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Understanding the Role of HIV Load in Determining Weight Change in the Era of Highly Active Antiretroviral Therapy

  1. D. Mkaya Mwamburi1,
  2. Ira B. Wilson2,3,
  3. Denise L. Jacobson4,
  4. Donna Spiegelman5,
  5. Sherwood L. Gorbach3,4,
  6. Tamsin A. Knox4, and
  7. Christine A. Wanke1,4
  1. 1Division of Geographic Medicine and Infectious Diseases, Boston, Massachusetts
  2. 2Institute for Clinical Research and Health Policy Studies, Boston, Massachusetts
  3. 3Department of Medicine, Tufts–New England Medical Center, Boston, Massachusetts
  4. 4Division of Nutrition and Infection, Department of Family Medicine and Community Health, Tufts University School of Medicine, Boston, Massachusetts
  5. 5Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, Massachusetts
  1. Reprints or correspondence: Dr. D. Mkaya Mwamburi, Div. of Geographic Medicine and Infectious Diseases, Tufts–New England Medical Center, 750 Washington St., Box 41, Boston, MA 02111 (mmwamburi{at}tufts-nemc.org.)
 
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Abstract

Background. In this prospective cohort study, we determined the relationship between human immunodeficiency virus (HIV) RNA load and body weight in patients with HIV infection.

Methods. Repeated-measures analysis was restricted to patients with ⩾2 study visits, 4–9-month intervals between study visits, and complete data on virus load, resting energy expenditure (REE), and highly active antiretroviral therapy (HAART). The outcome was change in body weight across study intervals. The main predictor was virus load. Separate analyses were performed for weight change in patients receiving and patients not receiving HAART.

Results. The eligible sample consisted of 318 participants associated with 1886 study intervals. Sixty-one patients (19%) were women, and 173 (54%) were undergoing HAART at the time of enrollment. There was a significant interaction (P = .01) between virus load and HAART use. In the absence of HAART, each log10 increase in virus load was associated with a 0.92-kg decrease in body weight (P = .003), but during HAART, virus load was not significantly associated with weight change. During HAART, a CD4+ cell count decrease of 100 cells/mm3, rather than a change in the virus load, was associated with a 0.35-kg decrease in body weight (P < .001). REE was independently associated with weight change in both models (P < .001).

Conclusions. Patients with HIV infection who are losing weight and are not taking HAART should be considered for HAART. Patients who are already receiving HAART and have unsuppressed virus loads may benefit virologically from an intensified regimen, because such a regimen may lead to complete suppression if there is an accompanying increase in CD4+ cell counts. Further research is needed to understand the strong independent effect of changes in REE among patients receiving and patients not receiving HAART.

Although the incidence and severity of decreases in body weight have diminished significantly with the advent of HAART, weight loss still occurs in 33% of patients with HIV disease [1]. Weight loss continues to be a threat to patients and a challenge to clinicians, and it results in death if progressive [2–6]. The basis of unintentional weight loss during the early stages of HIV disease or during HAART remains unclear. Understanding weight loss and managing this problem are now more complicated because of the impact of HAART use on HIV RNA load, CD4+ cell count, and body weight. Patients and physicians need to understand weight loss in the era of HAART and must know how to respond appropriately.

Current therapeutic options to counter weight loss include nutritional counseling and supplementation, pharmacotherapy, and resistance-based exercise training. Although the method of treatment selected is often based on the reason for weight loss, all of these methods are aimed directly at countering weight loss [7]. Treatment of opportunistic infections and use of antiretroviral therapy to suppress viral activity is often accompanied by weight gain. The dynamics of the restoration of weight under these circumstances are not well understood. Although the relationship between virus load and body weight has been described [8–12], inclusion of select study populations and methodological limitations have restricted the scope and generalizability of these findings. The roles of AIDS-defining illnesses [8], patient symptoms [9], diet [10], resting energy expenditure (REE) [11], and body composition changes [12] in HIV infection have each been described. However, determinants of longitudinal changes in body weight, as well as the interaction of these identifiers, in the general HIV-infected population during the HAART era remain poorly characterized.

We examined the associations between virus load and body weight and the impact of HAART use. We asked the following questions: is there a relationship between body weight and virus load; if there are associations between body weight and virus load, do they occur within 6 months of each other and what other factors are implicated; and how is this relationship influenced by HAART use. On the basis of this examination, we hope to improve the understanding of changes in body weight during the era of HAART and to guide both persons with HIV/AIDS and clinicians in the management of weight loss.

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Patients and Methods

Participants

Study participants were enrolled in the Nutrition for Healthy Living Study; study protocols for this cohort have been described elsewhere [1, 6, 8, 13–17]. This ongoing, cohort-based study is designed to investigate the role of nutrition in HIV disease. Adults ⩾18 years of age with any stage of HIV infection were eligible for the study, regardless of antiretroviral use. Persons who had malignancies other than Kaposi sarcoma and women who were pregnant were excluded from the study. Participants were recruited in Boston and in Providence, Rhode Island, between February 1995 and January 2003 and were observed biannually. The interval between 2 consecutive study visits was the unit of analysis. As of January 2003, a total of 704 participants in the Nutrition for Healthy Living Study had made at least 2 study visits. Analysis was restricted to intervals of 4–9 months, for which we had complete data on virus loads, REEs, and HAART use. All protocols and procedures were reviewed and approved by the human subjects review committees at all participating institutions.

Measurements

Weight and height were measured by use of a digital scale and a stadiometer to the nearest 0.1 kg and 0.1 cm, respectively. HIV RNA loads were determined by use of the Amplicor Monitor RT-PCR assay (Roche Molecular Systems), with a lower detection limit of 2.6 log10 copies/mL (400 copies/mL). CD4+ cells were counted with a fluorescent monoclonal antibody—labeled cell sorter. Participants kept detailed diary records of types and quantities of food consumed during the 3 days preceding each study visit. Food items were converted to corresponding nutritional energy value by use of the Nutrition Data System for Research software (University of Minnesota, Minneapolis). REE was measured by indirect calorimetry, after a minimum fasting period of 4 h, with a V2900 calorimeter (Sensormedics). HAART was defined as receipt of any of the following regimens: 2 protease inhibitors, 1 protease inhibitor and 2 nucleotide reverse-transcriptase inhibitors, or 1 nonnucleotide reverse-transcriptase inhibitor and 2 nucleotide reverse-transcriptase inhibitors. For our analysis, HAART use reported at a study visit was considered to be an indicator of HAART use during the preceding study interval.

Statistical Analyses

Key variables. We conducted parallel analyses with use of changes in body weight and changes in body mass index (BMI) as outcome variables. All change scores were calculated by subtracting the measurement at the start of the interval from that at the end of the interval. The main predictor was HIV load in log10 copies/mL. Patients with undetectable virus load were assigned a load of 2.3 log10 copies/mL (200 copies/mL). We defined HAART use across 2 consecutive study visits according to the following 4 distinct patterns: “no HAART,” patients who reported at both visits that they were not taking HAART; “continuous HAART,” patients who reported at both visits that they were taking HAART; “starters,” patients who reported during the first visit that they were not taking HAART but reported during the second visit that they had since started taking HAART; and “stoppers,” patients who reported during the first visit that they were taking HAART but reported during the second visit that they had since stopped taking HAART. A dichotomous variable was created to identify patients who were taking antiretroviral medications that did not satisfy the study definition of HAART.

Preliminary analysis. All analyses were done with SAS software, version 8.02 (SAS Institute). We performed univariate analyses between 3 formats of log10 virus load and body weight: changes in virus loads across intervals that immediately preceded intervals during which changes in body weight were observed, absolute virus load at the beginning of each interval, and changes in virus load and body weight across the same interval.

Multivariate analyses. We used mixed-model regression to adjust for the nonindependence of multiple intervals per individual and to obtain robust SEs. We constructed multivariable models in 2 steps. First, we used all of the intervals and specified HAART status by means of the 4-part categorical variable described earlier. We included an interaction between the change in virus load and HAART status. Second, we used separate models for the continuous-HAART and no-HAART groups.

To build the multivariable models that used all of the intervals, we compared each potential confounder with change in virus load and change in body weight. Potential confounders at the beginning of each interval included age, sex, education level, race, income level, risk factor associated with contracting HIV infection, use of drugs associated with weight gain, use of HAART, CD4+ cell count, nadir CD4+ cell count of <200 cells/mm3, daily energy intake per kilogram of body weight, and REE per kilogram of body weight. We also tested whether changes in CD4+ cell count and daily REE per kilogram of body weight were associated with changes in body weight during the same interval. Our cutoff for confounding was a P value of ⩽.2. A virus load—HAART use interaction term was included. Data on age, sex, and HAART use were forced into the model. For those not taking HAART, the dichotomous measure of non-HAART—based antiretroviral use was included in the model.

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Results

Descriptive analyses. A total of 318 participants were associated with 1886 intervals. Baseline characteristics of study participants are summarized in table 1. Sixty-one participants (19%) were women, and 115 participants (36%) were nonwhite. The mean body weight was 75 kg (77 kg for men and 70 kg for women), and the mean BMI was 25 kg/m2 (24.7 kg/m2 for men and 26.4 kg/m2 for women). The median CD4+ cell count and log10 HIV load were 311 cells/mm3 and 3.4 log10 copies/mL (2500 copies/mL), respectively. At the time of enrollment, mean BMI was significantly higher (25.5 vs. 24.4; P = .02) and median log10 virus load was significantly lower (2.3 vs. 4.4 copies/mL; P < .001) among HAART users, compared with non-HAART users.

Table 1
Table 1

Characteristics at the time of entry into the present study (baseline) for 318 patients enrolled in the Nutrition for Healthy Living cohort, according to baseline HAART status.

Univariate analyses. Unadjusted for other factors, each log10 increase in virus load was significantly associated with a weight loss of 0.34 kg across the same interval (P = .001). However, neither a change in virus load during the interval immediately preceding the interval in which changes in body weight were observed (P = .81) nor virus loads at the beginning of intervals in which changes in body weight were observed (P = .68) were significantly associated with changes in weight.

Distributions of median body weights, virus loads, and CD4+ cell counts at the start of and across study intervals (i.e., over 2 consecutive visits) are shown in table 2. The median change in virus load was 0 for the continuous-HAART and no-HAART groups. However, in contrast to the no-HAART group, there was minimal variation in virus load observed in the continuous-HAART group. On average, starters experienced weight gain, decreased virus loads, and increased CD4+ cell counts, whereas stoppers experienced weight loss, increased virus loads, and decreased CD4+ cell counts.

Table 2
Table 2

Patient body weight, virus load, and CD4+ cell count for 1886 intervals between 2 consecutive study visits, according to pattern of HAART use.

Multivariable analyses. The final model that included all of the study intervals and demonstrated the interaction between HAART use and changes in virus load is shown in table 3. Results from the multivariable analyses of change in body weight and change in BMI were similar; however, only findings from the body weight analyses are presented. The continuous-HAART pattern was the reference category. The interaction between no-HAART status and change in virus load was significant (P = .01). Other independent, statistically significant predictors of weight loss were increasing daily REE (0.31 kg per kcal/kg of body weight) and decreasing CD4+ cell count (0.33 kg per 100 CD4+ cells) (P < .05). Lower daily caloric intake per kilogram of body weight at the start of an interval was independently associated with weight loss. Energy intake and presence of AIDS-defining illness were nonsignificant for predicting weight change. The significant interaction between virus load and HAART use suggested that the relationship between virus load and body weight should be examined separately in the continuous-HAART and no-HAART groups.

Table 3
Table 3

Determinants of changes in patient body weight for 1886 intervals between 2 consecutive study visits, according to multivariable mixed regression analysis.

Influence of HAART. Results of separate statistical models that analyzed the relationship between HAART use and changes in body weight in the no-HAART and continuous-HAART groups are shown in table 4. In the absence of HAART, a virus load increase of 1 log10 was associated with a weight decrease of 0.92 kg (P = .003). Each unit increase in daily REE per kilogram of body weight was significantly associated with 0.38-kg decrease in weight (P < .001). In contrast, for the continuous-HAART group, a change in virus load was not associated with a change in body weight (P = .66). Instead, a CD4+ cell count decrease of 100 cells/mm3 was significantly associated with a weight loss of 0.35 kg (P < .001). During HAART, each unit increase in daily REE per kg of body weight was significantly associated with a 0.26-kg decrease in weight (P < .001).

Table 4
Table 4

Determinants of changes in patient body weight for 1605 intervals between 2 consecutive study visits, according to pattern of HAART use.

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Discussion

Understanding the fundamental but complex relationship between virus load and body weight and other factors for all stages of disease is important not only in the clinical treatment of patients infected with HIV but also for people living with HIV/AIDS. In the absence of HAART, fluctuations in virus load are associated with changes in weight. During HAART, when there is suppression and stabilization of virus load, changes in CD4+ cell counts but not virus loads are associated with changes in weight. We observed an independent effect of changes in REE on changes in weight in patients taking and patients not taking HAART.

To the best of our knowledge, there are no published reports of longitudinal relationships between virus load and weight that also describe how HAART use modifies this relationship. A cross-sectional study of 122 subjects, most of whom were male and 82% of whom were taking antiretroviral therapy, found that each log10 increase in virus load was associated with a 1.58-kg decrease in body weight [18]. Lyles et al. [19] also showed that higher baseline HIV loads were associated with higher adjusted relative hazard ratios for weight loss events in a cohort of 1558 homosexual men with HIV infection that had not progressed to AIDS. Silva et al. [13], using data from the Nutrition for Healthy Living Study, restricted their analysis to patients who had started taking protease inhibitors after enrollment. This analysis examined the effect that initiation of protease inhibitor therapy had on weight and found that responders (i.e., subjects with a decreased virus load) had a mean weight increase of 0.38 kg/month, compared with a mean increase of 0.13 kg/month among nonresponders [13]. In a longitudinal study of 29 HIV-positive adults, all of whom were receiving drugs to increase weight concomitant with HAART, baseline virus load was consistently associated with a change in body weight [20]. In this study, a 1-log10 decrease in virus load was associated with a 1.4-kg increase in weight. Two studies in which HIV-positive patients were continuously taking HAART did not demonstrate significant correlations between changes in body weight and virus load [21, 22]. Although these 2 studies support our findings, methodological or sample size limitations restricted their generalizability. No study assessed the influence of HAART on the relationship between virus load and weight.

HAART independently alters energy intake and REE [11, 23], in addition to its effects on virus load and CD4+ cell count. We found that, in the absence of HAART, decreases and increases in virus load across a 6-month interval strongly influenced changes in weight, suggesting that unsuppressed viral activity is, in part, responsible for weight loss. This was not surprising. What was unexpected was that, in patients taking HAART, neither virus load at the start of the interval nor change in virus load during the interval were associated with changes in weight; instead, changes in CD4+ cell counts were strongly associated with weight change. This suggests a biological model of weight loss in cases of HIV infection that has both virological and immunologic components. The finding that change in virus load, rather than change in CD4+ cell count, predicts weight loss in patients who are not taking HAART implies that virus load suppression is a necessary condition for control of weight loss. The finding that change in CD4+ cell counts but not change in virus loads predicts weight change in persons taking HAART suggests that virus load suppression is necessary but not sufficient for control of weight loss. In individuals who start HAART, clinical prognosis is associated with increases in CD4+ cell counts [24], and the same appears to be true with regard to weight loss. An important question is whether individuals taking HAART who have detectable virus loads will gain weight if their virus loads become undetectable. Although our data do not directly address this point, if achievement of an undetectable virus load is associated with an increase in CD4+ cell count [25], then it will be also be accompanied by an increase in weight.

The relationship of energy intake to weight changes in this study was complex. In the full model (table 3), energy intake was significantly associated with weight change, as we anticipated it would be. In subsequent models that examined patients who were and patients who were not taking HAART, this relationship was not significant. Of note, for patients who were not taking HAART, the coefficient for energy intake was the same as it was in the full model (0.02), but the P value changed from .01 to .08, probably because of a smaller sample size. We recommend that all patients with HIV-related weight loss receive nutrition counseling so that energy intake is optimized, but for the average patient taking HAART, our data suggest that an increase in energy intake is not likely to increase weight.

The association of REE with weight was independent of CD4+ cell count and virus load during and in the absence of HAART, respectively. Although the absolute virus load is strongly related to the absolute REE [11, 26], the factors associated with changes in virus load or REE may differ significantly [27]. We found that changes in REE over time are a powerful and independent determinant of weight change, confirming findings of another study [28]. Whereas previous thinking was founded on the idea that the effect of virus load on body weight was mediated through its impact on REE, our study suggests that additional independent mechanisms may exist. This observation of the independent influences of changes in REE on changes in weight in patients with HIV disease who were or were not receiving HAART may warrant further research to fully understand these relationships.

The strengths of this study include the diversity of the sample population, the longitudinal design of the study, and the large effective sample size. By considering 2 consecutive study visits for analysis of HAART use, we minimized the chance of misclassification. A potential weakness is that the 318 patients associated with intervals that were included in the analyses differed in some characteristics from the 386 patients with intervals that were not included. Differences between these 2 samples included smaller numbers of women, nonwhites, heterosexual persons, and injection drug users and larger numbers of homosexual men, high school graduates, and HAART users in the group included in the analyses. These factors were not significant in determining weight change. Energy intake was higher among patients included in the analyses, but there was no significant differences between the groups with respect to age, body weight, virus load, CD4+ cell count, REE, and proportion of persons with AIDS or living below the 1998 US federal poverty line. The potential for the introduction of bias due to differences in HAART use among patients is minimized because we performed separate analyses that adjusted for this factor. Our analysis suggests that the higher mean daily caloric intake among patients in the study draws results of our formal tests toward the null, thus resulting in conservative estimates. Finally, the absence of an association between AIDS-defining illness and weight changes may be because there were few such clinical end points in this cohort of subjects who were followed closely at a tertiary care center.

Our findings suggest that HIV-related weight loss is a function of both virological and immunologic processes. One clinical implication of this is that patients with HIV infection who are losing weight and are not taking HAART should consider starting HAART. For patients who have detectable virus loads and are already taking HAART, changes in adherence or changes in the HAART regimen are likely to result in weight gain, if there is an accompanying increase in the CD4+ cell count. For patients who have nondetectable virus loads and are already taking HAART, it is less clear from our data how to intervene. Further research is needed to understand the strong, independent effect of REE and changes in REE on weight change in all our models.

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Acknowledgments

Financial support. National Institutes of Health (grants DK-45734, RR-00054, CFAR P30-A-142853, and K24-AI-055293 and Fogarty grant TW-01083A).

Potential conflicts of interest. All authors: no conflicts.

  • Received June 15, 2004.
  • Accepted September 3, 2004.
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  1. Clin Infect Dis. (2005) 40 (1): 167-173. doi: 10.1086/426591
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