AIDS Behav DOI 10.1007/s10461-016-1514-7
ORIGINAL PAPER
Food Insecurity Is Associated with Cognitive Deficits Among HIV-Positive, But Not HIV-Negative, Individuals in a United States Sample Andre´a L. Hobkirk1,2
•
Sheri L. Towe1,2 • Puja Patel1 • Christina S. Meade1,2
Ó Springer Science+Business Media New York 2016
Abstract People living with HIV/AIDS (PLWHA) in the United States (US) have disproportionately high rates of food insecurity (FI). In the general population, FI has been associated with cognitive impairment among older adults and may exacerbate HIV-associated neurocognitive disorders. The current study assessed the effects of FI and HIV infection on the neuropsychological performance of 61 HIV-positive and 36 HIV-negative adults in the US. While the main effects were minimal, the interactive effects revealed that FI was related to deficits in speed of information processing, learning, memory, motor function, and overall cognitive impairment for the HIV-positive group, but not the HIV-negative group. The interactive effects remained after controlling for relevant sociodemographic characteristics. Although bidirectional associations cannot be ruled out in a cross-sectional study, the results suggest that FI may contribute to cognitive impairment among HIV-positive adults in the US. Given the high rates of socioeconomic disadvantage among PLWHA in the US, addressing FI as part of routine clinical care may be warranted. Keywords HIV/AIDS Food insecurity Cognitive Neuropsychology Nutrition
& Andre´a L. Hobkirk
[email protected] 1
Duke Global Health Institute, Duke University, 333, Trent Hall, 310 Trent Drive, Box 90519, Durham, NC 27708, USA
2
Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Introduction In the United States (US), HIV/AIDS is increasingly becoming an epidemic of the socially and economically marginalized [1–3]. From 2005 to 2009, mortality rates among people living with HIV/AIDS (PLWHA) were over three times higher for individuals living in low socioeconomic conditions compared to those in high socioeconomic conditions [2]. A complex set of individual, social, and systemic factors contribute to these disparities, including stigma and discrimination, economic hardship, social violence, and legal persecution [4–6]. Food insecurity (FI), defined as a lack of money or resources to consistently secure sufficient quantities of safe, nutritious food, is a common correlate of socioeconomic disadvantage [7]. An estimated 24–49 % of HIV-positive individuals in the US report experiencing FI [8, 9]. This rate is much higher than the estimated 14 % in the general population [10]. Among PLWHA, FI has been associated with higher rates of HIV transmission and poor clinical outcomes, including unsuppressed viral load, low CD4 counts, lower antiretroviral therapy (ART) adherence, and wasting [11–17]. Additionally, FI has been linked to a 50 % higher likelihood of death among PLWHA [13]. FI and HIV infection occurr in a vicious cycle, where the incidence and severity of one fuels the other through both biological and behavioral pathways [18, 19]. HIV is associated with functional impairments, reduced income, and loss of employment, which may lead to FI [18, 20]. FI is intertwined with other individual and socioeconomic factors that may contribute to poor HIV disease management by interfering with medication adherence and HIV care, including substance use, depression, lower educational attainment, and unstable housing [8, 9, 12–14, 21, 22]. In addition to behavioral and socioeconomic
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pathways, FI may impact HIV outcomes by interacting with HIV-related biological changes. HIV taxes the body’s metabolic and immune systems, making it critical for people living with HIV to maintain proper nutrition in order to fight off opportunistic infections, facilitate the efficacy of ART, and avoid HIV-associated wasting [23–25]. Despite the body’s need for more nutrients, the gastrointestinal symptoms of HIV make it more difficult to consume and digest food. In addition, HIV contributes to poor appetite and malabsorption [26]. Given the increased need for energy intake coupled with the gastrointestinal symptoms associated with HIV, PLWHA may be particularly susceptible to adverse health outcomes caused by FI. HIV also causes damage to the central nervous system. After passing through the blood–brain-barrier via cell-free virus and infected peripheral cells, HIV promotes the production of viral proteins and inflammatory cells that damage neurons and their supporting glia [27]. This neurodegeneration has been associated with cognitive impairment [28–32]. An estimated 50 % of all adults living with HIV experience some degree of cognitive impairment, with deficits commonly occurring in learning, memory, executive function, and attention [33–35]. The adequate consumption of vitamins and nutrients is crucial for maintaining brain health across the lifespan, and vitamin deficiencies have been linked with specific types of neurocognitive impairment [38, 39]. Thus, FI may exacerbate the neural damage caused by HIV-infection, leading to more severe impacts on cognitive function. Alternatively, HIV-associated cognitive impairment may contribute to FI through functional impairments [36]. Neuropsychological impairment among HIV-positive adults has been associated with functional impairments in managing finances, cooking, and shopping, as well as medication adherence [36, 37]. Among the general population, FI has been associated with reduced cognitive performance and lower academic achievement among children and adolescents and cognitive impairment among older ethnic minorities [40–43]. In the Third National Health and Nutrition Examination Survey (NHANES) of over 5000 US children, FI was associated with lower IQ scores, as well as poorer academic achievement and more psychosocial difficulties than children who were food secure [40]. For older Puerto Ricans living in the Northeastern US, FI was associated with worse mental status and executive function, but not memory or attention [41]. The effects of FI were stronger for older participants compared to younger ones, which suggests that FI may further exacerbate pre-existing vulnerabilities to cognitive impairment. Despite the high rates of FI and potential for cognitive impairment among PLWHA, the interaction of HIV and FI
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on cognitive function has not been investigated. The current study aimed to examine the independent and interactive effects of FI and HIV infection among demographically similar HIV-positive and negative adults from the southeastern US. We hypothesized that food insecurity would be associated with greater cognitive impairment and that this effect would be stronger among the HIV-positive group compared to the HIV-negative group.
Methods Participants The sample included 61 HIV-positive and 36 HIV-negative adults. HIV positive status was confirmed through medical records, and participants without a confirmed diagnosis of HIV completed an OraQuickÓ rapid HIV test to confirm their HIV-negative status. The sample was taken from a larger study assessing the effects of HIV and cocaine use on neurocognitive function (see [35] for results). The current sample included only non-drug users to avoid any confounding effects drug use may have on cognitive function [44]. Exclusion criteria were: (1) current alcohol or marijuana dependence; (2) for illicit drugs other than marijuana, any lifetime substance use disorder, history of regular use, or any use in the past year; (3) English nonfluency or illiteracy; (4) \9th grade education; (5) documented severe learning disability with co-occurring functional impairment; (6) pregnancy; (7) serious neurological disorders; (8) acute opportunistic brain infections or history of brain infections without return to normal function (e.g., cryptococcal meningitis); (9) severe head trauma with evidence of functional decline; and (10) severe mental illness (e.g., schizophrenia, bipolar I disorder). Exclusion criteria were selected to eliminate conditions that may confound neuropsychological assessment [45]. Procedures Participants were recruited from the Raleigh–Durham area between May 2010 and May 2014 through advertisements at community-based organizations and infectious diseases clinics. Preliminary eligibility was determined through a telephone screen, and interested eligible callers were invited for a comprehensive in-person eligibility screening. At the in-person screening, participants provided written informed consent, completed a breathalyzer to ensure sobriety, provided urine samples for drug and pregnancy screening, and completed an in-person interview and computerized survey. Eligible participants returned on a separate day to complete a neuropsychological testing
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battery and a computerized survey. Participants were compensated $35 for the screening visit and $65 for the neuropsychological testing visit. All procedures were approved by the institutional review boards at Duke University and University of North Carolina.
(2)
Measures Screening Measures The Addiction Severity Index-Lite (ASI) assessed socioeconomic factors (e.g., income, education, living arrangements), medical and psychiatric history, and substance use history [46]. Module E of the Structured Clinical Interview for DSM-IV-TR identified current and past substance use disorders [47], and the timeline follow-back procedure was used to assess frequency of substance use in the past 90 days [48, 49]. Psychiatric disorders were assessed with the Mini International Neuropsychiatric Interview [50]. Participants with a confirmed HIV diagnosis provided information on their HIV care and clinical outcomes, such as history of CD4 cell counts, viral load, and history of opportunistic infections [51]. At the screening visit participants provided a release for their medical records to corroborate self-reported medical history and HIV disease status. Participants rated their ART adherence in the past 4 weeks using a visual analog scale ranging from 0 to 100 % [52]. Premorbid verbal IQ was measured using the Wechsler Test of Adult Reading (WTAR) [53]. Food Insecurity FI in the past year was assessed on the computer-assisted survey. Participants responded yes or no to seven items adapted from the Household Food Insecurity Access Scale [54] that have been used in prior research with HIV-positive participants [12]. The items are described in Table 1. The number of FI items endorsed were summed to create a total score ranging from 0 to 7. FI was then dichotomized as no food insecurity (NFI), if no items were endorsed, and FI, if at least one item was endorsed. Neuropsychological Testing Battery Neuropsychological performance was measured with a 60-min battery of paper-and-pencil assessments administered by trained psychometrists. The neuropsychological battery included: (1)
Speed of information processing: Wechsler Adult Intelligence Scale-III (WAIS-III) Digit Symbol
(3)
(4)
(5)
(6)
(7)
subtest—total number correct [55]; and Trail Making Test Part A—number of seconds to completion [56]. Learning (immediate recall): Hopkins Verbal Learning Test-Revised (HVLT- R)—total number of words recalled on trials 1–3 [57]; and Brief Visuospatial Memory Test-Revised (BVMT-R)—total score for figures correctly recalled on trials 1–3 [58]. Memory (delayed recall): HVLT-R—number of words recalled on trial 4 [57]; and BVMT-R–total score for figures correctly recalled on trial 4 [58]. Executive functioning: Stroop Color and Word Test interference score—difference between actual and predicted score on the Color-Word trial [59]; and Trail Making Test Part B—number of seconds to completion [56]. Verbal fluency: FAS letter fluency—number of words generated; and category fluency—number of animals generated [60]. Attention: Paced Auditory Serial Addition Task100—number correct [61]; and NAB Digits Forward/Digits Backward Test—number correct [62]. Motor skills: Grooved Pegboard Test dominant and non-dominant hand—number of seconds to completion [63].
Raw scores for each neuropsychological test were transformed to demographically corrected T-scores using recent published norms (M = 50, SD = 10) [55, 61, 62, 64, 65]. In accordance with the published norms, race was divided into two categories, Caucasian and African American. One participant who identified as Native American and another who identified as White Hispanic were categorized as Caucasian. Each case was scored by two research assistants independently and discrepancies were resolved by a third research assistant who re-scored the discrepant test. Deficit scores for each test were calculated on a 0–5 rating where T C 40 = 0 (no impairment), 35–39 = 1, 30–34 = 2, 25–29 = 3, 20–24 = 4, and \20 = 5. Domain deficit scores were computed by averaging the deficit ratings for the tests in each domain. A Global Deficit Score (GDS) was computed by averaging the deficit scores for all domains. Impairment is defined as a domain deficit score [0.5, and a GDS C0.5 [66]. Data Analysis Descriptive statistics were used to characterize the sample. Chi square analyses compared the proportion of participants reporting FI across the HIV-positive and HIV-negative groups. T-tests were used to compare neuropsychological deficit scores across HIV-positive and
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AIDS Behav Table 1 Sample characteristics HIV-positive (n = 61) N (%) or M (SD)
HIV-negative (n = 36) N (%) or M (SD)
Statistic
Sociodemographic characteristics Female
17 (28 %)
17 (47 %)
v2(1) = 3.73
African American
53 (87 %)
30 (83 %)
v2(1) = 0.23
Age in years
46.30 (10.73)
44.44 (12.02)
t(67) = 0.76
Years of education
13.87 (2.42)
13.86 (2.07)
t(83) = 0.02
Gay/bisexual
35 (57 %)
3 (8 %)
v2(1) = 22.85**
8 (13 %) 1011 (1114)
6 (17 %) 1300 (1861)
v2(1) = 0.23 U(1) = 1037
Ever homeless
13 (21 %)
4 (11 %)
v2(1) = 1.63
Health insurance
37 (61 %)
20 (56 %)
v2(1) = 0.24
6 (10 %)
0 (0 %)
v2(1) = 3.77
Married Monthly incomea
Hepatitis C Premorbid verbal IQ
87.18 (17.94)
96.39 (16.75)
t(78) = 2.55*
Worried food would run out
21 (34 %)
7 (19 %)
v2(1) = 2.48
Unable to afford balanced meals
26 (43 %)
10 (28 %)
v2(1) = 2.14
Chose between buying medicine or food
12 (20 %)
6 (17 %)
v2(1) = 0.14
Cut the size of meals or skipped meals
18 (30 %)
10 (28 %)
v2(1) = 0.03
Ate less than needed
19 (31 %)
10 (28 %)
v2(1) = 0.12
Hungry, but couldn’t eat because of a lack of food
15 (25 %)
4 (11 %)
v2(1) = 2.61
8 (13 %)
3 (8 %)
v2(1) = 0.52
Food insecurity
Didn’t eat for a whole day because of a lack of food Average number of items endorsed Any FI items endorsed Cognitive deficit scores
1.95 (2.52) 30 (49 %)
1.39 (2.10) 16 (44 %)
t(84) = 1.18 v2(1) = 0.20
Information processing
0.26 (0.51)
0.15 (0.34)
t(93) = 1.32
Learning
1.31 (1.18)
1.18 (1.22)
t(72) = 0.52
Memory
1.30 (1.27)
0.99 (1.25)
t(74) = 1.20
Executive functioning
0.26 (0.45)
0.15 (0.44)
t(75) = 1.16
Verbal fluency
0.31 (0.46)
0.14 (0.22)
t(92) = 2.33*
Attention
0.63 (0.73)
0.31 (0.50)
t(93) = 2.53*
Motor skills
0.38 (0.95)
0.46 (1.00)
t(70) = 0.39
Global
0.64 (0.60)
0.48 (0.47)
t(87) = 1.39
* p \ .05; ** p \ .001 a
Median (interquartile range), Mann–Whitney U test
HIV-negative participants, and the food secure and insecure participants. Given the difference in sample size across the HIV groups, equal variances were not assumed. ANCOVA was used to assess the independent and interactive effects of HIV status and FI on deficit scores while controlling for premorbid verbal IQ, hepatitis C infection, income in the past 30 days, any lifetime history of homelessness, and current health insurance. To probe the significant interactions, the least squares difference between the marginal means of the domain deficit scores were contrasted across participants with and without FI among the HIV-positive and HIV-negative groups separately. To examine the role of HIV disease characteristics on FI among the HIV-positive group, post hoc Chi square
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analyses and ANOVAs examined the association between FI and HIV disease variables. In addition, post hoc ANCOVAs were conducted to compare domain deficit scores for the food secure and insecure HIV? positive groups while controlling for HIV disease characteristics, including viral suppression, nadir CD4 count, years since HIV diagnosis, and hepatitis C infection.
Results Sample characteristics are described in Table 1. The HIVpositive group had a significantly larger proportion of participants who identified as gay or bisexual, and
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significantly lower premorbid verbal IQ despite equivalent years of education. The HIV-positive and HIV-negative groups had FI total scores ranging from 0 to 7 and similar proportions of FI, with 49 % of the HIV-positive group and 44 % of the HIV-negative group endorsing at least one FI item. For the total sample, the number of items endorsed on the FI scale was significantly negatively correlated with income (r = -0.23, p = .023) and was significantly higher for those participants without health insurance [t (95) = 2.72, p = .008]. The HIV-positive participants were diagnosed with HIV for an average of 11.21 years (SD = 7.75) and had an average nadir CD4 T cell count of 231.42 (SD = 203.62) and recent CD4 T-cell count of 551.27 (SD = 286.53). Approximately 75 % of the group had an undetectable viral load. The 15 participants with a detectable viral load had a median viral count of 257 copies/mL (IQR = 67,280). All participants except two were currently on ART, 80 % of participants on ART had been on their current regimen for 12 months or longer, and more than 80 % reported excellent adherence (C90 % adherence). Half of the sample (53 %) had a lifetime AIDS diagnosis and six participants had hepatitis C infection (10 %). The HIV-positive group had significantly higher deficit scores than the HIV-negative group in verbal fluency and attention, but there were no significant group differences on speed of information processing, learning, memory, motor function, or GDS (see Table 1). Across all participants, deficit scores were higher for the participants who reported FI than those who did not for the domain of speed of information processing (FI: M = 0.34, SD = 0.57, NFI: M = 0.11, SD = 0.28; t (95) = 2.54, p = .013), but not any other domain. There were significant interaction effects of HIV and FI on speed of information processing (g2p = 0.09), learning (g2p = 0.04), memory (g2p = 0.04), and motor function (g2p = 0.05) as well as the GDS (g2p = 0.07) (see Table 2). In post hoc contrasts, food insecure HIV-positive participants had significantly higher domain deficit scores than the food secure HIV-positive participants in the domains of speed of information processing (Mdiff = 0.42, p = .001),
learning (Mdiff = 0.60, p = .049), motor function (Mdiff = 0.60, p = .014), and global deficit (Mdiff = 0.40, p = .004; see Fig. 1), but not memory (Mdiff = 0.52, p = .109). There were no significant differences in domain deficit scores across the food insecure and secure HIVnegative participants (all ps [ .05). When controlling for HIV-disease characteristics in post hoc ANCOVAs, there was a significant effect of FI on several domain deficit scores among the HIV-positive group, including speed of information processing [F (1,53) = 12.22, p = .001, g2p = 0.19], learning [F(1,53) = 6.18, p = .016, g2p = 0.10], executive function [F(1,53) = 5.11, p = .028, g2p = 0.09], motor function [F(1,53) = 7.69, p = .008, g2p = 0.13], and global deficit [F(1,53) = 8.83, p = .004, g2p = 0.14]. Among the HIVpositive group, FI was not associated with viral load suppression, nadir CD4 count, most recent CD4 count, years since HIV diagnosis, AIDS diagnosis, hepatitis C infection, or ART adherence (all ps [ .05). Among the HIV? participants, FI total score was correlated with the GDS (r = 0.26, p = .047). Several FI items were associated with higher global deficits scores when assessed individually including, worried that food would run out [t(59) = 2.08, p = .041], unable to afford balanced meals [t(59) = 2.46, p = .017], and chose between buying medicine or food [t(13) = 2.45, p = .030].
Discussion The results of this study highlight the role of FI in cognitive function among HIV-positive individuals. While HIV infection and FI had limited independent effects on neurocognitive deficits, the interactive effects were consistent across several domains where the HIV-positive group was more vulnerable to cognitive impairment in relation to FI than the HIV-negative group. The effects of FI on cognitive function remained after controlling for HIV disease characteristics. This study is the first to draw attention to FI as one factor that may be contributing to cognitive impairment for PLWHA in the US, a population with
Table 2 The effects of HIV status, FI, and their interaction on neuropsychological domain deficit scores Information processing F
Learning F
Memory F
Executive function F
Verbal fluency F
Attention F
Motor F
Global deficit F
HIV status
0.31
0.72
0.01
0.29
2.95
1.79
0.12
0.04
FI
2.22
0.09
0.75
1.77
1.10
0.41
0.59
0.18
Interaction
9.14**
4.02*
3.98*
0.73
0.42
0.21
4.70*
6.54*
Covariates included premorbid verbal IQ, hepatitis C infection, 30-day income, history of homelessness, current health insurance * p \ .05; ** p \ .01
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Fig. 1 Mean GDS by HIV and FI status
disproportionately high rates of socioeconomic disadvantage. Other research with HIV-negative samples has identified a similar trend in which FI may exacerbate predispositions to cognitive impairment, (e.g., aging) [41], likely in conjunction with other socioeconomic, environmental, and systemic factors [40, 42]. In the current study, the HIV-negative group did not have age-related or other predispositions to cognitive impairment, which may help to explain the lack of association between FI and cognitive function in this group. There are several hypothesized pathways through which FI and cognitive impairment may be associated, including behavioral and biological mechanisms. One barrier to measuring the impact of FI is that this phenomenon cannot be studied in isolation because it tends to co-occur with several other factors that may also impact cognitive function, including homelessness, substance use, low income, and reduced access to health care. In the current study, we were able to control for several of these factors through participant selection, statistical covariation, and accounting for demographics in the neuropsychological test scoring; however, there were other factors that were not measured or controlled in the current study that have been shown to contribute to FI and may impact the effect of FI on cognitive impairment. For example, in the Nutrition for Healthy Living (NFHL) study of HIV wasting disease, approximately 25 % of participants reported that they lacked assistance with food shopping and preparation [26]. A more in-depth analysis into the severity and duration of FI, the behavioral consequences (e.g., how often one chooses to purchase food over medications), the biological outcomes (e.g., nutritional deficiencies), and the potential neural alterations (e.g., variation in task-based neural activation) caused by FI would help to explain the current findings. Alternatively, HIV-associated cognitive impairment may contribute to higher rates of FI by limiting activities of daily living necessary for maintaining a healthy diet [36]. Longitudinal research is needed to shed light on the temporality of FI and cognitive impairment to better understand causal pathways.
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Randomized controlled trials and governmental programs have been implemented to address FI and malnutrition for people living with HIV. In higher resource settings like the US, interventions that include nutrient supplementation (e.g., amino-acid mixtures, balanced oral diet supplements) have been related to improved nutrition intake [67, 68], weight gain [69–71], and increased CD4 T-cell counts [72]; however, the findings are inconsistent and limited, and one multisite US study did not find any benefits for oral supplements [ [73], see [74] and [75] for review]. To our knowledge, there are no food supplement interventions for PLWHA that include neurocognitive function as a one of the outcomes of interest. In light of the current study results and the importance of neurocognitive function for engaging in self-care and HIV transmission prevention, this would be an informative and relevant addition to future intervention outcomes. The current study has several limitations that can be addressed in future research. First, the measure of FI was a brief, self-report survey that was adapted for use with HIVpositive samples to capture the presence of any FI over the past year, without an assessment of frequency. FI is a complex social problem that may warrant a more nuanced assessment tool. For example, understanding the different reasons for FI (lack of money vs. lack of transportation to purchase nutritious food) may be associated with different cognitive outcomes. Combining an assessment of FI with objective measures of nutritional intake, vitamin deficiencies, body mass index, and physiological stress reactivity, may also provide insight into the biological mechanisms that may be driving this effect. Second, while designed to ensure valid measures of neuropsychological function, our eligibility criteria may have also excluded individuals who are at highest risk for FI and cognitive impairment (e.g., substance users and individuals with serious mental illness or low educational attainment). Finally, while the hypothesized interactive effect of FI and HIV status was supported, the null findings should be interpreted with caution given the small sample sizes. This study should be replicated with a larger sample size before concluding that there are no effects of FI on cognitive function for HIV-negative individuals. In conclusion, the current study highlights the role of FI in cognitive impairment among individuals living with HIV, an understudied area. Given the relevance of cognitive function for maintaining health and well-being, it is important that we begin to better understand how social and economic factors may perpetuate the disproportionate rates of HIV incidence, morbidity, and mortality for our most at-risk populations. Future research could improve our knowledge of the association between FI and cognitive function among HIV-positive adults by implementing thorough measures of FI, identifying behavioral and
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biological mediators of this pathway, and broadening inclusion criteria to vulnerable populations, such as drug users, ethnic minorities, and individuals with low educational attainment. Acknowledgments This study was funded by Grants K23DA028660 and F32-DA038519 from the National Institute on Drug Abuse. We would like to thank the staff and students who assisted with this project, and we are grateful to the participants who volunteered their time for this study. Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. Ethical approval All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent Informed consent was obtained from all individual participants enrolled in the study.
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