Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Jul 1.
Published in final edited form as: AIDS. 2024 Feb 7;38(8):1186–1197. doi: 10.1097/QAD.0000000000003862

Age-associated dementia among older people aging with HIV in the US:a modeling study

Emily P Hyle 1,2,3,4, Nattanicha Wattananimitgul 1, Shibani S Mukerji 3,5, Julia H A Foote 1, Krishna P Reddy 1,3,6, Acadia Thielking 1, Liyang Yu 1, Anand Viswanathan 3,5, Leah H Rubin 7,8,9, Fatma M Shebl 1,3, Keri N Althoff 7, Kenneth A Freedberg 1,2,3,4,10,11
PMCID: PMC11141339  NIHMSID: NIHMS1964340  PMID: 38329107

Abstract

Objective

Almost 400,000 people with HIV (PWH) in the US are over age 55y and at risk for age-associated dementias (AAD), including Alzheimer’s disease and vascular contributions to cognitive impairment and dementia (VCID). We projected the cumulative incidence and mortality associated with AAD among PWH ≥60y in the US compared with the general population.

Design/Methods

Integrating the CEPAC and AgeD-Pol models, we simulated two cohorts of males and females ≥60y: (1) PWH, and (2) general US population. We estimated AAD incidence and AAD-associated mortality rates. Projected outcomes included AAD cumulative incidence, life expectancy, and quality-adjusted life-years (QALYs). We performed sensitivity and scenario analyses on AAD-specific (e.g., incidence) and HIV-specific (e.g., disengagement from HIV care) parameters, as well as premature aging among PWH.

Results

We projected that 22.1%/16.3% of 60-year-old males/females with HIV would develop AAD by 80 years compared with 15.9%/13.3% of males/females in the general population. Accounting for age- and dementia-associated quality of life, 60-year-old PWH would have a lower life expectancy (QALYs): 17.4y (14.1 QALYs) and 16.8y (13.4 QALYs) for males and females, respectively, compared with the general population (males, 21.7y [18.4 QALYs]; females, 24.7y [20.2 QALYs]). AAD cumulative incidence was most sensitive to non-HIV-related mortality, engagement in HIV care, and AAD incidence rates.

Conclusions

Projected estimates of AAD-associated morbidity, mortality, and quality of life can inform decision-makers and health systems planning as the population of PWH ages. Improved AAD prevention, treatment, and supportive care planning are critical for people aging with HIV.

Keywords: HIV, aging, dementia, cognitive impairment, comorbidity, simulation modeling

INTRODUCTION

With antiretroviral therapy (ART), people with HIV (PWH) are aging and expected to attain life expectancies near those of the general population [1]. In 2019, almost 400,000 (38%) people living with diagnosed HIV in the US were 55 years or older [2]. Older PWH are at increased risk for comorbidities, such as cardiovascular disease and dementia, which can be either accentuated or accelerated due to HIV [3–6].

Age-associated dementias (AAD), such as Alzheimer’s disease and vascular contributions to cognitive impairment and dementia (VCID), are increasingly common in the general US population. With more people aging into their 80’s, the burden of AAD in the US is projected to more than double from 5.8 million in 2019 to 13.9 million by 2060 [7–9]. AAD has been rarely reported among PWH because of historical challenges with distinguishing AAD from HIV-associated neurocognitive disorder (HAND); additionally, most PWH are only recently reaching ages at which AAD is diagnosed [10–12]. AAD is expected to affect PWH when they age beyond 60 years, at least at similar rates as in the general population, if not more frequently [6,13].

Beyond age as a risk factor, PWH are at increased risk of developing AAD due to pathophysiologic mechanisms, including abnormal deposition of amyloid and other proteins associated with neurodegeneration [14,15], immune activation [16,17], vascular diseases [18,19], and brain atrophy [12]. Additionally, compared with the general population, PWH are at increased risk for VCID due to higher rates of smoking [20,21], as well as higher risks of diabetes, hypertension, atherosclerosis, and stroke [22,23]. Recent data suggest that AAD incidence among PWH may be almost twice that of people without HIV within the same healthcare system [6].

As the population of PWH in the US ages, evidence-based projections of AAD-associated morbidity, quality of life, and mortality are essential for health services planning, coordination of AAD and HIV care, and expansion of services that are effective and affordable. Our objective was to populate a microsimulation model for HIV and AAD and then simulate cumulative AAD incidence and life expectancy for 60-year-old people with and without HIV in the US.

METHODS

Analytic Overview

We expanded the Cost-Effectiveness of Preventing AIDS Complications (CEPAC) microsimulation model of HIV natural history and treatment to incorporate features of the Age-associated Dementia Policy (AgeD-Pol) model, a computer microsimulation model that projects age- and sex-specific prevalence, incidence, and mortality of AAD in the US. We simulated male and female cohorts: (1) people with HIV (“PWH”) and (2) the general US population. At model start, all people are 60 years old and without AAD. We parameterized AAD-associated input parameters (i.e., AAD incidence, progression, and mortality) with data from the general US population; for AAD incidence in PWH, we increased age-/sex-stratified AAD incidence as recently reported [6]. We accounted for competing risks of deaths from HIV-related and non-HIV/non-AAD-related causes. We projected the 10-year, 20-year, and lifetime cumulative AAD incidence, as well as overall life expectancy, and quality-adjusted life-years for PWH and the general US population.

Model Structure

The Age-associated Dementia Policy (AgeD-Pol) Model

The AgeD-Pol model is a microsimulation model of age-associated dementia previously validated for the general US population [24,25]. Simulated individuals are assigned AAD status at model start based on age- and sex-stratified AAD prevalence. As individuals without AAD progress throughout the simulation, they are subject to age-/sex-stratified monthly AAD incidence. Individuals with AAD can progress from mild to moderate disease to severe disease; prior studies have suggested that only individuals with severe AAD experience AAD-associated mortality [26–28]. Therefore, only simulated people with severe AAD incur an additional risk for monthly AAD-related mortality, in addition to non-AAD-related mortality.

The Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model

The CEPAC model is a validated microsimulation of HIV disease and treatment [29–32]. Upon entry into the model, simulated individuals draw for CD4 count and HIV RNA from user-defined initial distributions. Simulated PWH in care are treated with ART and transition monthly between health states defined by CD4 count, HIV RNA, history of opportunistic infection (OI), and ART use. They can disengage from HIV care, stop ART, and subsequently return to care and reinitiate ART. Death among PWH can occur from HIV-related causes (OI or chronic HIV-related mortality), AAD, or other non-HIV-/non-AAD-related causes (e.g., cancers, suicide). Model details are available at https://www.massgeneral.org/medicine/mpec/research/cpac-model.

Simulated Cohorts

We simulated male and female cohorts of (1) PWH and (2) the general US population who are 60 years old at model start. Compared with the general US population, PWH are at risk for HIV-related mortality and at increased risk of age- and sex-stratified non-HIV-/non-AAD-related mortality that reflects the proportions of PWH from different HIV acquisition risk groups defined by the Centers for Disease Control and Prevention (CDC): men who have sex with men (MSM); people who ever used injection drugs (PWID); people who are heterosexually active at increased risk for HIV acquisition [31,33,34]. The general US population consists of people without HIV who experience average non-HIV-/non-AAD-related mortality.

Input Parameters (Table 1)

Table 1.

Input parameters for analysis of AAD risk in people aged 60 years and older in the US

Input parameter Base Case Value Sensitivity Analysis Range Reference
Cohort characteristics All cohorts
Age, mean years 60
Initial CD4 count, cells/μL (SD)
 Diagnosed, on ART 600 (313) [35]
 Diagnosed, not in care 325 (53) [36]*
Virologic suppression among PWH in care, % 80 100 [37–39]*
Monthly probability of disengagement from care, range by adherence, % 0.01–15 [2,40]*
Monthly probability of return to care, % 3.0 Assumption
Proportion of population with HIV, % Males Females
 Men who have sex with men 79.9 -- [2]
 People who have ever injected drugs 9.2 20.6
 Heterosexually active individuals at increased risk for HIV 10.9 79.4
AAD-related inputs All cohorts
General population AAD incidence, per 1,000 person-years
 Age, years, mean (SD) Males Females
  60–64 4.5a 3.2a [72,73]*
  65–69 7.4 3.8 [41]*
  70–74 11.4 7.9
  75–79 21.1 18.1
  80–84 49.2 44.7
  85+ 80.8b 94.1b
AAD incidence rate ratio:
 PWH vs. general population 1.8 1.8 1.4–2.2 [6]
Duration of AAD stages, months (SD) 0.5–2x
 Mild to moderate AAD 43.6 (37.0) [74,75]*
 Moderate to severe AAD 24.0 (16.7)
AAD-associated quality of life decrement by stage 0.75–1.25x
 Mild −0.09
 Moderate −0.18 [42]*
 Severe −0.26
Mortality
Monthly AAD-associated mortality among people with severe AAD, % 0.5–2.0x
 Age, years Males Females
  60–64 0.002 0.001 [27,44]*
  65–69 0.004 0.004
  70–74 0.013 0.011
  75–79 0.036 0.034
  80–84 0.092 0.093
  85+ 0.280 0.350
Non-HIV, non-AAD-related mortality, monthly, % Males Females
 Ages 60–64y 0.094–0.125 0.058–0.074 [43,44]*
 Ages 65–69y 0.135–0.166 0.079–0.104
 Ages 70–74y 0.179–0.241 0.115–0.159
 Ages 75–79y 0.259–0.364 0.172–0.248
 Ages 80–84y 0.398–0.583 0.269–0.394
 Ages 85+ 0.619–2.668 0.423–1.849
Relative mortality ratios applied to non-HIV/non-AAD-related mortality for PWH, mean [95% CI]a Males Females Males Females
 Men who have sex with men 1.5 [1.0–2.3] -- [2,34]*
 People who have ever injected drugs 1.7 [1.1–2.5] 3.5 [2.0–6.0]
 Heterosexually active individuals at increased risk for HIV 1.7 [1.0–2.1] 2.4 [1.9–3.0]
 Weighted average 1.5 [1.1–1.9] 2.6 [2.3–3.6] 1.0–4.0 1.0–4.0
Monthly probability of chronic HIV mortality by CD4 count (cells/μL), range by OI history, %
 >500/μL 0.003 [43,53,76–80]*
 351–500/μL 0.011
 201–350/μL 0.021
 101–200/μL 0.020–0.270
 50–100/μL 0.028–0.270
 <50/μL 0.120–0.560
Open in a new tab
*

Inputs derived from listed sources

a

The AAD incidence rate for ages 60-64 was derived from estimates reported by Knopman et al. 2005 and the World Alzheimer’s Report 2015 [37,38].

b

The AAD incidence rate for ages 85+ is an average of the 80-84 and 85+ age groups reported by Tom et al. 2015 [36].

a

Relative mortality ratios compare people in each risk group with the general population

AAD: Age-associated dementia; PWH: people with diagnosed HIV; SD: standard deviation; ART: antiretroviral therapy; DTG: dolutegravir; PI: protease inhibitor; OI: opportunistic infection.

Cohort characteristics

We assigned cohort characteristics (e.g., age, sex at birth, CD4 count) to simulated PWH at model start based on whether they are on ART (75% of PWH; mean CD4 600/μL) or disengaged from HIV care and not taking ART (25% of PWH; mean CD4 325/μL) [35,36]; 71–73% of all PWH are virologically suppressed (80% of PWH in care) [37–39]. During the simulation, PWH experience monthly rates of disengagement from care and stopping ART (0.01–15%/month depending on adherence), and returning to care with ART reinitiation (3%/month after 12m of loss to follow-up) [2,40].

AAD incidence

For the general population, we derived age-/sex-stratified AAD incidence rates from the Adult Changes in Thought (ACT) study, a prospective cohort study of dementia among the general population in Seattle, WA, that uses prospective screening with adjudication of new dementia diagnoses by a multidisciplinary team [41]. We estimated that AAD monthly incidence rates were 1.8 times higher for PWH compared with the general US population [6].

Quality of life (QoL)

To incorporate health utilities that account for age- and dementia-associated QoL for the general population and PWH, we defined a sex-stratified baseline QoL. Then, we incorporated reductions in QoL due to age (in 5-year increments) and dementia. We stratified dementia QoL by disease stage (i.e., mild, moderate, and severe AAD), using marginal disutility values from the regression results of EQ-5D values taken from the Medical Expenditure Panel Survey, which are already adjusted for age, sex at birth, race/ethnicity, comorbidity, education, and income [42]. PWH experience an additional QoL decrement from chronic HIV and acute OIs (−0.036) [42].

Mortality

Three distinct sources of mortality are incorporated into the model: AAD-related (for people with AAD regardless of HIV status), non-HIV/non-AAD-related (for all people), HIV-related (for PWH only). We derived age-/sex-stratified AAD-associated and non-AAD-associated mortality from the Human Mortality Database 2019 and the Multiple Cause-of-Death Mortality Data from the National Bureau of Economic Research [43,44], which we applied to the general population and PWH with AAD. We also derived age-/sex-stratified non-HIV/non-AAD-related mortality for the general population [43,44].

To account for increased non-HIV/non-AAD-related mortality among PWH due to substance use, systemic racism, and poverty, among other structural barriers [32,44–46], we developed relative mortality ratios from the National Health and Nutrition Examination Survey (NHANES) to quantify independent associations of mortality with the major HIV acquisition risk categories compared with the general population [47,48]. We applied these relative mortality ratios to the age-/sex-stratified, non-HIV/non-AAD-related mortality rates, weighted by the distribution of the major HIV risk acquisition groups among PWH in the US [2]. Last, PWH also experience additional CD4-stratified HIV-related mortality, including from OIs [49].

Sensitivity and Scenario Analyses

We performed univariate sensitivity analyses on selected input parameters for the PWH cohorts given uncertainty in the natural history of AAD in PWH: AAD incidence, AAD progression rates, AAD-associated mortality, and AAD-associated quality-of-life. We also varied non-HIV/non-AAD-related mortality rates among PWH. Then, we examined scenarios of improved HIV clinical care: 1) no disengagement from care (i.e., all start in care with standard rates of virologic suppression and no loss to follow-up) and 2) 100% sustained virologic suppression among all PWH in care (i.e., perfect virologic suppression with standard rates of loss to follow-up). Each scenario decreases HIV-related mortality by increasing CD4 counts. We also assessed the potential impact of “premature aging” on PWH by incorporating an age-stratified forward shift in AAD incidence and non-HIV/non-AAD-related mortality by 5y (i.e., model inputs for AAD incidence and non-HIV/non-AAD-related mortality of 70y males were instead applied to 65y males) [50,51]. Last, we performed multivariate sensitivity analysis on the most influential parameters by varying simultaneously: 1) age-stratified AAD incidence rates and monthly probability of disengagement from HIV care, and 2) age-stratified AAD incidence rates and non-HIV-related mortality rates among PWH.

RESULTS

Base case

For 60-year-old-males, model-projected cumulative incidence of AAD would be 8.7%/22.1%/34.1% and 5.3%/15.9%/34.1% at 70 years, 80 years, and lifetime among PWH and in the general population, respectively (Table 2, Figure 1A). We projected a cumulative incidence of AAD for 60-year-old-females of 5.4%/16.3%/27.5% and 3.3%/13.3%/40.2% at 70 years, 80 years, and lifetime among PWH and in the general population (Table 2, Figure 1B).

Table 2.

Base case, sensitivity, and scenario analysis in a modeling analysis of AAD among PWH In the US: Projected life years, quality-adjusted life years, AAD cumulative incidence (10-year, 20-year, and lifetime).

Population AAD cumulative incidence
at 70y, %		 AAD cumulative incidence
at 80y, %		 Lifetime AAD cumulative incidence, % Life years Quality-adjusted life years
Males Females Males Females Males Females Males Females Males Females
Base case
 PWH 8.7 5.4 22.1 16.3 34.1 27.5 17.4 16.8 14.1 13.4
 General 5.3 3.3 15.9 13.3 34.1 40.2 21.7 24.7 18.4 20.2
Varying AAD in PWH
 Lower AAD incidence rate (1.6x) 7.8 4.8 20.0 14.7 31.7 25.4 17.4 16.8 14.1 13.4
 Higher AAD incidence rate (2.0x) 9.7 6.0 24.1 18.0 36.3 29.4 17.3 16.8 14.0 13.3
 5y premature aging 13.3 8.6 31.0 24.6 36.1 29.3 14.4 13.7 11.6 10.9
Varying non-HIV/non-AAD-related mortality in PWH
 Lower non-HIV/non-AAD-related mortality rate (M:1.1x; F:1.9x) 9.1 5.6 24.8 18.1 43.1 34.1 20.2 18.7 16.2 14.8
 Higher non-HIV/non-AAD-related mortality rate
 (M: 2.3x; F: 3.6x)		 8.3 5.2 18.9 14.4 25.7 21.9 14.6 14.9 12.0 11.9
Varying HIV-related parameters in PWH
 No disengagement from care 8.9 5.5 23.1 17.1 36.3 29.5 18.1 17.5 14.6 13.8
 100% virologic suppression among PWH engaged in care 8.8 5.4 22.5 16.7 35.0 28.3 17.6 17.0 14.3 13.6
Open in a new tab

Abbreviations: AAD, age-associated dementia; PWH, people with HIV.

Figure 1. Model-projected lifetime AAD cumulative incidence and survival among 60y males and females in the US: comparing people with HIV and people in the general US population.

Figure 1.

Open in a new tab

The model-projected lifetime AAD cumulative incidence is displayed for males (Panel A), and females (Panel B); the vertical lines show the AAD cumulative incidence at 10 years (red), 20 years (blue), and lifetime (black). Model-projected survival is shown for males (Panel C) and females (Panel D). The solid lines represent people with HIV, and the dashed lines represent the general US population.

AAD: age-associated dementia.

We projected life expectancy (unadjusted years) and quality-adjusted life years (QALYs) for 60y males with HIV to be 17.4 years (14.1 QALYs) compared with 21.7 years (18.4 QALYs) among males from the general US population (Table 2, Figure 1C). Among 60y females with HIV, we projected 16.8 years of life (13.4 QALYs) compared with 24.7 years (20.2 QALYs) among females from the general US population (Table 2, Figure 1D). These model-based estimates for life expectancy in the general population are consistent with published data [52].

Sensitivity and scenario analyses

AAD-associated parameters

Lifetime AAD cumulative incidence was substantially influenced by the estimated age-/sex-stratified AAD incidence rates among PWH. Applying the lower bound AAD incidence rate ratio (IRR) (1.6x) or upper bound AAD IRR (2.0x) for PWH compared with the base case would result in a range of lifetime AAD cumulative incidence (males: 31.7–36.3% versus 34.1%; females: 25.4–29.4% versus 27.5%) (Table 2; Figure 2A and 2B, yellow and orange squares). For males with HIV, lifetime AAD cumulative incidence would be higher than among males in the general population when applying the upper bound AAD IRR. However, lifetime AAD cumulative incidence remained lower among females with HIV than females in the general population, even at the highest estimated AAD incidence rates among PWH, given the greater risks of competing mortality among females with HIV (Figure 2D, yellow square). A range of values in other AAD-focused parameters had minimal influence on projected outcomes (Table 2).

Figure 2. Effects of varying AAD- and HIV-associated parameters on the lifetime AAD cumulative incidence and survival among males and females with HIV compared with the general US population.

Figure 2.

Open in a new tab

This figure shows the results of one-way sensitivity analyses and scenario analyses, varying HIV- and AAD-associated parameters on lifetime AAD cumulative incidence and survival. Panels A and B report the lifetime AAD cumulative incidence for males and females; Panels C and D report survival outcomes for males and females. The black dashed and solid lines represent the AAD cumulative incidence in the base case for the “general” and “PWH” cohorts, respectively. The yellow and orange square lines represent lower and higher AAD cumulative incidence rates when applying the lower (1.6x) and upper bounds (2.0x) of the AAD incidence rate ratio for PWH compared with the general population [6]. The green and purple circle lines represent the cumulative incidence of AAD when the relative mortality ratios were adjusted to the lower and upper bounds of the 95% confidence intervals (males, 1.1x and 1.9x; females, 2.3x and 3.6x) for the “PWH” cohort. The light blue diamond line represents lifetime AAD cumulative incidence if there was no disengagement from HIV care among PWH. The red triangle line represents the cumulative incidence of AAD when a 5 year forward-shift in both AAD incidence and non-HIV-related mortality were applied to capture the potential for premature aging among PWH.

AAD: age-associated dementia; PWH: people with HIV.

Non-HIV-/non-AAD-related mortality

Estimated non-HIV-/non-AAD-related mortality also had a major impact on AAD cumulative incidence. With lower non-HIV-/non-AAD-related mortality for PWH (Table 1), life expectancy would increase compared with the base case (males: 20.2y [16.2 QALYs] versus 17.4y [14.1 QALYs]; females: 18.7y [14.8 QALYs] versus 16.8y [13.4 QALYs]) (Table 2; Figure 2A and 2B, green circle). With lower non-HIV-/non-AAD-related mortality, AAD cumulative incidence for PWH would increase compared with the base case (males: 43.1% versus 34.1%; females 34.1% versus 27.5%); despite the increased life expectancy and AAD cumulative incidence, model-based projections for females with HIV would remain lower than for the general population (Table 2; Figure 2C and 2D, green circles). Increasing the rates of non-HIV-/non-AAD-related mortality among PWH would have the greatest effect on decreasing AAD cumulative incidence, life expectancy, and QALYs compared with the base case (Table 2; Figure 2, purple circles).

HIV-related parameters

Improving engagement in care among PWH would result in a higher lifetime cumulative incidence of AAD (males: 36.3% versus 34.1%; females: 29.5% versus 27.5%) given increased life expectancy compared with the base case (Table 2; Figure 2, blue diamonds). Eliminating disengagement from HIV care would increase life expectancy and AAD cumulative incidence more than improving virologic suppression to 100% among people already in care (Table 2). Changes to HIV-related parameters resulted in lifetime AAD cumulative incidence among PWH surpassing estimates among the general population for males but not females.

Premature aging scenario analysis

Simulating premature aging among PWH, we projected greater AAD cumulative incidence and lower life expectancy compared with the base case (Table 2; Figure 2A and 2B, red triangles). Model-projected AAD cumulative incidence at 70 and 80 years would be higher among males and females with HIV when accounting for premature aging (males: 70y, 13.3% and 80y, 31.0%; females: 70y, 8.6% and 80y, 24.6%) compared with the general population (Table 2; Figure 2A and 2B, red triangles), and life expectancy would remain lower (males: 14.4 [11.6 QALYs]; females: 13.7y [10.9 QALYs]) (Table 2; Figure 2C and 2D, red triangles). When accounting for premature aging, model-projected lifetime AAD cumulative incidence would be higher for PWH than for the general population among males (36.1% versus 34.1%) but would remain lower for PWH than for the general population among females (29.3% versus 40.2%).

Two-way sensitivity analyses

We examined the impact of changes in engagement in HIV care and AAD incidence rates on the lifetime cumulative incidence of AAD among people with HIV (Figure 3A). When people are more engaged in HIV care (i.e., lower probability of HIV-related mortality), we projected that lifetime AAD cumulative incidence would rise among PWH, especially as AAD incidence rates increase (bottom and right of Figure 3A). If disengagement from care was 5% or less over three years and AAD incidence rates among PWH were 1.6x the general population, or if disengagement from care was 20% or less at three years and AAD incidence rates were greater than 1.8x the general population (Figure 3A, top left panel), AAD cumulative incidence among males with HIV would surpass the general population. Among females with HIV, lifetime AAD cumulative incidence would be lower than in the general female population even with no disengagement from care and 2.2x AAD incidence rates, given higher non-HIV-related mortality estimated among females with HIV (Figure 3A, top right panel).

Figure 3. Results from two-way sensitivity analyses: Panel A) the effect of disengagement from HIV clinical care and AAD incidence rates and Panel B) the effect of non-HIV/non-AAD-related mortality and AAD incidence rates on lifetime AAD cumulative incidence among PWH.

Figure 3.

Open in a new tab

Panel A shows the results of a two-way sensitivity analysis varying the percent of males (top left panel) and females (top right panel) with HIV who are disengaged from HIV care at 3 years (y-axis) and AAD incidence rates (x-axis). The base case estimates for projected lifetime AAD cumulative incidence are marked with an “X” (PWH); more cumulative incidence of AAD will occur at higher AAD incidence rates (right) and lower disengagement from care (bottom), as shown in orange. Model-projected lifetime AAD cumulative incidence within the black box are greater than published estimates for males in the general US population. Published estimates of lifetime AAD cumulative incidence among females from the general US population is 40.2%, which is not shown on the figure because it is greater than model-projections for PWH even with a 0% disengagement from HIV care at 3 years and 2.2-fold increase in age-stratified AAD incidence rates. Panel B shows the results of a two-way sensitivity analysis varying non-HIV/non-AAD-related mortality RMRs and AAD incidence rates among males (bottom left panel) and females (bottom right panel) with HIV. The base case estimates for projected lifetime AAD cumulative incidence are marked with an “X” (PWH). A black box surrounds the model-projected lifetime AAD cumulative incidence that would be greater than published estimates for the general population. Lifetime AAD cumulative incidence increases at lower non-HIV-related mortality (bottom) and higher AAD incidence rates (right).

Abbreviations: AAD, age-associated dementias; PWH, people with HIV; RMR, relative mortality ratio.

We also examined the impact of changes in non-HIV-/non-AAD-related mortality and AAD incidence rates on the lifetime cumulative incidence of AAD among people with HIV (Figure 3B). We projected that lifetime AAD cumulative incidence would rise among PWH as non-HIV-/non-AAD-related mortality decreases and AAD incidence rates increase (bottom and right of Figure 3B). Lifetime AAD cumulative incidence among males with HIV would surpass the general population if non-HIV-related mortality was the same for PWH and the general population (RMR, 1.0) and AAD incidence rates among PWH were 1.4x the general population or if non-HIV-related mortality RMRs were 1.5 or less and AAD incidence was 2.0x the general population (Figure 3B, bottom left panel). A similar pattern was observed for females with HIV (Figure 3B, bottom right panel).

DISCUSSION

Using the previously validated CEPAC and AgeD-Pol simulation models together, we projected that 34.1% of males and 27.5% of females who are 60y and living with HIV would develop AAD over their lifetimes. Disparities in AAD cumulative incidence between people with and without HIV would increase later over a lifetime, reflecting the impact of higher competing risks of mortality among people with HIV. This trend is accentuated among females with HIV compared with males because females with HIV often experience a substantially higher risk of non-HIV-related mortality compared with females from the general population. We also found that parameters with a greater effect on life expectancy among people at 60y, such as non-HIV-related mortality and rates of engagement in HIV care, had a substantial influence on the cumulative incidence of AAD. Among dementia-associated parameters, age-/sex-stratified AAD incidence rates, which are known to be uncertain among people with HIV, substantially influenced lifetime AAD cumulative incidence.

Competing risks of mortality are key components of this model-based analysis. Shorter life expectancies among PWH than the general population are explained by the higher prevalence of smoking, substance use disorder, serious mental illness, and disadvantageous social determinants of health, as well as OIs that occur more frequently among PWH not on ART [20,52]. We found that lifetime AAD cumulative incidence was sensitive to these competing risks of mortality since PWH would be more likely to die at ages prior to the highest incidence of AAD [21–23,41]. Earlier initiation of less toxic, more effective ART regimens as per current guidelines could further reduce HIV-related mortality [54], as could efforts to improve non-HIV-related mortality such as tobacco cessation, statin use, and care for substance use disorder, among other initiatives. Most of this excess mortality was due to non-HIV-related mortality, given the smaller impact of improving engagement in care compared with reducing estimates of non-HIV-related mortality among PWH. We found that this effect was more substantial among females than males with HIV, given the demographics of females at highest risk for HIV acquisition [55–57], resulting in a lower model-projected lifetime AAD cumulative incidence among females with diagnosed HIV compared with females in the general population.

Even with increased non-HIV-related mortality compared with the general US population, over a quarter of PWH aged 60 years and older would develop AAD over their lifetimes in model projections. Because PWH have higher rates of tobacco use and increased risk of cardiovascular disease, they are likely to have a further increased risk of vascular and other related dementias [58,59]. One recent study showed that PWH have nearly double the AAD risk compared to people without HIV [6]. Accounting for this increased risk of AAD, we projected high cumulative AAD incidence among PWH despite increased competing mortality risks compared with the general population. We found that varying age-stratified AAD incidence rates or incorporating premature aging for PWH had a marked impact on the cumulative incidence of AAD but minimal impact on survival.

These results support a focus on further understanding the interplay between HIV and AAD, factors contributing to increased AAD risk among PWH, and the need for increased services for people aging with HIV. Improving engagement in care would reduce competing HIV-related mortality, which could, however, further increase the lifetime risk of developing AAD, unless interventions to reduce AAD risk are made available and accessible. Interventions to counter disadvantageous social determinants of health, reduce tobacco use, and treat substance use disorder are therefore essential to improve life expectancy and reduce the lifetime risk of AAD among people aging with HIV, such as has been investigated in the general population [60]. A published cost-effectiveness analysis showed that interventions aimed at lowering vascular risk factors, such as treating hypertension and smoking cessation, could be cost-effective in reducing dementia among the general population [61]. Similar analytic approaches are critical to study policies that can improve the health and lifespan of people living with HIV.

PWH often encounter structural barriers to clinical care. Caregiver services in the US are most often offered in traditional family structures with kinship networks as primary caregivers; many PWH may not be supported in traditional family structures [62,63]. In addition, population aging – due to an increase in the number of people 65 years and older and a decrease in the number of working-age people – will likely exacerbate this problem [64]. Further, national guidelines for the care of people with HIV do not include any specific guidance regarding the neurologic evaluation of people aging with HIV and offer no recommendations on best practices for cognitive impairment testing [54,65,66]. Additionally, many PWH experience stigma at facilities that care for older persons, where there might be less experience with HIV than traditional HIV-focused providers [67,68]. Our model-based results highlight the consideration needed when planning health systems support for people aging with HIV.

This analysis has several limitations. We focused on people living with diagnosed HIV as available estimates of dementia and HIV outcomes are limited to people already diagnosed with HIV. Estimates of AAD incidence and AAD-associated mortality among PWH are uncertain; we used the best available data regarding differences in AAD incidence for PWH compared with the general population. We varied these estimates in sensitivity and scenario analyses to provide a range of model projections and found that they converge on the single message of a rising cumulative AAD incidence in PWH that should inform healthcare planning. Available cohort data are disproportionately from White people; racial differences in AAD incidence and survival could affect model-projected outcomes. The past few years are notable for markedly increased non-HIV/non-AAD-related mortality in the US (e.g., COVID-19 pandemic, opiate crisis); if these trends continue, life expectancy could further decline among PWH, which would influence the cumulative incidence of AAD [69]. Finally, we intentionally do not attempt to isolate the incidence and outcomes of HAND in this analysis, given the lack of clear diagnostic criteria [70], although the increased risk of dementia diagnoses among PWH could include some diagnoses of HAND [6]. Mild and moderate cognitive impairment is evident in approximately 30–50% of PWH [71], which might not be captured in these model projections of AAD.

In summary, with HIV clinical care dramatically reducing HIV-related mortality in the United States, people with HIV are now at risk for developing age-associated dementia as they survive to older ages. It is critical to improve screening, diagnosis, and treatment of dementia among people aging with HIV. Differences in mortality risks and support structures for PWH should be considered when coordinating AAD and HIV prevention and mitigation efforts. This analysis provides insights to inform decision-makers and health systems planning for people aging with HIV.

Acknowledgements

We thank Ms. Yiqi Qian for technical assistance updating input parameters to 2019.

Funding

This work was supported by the National Institute of Allergy and Infectious Diseases [R01AI042006 (KAF); R01AI093269 (KPR); U01AI069918 (KNA)], the National Institute on Aging [R01AG069575 (EPH); R56AG074839 (KNA)], the National Institutes of Health [R01AG047975, R01AG026484, P50AG005134 (AV); K23MH115812, R01MH131194 (SM)], the JHU Center for the Advancement of Neurotherapeutics [JHU CAHN, P30 MH075673 (LR)], the Rappaport Fellowship (SM), the Steve and Deborah Gorlin MGH Research Scholars Award (KAF), and the MGH Jerome and Celia Reich Endowed Scholar Award (EPH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Massachusetts General Hospital.

Role of Funding Source

The funding sources had no role in the design, analysis, or interpretation of the study, the writing of the manuscript, or in the decision to submit the manuscript for publication.

Footnotes

Conflicts of Interest

All authors declare no conflicts of interest.

REFERENCES

  • 1.Trickey A, May MT, Vehreschild J-J, Obel N, Gill MJ, Crane HM, et al. Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV 2017; 4:e349–e356. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Estimated HIV incidence and prevalence in the United States, 2015–2019. Centers for Disease Control and Prevention; 2021. https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hiv-surveillance-supplemental-report-vol-26-1.pdf (accessed 24 Dec 2023).
  • 3.Schouten J, Wit FW, Stolte IG, Kootstra NA, van der Valk M, Geerlings SE, et al. Cross-sectional comparison of the prevalence of age-associated comorbidities and their risk factors between HIV-infected and uninfected individuals: the AGEhIV cohort study. Clin Infect Dis 2014; 59:1787–1797. [DOI] [PubMed] [Google Scholar]
  • 4.Hasse B, Ledergerber B, Furrer H, Battegay M, Hirschel B, Cavassini M, et al. Morbidity and aging in HIV-infected persons: the Swiss HIV cohort study. Clin Infect Dis 2011; 53:1130–1139. [DOI] [PubMed] [Google Scholar]
  • 5.Wong C, Gange SJ, Moore RD, Justice AC, Buchacz K, Abraham AG, et al. Multimorbidity among persons living with human immunodeficiency virus in the United States. Clin Infect Dis 2018; 66:1230–1238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Lam JO, Lee C, Gilsanz P, Hou CE, Leyden WA, Satre DD, et al. Comparison of dementia incidence and prevalence between individuals with and without HIV infection in primary care from 2000 to 2016. AIDS 2022; 36:437–445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Matthews KA, Xu W, Gaglioti AH, Holt JB, Croft JB, Mack D, et al. Racial and ethnic estimates of Alzheimer’s disease and related dementias in the United States (2015–2060) in adults aged ≥65 years. Alzheimers Dement 2019; 15:17–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Alzheimer’s Association. 2019. Alzheimer’s disease facts and figures. Alzheimers Dement 2019; 15:321–387. [Google Scholar]
  • 9.Corrada MM, Brookmeyer R, Paganini-Hill A, Berlau D, Kawas CH. Dementia incidence continues to increase with age in the oldest old the 90+ study. Ann Neurol 2010; 67:114–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Turner RS, Chadwick M, Horton WA, Simon GL, Jiang X, Esposito G. An individual with human immunodeficiency virus, dementia, and central nervous system amyloid deposition. Alzheimers Dement 2016; 4:1–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Milanini B, Valcour V. Differentiating HIV-associated neurocognitive disorders from Alzheimer’s disease: an emerging issue in geriatric neuroHIV. Curr HIV/AIDS Rep 2017; 14:123–132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Rubin LH, Sundermann EE, Moore DJ. The current understanding of overlap between characteristics of HIV-associated neurocognitive disorders and Alzheimer’s disease. J Neurovirol 2019; 25:661–672. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Lam JO, Hou CE, Hojilla JC, Anderson AN, Gilsanz P, Alexeeff SE, et al. Comparison of dementia risk after age 50 between individuals with and without HIV infection. AIDS 2021; 35:821–828. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Clifford DB, Fagan AM, Holtzman DM, Morris JC, Teshome M, Shah AR, et al. CSF biomarkers of Alzheimer disease in HIV-associated neurologic disease. Neurology 2009; 73:1982–1987. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Stern AL, Ghura S, Gannon PJ, Akay-Espinoza C, Phan JM, Yee AC, et al. BACE1 mediates HIV-associated and excitotoxic neuronal damage through an APP-dependent mechanism. J Neurosci 2018; 38:4288–4300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kamat A, Lyons JL, Misra V, Uno H, Morgello S, Singer EJ, et al. Monocyte activation markers in cerebrospinal fluid associated with impaired neurocognitive testing in advanced HIV infection. J Acquir Immune Defic Syndr 2012; 60:234–243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Lyons JL, Uno H, Ancuta P, Kamat A, Moore DJ, Singer EJ, et al. Plasma sCD14 is a biomarker associated with impaired neurocognitive test performance in attention and learning domains in HIV infection. J Acquir Immune Defic Syndr 2011; 57:371–379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Lorius N, Locascio JJ, Rentz DM, Johnson KA, Sperling RA, Viswanathan A, et al. Vascular disease and risk factors are associated with cognitive decline in the Alzheimer disease spectrum. Alzheimer Dis 2015; 29:18–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Viswanathan A, Greenberg SM, Scheltens P. Role of vascular disease in Alzheimer-like progressive cognitive impairment. Stroke 2016; 47:577–580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Mdodo R, Frazier EL, Dube SR, Mattson CL, Sutton MY, Brooks JT, et al. Cigarette smoking prevalence among adults with HIV compared with the general adult population in the United States: cross-sectional surveys. Ann Intern Med 2015; 162:335–344. [DOI] [PubMed] [Google Scholar]
  • 21.Wright EJ, Grund B, Cysique LA, Robertson KR, Brew BJ, Collins G, et al. Factors associated with neurocognitive test performance at baseline: a substudy of the INSIGHT Strategic Timing of AntiRetroviral Treatment (START) trial. HIV Med 2015; 16 Suppl 1:97–108. [DOI] [PubMed] [Google Scholar]
  • 22.Chow FC, Regan S, Feske S, Meigs JB, Grinspoon SK, Triant VA. Comparison of ischemic stroke incidence in HIV-infected and non-HIV-infected patients in a US health care system. J Acquir Immune Defic Syndr 2012; 60:351–358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Chow FC, Regan S, Zanni MV, Looby SE, Bushnell CD, Meigs JB, et al. Elevated ischemic stroke risk among women living with HIV infection. AIDS 2018; 32:59–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Hyle EP, Foote JH, Mukerji S, Althoff K, Sax P, Reddy KP, et al. Age-associated dementia among older people with HIV in the US: a model based-analysis. 2020. [Google Scholar]
  • 25.Hyle EP, Foote JHA, Shebl FM, Qian Y, Reddy KP, Mukerji SS, et al. Development and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe. BMJ Open 2022; 12:e056546. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Brookmeyer R, Abdalla N, Kawas CH, Corrada MM. Forecasting the prevalence of preclinical and clinical Alzheimer’s disease in the United States. Alzheimers Dement 2018; 14:121–129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Johnson E, Brookmeyer R, Ziegler-Graham K. Modeling the effect of Alzheimer’s disease on mortality. Int J Biostat 2007; 3:Article 13. [DOI] [PubMed] [Google Scholar]
  • 28.Brookmeyer R, Evans DA, Hebert L, Langa KM, Heeringa SG, Plassman BL, et al. National estimates of the prevalence of Alzheimer’s disease in the United States. Alzheimers Dement 2011; 7:61–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Freedberg KA, Losina E, Weinstein MC, Paltiel AD, Cohen CJ, Seage GR, et al. The cost effectiveness of combination antiretroviral therapy for HIV disease. N Engl J Med 2001; 344:824–831. [DOI] [PubMed] [Google Scholar]
  • 30.Borre ED, Hyle EP, Paltiel AD, Neilan AM, Sax PE, Freedberg KA, et al. The clinical and economic impact of attaining national HIV/AIDS strategy treatment targets in the United States. J Infect Dis 2017; 216:798–807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Losina E, Hyle EP, Borre ED, Linas BP, Sax PE, Weinstein MC, et al. Projecting 10-year, 20-year, and lifetime risks of cardiovascular disease in persons living with Human Immunodeficiency Virus in the United States. Clin Infect Dis 2017; 65:1266–1271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Reddy KP, Kong CY, Hyle EP, Baggett TP, Huang M, Parker RA, et al. Lung cancer mortality associated with smoking and smoking cessation among people living with HIV in the United States. JAMA Intern Med 2017; 177:1613–1621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Losina E, Schackman BR, Sadownik SN, Gebo KA, Walensky RP, Chiosi JJ, et al. Racial and sex disparities in life expectancy losses among HIV-infected persons in the United States: impact of risk behavior, late initiation, and early discontinuation of antiretroviral therapy. Clin Infect Dis 2009; 49:1570–1578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Shebl FM, Qian Y, Foote JHA, Wattananimitgul N, Reddy KP, Neilan AM, et al. The association between all-cause mortality and HIV acquisition risk groups in the United States, 2001–2014. PLoS ONE 2023; 18:e0290113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Buchacz K, Frazier EL, Hall HI, Hart R, Huang P, Franklin D, et al. A matter of perspective: comparison of the characteristics of persons with HIV infection in the United States from the HIV Outpatient Study, Medical Monitoring Project, and National HIV Surveillance System. Open AIDS J 2015; 9:123–133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Althoff KN, Rebeiro PF, Hanna DB, Padgett D, Horberg MA, Grinsztejn B, et al. A picture is worth a thousand words: maps of HIV indicators to inform research, programs, and policy from NA-ACCORD and CCASAnet clinical cohorts. J Int AIDS Soc 2016; 19:20707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.HIV by Age: Viral Suppression. Cent. Dis. Control Prev. 2022.https://www.cdc.gov/hiv/group/age/viral-suppression.html (accessed 15 Dec 2023).
  • 38.Raffi F, Rachlis A, Stellbrink HJ, Hardy WD, Torti C, Orkin C, et al. Once-daily dolutegravir versus raltegravir in antiretroviral-naive adults with HIV-1 infection: 48 week results from the randomised, double-blind, non-inferiority SPRING-2 study. Lancet 2013; 381:735–43. [DOI] [PubMed] [Google Scholar]
  • 39.Walmsley SL, Antela A, Clumeck N, Duiculescu D, Eberhard A, Gutierrez F, et al. Dolutegravir plus abacavir-lamivudine for the treatment of HIV-1 infection. N Engl J Med 2013; 369:1807–18. [DOI] [PubMed] [Google Scholar]
  • 40.Rebeiro PF, Gange SJ, Horberg MA, Abraham AG, Napravnik S, Samji H, et al. Geographic variations in retention in care among HIV-infected adults in the United States. PLoS One 2016; 11:e0146119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Tom SE, Hubbard RA, Crane PK, Haneuse SJ, Bowen J, McCormick WC, et al. Characterization of dementia and Alzheimer’s disease in an older population: updated incidence and life expectancy with and without dementia. Am J Public Health 2015; 105:408–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Sullivan PW, Lawrence WF, Ghushchyan V. A national catalog of preference-based scores for chronic conditions in the United States. Med Care 2005; 43:736–749. [DOI] [PubMed] [Google Scholar]
  • 43.University of California, Berkeley (USA), Max Planck Institute for Demographic Research (Germany). Human Mortality Database. 2019.https://www.mortality.org/ (accessed 15 Dec 2023).
  • 44.National Bureau of Economic Research. Mortality data—Vital statistics NCHS multiple cause of death data, 1959–2019. https://www.nber.org/data/vital-statistics-mortality-data-multiple-cause-of-death.html (accessed 15 Dec 2023).
  • 45.Smith CJ, Ryom L, Weber R, Morlat P, Pradier C, Reiss P, et al. Trends in underlying causes of death in people with HIV from 1999 to 2011 (D:A:D): a multicohort collaboration. Lancet 2014; 384:241–248. [DOI] [PubMed] [Google Scholar]
  • 46.Hutton HE, McCaul ME, Chander G, Jenckes MW, Nollen C, Sharp VL, et al. Alcohol use, anal sex, and other risky sexual behaviors among HIV-infected women and men. AIDS Behav 2013; 17:1694–1704. [DOI] [PubMed] [Google Scholar]
  • 47.Ingle SM, May MT, Gill MJ, Mugavero MJ, Lewden C, Abgrall S, et al. Impact of risk factors for specific causes of death in the first and subsequent years of antiretroviral therapy among HIV-infected patients. Clin Infect Dis 2014; 59:287–297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey Data (NHANES), 2001–2014. https://wwwn.cdc.gov/nchs/nhanes/default.aspx (accessed 15 Dec 2023).
  • 49.Hyle EP, Kasaie P, Schwamm E, Stewart C, Humes E, Reddy KP, et al. A growing number of men who have sex with men aging with HIV (2021–2031): a comparison of two microsimulation models. J Infect Dis 2023; 227:412–422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Akusjärvi SS, Neogi U. Biological aging in people living with HIV on successful antiretroviral therapy: do they age faster? Curr HIV/AIDS Rep Published Online First: 25 January 2023. doi: 10.1007/s11904-023-00646-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Aung HL, Aghvinian M, Gouse H, Robbins RN, Brew BJ, Mao L, et al. Is there any evidence of premature, accentuated and accelerated aging effects on neurocognition in people living with HIV? A systematic review. AIDS Behav 2021; 25:917–960. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Arias E, Xu J. United States Life Tables, 2019. Centers for Disease Control and Prevention; 2022. [PubMed] [Google Scholar]
  • 53.Bosh KA, Johnson AS, Hernandez AL, Prejean J, Taylor J, Wingard R, et al. Vital signs: deaths among persons with diagnosed HIV infection, United States, 2010–2018. MMWR Morb Mortal Wkly Rep 2020; 69:1717–1724. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in adults and adolescents living with HIV. Department of Health and Human; Serviceshttps://clinicalinfo.hiv.gov/en/guidelines/hiv-clinical-guidelines-adult-and-adolescent-arv/introduction?view=full (accessed 15 Dec 2023). [Google Scholar]
  • 55.Sundermann EE, Heaton RK, Pasipanodya E, Moore RC, Paolillo EW, Rubin LH, et al. Sex differences in HIV-associated cognitive impairment. AIDS 2018; 32:2719–2726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Pellegrino RA, Rebeiro PF, Turner M, Davidson A, Best N, Shaffernocker C, et al. Sex and race disparities in mortality and years of potential life lost among people with hiv: a 21-year observational cohort study. Open Forum Infect Dis 2022; 10:ofac678. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Women and HIV in the United States. Kais. Fam. Found. 2020.https://www.kff.org/hivaids/fact-sheet/women-and-hivaids-in-the-united-states/ (accessed 3 Dec 2023).
  • 58.Gutierrez J, Albuquerque ALA, Falzon L. HIV infection as vascular risk: a systematic review of the literature and meta-analysis. PLoS ONE 2017; 12:e0176686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Asfar T, Perez A, Shipman P, Carrico AW, Lee DJ, Alcaide ML, et al. National estimates of prevalence, time-trend, and correlates of smoking in US people living with HIV (NHANES1999–2016). Nicotine Tob Res 2021; 23:1308–1317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Yaffe K, Vittinghoff E, Dublin S, Peltz CB, Fleckenstein LE, Rosenberg DE, et al. Effect of personalized risk-reduction strategies on cognition and dementia risk profile among older adults: the SMARRT randomized clinical trial. JAMA Intern Med 2023; :e236279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Mukadam N, Anderson R, Knapp M, Wittenberg R, Karagiannidou M, Costafreda SG, et al. Effective interventions for potentially modifiable risk factors for late-onset dementia: a costs and cost-effectiveness modelling study. Lancet Healthy Longev 2020; 1:e13–e20. [DOI] [PubMed] [Google Scholar]
  • 62.Belsey MA. AIDS and the family: Policy options for a crisis in family capital. U. N. Dep. Econ. Soc. Aff. 2005.https://www.un.org/esa/socdev/family/Publications/belsey/FINAL%20REPORT%20-%20BELSEY’S%20HIV%20REPORT%20(PDF).pdf (accessed 15 Dec 2023).
  • 63.Hudson P, Morrison RS, Schulz R, Brody AA, Dahlin C, Kelly K, et al. Improving Support for Family Caregivers of People with a Serious Illness in the United States: Strategic Agenda and Call to Action. Palliat Med Rep 2020; 1:6–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Alzheimer’s Association. 2022. Alzheimer’s disease facts and figures. Alzheimers Dement 2022; 18:700–789. [DOI] [PubMed] [Google Scholar]
  • 65.Gandhi RT, Bedimo R, Hoy JF, Landovitz RJ, Smith DM, Eaton EF, et al. Antiretroviral drugs for treatment and prevention of HIV infection in adults: 2022 recommendations of the international antiviral society-USA panel. JAMA 2023; 329:63–84. [DOI] [PubMed] [Google Scholar]
  • 66.Thompson MA, Horberg MA, Agwu AL, Colasanti JA, Jain MK, Short WR, et al. Primary care guidance for persons with human immunodeficiency virus: 2020 update by the HIV medicine association of the Infectious Diseases Society of America. Clin Infect Dis 2021; 73:e3572–e3605. [DOI] [PubMed] [Google Scholar]
  • 67.Relf MV, Pan W, Edmonds A, Ramirez C, Amarasekara S, Adimora AA. Discrimination, medical distrust, stigma, depressive symptoms, antiretroviral medication adherence, engagement in care and quality of life among women living with HIV in North Carolina: a mediated structural equation model. J Acquir Immune Defic Syndr 1999 2019; 81:328–335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Brown MJ, Adeagbo O. HIV and aging: double stigma. Curr Epidemiol Rep 2021; 8:72–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Life Expectancy in the U.S. Dropped for the Second Year in a Row in 2021. Cent. Dis. Control Prev. Natl. Cent. Health Stat. 2022.https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2022/20220831.htm (accessed 15 Dec 2023).
  • 70.Nightingale S, Ances B, Cinque P, Dravid A, Dreyer AJ, Gisslén M, et al. Cognitive impairment in people living with HIV: consensus recommendations for a new approach. Nat Rev Neurol 2023; 19:424–433. [DOI] [PubMed] [Google Scholar]
  • 71.UCSF Weill Institute for Neurosciences Memory and Aging Center. A healthcare provider’s guide to HIV-associated neurocognitive disorder (HAND): Diagnosis, pharmacologic management, non-pharmacologic management, and other considerations. ; 2017. [Google Scholar]
  • 72.Knopman DS, Petersen RC, Cha RH, Edland SD, Rocca WA. Incidence and causes of nondegenerative nonvascular dementia: a population-based study. Arch Neurol 2006; 63:218–221. [DOI] [PubMed] [Google Scholar]
  • 73.Prince M, Wimo A, Guerchet M, Ali G-C, Wu Y-T, Prina M. World Alzheimer report 2015. The global impact of dementia: an analysis of prevalence, incidence, cost and trends. London, UK: Alzheimer’s Disease International; 2015. https://www.alz.co.uk/research/worldalzheimerreport2015summary.pdf (accessed 15 Dec 2023). [Google Scholar]
  • 74.Neumann PJ, Araki SS, Arcelus A, Longo A, Papadopoulos G, Kosik KS, et al. Measuring Alzheimer’s disease progression with transition probabilities: estimates from CERAD. Neurology 2001; 57:957–964. [DOI] [PubMed] [Google Scholar]
  • 75.Davis M, O Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer’s disease progression rates from normal cognition through mild cognitive impairment and stages of dementia. Curr Alzheimer Res 2018; 15:777–788. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76.The HIV-CAUSAL Collaboration. The effect of combined antiretroviral therapy on the overall mortality of HIV-infected individuals. AIDS 2010; 24:123–137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77.Engels EA, Yanik EL, Wheeler W, Gill MJ, Shiels MS, Dubrow R, et al. Cancer-attributable mortality among people with treated human immunodeficiency virus infection in North America. Clin Infect Dis 2017; 65:636–643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.National Population by Characteristics: 2010–2019. US Census Bur. https://www.census.gov/data/tables/time-series/demo/popest/2010s-national-detail.html (accessed 17 Dec 2023).
  • 79.Atlas Plus, National Center for HIV, Viral Hepatitis, STD, and TB Prevention (NCHHSTP). 2021.https://gis.cdc.gov/grasp/nchhstpatlas/main.html (accessed 15 Dec 2023). [Google Scholar]
  • 80.Hessol NA, Kalinowski A, Benning L, Mullen J, Young M, Palella F, et al. Mortality among participants in the Multicenter AIDS Cohort Study and the Women’s Interagency HIV Study. Clin Infect Dis 2007; 44:287–294. [DOI] [PubMed] [Google Scholar]

RESOURCES