Share this article on:

Synergistic Effects of HIV Infection and Older Age on Daily Functioning

Morgan, Erin E. PhD*; Iudicello, Jennifer E. PhD*; Weber, Erica MS; Duarte, Nichole A. PhD*; Riggs, P. Katie BS; Delano-Wood, Lisa PhD*,§; Ellis, Ronald MD, PhD; Grant, Igor MD*; Woods, Steven P. PsyD*; For The HIV Neurobehavioral Research Program (HNRP) Group

JAIDS Journal of Acquired Immune Deficiency Syndromes: 1 November 2012 - Volume 61 - Issue 3 - p 341–348
doi: 10.1097/QAI.0b013e31826bfc53
Clinical Science

Objective: To determine whether HIV infection and aging act synergistically to disrupt everyday functioning.

Design: Cross-sectional factorial study of everyday functioning in the context of HIV serostatus and age (≤40 years vs. ≥50 years).

Methods: One hundred three HIV+ and 87 HIV− participants were administered several measures of everyday functioning, including self-report indices of health-related quality of life (HRQoL) and instrumental and basic activities of daily living (IADLs and BADLs), and objective measures of functioning, including employment and Karnofsky Performance Scale ratings.

Results: Significant interaction effects of HIV and aging were observed for IADL and BADL declines, and for Karnofsky Performance Scale ratings (Ps < 0.05), independent of potentially confounding factors. Follow-up contrasts revealed significantly worse functioning in the older HIV+ group for most functional outcome measures relative to the other study groups (Ps < 0.05). A significant interaction effect was also observed on the emotional functioning HRQoL subscale, and additive effects of both age and HIV were observed for the physical functioning and general health perceptions HRQoL subscales (Ps < 0.05). Significant predictors of poorer functioning in the older HIV+ group included current major depressive disorder for all outcomes, and comorbid medical conditions, lower estimated premorbid functioning, neurocognitive impairment, and nadir CD4 count for selected outcomes.

Conclusion: Findings suggest that older age may exacerbate the adverse effects of HIV on daily functioning, which highlights the importance of evaluating and monitoring the functional status of older HIV-infected adults. Early detection of functional difficulties could facilitate delivery of compensatory strategies (eg, cognitive remediation) or assistive services.

*Department of Psychiatry, University of California, San Diego, CA

Departments of Psychology and Psychiatry, San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA

Department of Neurosciences, University of California, San Diego, CA

§Research and Psychology Services, VA San Diego Healthcare System, San Diego, CA.

Correspondence to: Steven P. Woods, PsyD, Department of Psychiatry (8231), University of California, San Diego, 220 Dickinson St, Suite B, San Diego, CA 92103 (e-mail:

Dr. Erin Morgan receives ongoing research support from NIH T32 AA013525. Dr. Jennifer Iudicello receives ongoing research support from NIH T32 DA31098. Erica Weber receives ongoing research support from NIH T32 DA31098. Nichole Duarte receives ongoing research support from NIH Grants MH73419, P50 DA26306, MH62512, and MH59745. P. Katie Riggs receives ongoing research support from NIH Grants R01 MH92225, P30 MH62512. Dr. Lisa Delano-Wood receives ongoing research support from New Investigator Research Grant (Alzheimer's Association) 09 134067, National Institute of Aging (NIA) 5 R01 AG012674 14, Congressionally Directed Medical Research Programs (CFMRP)/Department of Defense (DoD) (two Awards: Delano-Wood, Principal Investigator, and Jak, Principal Investigator), NIH R01 MH083969 01A2, and NIH R01 MH73419. Dr. Ronald Ellis received consultant fees from NeurogesX and is funded by NIH grants R01 MH058076, U01 MH83506, P30 MH62512, R01 MH83552, P50 DA26306, R01 MH095621, U01 NS32228. Dr. Grant receives ongoing research support from NIH Grants P30 MH62512, P50 DA26306, P01 DA12065, N01 MH22005, U01 MH83506, R01 MH78748, R01 AG15301, R01 MH83552, and NIH/University of Nebraska P01 DA026146. He has also received honoraria from Abbott Pharmaceuticals as part of their Educational Speaker Program. Dr. Woods receives ongoing research support from NIH Grants P30 MH62512, P50 DA26306, R01 MH73419, T32 DA31098, and R01 MH084794. This research was supported by NIH Grants R01 MH73419 and T32 DA31098 to Dr. Woods, P30 MH62512 (I. Grant, Principal Investigator) and T32 AA013525 (E. Riley, Principal Investigator).

The authors have no other conflicts of interest to disclose.

Received February 23, 2012

Accepted July 26, 2012

Back to Top | Article Outline


Due, in large part, to advances in combined antiretroviral therapy (cART), there is a growing population of older adults who are aging with HIV. Indeed, the Centers for Disease Control recently reported that more than a quarter of adults with HIV are 50 years of age and older.1 As individuals grow older with HIV infection, they may be susceptible to a host of different aging-related comorbidities, including cardiovascular disease,2 changes in bone density,3 metabolic dysregulation,4 and neurocognitive impairment.5,6 Importantly, these conditions may be associated with poor long-term clinical outcome.

The increased mental and physical health burden of aging with HIV infection may increase older HIV-seropositive adults' vulnerability to disruption in basic (eg, grooming) and instrumental (eg, financial management) aspects of everyday functioning that are critical to optimal health outcomes. Important predictors of daily functioning problems in the context of both HIV and aging include certain demographics (eg, male sex7), depressed mood,8 overall burden of disease,9 and neurocognitive deficits (eg, memory and executive impairment10). A recent study revealed a synergistic effect of age and neurocognitive status on functional task performance in HIV+ individuals, such that the older impaired group evidenced worse medication and finance management than the younger groups.11 Irrespective of neurocognitive status, older age has been significantly associated with both physical difficulty (eg, climbing stairs) and role limitations (eg, employment) in persons with HIV.12 However, no studies have yet investigated potential synergistic effects of HIV and aging on daily functioning outcomes through inclusion of an HIV-seronegative comparison group using a comprehensive assessment of daily functioning domains.

The present study aimed to investigate the combined effects of HIV and aging on everyday functioning across several measures ranging in complexity and objectivity (ie, source of information). Self-reported indices of daily functioning included measures of instrumental and basic activities of daily living (IADLs and BADLs), and scales representing both physical and mental health-related quality of life (HRQoL). Objective functional measures included employment status and the clinician-assigned Karnofsky Scale of Performance Status. We hypothesized that older HIV+ adults would be at greatest risk for functional problems, independent of potential confounding variables (eg, education). Finally, we examined relationships between these outcomes and clinical factors expected to impact successful daily functioning in older HIV+ adults (eg, mood and HIV disease severity).

Back to Top | Article Outline



This study included 179 participants recruited from the San Diego community and local HIV clinics. Participants were classified by HIV serostatus and age (ie, young: aged 40 years or younger and old: aged 50 years or older; Table 1). HIV serostatus was determined by enzyme-linked immunosorbent assays and confirmed by a Western blot test. All HIV+ individuals were on stable antiretroviral therapy at the time of their assessment.

Participants were excluded if they had histories of severe psychiatric disorders (eg, schizophrenia), chronic medical, or neurological conditions such as active central nervous system opportunistic infections, seizure disorders, head injury with loss of consciousness more than 30 minutes, stroke with neurological sequelae, and non–HIV-associated dementias or if they had an estimated verbal IQ score less than 70 on the Wechsler Test of Adult Reading (WTAR).13 Individuals were also excluded if they met Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV)14 criteria for substance use disorders within 6 months of evaluation or if they tested positive on a urine toxicology (u-tox) screen for illicit drugs (except marijuana) on the day of testing. Demographic, cognitive, psychiatric, and medical characteristics of the sample may be found in Table 1.

Back to Top | Article Outline

Materials and Procedure

The study procedures were approved by the human subjects institutional review board. Each participant provided written informed consent and was administered a comprehensive medical, psychiatric, and neuropsychological medical evaluation.

Back to Top | Article Outline

Evaluation of Daily Functioning

Each participant completed a modified form of the Lawton and Brody15 ADL Scale.8 This scale requires participants to rate their current and best levels of functioning with regard to 7 IADLs (ie, finance management, purchasing groceries, cooking, using transportation, shopping, medication management, and social activity planning) and 5 BADLs (ie, housekeeping/cleaning, laundry, home repairs, bathing, and dressing), with the summed difference scores interpreted so that higher values denote poorer functioning (see Ref.16) Ranges of the IADL and BADL subscales are 0–17 and 0–13, respectively. Second, each participant was assigned an overall functional impairment rating by a certified nurse, based on the Karnofsky Scale of Performance Status,17 which has been validated in HIV,18 and ranges from 100 (ie, able to carry on normal activity) to zero (ie, death).

Each participant was also administered the RAND 36-item Short Form Health Survey (SF-36), which is a disease nonspecific 36-item self-report questionnaire assessing physical and mental health well-being, that has been validated as an index of HRQoL in HIV.19,20 The SF-36 consists of 8 subscales that range from 0 to 100, with higher scores indicating better HRQoL.

Employment status was coded via a semistructured neurobehavioral interview (see Ref.21) Each participant was classified as employed (full time only) or unemployed, which included those classified as disabled (ie, 29.3%).

Back to Top | Article Outline

Medical Evaluation

Each individual received a medical evaluation including a blood draw and an assessment of medical conditions common in HIV-infected and aging populations, including diabetes mellitus, cardiovascular disease (eg, hypertension), respiratory disease (eg, chronic obstructive pulmonary disease), and hepatitis C virus (HCV; Table 1). A composite medical comorbidities index (ie, the “Medical Comorbidity Burden”) was derived by summing the total number of medical conditions endorsed.22 An estimated 5-year risk of developing coronary heart disease was calculated for each participant using published Framingham Risk Score equations.23

Back to Top | Article Outline

Neuropsychological Evaluation

The neuropsychological evaluation included an estimated measure of premorbid verbal IQ (ie, WTAR), alongside a comprehensive neuropsychological test battery designed to assess the cognitive domains most frequently impacted in HIV-associated neurocognitive disorders (HAND) in accordance with Frascati research criteria,24 including executive functions, attention/working memory, episodic learning and memory, verbal fluency, information processing speed, and motor skills (for details, see Ref.16). Clinical ratings ranging from 0 (above average) to 9 (severely impaired) were assigned for each participant by trained neuropsychologists using published, standardized, and well-validated blind clinical ratings procedures25 that have been previously demonstrated to be predictive of daily functioning outcomes in HIV+ individuals.8 A cut point of 5 or more indicating global neuropsychological impairment (ie, Global NPI; Table 1 for rates of impairment). HIV+ individuals with HAND were further classified as having asymptomatic neurocognitive impairment, minor neurocognitive disorder, or HIV-associated dementia using Antinori et al24 research criteria (Table 1).

Each participant was also assigned a score representing their highest occupational level based on the Hollingshead Occupational Scale,26 which rates occupations along a continuum ranging from 1 (eg, managers or other professionals) to 7 (eg, nonspecialized manual labor). Each participant's Hollingshead score was converted to a population-based z score and averaged with population-based z scores for years of education and WTAR verbal IQ to derive a putative estimate of premorbid functioning, also known as cognitive reserve, in which higher scores reflect greater levels of estimated reserve.

Back to Top | Article Outline

Psychiatric Evaluation

Current mood symptoms were assessed using the Profile of Mood States,27 which is a 65-item self-report measure of current affective distress. Current (ie, within the last 30 days) and lifetime major depressive disorder (MDD) and substance use disorders were determined using the Composite International Diagnostic Interview (version 2.128).

Back to Top | Article Outline

Data Analysis

Statistical analyses were conducted using a JMP software package (version 9.0.2) and the critical alpha was set at P < 0.05. Multiple linear regression analyses were used to evaluate the models involving continuous criterion variables (ie, ADL declines, Karnofsky, and SF-36). A logistic regression was conducted to examine the model involving the dichotomous employment variable. To address potential confounding effects, several factors that differed across the groups were included as covariates, including ethnicity, Profile of Mood States Total, Global NPI, and the Framingham. Although significant group differences were observed for other potentially important factors (ie, HCV, antidepressants, and marijuana u-tox), these variables were not included in our regression models due to low prevalence rates. Nevertheless, when respective regression models were conducted including these factors, the pattern of findings was unchanged. For the planned post hoc analyses, we used one-way ANOVA (and Cohen d effect size estimates) or χ2 tests as appropriate. Multiple linear regression models were used to investigate predictors of each functional outcome within the older HIV+ group, and included current MDD diagnosis, nadir cluster of differentiation 4 (CD4) count, plasma viral load, global NPI, medical comorbidity burden, and cognitive reserve.

Back to Top | Article Outline


Results of the analyses examining the independent and synergistic effects of age and HIV infection on self-reported IADL and BADL declines, Karnofsky scores, and employment are displayed in Table 2. Significant synergistic effects of age and HIV infection were observed for IADL and BADL declines and Karnofsky scores (Ps < 0.05), although no significant interaction was observed for employment (P > 0.10; Table 2). Significant main effects of HIV were observed for all 4 functional outcomes (Ps < 0.05), although a significant main effect of age was only observed for Karnofsky scores (P = 0.010). With regard to the SF-36 HRQoL subscales, a significant age by HIV interaction was observed only for the emotional functioning subscale (β = −0.13, P = 0.026). Independent effects of both age and HIV (ie, additive effects) were observed for physical functioning (age: β = −0.29, HIV: β = 0.17, Ps < 0.05) and general health perceptions (age: β = −0.24, HIV: β = 0.16, Ps < 0.01) subscales. A main effect of aging was observed for the bodily pain subscale (β = −0.19, P = 0.040), and a main effect of HIV was observed for the role limitations because of physical health problems subscale (β = 0.19, P = 0.005). No significant age, HIV, or interaction effects were observed for the emotional well-being, role limitations caused by emotional problems, and social functioning subscales (Ps > 0.05).

As displayed in Figures 1 and 2, the older HIV+ group reported a significantly higher number (ie, reported greater severity) of both IADL and BADL declines and had significantly lower Karnofsky ratings relative to each of the remaining groups (Ps < 0.05). Last, the older HIV+ group had greater proportions of individuals who were unemployed or disabled relative to both HIV− groups (Ps < 0.05), although they had similar rates of employment to their younger HIV+ counterparts (P = 0.117; Fig. 2).

Results for the analyses used to determine predictors of ADL declines, Karnofsky ratings, and employment status within the older HIV+ group are presented in Table 3. Current MDD was a significant predictor of all 4 functional outcomes (Ps < 0.05). Additional significant predictors of IADL declines included global NPI, nadir CD4 count, and cognitive reserve (Ps < 0.05). Lower cognitive reserve was also associated with BADL disability, albeit at a trend level (P = 0.055). A greater medical comorbidity burden and lower cognitive reserve were both significant predictors of lower Karnofsky ratings (Ps < 0.05), and reached a trend level of significance as predictors of unemployment (Ps < 0.10). For the SF-36 HRQoL subscales, significant regression models were observed for physical functioning (F6,53 = 2.3; adjusted R2 = 0.12; P = 0.048), emotional well-being (F6,51 = 5.35; adjusted R2 = 0.31; P = 0.002), role limitations caused by emotional problems (F6,54 = 4.37; adjusted R2 = 0.25; P = 0.001) and social functioning (F6,54 = 3.22; adjusted R2 = 0.18; P = 0.009). Presence of current MDD was the only significant predictor of these HRQoL subscales (Ps < 0.01). Additional associations, albeit at a trend level, were observed between the medical comorbidity burden and the physical functioning subscale (β = −0.22), and between global NPI and social functioning (β = −0.21; Ps < 0.10).

Back to Top | Article Outline


Everyday functioning impairment is an important sequelae of HIV infection to which older infected adults may be particularly vulnerable. This study demonstrated synergistic adverse effects of HIV and aging on daily functioning outcomes, including self-reported decline in both IADLs and BADLs and poorer scores on a clinician-assigned rating of overall functional status. The interaction of HIV infection and aging observed for these functional outcomes persisted despite controlling for important cofactors on which the groups differed (eg, demographic or medical factors). For each of the functional outcomes, the older HIV+ group demonstrated poorer everyday functioning relative to the other study groups. With the foundation of a rigorous and comprehensive study design, these findings extend prior literature because of inclusion of both older and younger HIV-seronegative individuals for comparison to the HIV+ groups and by examining a wide range of everyday functioning measures. Accordingly, these findings suggest that older age may exacerbate HIV-associated disability in daily life.

Such findings raise important questions about the specific clinical characteristics that may increase older HIV-infected adults' vulnerability to poorer functional outcomes. Importantly, several of these predictors are highly amenable to proper screening and treatment, which may facilitate efforts to improve the health status of this high-risk group. For example, MDD was arguably the most reliable predictor of adverse functional outcomes in our older HIV+ cohort, which is consistent with abundant evidence from the HIV literature.8 Notably, this relationship may be bidirectional such that depressed mood may negatively impact performance of daily activities, but also poor performance of everyday functions may itself precipitate depressed mood.29 These findings highlight the need to regularly screen older HIV+ adults for symptoms of depression given that episodes of major depression can disrupt performance of important daily activities and are potentially remediable.30 It is important to note, however, that in the present sample, 44% of the older HIV+ adults with lifetime MDD diagnoses were currently taking antidepressants, and a post hoc analysis revealed that antidepressant use was not associated with better daily functioning in the older HIV+ individuals with MDD (current or lifetime). As such, future studies should explore the most effective interventions for MDD and ameliorating the impact of MDD on functioning, which may include a combination of pharmacologic and psychotherapeutic intervention.

The presence of HAND was a significant predictor of greater levels of IADL declines, which is consistent with prior studies demonstrating disproportionate effects of HAND among older HIV+ individuals, particularly as it relates to medication and finance management.11 Older HIV+ individuals who report difficulty with complex daily activities might benefit from neurocognitive screening and training in compensatory strategies (eg, pill boxes and automatic bill pay). Interestingly, estimated premorbid functioning, also known as cognitive reserve, was uniquely associated with aspects of everyday functioning among older HIV+ adults. This construct represents the effects of enrichment of cognitive resources through educational and vocational experiences coupled with elements of innate intellectual ability that have been proposed to moderate the relationship between central nervous system insults, such as infection and neurobehavioral outcomes.31 For example, HIV+ individuals with low cognitive reserve are at greater risk for concurrent32 and incident HAND.33 In the present study, lower cognitive reserve was associated with greater IADL declines and lower Karnofsky ratings. This evidence suggests that in older HIV-infected adults, lower cognitive reserve may interfere with the adaptive ability to engage alternate brain networks and/or initiate the use of compensatory strategies when they encounter problems in their daily life, resulting in disability.

Medical comorbidity burden, which summarizes the extent of each individual's concurrent medical comorbidities, including diabetes mellitus, cardiovascular disease, respiratory disease, and HCV, was associated with lower Karnofsky ratings. It is possible that the gross nature of the Karnofsky score is sensitive to the problems imposed by managing comorbid conditions, especially given that HIV+ individuals may be particularly vulnerable to these conditions as they age, including cardiovascular and metabolic conditions (eg, hypertension and diabetes3,34). Furthermore, information regarding the patient's medical history that is available to the clinician assigning the rating may also contribute to the contribution of medical comorbidity burden to prediction of the Karnofsky score.

While the index of current HIV disease status (ie, detectable plasma viral load) was not related to any of the functional outcomes in the older HIV+ group, lower nadir CD4 count (ie, a marker of worse historical HIV disease) was significantly associated with greater IADL declines. This is consistent with evidence suggesting that low nadir CD4 predicts development of HAND, which is a robust predictor of daily functioning outcomes in older HIV+ adults.11 The lack of associations between current detectable plasma load and everyday functioning outcomes could be due in part to the improved HIV management in the cART era, which may decrease the relevance of HIV disease-specific markers for predicting a downstream outcome, such as daily functioning performance. Indeed, the entire HIV+ sample in this study was on stable antiretroviral medications at the time of evaluation, and only about 10% of our older HIV+ group had detectable plasma viral loads. Furthermore, HIV+ individuals who have reached older age may carry a survival bias that should temper conclusions regarding the association between HIV disease characteristics and disability. With regard to markers of current disease status, in the present cohort of older HIV+ adults, many of whom may be long-term survivors, the added burden of comorbid conditions, such as cardiovascular disease or diabetes seems to be much more likely to negatively impact performance of daily activities.35 Moreover, the significant negative association between low nadir CD4 count and increased daily functioning difficulty may actually be a cohort effect that is most relevant to long-term survivors who have experienced greater disease severity in the past and recovered. In the current cART era, individuals who are treated earlier with more effective and less neurotoxic regimens may not experience periods of such drastic disease severity (as evidenced by low nadir CD4), thereby reducing the likelihood that this historic disease marker would represent a significant risk for disability in future older HIV+ cohorts.

With regard to HRQoL, the disproportionately worse emotional functioning observed among older HIV+ adults is consistent with the high prevalence of depression among older HIV+ adults. Indeed, among the older HIV+ group only, current MDD emerged as the sole important risk factor for reductions in several types of HRQoL, including worse emotional well-being and role limitations due to emotional functioning, and lower physical and social functioning. This evidence further supports the need for careful depression screening and effective treatment among older HIV+ individuals, whose HRQoL can be negatively impacted by depression across many dimensions. Although synergistic effects were not observed for the other HRQoL subscales, additive effects of HIV and aging were observed for the physical functioning and general health perceptions subscales. As such, it is likely that older patients with HIV may experience incremental rather than synergistic limitations in their physical activities and changes in their beliefs about their health overall than would be associated with HIV or aging alone. These results are consistent with prior evidence of lower quality of life relating to limitations in physical activities demonstrated among HIV+ individuals,12 and they extend these prior findings by demonstrating the additive component of aging in reducing this aspect of HRQoL.

The present study has limitations worth noting that may also inform future work. First, the cross-sectional nature of the study does not allow for interpretations regarding potential synergistic effects of HIV and aging on decline in daily functioning status over time. This is an important future direction given that it would inform daily functioning prognosis for older HIV+ individuals. In addition, it would be helpful to replicate our study with a sample that included greater numbers of individuals at more advanced age (eg, older than 65 years of age). It is likely that the observed interaction effect would be strengthened in such a sample, but it would also be interesting to examine whether the cognitive reserve relationship holds at older ages such that higher levels of reserve protect again daily functioning failures. As discussed above, survivor bias is also an important consideration, especially in light of the fact that current HIV disease status was not a significant predictor of any everyday functioning measures, and risk for disability may change as the characteristics of the cohorts of older adults living with HIV evolve over time (eg, the nature of the predictors may change as people age with better managed HIV disease). Moreover, although the current study used both self-reported and objective indices of daily functioning, performance-based measures of functional capacity were not included. Such ecologically valid measures would be another important criterion for examining the combined effects of HIV and aging. Finally, although all individuals in the HIV+ sample were prescribed a stable cART regimen, the present study did not specifically examine measures of medication adherence among the selected daily functioning outcomes. On one hand, some evidence suggests that older HIV+ adults without cognitive impairment are more adherent to their cART regimens for a variety of reasons.36 On the other hand, medication nonadherence could be particularly problematic in older HIV+ adults, not only for proper maintenance of HIV disease but also of comorbid conditions related to aging (eg, hypertension). Given the evidence that HIV and aging in combination negatively impact other important daily activities, future studies investigating these combined effects on medication adherence are warranted.

Back to Top | Article Outline


The San Diego HIV Neurobehavioral Research Program (HNRP) group is affiliated with the University of California, San Diego; the Naval Hospital, San Diego, and the Veterans Affairs San Diego Healthcare System, and includes Director: Igor Grant, MD; Co-Directors: J. Hampton Atkinson, MD, Ronald J. Ellis, MD, PhD, and J. Allen McCutchan, MD; Center Manager: Thomas D. Marcotte, PhD; Jennifer Marquie-Beck, MPH; Melanie Sherman; Neuromedical Component: Ronald J. Ellis, MD, PhD (P.I.), J. Allen McCutchan, MD, Scott Letendre, MD, Edmund Capparelli, PharmD, Rachel Schrier, PhD, Terry Alexander, RN, Debra Rosario, MPH, Shannon LeBlanc; Neurobehavioral Component: Robert K. Heaton, PhD (P.I.), Steven Paul Woods, PsyD, Mariana Cherner, PhD, David J. Moore, PhD, Matthew Dawson; Neuroimaging Component: Terry Jernigan, PhD (P.I.), Christine Fennema-Notestine, PhD, Sarah L. Archibald, MA, John Hesselink, MD, Jacopo Annese, PhD, Michael J. Taylor, PhD; Neurobiology Component: Eliezer Masliah, MD (P.I.), Cristian Achim, MD, PhD, Ian Everall, FRCPsych, FRCPath, PhD (Consultant); Neurovirology Component: Douglas Richman, MD, (P.I.), David M. Smith, MD; International Component: J. Allen McCutchan, MD, (P.I.); Developmental Component: Cristian Achim, MD, PhD; (P.I.), Stuart Lipton, MD, PhD; Participant Accrual and Retention Unit: J. Hampton Atkinson, MD (P.I.), Jennifer Marquie-Beck, MPH; Data Management Unit: Anthony C. Gamst, PhD (P.I.), Clint Cushman (Data Systems Manager); Statistics Unit: Ian Abramson, PhD (P.I.), Florin Vaida, PhD, Reena Deutsch, PhD, Anya Umlauf, MS, and Tanya Wolfson, MA.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 Marizela Cameron and Katie Doyle for their help with study management.

Back to Top | Article Outline


1. Centers for Disease Control. HIV/AIDS Surveillance Report, 2007. Atlanta, GA: U.S. Department of Health and Human Services, CDC; 2009:1–65.
2. Magalhaes MG, Greenberg B, Hansen H, et al.. Comorbidities in older patients with HIV: a retrospective study. J Am Dent Assoc. 2007;138:1468–1475.
3. Cotter AG, Mallon PWG. HIV infection and bone disease: implications for an aging population. Sex Health. 2011;8:493–501.
4. Valcour V, Paul R. HIV infection and dementia in older adults. Clin Infect Dis. 2006;42:1449–1454.
5. Valcour V, Shikuma C, Shiramizu B, et al.. Higher frequency of dementia in older HIV-1 individuals: the Hawaii Aging with HIV Cohort. Neurology. 2004;63:822–827.
6. Valcour V, Paul R, Neuhaus J, et al.. The effects of age and HIV on neuropsychological performance. J Int Neuropsychol Soc. 2011;17:190–195.
7. Pérès K, Helmer C, Amieva H, et al.. Gender differences in the prodromal signs of dementia: memory complaint and IADL-restriction. A prospective population-based cohort. J Alzheimers Dis. 2011;27:39–47.
8. Heaton RK, Marcotte TD, Rivera-Mindt M, et al.. The impact of HIV-associated neuropsychological impairment on everyday functioning. J Int Neuropsychol Soc. 2004;10:317–331.
9. Blaum CS, Ofstedal MB, Liang J. Low cognitive performance, comorbid disease, and task-specific disability: findings from a nationally representative study. J Gerontol A Biol Sci Med Sci. 2002;57:M523–M531.
10. Barclay TR, Hinkin CH, Castellon SA, et al.. Age-associated predictors of medication adherence in HIV-positive adults: health beliefs, self-efficacy, and neurocognitive status. Health Psychol. 2007;26:40–49.
11. Thames AD, Kim MS, Becker BW, et al.. Medication and finance management among HIV-infected adults: the impact of age and cognition. J Clin Exp Neuropsychol. 2011;33:200–209.
12. Crystal S, Fleishman JA, Hays R, et al.. Physical and role functioning among persons with HIV: results from a nationally representative survey. Med Care. 2000;38:1210–1223.
13. Psychological Corporation. Wechsler Test of Adult Reading. San Antonio, TX: Psychological Corporation; 2001.
14. American Psychiatric Association. Diagnostic and Statistics Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
15. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–186.
16. Woods SP, Morgan EE, Dawson M, et al.; The HIV Neurobehavioral Research Center (HNRC) Group. Action (verb) fluency predicts dependence in instrumental activities of daily living in persons infected with HIV-1. J Clin Exp Neuropsychol. 2006;28:1030–1042.
17. Karnofsky DA, Burchenal JH. The clinical evaluation of chemo-therapeutic agents in cancer. In: Maclead CM, ed. Evaluation of Chemotherapeutic Agents. New York, NY: Columbia University Press; 1949:191–205.
18. Gandhi NS, Skolansky RL, Peters KB, et al.. A comparison of performance-based measures of function in HIV-associated neurocognitive disorders. J Neurovirol. 2011;17:159–165.
19. Bing EG, Hays RD, Jacobson LP, et al.. Health-related quality of life among people with HIV disease: results from the Multicenter AIDS Cohort Study. Qual Life Res. 2000;9:55–63.
20. Lamping DL. Methods for measuring outcomes to evaluate interventions to improve health-related quality of life in HIV infection. Psychol Health. 1994;9:31–49.
21. Woods SP, Weber E, Weisz B, et al.. Prospective memory deficits are associated with unemployment in persons living with HIV infection. Rehabil Psychol. 2011;56:77–84.
22. Duff K, Mold JW, Roberts MM, et al.. Medical burden and cognition in older patients in primary care: selective deficits in attention. Arch Clin Neuropsychol. 2007;22:569–575.
23. Anderson KM, Odell PM, Wilson PW, et al.. Cardiovascular disease risk profiles. Am Heart J. 1991;121:293–298.
24. Antinori A, Arendt G, Becker JT, et al.. Updated research nosology for HIV-associated neurocognitive disorders. Neurology. 2007;69:1789–1799.
25. Woods SP, Rippeth JD, Frol AB, et al.. Interrater reliability of clinical ratings and neurocognitive diagnoses in HIV. J Clin Exp Neuropsychol. 2004;26:759–778.
26. Hollingshead AB. Four Factor Index of Social Status. New Haven, CT: Yale University Press; 1975.
27. McNair DM, Lorr M, Droppleman LF. Profile of Mood States. San Diego, CA: Educational and Industrial Testing Service; 1981.
28. World Health Organization. Composite International Diagnostic Interview (CIDI, Version 2.1). Geneva, Switzerland: World Health Organization; 1998.
29. Ettenhofer ML, Foley J, Behdin N, et al.. Reaction time variability in HIV-positive individuals. Arch Clin Neuropsychol. 2009:25:791–798.
30. Sherr L, Clucas C, Harding R, et al.. HIV and depression—a systematic review of interventions. Psychol Health Med. 2011;16:493–527.
31. Stern Y. The concept of cognitive reserve: a catalyst for research. J Clin Exp Neuropsychol. 2003;25:589–593.
32. Pereda M, Ayuso-Mateos JL, Gomez Del Barrio A, et al.. Factors associated with neuropsychological performance in HIV-seropositive subjects without AIDS. Psychol Med. 2000;30:205–217.
33. Basso MR, Bornstein RA. Estimated premorbid intelligence mediates neurobehavioral change in individuals infected with HIV across 12 months. J Clin Exp Neuropsychol. 2000;22:208–218.
34. Valcour VG, Shikuma CM, Shiramizu BT, et al.. Diabetes, insulin resistance, and dementia among HIV-1-infected patients. J Acquir Immune Defic Syndr. 2005;38:31–36.
35. Becker JT, Kingsley L, Mullen J, et al.. Vascular risk factors, HIV serostatus, and cognitive dysfunction in gay and bisexual men. Neurology. 2009;73:1292–1299.
36. Ettenhofer ML, Hinkin CH, Castellon SA, et al.. Aging, neurocognition, and medication adherence in HIV infection. Am J Geriatr Psychiatry. 2009;17:281–290.

HIV; aging; assessment; daily functioning; health status; disability

© 2012 Lippincott Williams & Wilkins, Inc.