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Brief Report: Body Mass Index and Cognitive Function Among HIV-1–Infected Individuals in China, India, and Nigeria

Jumare, Jibreel MBBS, PhD*; El-Kamary, Samer S. MD, MPH*; Magder, Laurence PhD*; Hungerford, Laura DVM, PhD*; Umlauf, Anya MS; Franklin, Donald PhD; Ghate, Manisha MBBS, PhD; Abimiku, Alash'le PhD*; Charurat, Man PhD*; Letendre, Scott MD; Ellis, Ronald J. MD, PhD; Mehendale, Sanjay MD, MPH; Blattner, William A. MD*; Royal, Walter III MD*; Marcotte, Thomas D. PhD; Heaton, Robert K. PhD; Grant, Igor MD; McCutchan, John A. MD, MSc

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: February 1, 2019 - Volume 80 - Issue 2 - p e30-e35
doi: 10.1097/QAI.0000000000001906

Abstract

INTRODUCTION

The pathogenesis of HIV-associated neurocognitive disorders involves interaction of viral, host, treatment, and comorbid factors, but the specific mechanisms remain unclear.1–3 Among important comorbid factors implicated in cognitive impairment are metabolic disorders such as overweight/obesity.4,5 High body mass index (BMI) is associated with hypertension, diabetes mellitus, and metabolic syndrome, which are risk factors for cardiovascular disease and neurocognitive dysfunction.6–14 Several studies in the general population have linked high and low BMI with increased risk of cognitive impairment.15–20 The studies that explored this association in the context of HIV infection are mainly in whites from HIV low-burden and resource-rich settings, cross-sectional in design, generally limited in power, and reported variable findings.21–23

As patients with HIV receive antiretroviral treatment, many gain weight and may become overweight/obese at rates similar to or greater than the general population.24,25 In fact, one report indicated that overweight/obesity is now more prevalent than wasting among individuals living with HIV/AIDS.25 Elevated BMI in these patients may increase the risk of neurocognitive impairment (NCI).26 In this study, we examined the association between BMI categories and cognitive function, using data from 3 cohort studies conducted in middle income countries in Asia and Africa.

METHODS

Design

This was a secondary analysis of data from 3 cohort studies conducted in China,27,28 India,29 and Nigeria.30,31

Study Participants

Of 761 HIV-1–infected participants in this study, 404 (53%) were from the China study, 200 (26%) from the India cohort, and 157 (21%) from the Nigeria cohort. At enrollment, participants were 18 years or older, antiretroviral treatment-naive in the India and Nigeria studies, and mixed naive and experienced in the China study. Participants with hepatitis B or C infections (India and China) and substance use (China) were also included. Informed consent was obtained from all participants, and study procedures were approved by relevant Institutional Review Boards.

Neuropsychological Assessment

A standardized comprehensive 7-domain neuropsychological battery was administered to participants at each study visit. Tests were translated as needed into local languages (China and India). Details of these are described in our other reports.27,29,31 Mean T score below 40 in each domain signified impairment for that domain, while global NCI was defined as global deficit score of ≥0.5.32,33

Clinical Assessment

Demographic and clinical information were obtained using standardized questionnaires, including general medical assessment at each study visit. Weight and height were used to determine BMI, calculated as the ratio of weight [in kilograms (Kg)] to the square of height [in meters squared (m2)]. Weight classifications used were: underweight: <18.5 kg/m2; normal weight: 18.5 to <23 kg/m2; and overweight/obese: ≥23 kg/m2.34

Follow-up Schedule

Participants were seen at 6, 12, and 24 months after their baseline assessment in the Nigeria study. For the China and India studies, there were 4 annual visits after enrollment.

Statistical Analyses

Demographic and clinical characteristics were compared between normal weight, overweight, and underweight participants, using χ2, Kruskal–Wallis, and analysis of variance tests, in addition to pairwise comparisons. Generalized linear and generalized estimating equation (with exchangeable correlation structure) models were used for the baseline and longitudinal regression analyses, respectively. Conditional logistic regression analyses were also used to assess within-person associations. All statistical analyses were performed using SAS 9.3 (SAS Institute, Inc.).

RESULTS

Baseline Demographic and Clinical Characteristics

The median age of participants was 35 years and about 42% were women. Participants' median number of years of education did not differ significantly between the weight categories (P = 0.058). A higher proportion of overweight individuals had hypertension compared with the normal weight or underweight participants (P < 0.001). The underweight participants had lower median nadir CD4 count (P = 0.048) and hemoglobin level (P < 0.001) as well as higher mean plasma log10 HIV RNA (P = 0.002) when compared with the other weight categories. Median Beck's depression score was lower among the overweight as compared to normal weight and underweight participants (P = 0.001). Overall, the prevalence of global NCI at baseline was 27.7% [28.5% (China), 26% (India), and 28% (Nigeria)] (Table 1) (see Table 1, Supplemental Digital Content 1, http://links.lww.com/QAI/B250).

TABLE 1.
TABLE 1.:
Baseline Demographic and Clinical Characteristics

Association of BMI Categories With Global and Domain-Specific Cognitive Impairment

Baseline

Odds of global NCI were 48% higher among the overweight as compared to normal weight participants {odds ratio [OR]: 1.48 [95% confidence interval (CI): 0.99 to 2.2]} in a multivariable logistic regression analysis. The odds of NCI tended to be higher among the underweight as compared to normal weight participants, but this was not statistically significant [OR: 1.35 (95% CI: 0.80 to 2.29)] (Fig. 1).

FIGURE 1.
FIGURE 1.:
Forest plots for baseline and longitudinal association of overweight and underweight with global cognitive impairment (A–D). Regression models were adjusted for plasma HIV RNA, CD4 count, Beck's depression score, years of education, age, gender, antiretroviral treatment status, hypertension, diabetes mellitus, and intravenous drug use.

Longitudinal

In a multivariable logistic regression, the odds of NCI were 38% higher among the overweight as compared to normal weight participants [OR: 1.38 (95% CI: 1.1 to 1.72)]. Similarly, the odds of NCI were 39% higher among the underweight compared with normal weight participants [OR: 1.39 (95% CI: 1.03 to 1.87)] (Fig. 1) (see Table 2, Supplemental Digital Content 1, http://links.lww.com/QAI/B250).

The odds of impairment tended to be higher among the overweight as compared to normal weight participants across all cognitive domains. Comparing the underweight with normal weight participants, the odds of impairment were significantly higher for the attention and memory domains, as well as marginally significant for the executive function domain (see Table 2, Supplemental Digital Content 1, http://links.lww.com/QAI/B250).

Although differences were seen between the 3 cohorts, these were not statistically significant (global P value for interaction: 0.121). Within cohort, associations were statistically significant only for the underweight in the India study (OR: 1.78; P = 0.012) and the overweight in the China study (OR: 1.48; P = 0.011) (Fig. 1).

In conditional logistic regression analyses among participants who experienced changes in weight category and cognitive status, the odds of NCI were higher among the underweight (OR: 2.57; P = 0.016) and among the overweight (OR: 2.05; P = 0.025), as compared to normal weight participants (see Table 3, Supplemental Digital Content 1, http://links.lww.com/QAI/B250).

DISCUSSION

In this study, we found a significantly higher likelihood of NCI among overweight as compared to normal weight participants, in both baseline and longitudinal repeated-measures analyses. We also showed a similar association for underweight participants, particularly in the longitudinal analysis.

Our findings are consistent with results of other studies in the general population and among HIV-infected populations in resource-rich settings. In a meta-analysis of cohort studies of older adults in the general population, Beydoun et al35 found evidence of a U-shaped association between BMI and dementia, with dementia risk increased for obese and underweight persons. Anstey et al,36 in another meta-analysis, showed similar results.

For HIV-infected individuals, McCutchan et al21 reported a significantly higher likelihood of NCI as BMI increased in a baseline substudy of the CHARTER cohort. An even stronger association was found in that study for waist circumference, a better indicator of visceral adiposity, although among a much smaller subset of participants. This relationship was confirmed in another CHARTER study that also showed a greater effect among those with abdominal obesity and those with the highest level of systemic inflammation.23

In contrast to these observations, some reports describe a seemingly protective role of higher BMI on cognition, an example of the so-called obesity paradox.37–40 Such contradictory reports may be due partly to methodologic limitations in some of the studies, but more importantly, may be an indication of the limitations of BMI, which is a surrogate marker for central adiposity. Nevertheless, the preponderance of evidence, including from systematic reviews and meta-analyses, supports an adverse effect, although modest, of excess weight on cognition.

Our study found similar effect sizes to studies in the general population with significantly older participants and lengthy follow-up. This similarity may reflect the synergistic effects of HIV and abnormal BMI categories, potentially leading to an earlier onset of cognitive decline. HIV disease is associated with accelerated aging, and may result in earlier occurrence of comorbid conditions and their adverse sequelae.41

A number of potential causal pathways have been postulated in the association between overweight/obesity and cognitive dysfunction.42 First, overweight/obesity has been linked to cardiometabolic disorders such as type-2 diabetes mellitus and hypertension, which are strongly associated with cognitive impairment.9,43,44 These disorders may potentially play substantial mediating or synergistic role in this relationship.45

Second, adipocyte enlargement and proliferation, the histopathologic hallmark of overweight/obesity, is associated with macrophage recruitment and promotion of local and systemic inflammation. This manifests through higher expression of proinflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and monocyte chemotactic protein-1 (MCP-1). Such cytokines are believed to mediate many of the downstream complications of overweight/obesity.23,46 Studies have demonstrated associations between these cytokines and cognitive decline, and this may be due to direct neural damage or the result of induced atherosclerotic changes, also known to interfere with cognitive function.47–49

Third, obesity is associated with adipokine changes, including central leptin resistance and reduction in adiponectin levels.46 Leptin resistance, coupled with associated insulin resistance, may lead to dysregulated neuronal metabolism and dysfunction.50 Similarly, reduction in adiponectin levels may result in impairment of its anti-inflammatory, antihyperglycemic, and antiatherogenic activity,51 potentially leading to adverse outcomes that may include cognitive dysfunction.

Significant interactions may occur among these potential causal pathways. Studies are needed to characterize the contributions of these factors in the relationship between overweight/obesity and cognitive function.

The observed association between underweight and cognitive impairment probably reflects the effects of advanced HIV disease, which causes both NCI and wasting, a manifestation of the phenomenon of “confounding by severity.”52 Another plausible explanation for this association is reverse causality, which refers to weight loss caused by cognitive impairment, as reported in some studies among older adults.16,39 Mechanistically, however, hormonal and metabolic dysregulation, malnutrition, and proinflammatory cytokine elaboration in the underweight may have an underlying causal effect on the observed cognitive dysfunction.53–55

In this study, the association between underweight and global NCI appears to be driven by deficits in the domains of attention, memory, and executive function. Gustafson et al22 also found lower performance in executive function and speed of information processing domains among underweight HIV-infected women. Overall, these domains are the most frequently affected in HIV-related cognitive disorders,56,57 a further indication that the underweight association may be largely a reflection of the HIV disease process. By contrast, the pattern for overweight/obesity did not appear to preferentially select for particular cognitive domains. Other studies also reported significant findings for virtually all domains.16,22,58 Therefore, overweight/obese patients exhibit a more diffuse pattern of deficits, possibly indicating a predominantly vascular pathogenic mechanism.59,60

This study has some limitations. First, BMI is considered a surrogate marker for visceral adiposity, which is the more likely biological factor involved.21 Such an indirect measure may be associated with misclassification bias among persons with more widely distributed adipose tissue or high lean body mass.61 However, such misclassification is expected to be nondifferential and would tend to attenuate estimates of association.

Second, about 30% of participants were lost to follow-up by the penultimate study visit, and over half had missing assessment at the final visit. However, those lost did not differ significantly from those retained by baseline impairment status or BMI category up to the penultimate visit. We also found the same estimates of longitudinal association with or without the final study visit. Therefore, the loss to follow-up in this study was unlikely to have introduced significant selection bias.

Another limitation is the recruitment of only English-speaking participants in the Nigeria study and individuals with significant history of injection drug use in the China cohort. These would potentially limit the generalizability of findings but are unlikely to significantly affect the internal validity of the study. The net effect of these selection factors might be an attenuation of estimates when compared with expected effect sizes from a more representative cohort.

CONCLUSIONS

We confirmed in a pooled analysis of data for HIV-1–infected persons from China, India, and Nigeria the U-shaped relationship of BMI and cognitive function reported by multiple studies in the general population. Given the global epidemic of overweight/obesity and the similarity in its prevalence among HIV-infected patients treated with antiretroviral drugs and HIV-uninfected populations, overweight/obesity may be an increasing cause of cognitive impairment in both groups globally. Although systemic inflammation constitutes the leading causal hypothesis for this association, further studies are required to define the biological mechanisms involved and to guide development of therapeutic interventions.

ACKNOWLEDGMENTS

The authors acknowledge the study participants and staff of the primary projects in China, India, and Nigeria, staff and management at the individual study sites, National AIDS Research Institute (NARI) India, China CDC/National Center for AIDS (NCAIDS), Peking University, CDC Nigeria, and Institute of Human virology Nigeria.

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Keywords:

HIV-1; BMI; cognitive function; China; India; Nigeria

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