, 95%CI=1.93–4.35, p<.001) and men (OR=1.95, 95%CI=1.54–2.47, p<.001). The HIV-serostatus and NCI association in men was not attenuated after adjusting for biopsychosocial factors (p’s<.001). Among women, the association was attenuated after adjusting for reading level (OR=2.33, 95%CI=1.52–3.57, p<.001) but not for other factors (p’s<.001).
Race/ethnicity-stratified analyses
The higher prevalence of HIV-associated NCI and the larger effect of HIV-serostatus on NCI in women in the overall sample was specific to blacks (Supplemental Information).
DISCUSSION
Our findings present evidence supporting greater NCI among HIV+ women compared to HIV+ men. Race/ethnicity-stratified analyses indicated that this sex difference was primarily due to a higher proportion of black women in the HIV+, versus HIV-, group. We extend previous findings by determining whether discrepancies in biopsychosocial factors may explain higher rates of HIV-associated NCI in women. In partial support of hypotheses, adjusting for low reading level eliminated the sex difference in HIV-associated NCI.
The race disparity in findings may be due to the overall higher rates and larger sex difference in biopsychosocial factors in blacks versus whites. The race disparity may also be partially due to race/ethnicity differences in health literacy [31], which have accounted for racial disparities in age-associated cognitive decline [32]. Perhaps sex differences in HIV-associated NCI are more common in the context of low health literacy possibly due to suboptimal engagement in HIV care/treatment. Alternatively, reading level may represent other NCI risk factors that show a female preponderance among black, HIV+ individuals but were unmeasured (e.g., early life trauma). Our race/ethnicity differences may explain inconsistent findings. Because our sample included more black women with lower reading level, the sex differences in HIV-related NCI may be more evident than in predominantly white samples.
Low reading level was the only biopsychosocial factor to attenuate the sex difference in HIV-associated NCI in the overall sample and blacks. This may be because, among the biopsychosocial factors, low reading level demonstrated the strongest relationship with NCI and the largest sex difference. Low education was not associated with NCI likely because NCI was determined using education-adjusted, neurocognitive T-scores. SUDs were not associated with NCI possibly because most SUDs in our sample were not current (due to parent study exclusion criteria). Furthermore, reading level may better reflect education quality than years of education, especially in lower socioeconomic populations because of the many factors impacting education quality (e.g., ability to attend school) [33]. Notably, low reading level, but not education, was a risk factor for cognitive decline among ethnically-diverse elders in the general population [33]. Additionally, reading level is associated with health outcomes including hospitalizations and outpatient doctor visits [34], and, thus, may be a proxy for biopsychosocial factors underlying general health (e.g. socioeconomic status, self-efficacy).
Although mean syndemic count was higher in HIV+ women versus HIV+ men, adjustment for syndemic count did not attenuate the sex difference in HIV-associated NCI, suggesting that the other biopsychosocial factors dilute the sex-related variance explained by reading level. Our syndemic count likely contains factors with non-additive effects on NCI. Given findings that stress is more strongly associated with trajectories of cognitive impairment than depression in HIV+ women [15], a syndemic count that included factors such as early life trauma and perceived stress may better capture biopsychosocial differences between HIV+ men and women.
Sex differences in the profile of HIV-associated NCI were only observed within race/ethnicity groups. Among whites, women demonstrated poorer learning than men, and this difference was attenuated after adjusting for reading level. White women also demonstrated poorer verbal fluency than white men and this difference was unchanged after adjustments. The sex difference in HIV-associated NCI among blacks was not driven by specific cognitive domains. In fact, in contrast to whites, black women outperformed black men in verbal fluency and this difference was unchanged after adjustments. Sex differences in verbal fluency were likely masked in the overall sample due to differing associations within race/ethnicity groups.
The sex by HIV interaction was not significant; however, sex-stratified analyses suggest a moderating role of sex in the HIV and NCI association, particularly in blacks. Compared to their HIV- counterparts, NCI was 3.5 times more likely in black, HIV+ men but six times more likely in black, HIV+ women. Adjustment for reading level marginally attenuated the HIV and NCI association in black women, suggesting that the large discrepancy in reading level between HIV+ and HIV- black women contributes to the higher risk of NCI in HIV+ black women. Conversely, the HIV and NCI association was unchanged with adjustments in black men. Previously-reported sex differences in disease characteristics unmeasured herein (e.g., size of viral reservoirs, CD4 cell count at seroconversion) [35,36] may contribute to sex differences in HIV and NCI associations. Overall, results suggest that HIV+ black women are at the highest risk for NCI.
Our study has limitations including the small proportion of women (20%) and, thereby, the potential of being underpowered to detect an HIV by sex interaction. We were also unable to explore certain biopsychosocial factors (e.g., early life trauma, perceived stress). Study strengths include the large sample, an HIV- control group, race/ethnicity-stratified analyses and a comprehensive test battery that defined NCI. Demographically-adjusted T-scores based on HIV- data allowed us to examine sex differences in HIV-specific cognitive profiles; however, by restricting this analysis to HIV+ individuals with NCI, our statistical power was limited.
In conclusion, we contribute evidence that HIV-associated NCI is more prevalent in women versus men and indicate that this difference is accounted for by a lower reading level among HIV+ women. The frequent suboptimal educational experience of HIV+ women and the resulting lower cognitive reserve may make HIV+ women more susceptible to HIV-associated NCI. The effect of HIV on NCI was also greater in women versus men, particularly among blacks. Adjusting for education quality rather than years of education may improve the specificity of neuropsychological tests for measuring cerebral dysfunction and sex differences in HIV. Clinically, practitioners should be advised that black HIV+ women appear to be particularly at risk for NCI and provide resources to accommodate for these possible impairments.
Supplementary Material
ACKNOWLEDGMENTS
Erin Sundermann and David Moore conceptualized and designed the research project. All authors contributed to the statistical analysis plan. Erin Sundermann conducted statistical analyses and wrote the manuscript draft. All authors reviewed results, offered data interpretations, and edited the paper and contributed to the final version. All authors approved the final manuscript. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, Department of Defense, nor the United States Government. The authors thank Stephanie Corkran and Donald Franklin and for their help with data processing.
Source of Funding:
This work was supported by the National Institute of Health and the National Institute of Mental Health [P30MH062512, N01 MH22005, HHSN271201000036C and HHSN271201000030C, U24 MH100928]. This work was further supported by salary support for Dr. E. Sundermann from the Interdisciplinary Research Fellowship in NeuroAIDS [R25MH081482] and from salary support for Dr. RC Moore from a K23 award from the National Institute of Mental Health [K23 MH107260].
Footnotes
Conflicts of Interest
The authors have no conflicts of interest to declare.
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