HIV Infection and Obesity: A Review of the Evidence

HIV Infection and Obesity: A Review of the Evidence Joyce K. Keithley, DNSc, RN, FAAN Anna M. S. Duloy, BS Barbara Swanson, PhD, RN, ACRN Janice M. Zeller, PhD, RN, FAAN This article provides a review of recent evidence pertinent to the prevalence, morbidities, and predictive value of overweight and obesity in PLWH. Implications for clinical outcomes are discussed, and recommendations for patient management and future research are advanced. (Journal of the Association of Nurses in AIDS Care, 20, 260-274) Copyright Ó 2009 Association of Nurses in AIDS Care Key words: advanced clinical management, HIV infection, morbidities, obesity, overweight, predictive value, prevalence

HIV disease and obesity are significant public health problems. Only a decade ago, HIV disease was a progressively fatal illness accompanied by severe wasting. Today, highly active antiretroviral therapy (ART) has transformed HIV disease into a chronic illness, increasingly accompanied by obesity. The consequences of obesity on HIV infection are as yet unknown: Are the effects of obesity on HIV disease progression protective or harmful? Research reports are beginning to describe the prevalence, morbidities, and predictive value of overweight and obesity in persons living with HIV (PLWH). In this report, the results of these studies are reviewed, and recommendations for current clinical care and future research are made. A brief overview of the evolution of metabolic and morphologic abnormalities in HIV will place current evidence related to obesity in context.

Evolution of Metabolic Abnormalities 1981 to 1995 Since the identification of AIDS in 1981, metabolic abnormalities associated with HIV infection have varied over the course of the epidemic. During the early years, roughly spanning 1981 to 1995, wasting syndrome was the hallmark of AIDS. Pronounced loss of weight, lean body mass, and fat mass were attributed to an array of factors including opportunistic infections, living below the poverty level, low CD41 cell count, and high viral load. Although the incidence of wasting syndrome has declined dramatically since the implementation of advances in ART, wasting still occurs—especially in individuals who are not receiving ART and who are of lower socioeconomic status—yet it often goes unrecognized, emerging subtly over a longer period of time (Tang, Jacobson, Spiegelman, Knox, & Wanke, 2005). 1995 to 2004 Shortly after the introduction of highly active ART in late 1995, several new metabolic abnormalities Joyce K. Keithley, DNSc, RN, FAAN, is professor, Adult Health Nursing; Anna M. S. Duloy, BS, is research assistant, Adult Health Nursing; Barbara Swanson, PhD, RN, ACRN, is associate professor, Adult Health Nursing; Janice M. Zeller, PhD, RN, FAAN, is professor, Adult Health Nursing; all at Rush University College of Nursing, Chicago.

JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 20, No. 4, July/August 2009, 260-274 doi:10.1016/j.jana.2009.02.006 Copyright Ó 2009 Association of Nurses in AIDS Care

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were reported and linked to its use (Carr et al., 1998). These abnormalities included lipodystrophy (fat redistribution), dyslipidemia, and insulin resistance. Whereas the etiology of lipodystrophy syndrome (fat redistribution along with dyslipidemia and/or insulin resistance) remains poorly understood, it has been associated with use of all classes of antiretroviral medications, particularly the nucleoside reverse transcriptase inhibitor stavudine and the protease inhibitor (PI) ritonavir. The prevalence of this metabolic disorder has been difficult to determine because of lack of precise diagnostic criteria; however, it has been estimated to occur in up to 60% to 80% of individuals treated with ART (Heath et al., 2002). 2004 to Present More recently, reports suggest that PLWH are gaining weight and beginning to approach weight levels seen in the general U.S. population, in which approximately two out of every three adults are overweight (i.e., body mass index [BMI] $ 25) and one in every four adults is obese (i.e., BMI $ 30) (Ogden et al., 2006). Overweight and obesity are considered to be primarily responsible for the rising prevalence of metabolic syndrome. Components of metabolic syndrome include abdominal obesity, atherogenic dyslipidemia, elevated blood pressure, insulin resistance with or without glucose intolerance, and proinflammatory and prothrombotic states (Grundy, Brewer, Cleeman, Smith, & Lenfant, 2004), many of which overlap with correlates of lipodystrophy syndrome. The prevalence of metabolic syndrome has not been consistently shown to be higher among PLWH than in the general population (Jacobson et al., 2006; Mondy et al., 2007; Samaras et al., 2007). Whereas metabolic syndrome occurs in approximately 24% of the U.S. general population (Ford, Giles, & Dietz, 2002), the prevalence among PLWH has ranged from 14% to 18%, depending on the diagnostic criteria used (Samaras et al., 2007). This unexpected result supported the emerging view that metabolic abnormalities in PLWH are part of discrete conditions that are not linked to a single underlying etiology; rather, they reflect individual responses to HIV infection and its treatment (Pao, Lee, & Grunfeld, 2008).

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Review of the Evidence Fifteen studies were reviewed for this analysis. Table 1 provides an overview of these studies, documenting the purpose, participants, design, and results of each study.

Prevalence One of the earliest overweight/obesity prevalence studies examined HIV-infected adults in the Nutrition for Healthy Living (NFHL) cohort, a large longitudinal nutritional study of more than 600 PLWH. In 1998, only a couple of years after more effective ART was introduced, 6% of men and 21% of women in this cohort were obese and 33% of men and 27% of women were overweight (Shevitz & Knox, 2001). More recently, Hendricks, Willis, Houser, and Jones (2006) examined 321 HIV-infected adults enrolled in the NFHL cohort between 2000 and 2003 and reported that 13% of men and 29% of women were obese, and 40% of men and 34% of women were overweight. This represented nearly a doubling of obesity prevalence in this cohort since 1998. Among overweight and obese male participants, shorter duration of known HIV seropositivity, trying to lose weight, and non-White race were associated with a higher BMI. Although there were relatively few female participants (n 5 56), obese women were more likely to be nonwhite. Additionally, women were more overweight and had higher central adiposity than a population-based comparison group; 52% of the NFHL cohort vs. 42% of the National Health and Nutrition Examination Survey III cohort had truncal adiposity, BMI of 27.3 versus 26.4 kg/ m2, and waist circumference of 89.5 versus 88 cm (Jones et al., 2005). Other studies have also reported a high prevalence of overweight/obesity among HIV-infected populations. A study of 189 HIV-infected adults recruited at different stages of infection and from an innercity HIV clinic reported that 12% of men and 32.5% of women were overweight (BMI $ 27.8 for men and $ 27.3 for women). Female gender and lack of AIDS diagnosis were independently associated with overweight (Shuter, Chang, & Klein, 2001).

Review of HIV and Obesity Literature

Reference

Purpose To determine the relationship between adipose tissue distribution and insulin resistance among obese HIV-infected women

N 5 49 obese women  17 HIV-infected (11 African American)  32 uninfected

Prospective cross-sectional

Amorosa et al., 2005

To determine the prevalence and risk factors for overweight and obesity in HIV-infected individuals

N 5 1,689 HIV-infected subjects  78% men  60% African American

Retrospective cross-sectional

Blass et al., 2008 abstract

To examine factors associated with abnormalities in glucose metabolism among HIV-infected adults

N 5 55 adults  44 HIV-infected  11 uninfected

Prospective cross-sectional

Brar et al., 2007

To examine the prevalence of diabetes mellitus and its predictors in ART-naive HIV-infected patients

N 5 9,150 adults  2,565 HIV-infected adults from the CPCRA cohort  6,585 uninfected adults from the NHANES cohort

Retrospective cross-sectional

Danoff et al., 2005

To determine the prevalence of diabetes, prediabetes, and insulin resistance among HIV-infected and HIV-uninfected women

N 5 258 women  88 uninfected  74 HIV-infected not on ART  96 HIV-infected on ART  Predominantly African American or Latina

Prospective cross-sectional

Albu et al., 2007

Participants

Design

Findings High whole-body intermuscular adipose tissue and low leg subcutaneous adipose tissue distribution were independently associated with insulin resistance in obese HIV-infected and uninfected women. Obesity (14%) and overweight (31%) were more common than wasting (9%) among the HIV cohort. Men and women were equally overweight (31% vs. 30%), although women were more obese than men (28% vs. 11%) with African American race, nonsmoking status, and CD4 count . 200 cells/mL associated with a greater BMI among women. BMI was positively correlated with total cholesterol, triglycerides, and glucose levels, although nonfasting blood samples were used. Overweight, duration of ART, and familial disposition for diabetes mellitus significantly affected fasting glucose among PI users, and waist circumference affected C peptide. Older age, higher BMI, and Black race were associated with diabetes mellitus in both the HIV-infected cohort and the uninfected cohort. After adjustments for age, race/ethnicity, and BMI, there was no significant difference in the prevalence of self-reported diabetes between the two groups. Frequency of diabetes, prediabetes, or insulin resistance was not related to HIV status or ART. BMI was the only variable significantly associated with diabetes and prediabetes.

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Table 1.

To examine regional body composition, insulin, and lipids among HIV-infected women

N 5 105 women  75 HIV-infected (59 wasted)  30 uninfected matched by weight

Prospective cross-sectional

Hadigan et al., 2001

To examine metabolic abnormalities and cardiovascular disease risk parameters among HIVinfected adults with and without lipodystrophy

N 5 284 adults  71 HIV-infected with lipodystrophy (49 men, 77% White)  213 controls from the Framingham Offspring Study matched for age, sex, and BMI (predominantly white)

Prospective cross-sectional

Hadigan et al., 2003

To compare the 10-year CHD risk among a matched HIV-infected cohort with fat redistribution

N 5 364 adults  91 HIV-infected men and women with fat redistribution (65 men)  273 age-, sex-, and BMI-matched Framingham study control subjects

Prospective cross-sectional

HIV-infected women had significant hyperinsulinemia, truncal adiposity, and increased insulin-to-glucose ratio compared with controls. HIV-infected women with truncal adiposity had the largest elevation in insulin and insulinto-glucose ratio. Insulin and glucose levels correlated with BMI in the HIVinfected cohort. A significant inverse relationship was reported between BMI and viral load as well as between percent truncal fat and viral load. Patients with lipodystrophy were more likely to have reduced levels of HDL, hypertriglyceridemia, impaired glucose tolerance, and diabetes compared with controls. Among the HIV-infected subjects with lipodystrophy, waist and thigh circumference were significant predictors of fasting insulin levels. 10-year CHD risk estimate based on the Framingham risk equation was significantly greater among HIVinfected subjects with fat redistribution, particularly among men. When subjects were matched with controls by BMI and WHR, there was no longer a significant difference in the 10-year CHD risk estimate. CHD risk estimate was greatest in HIV-infected patients with primary lipoatrophy compared with patients who had either lipohypertrophy or mixed fat redistribution. (Continued)

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Hadigan et al., 1999

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Reference

Purpose

Participants

Design

Findings

Hendricks et al., 2006

To determine the prevalence of obesity among HIV-infected individuals and to examine the differences in dietary intake among subjects who are normal weight, overweight, and obese

N 5 321 HIV-infected subjects  265 males

Retrospective cross-sectional

40% of men and 34% of women were overweight, and 12.5% of men and 29% of women were obese. Among the men, shorter duration of known HIV seropositive, trying to lose weight, and non-White race were associated with higher BMI. Serum markers of insulin resistance were significantly different by BMI category for both men and women, in addition to triglycerides and total cholesterol for men. Mean total fat and saturated fat intakes were above recommendations and micronutrient intakes were below recommendations for all participants in all BMI categories. Total grams dietary fiber decreased as BMI increased for both men and women. Overweight (34%) and obese (9%) were more common than wasting (6%) and marginally underweight (7%). Women had a higher BMI than men, and Black Africans had higher BMIs than Whites; 80% of obese patients were African women. ART was not associated with being overweight or obese. A higher BMI and increases in BMI were associated with a decreased risk of HIV progression and small increases in CD4 cell counts. Estimated odds of death were 3.1 times greater among women in the underweight category versus those in the obese category.

Hodgson et al., 2001

To assess the incidence of wasting and excess weight in HIV-infected individuals

N 5 162 HIV-infected subjects  59% men  48% White  51% Black African

Prospective cross-sectional

Jones et al., 2003

To determine the association between HIV disease progression and BMI

N 5 871 HIV-infected women  60.4% African American  17.6% Latina

Longitudinal: 3-year, semiannual follow-up visits

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Table 1. Review of HIV and Obesity Literature (Continued)

To compare the prevalence of insulin resistance and the associations of insulin resistance with body composition between HIVinfected adults in the NFHL study versus adults in the NHANES study

N 5 8,690 adults  378 nondiabetic HIV-infected men and women in the NFHL study  8,312 NHANES III population-based comparisons

Justman et al., 2008

To describe the longitudinal patterns of BMI, WHR, and waist and hip circumference among HIV-infected and uninfected women

N 5 1,208 women  942 HIV-infected (59% African American)  266 uninfected (62% African American)

Shor-Posner et al., 2000

To evaluate the effects of obesity on immune function, disease progression, and mortality

N 5 273 adult drug users  125 HIV-infected (82 men, 88.8% African American, 8% Hispanic)  148 uninfected (101 men, 72% African American, 12% Hispanic)

Prospective cross-sectional

Longitudinal: 5-year, semiannual follow-up visits

Longitudinal: 4-year, semiannual follow-up visits

HIV-infected women in the NFHL study were more overweight than HIVuninfected women in the NHANES III cohort. Factors associated with insulin resistance among the general population are also associated with it among HIV-infected subjects. BMI, waist circumference, and WHR were significantly higher among the insulin resistant HIV-infected subjects. BMI, waist and hip circumference, and WHR remained stable over 5 years among HIV-infected women but consistently increased among uninfected women. HIV-infected women had higher WHRs compared with uninfected women, despite lower BMIs and waist and hip measurements. Predictors of a larger WHR among HIV-infected women were White race, age, PI use, and higher CD4 count. ART use itself was not associated with BMI or WHR. Over an 18-month follow-up period, measurements of BMI among the HIVinfected cohort were inversely associated with progression to death, independent of CD4 cell count , 200 cells/mm3. Risk of declining CD4 cell counts was lower in overweight/obese participants than in nonobese participants. (Continued)

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Jones et al., 2005

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NOTE: ART 5 antiretroviral therapy, BMI 5 body mass index, CHD 5 coronary heart disease, CPCRA 5 Community Programs for Research on AIDS, HDL 5 high-density lipoprotein, NHANES 5 National Health and Nutrition Examination Survey, NFHL 5 Nutrition for Healthy Living, PI 5 protease inhibitor, WHR 5 waist-to-hip ratio.

Baseline prevalence of overweight was 12.6% among men and 32.5% among women. Female gender and lack of AIDS diagnosis were independently associated with overweight. Independent of baseline CD4 cell counts and time to the initiation of ART, overweight adults without AIDS had lower viral loads and experienced slower disease progression compared with participants who were not overweight. A lower baseline BMI and decreases in BMI over time were independent predictors of progression to AIDS. N 5 189 HIV-infected adults  103 men (54.4% Latino, 36.9% African American)  86 women (46.5% Latina, 45.3% African American) To determine the prevalence and predictive value of overweight and nonoverweight subjects in an urban HIV clinic

Design Participants Purpose

Reference Shuter et al., 2001

Table 1. Review of HIV and Obesity Literature (Continued)

Retrospective cross-sectional

Findings

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Several studies indicated that overweight/obesity was more prevalent than wasting. Amorosa et al. (2005) compared the prevalence of obesity and overweight among a large (N 5 1,689) urban population of HIV-infected participants; the majority were male, African American, and on ART. Obesity (14%, BMI $ 30 kg/m2) and overweight (31%, BMI 2529.9 kg/m2) were more common than wasting (9%, BMI # 20 kg/m2). Women and men were equally overweight (30% vs. 31%), although women were more likely to be obese than men (28% vs. 11%). Among women, African American race, nonsmoking status, and CD4 count at or above 200 cells/mL were associated with a greater BMI, whereas among men, only CD4 count at or above 200 cells/mL was associated with an increased BMI. BMI was not correlated with ART, treatment with a PI, or being antiretroviral-naive. Hodgson et al. (2001) also reported overweight/ obesity to be more prevalent than wasting among predominantly male, ART-treated, PLWH in South London, of whom half were White and half were Black African. Among 162 participants, 34% were overweight (BMI 25-29.9 kg/m2), 9% were obese (BMI $ 30 kg/m2), and 6% were wasted (defined as BMI , 18.5 kg/m2 in this study). Women had higher BMI values than men, and Black Africans had higher BMIs than Whites. Out of 15 obese participants, 12 (80%) were African women. Like Amorosa et al. (2005), Hodgson et al. (2001) reported no correlation between ART and being overweight or obese. Unlike the results seen by Hendricks et al. (2006) among the NFHL cohort, Justman et al. (2008) reported no indication of progressive obesity among an urban cohort of HIV-infected women followed over 5 years. HIV-infected (n 5 942) and uninfected women (n 5 266), the majority being African American, were recruited from the Women’s Interagency HIV Study, a multicenter cohort study started in 1994. At baseline, both groups had mean BMIs in the overweight range or higher, and the HIV-infected group had greater waist-to-hip ratios (WHRs) than the uninfected group (equivalent waist circumference in both groups, with smaller hip circumference in the HIV-infected than uninfected women). Over the study period, BMI, waist and hip circumference, and WHR remained stable among HIV-infected women but consistently increased among uninfected women. Despite

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lower BMIs and waist and hip measurements, HIVinfected women had higher WHRs, possibly because of nonequivalent hip circumference measures at baseline. Predictors of a larger WHR among these women were White race, age, PI use, and a higher CD4 cell count. ART was not associated with BMI or WHR. Most reports to date show a high prevalence of obesity in HIV-infected populations, with risk being greater among women and persons of color. Of note, obesity is now more prevalent than wasting. Additional studies are needed to clarify predictors of obesity within HIV-infected populations. Morbidities Several studies have examined metabolic abnormalities within HIV-infected populations. Danoff et al. (2005) compared the prevalence of prediabetes, diabetes, and insulin resistance among 258 women, 88 uninfected, 74 HIV-infected and not on ART, and 96 HIV-infected and on ART, from six urban clinical sites in the United States. The majority of participants in all groups were African American or Latina and overweight (BMI 25-29.9 kg/m2). The investigators reported that the frequency of prediabetes (17% uninfected; 17.6% HIV-infected not on ART, 11.5% HIV-infected on ART), diabetes (10.2% uninfected; 8.1% HIV-infected not on ART, 4.2% HIV-infected on ART), or insulin resistance (continuous data reported rather than frequencies) was not related to HIV status or ART. Increasing BMI was the only variable significantly associated with diabetes and prediabetes. Hadigan et al. (1999) also compared metabolic abnormalities within an HIV-infected female population. Investigators compared regional body composition, insulin, and lipids between a small population of HIV-infected women (n 5 75) and weight-matched uninfected controls (n 5 30). A small number (n 5 17) of HIVinfected subjects were on PIs. Compared with controls, HIV-infected women showed significant hyperinsulinemia, truncal adiposity, and increased insulin-to-glucose ratio. The largest elevation in insulin and the insulin-to-glucose ratio was reported among HIV-infected women with truncal adiposity, regardless of PI use. Additionally, among the entire HIV-infected cohort, insulin and glucose levels were correlated with BMI, whereas viral load was

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inversely correlated with BMI. Control patients were considerably younger than HIV-infected patients (mean age of 24 vs. 36), which may have affected the normative range applied to the HIV-infected cohort. Hadigan et al. (2001) reported that HIV-infected adults with lipodystrophy have considerable insulin resistance and hyperlipidemia. They compared 71 PLWH with lipodystrophy and 30 PLWH without lipodystrophy with age, sex, and BMI-matched controls from the Framingham Offspring Study, a population of healthy control subjects with known cardiovascular disease risk parameters. Compared with controls, HIV-infected participants with lipodystrophy had an increased WHR, increased waist circumference, decreased hip circumference, and decreased mid-thigh circumference. The lipodystrophy cohort was more likely to have reduced levels of highdensity lipoprotein, hypertriglyceridemia, impaired glucose tolerance, and diabetes. Except for highdensity lipoprotein levels, these cardiovascular disease risk factors were diminished among HIVinfected participants without lipodystrophy and were not significantly different from controls. HIVinfected participants with lipodystrophy also showed significant fasting hyperinsulinemia compared with Framingham control subjects. Among the lipodystrophy cohort, waist and thigh circumference were significant predictors of fasting insulin levels, whereas only waist circumference was a significant predictor for the matched controls. Other studies have compared the relationship between anthropometric measures and metabolic abnormalities in HIV-infected populations. Albu et al. (2007) examined the relationship between adipose tissue distribution and insulin resistance in a small sample of obese HIV-infected women recruited for a weight loss and exercise study. High whole-body intermuscular adipose tissue and low leg subcutaneous adipose tissue distribution, as measured by whole-body magnetic resonance imaging (MRI), were independently associated with insulin resistance in both obese HIV-infected and uninfected women. In another study, overweight was positively associated with fasting glucose among PI users, whereas waist circumference was positively associated with C peptide (Blass et al., 2008). In a study that compared HIV-infected subjects from

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the NFHL study, serum markers of insulin resistance differed significantly by BMI category for both men and women, as did triglycerides, blood pressure, and total cholesterol for men (Hendricks et al., 2006). Similarly, Brar et al. reported that a higher BMI was associated with diabetes mellitus in HIVinfected and uninfected adults (Brar et al., 2007). Finally, in a large study that compared body composition and insulin resistance among HIV-infected subjects from the NFHL study, BMI, waist circumference, and WHR were significantly higher among the insulin resistant HIV-infected subjects (Jones et al., 2005). A later study by Hadigan et al. (2003) examined the 10-year coronary heart disease (CHD) risk among an HIV-infected cohort with fat redistribution. HIV-infected men and women with and without fat redistribution were compared with age-, sex-, and BMI-matched Framingham control subjects. The 10year CHD risk estimate based on the Framingham risk equation was significantly greater among HIVinfected subjects with fat redistribution, particularly among men. However, when subjects were matched with controls by BMI and WHR, there was no longer a significant difference in the 10-year CHD risk estimate. Regardless of matching, HIV-infected patients without fat redistribution did not have an increased 10-year CHD risk estimate. Interestingly, the CHD risk estimate was greatest in HIV-infected patients with primary lipoatrophy, compared with patients who had either lipohypertrophy or mixed fat redistribution. Lipohypertrophy was defined as increased abdominal fat with or without increased neck fat and no evidence of peripheral fat atrophy. Mixed lipodystrophy was defined as both increased abdominal fat and peripheral fat atrophy. Although the Framingham equation has been validated in other patient populations, its validity for predicting coronary events among HIV-infected patients with fat redistribution and metabolic abnormalities is unknown. In most studies, metabolic abnormalities have been associated with HIV status, increased BMI, and lipodystrophy. Whether HIV status places persons at risk for cardiovascular disease remains uncertain, given the recent observation that PLWH without lipodystrophy did not have an increased 10year CHD risk estimate above control subjects.

Predictive Value as Related to Disease Progression A few studies have examined the relationship between BMI and disease progression among PLWH. Results from a study by Shor-Posner et al. (2000) suggested that obesity did not impair immune function among HIV-infected drug users and may in fact have been associated with better survival. The investigators compared the relationships between obesity and immune function, disease progression, and mortality in a longitudinal study of 125 HIV-infected drug users and 148 uninfected drug users, the majority of whom were African American. At baseline, overweight/ obesity (BMI $ 27) prevalence was 18% in the HIVinfected cohort and 29% in the uninfected cohort. No significant differences in immunologic parameters by BMI were reported in either cohort. Over an 18-month follow-up period, investigators reported that BMI measurements among the HIV-infected cohort were inversely related to progression to death, independent of CD4 cell count (, 200 cells/mm3); and that risk of declining CD4 cell counts was lower in overweight/obese participants than in nonobese participants. Shuter et al. (2001) reported similar results among 189 HIV-infected subjects recruited from an urban HIV clinic. Overweight men and women (BMI $ 27.8 and $ 27.3, respectively) without AIDS experienced slower disease progression and had lower viral loads than participants who were not overweight, despite similar time to the initiation of ARTand similar baseline CD4 cell counts. In addition, a lower baseline BMI and decreases in BMI over time were independent predictors of progression to AIDS. Jones et al. (2003) also reported a decreased risk of disease progression among overweight/obese HIVinfected subjects. In a longitudinal study of 871 HIVinfected women, of whom 60.4% were African American and 17.6% were Latina, prevalence of overweight (BMI $ 25 and , 30) or obesity ($ 30) was 49% at baseline. A higher BMI and increases in BMI were associated with a decreased risk of HIV progression and small increases in CD4 cell counts. A higher baseline BMI was also associated with a lower rate of occurrence of the first CD4 cell count at less than 200 cells/mm3. Estimated odds of death were 3.1 times greater among women in the underweight category (BMI , 20) than those in the

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obese category. Increases in BMI were likely associated with increases in fat mass as opposed to increases in lean body mass. In summary, extant research suggests that the prevalence of overweight and obesity is increasing in adult HIV-infected populations and is more prevalent than wasting. Diabetes, prediabetes, insulin resistance, and dyslipidemia are among the most commonly studied morbidities, and their occurrence is not unlike that reported in the overweight/obese U.S. population or those with metabolic syndrome. Only a handful of studies have examined the predictive value of obesity. Nonetheless, a higher BMI appears to be associated with decreased risk of disease progression and increases in CD4 cell counts.

Implications for Clinical Outcomes Whereas the studies reviewed provide evidence suggesting that PLWH who are overweight or obese fare better than those who are underweight or within a normal weight range in the short run, this may not be the case over the life span of an individual. Given the preliminary nature of data in this area, it would be premature to discount obesity as a significant risk factor in this population. Although it remains controversial as to whether the predicted CHD risk is greater in HIV-infected than noninfected persons, there are numerous reports indicating that rate of myocardial infarction (MI) is higher among HIV-infected than uninfected persons (Currier et al., 2008; Kaplan et al., 2007; Khunnawat, Mukerji, Havlichek, Touma, & Abela, 2008). Clinical imaging studies have shown an increased prevalence of subclinical atherosclerosis in PLWH on ART therapy (Mu, Chai, Lin, Yao, & Chen, 2007). Numerous factors have been proposed to contribute to higher rates of MI and subclinical atherosclerosis in this population, including damage to endothelial tissues by HIV infection, inflammatory changes within the vessel wall, and/or a state of hypercoagulation (Mu et al., 2007). Elevated levels of monocyte-derived proinflammatory cytokines not only are involved in the initiation and progression of vascular damage, but also contribute to fat redistribution and metabolic disorders associated with HIV infection (Torres & Nowson, 2007). Although it is not clear whether the increased MI rate can be reduced by

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decreasing viral load, pharmacologic management of metabolic alterations, or modifying lifestyle behaviors that are more prevalent among PLWH (e.g., smoking, high saturated fat intake), it is intuitive that these approaches would improve health outcomes. As such, clinicians are increasingly assessing and more aggressively treating cardiovascular risk factors in PLWH.

Recommendations for Patient Care Management Current strategies for assessing and managing overweight and obesity in PLWH parallel those recommended for the general U.S. population, such as greater physical activity and dietary adjustments. To date, results have been mixed on the safety and efficacy of other strategies, especially in individuals with HIV-associated visceral adiposity. For example, antiretroviral substitution has not been shown to consistently reverse visceral adiposity (Dreschler & Powderly, 2002) and, although growth hormone may reduce visceral adiposity and some lipid parameters, it may also produce glucose intolerance (Falutz et al., 2007; Lo et al., 2008). Similarly, metformin may promote weight loss, but it can also promote loss of subcutaneous fat and lean body mass (Kohli, Shevitz, Gorbach, & Wanke, 2007). Finally, surgery to remove excess adipose tissue may be offset by tissue regrowth and surgical complications such as infection and bleeding (Moyle, 2005). Body Composition Assessment BMI and waist circumference (fat distribution) are routinely used to assess weight status in both HIVinfected and non-HIV-infected individuals. Because it provides a more accurate measure of total body fat compared with weight alone, BMI is now the preferred method for assessing weight status. BMI can be estimated by equations using pounds/inches or kilograms/meters or by nomograms and automatic calculators available online, eliminating mathematical calculations. Overweight is defined as a BMI of 25 or greater, and obesity is defined as a BMI of 30 or greater (National Heart, Lung, and Blood Institute [NHLBI], 2000) (see Table 2). A limitation of BMI is

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that its accuracy can be affected by factors such as large muscle mass, muscle wasting, and edema. For example, an HIV-infected person with muscle wasting may have more fat than an HIV-infected person with no muscle wasting. In general, however, these factors do not significantly alter the accuracy of BMI as a measure for classifying individuals into broad categories of underweight, normal weight, overweight, and obesity. Waist circumference estimates intraabdominal fat or visceral adipose tissue (VAT), which is an independent risk factor for type 2 diabetes, hypertension, and cardiovascular disease. Awaist circumference over 40 inches in men and over 35 inches in women confers heightened risk for cardiovascular disease (NHLBI, 2000) (see Table 3). Because a number of PLWH may have increased abdominal girth within the context of ART, it is helpful to distinguish whether increased waist circumference is accompanied by other characteristics of lipodystrophy or lipodystrophy syndrome such as loss of subcutaneous fat or dyslipidemia. MRI and computed tomography imaging techniques are used to more precisely evaluate VAT and subcutaneous adipose tissue in research studies, but they are currently impractical for routine clinical use. WHR is another common measure used to assess intraabdominal obesity, and a high WHR (. .9 in men and . .85 in women) is often used to diagnose metabolic syndrome (World Health Organization, 1999). Given that the WHR ratio may under- or overestimate waist circumference in PLWH with VAT, it is unclear whether WHR is an accurate measure for all HIVinfected patients (Engleson et al., 1999; Kotler, Rosenbaum, Wang, & Pierson, 1999; Wohl et al., 2006). Weight Reduction Lifestyle modifications for successful weight loss include (a) reducing calorie intake; (b) increasing physical activity; (c) monitoring food intake, physical activity, and weight; (d) setting realistic weight loss goals; and (e) assessing and managing stress. To be successful, weight loss initiatives must also take into account patient preferences, lifestyle, and readiness to lose weight. Reducing calorie intake. Short-term calorie reduction can be accomplished by reducing sugar

Table 2.

Classifications for Body Mass Index

Weight Class

Body Mass Index , 18.5 18.5-24.9 25-29.9 30-34.9 35-39.9 . 39.9

Underweight Normal Weight Overweight Obesity (Class 1) Obesity (Class 2) Extreme obesity (class 3)

SOURCE: National Heart, Lung, and Blood Institute (2000).

and fat consumption and monitoring portion size. Diets that reduce calorie intake by 500 to 1,000 calories per day will result in a weight loss of 1 to 2 pounds per week. Many overweight and obese individuals are unaware of the gradual effects of portion distortion or portion ‘‘creep’’ on overall calorie intake; for example, 20 years ago the average bagel was 3 inches in diameter and contained 140 calories; today, the average bagel is 6 inches in diameter and contains 350 calories. Similarly, the average portion of French fries 20 years ago contained 210 calories, and a current average portion contains 610 calories (NHLBI, 2008). Adding to the problem is the fact that nearly one in five meals is eaten away from home, and foods eaten away from home result in significantly higher intake of calories (Lin & Guthrie, 1999). Even so-called healthy foods such as a large fruit smoothie may contain more than 500 calories, and a couple of pieces of Chicago-style deep-dish sausage pizza may exceed 1,000 calories. Long-term dietary adjustments are more likely to be effective when they incorporate educational information such as reading food labels, maintaining consistent eating patterns, reducing fast-food and sweetened beverage consumption, snacking on fresh fruits and vegetables, increasing fiber intake, shopping for groceries after a full meal, eating slowly and savoring each bite, serving food on a smaller plate, and avoiding all-you-can-eat buffets. Recently, Shai et al. (2008) compared weight loss with lowTable 3.

High-Risk Waist Circumference

Gender

Inches

Centimeters

Men Women

. 40 in . 35 in

. 102 cm . 88 cm

SOURCE: National Heart, Lung, and Blood Institute (2000).

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carbohydrate, nonrestricted calorie diets; Mediterranean, restricted calorie diets; and low-fat, restricted calorie diets in a 2-year randomized trial. All three diets were safe and effective in producing sustained weight loss, allowing for some individualization and flexibility of approach. Such flexibility is needed, given the context of ART and urban environments with limited food choices. Increasing physical activity. Exercise is also crucial for weight loss. Current physical activity guidelines recommend 30 to 60 minutes per day of moderate to vigorous physical activity (Haskell et al., 2007; Kumanyika et al., 2008). It is estimated that fewer than 10% of adults in the United States meet these guidelines (Centers for Disease Control and Prevention, 2005). Some strategies to counter a sedentary lifestyle are taking the stairs, walking more and driving less, participating in recreational activities such as swimming, and spending less time watching television and using the computer. A recent meta-analysis indicates that progressive resistive exercise and/or aerobic exercise is safe and improves body composition and lipid parameters in PLWH (O’Brien, Nixon, Glazier, & Tynan, 2007). Monitoring. Daily records of physical activity, food intake, and weight help to identify any slips or triggers before they turn into large weight regains. A recent study reported that keeping food and physical activity records significantly improves weight loss and that the longer records are kept, the more weight is lost (Hollis et al., 2008). Setting realistic weight loss goals. Perhaps prompted by popular get-thin TV shows such as The Biggest Loser, it is not uncommon to set lofty weight loss goals. However, even a 5% to 10% reduction in weight is associated with improved health and well-being and fewer obesity-related comorbidities such as type 2 diabetes, heart disease, and sleep apnea (Knowler et al., 2002). Stress management. Assessing for and managing stress is also critical in the treatment of obesity and metabolic disturbances in PLWH. It is well-recognized that activation of the hypothalamic-pituitary-adrenal axis during a psychosocial stress response increases total cortisol release over the course of a day (Nieuwen-

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huizen & Rutters, 2008). Chronically elevated levels of cortisol selectively contribute to central fat deposition, which is more metabolically active than other fat stores (Bjorntorp, 1996), and influence eating behaviors (Torres & Nowson, 2007). There is evidence to suggest that overweight and obese individuals will benefit by incorporating stress management/psychological interventions into weight management programs (Innes, Vincent, & Taylor, 2007; Shaw, O’Rourke, Del Mar, & Kenardy, 2005).

Recommendations for Research The following research recommendations identify unanswered questions and outstanding gaps in the evidence. The recommendations encompass early identification of risk factors, prevention and management strategies, and health outcome effects.  Identify additional valid and reliable measures that are practical, feasible, and less costly than current measures (i.e., MRI and computed tomography scans) for assessing body composition in overweight and obese PLWH.  Clarify the role of HIV infection, ART, and metabolic derangements in the development of overweight and obesity.  Examine the similarities and dissimilarities between metabolic syndrome and lipodystrophy in PLWH.  Study the contribution of diet to obesity, lipodystrophy syndrome, and metabolic syndrome in PLWH.  Examine nutritional, physical activity, stress management, and behavioral strategies to achieve weight loss and improve body composition in PLWH with obesity, lipodystrophy syndrome, and metabolic syndrome.  Determine the effects of overweight and obesity on clinical outcomes in PLWH.

Conclusions Recent developments in the prevalence, morbidities, and predictive value of overweight and obesity

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in PLWH emphasize the need for greater attention to early evaluation and management strategies. Whereas a significant proportion of PLWH with overweight and obesity may respond to conventional weight reduction and physical activity strategies, it is unclear which strategies are most effective, especially for better clinical outcomes and long-term maintenance. Currently, a few clinical trials of assessment and management strategies are under way. It is anticipated that the results of ongoing and future trials will provide additional evidence for future recommendations for the management of overweight and obese individuals with HIV infection.

Clinical Considerations  In addition to other metabolic abnormalities, it is important to assess HIV-infected individuals for overweight/obesity.  Nurses can help patients implement appropriate lifestyle modifications for weight reduction such as reduced calorie intake and increased physical activity.  The benefits of modest weight loss of 5% to 10% include improvements in physical functioning, quality of life, blood pressure, and glucose and lipid parameters.

References Albu, J. B., Kenya, S., He, Q., Wainwright, M., Berk, E. S., Heshka, S., et al. (2007). Independent associations of insulin resistance with high whole-body intermuscular and low leg subcutaneous adipose tissue distribution in obese HIV-infected women. American Journal of Clinical Nutrition, 86, 100-106. Amorosa, V., Synnestvedt, M., Gross, R., Friedman, H., MacGregor, R. R., Gudonis, D., et al. (2005). A tale of 2 epidemics: The intersection between obesity and HIV infection in Philadelphia. Journal of Acquired Immune Deficiency Syndromes, 39, 557-561. Bjorntorp, P. (1996). The regulation of adipose tissue distribution in humans. International Journal of Obesity and Related Metabolic Disorders, 20(4), 291-302. Blass, S. C., Ellinger, S., Vogel, M., Ingiliz, P., Spengler, U., Stehle, P., et al. (2008). Overweight HIV patients with

abdominal fat distribution treated with protease inhibitors are at high risk for abnormalities in glucose metabolism: A reason for glycemic control. European Journal of Medical Research, 13, 209-214. Brar, I., Shuter, J., Thomas, A., Daniels, E., & Absalon, J.: Minorities and Women’s Task Force of Terry Beirn Community Programs for Clinical Research on AIDS (2007). A comparison of factors associated with prevalent diabetes mellitus among HIV-infected antiretroviral-naive individuals versus individuals in the national health and nutritional examination survey cohort. Journal of Acquired Immune Deficiency Syndromes, 45, 66-71. Carr, A., Samaras, K., Burton, S., Law, M., Freund, J., Chisholhm, D., et al. (1998). A syndrome of peripheral lipodystrophy, hyperlipidemia and insulin resistance in patients receiving HIV protease inhibitors. AIDS, 14, F25-F32. Centers for Disease Control and Prevention. (2005). Adult participation in recommended levels of physical activity— United States, 2001 and 2003. Morbidity Mortality Weekly Report, 54, 1208-1212. Currier, J. S., Lundgren, J. D., Carr, A., Klein, D., Sabin, C. A., Sax, P. E., et al. (2008). Epidemiological evidence for cardiovascular disease in HIV-infected patients and relationship to highly active antiretroviral therapy. Circulation, 118, e29e35. Danoff, A., Shi, Q., Justman, J., Mulligan, K., Hessol, N., Robison, E., et al. (2005). Oral glucose tolerance and insulin sensitivity are unaffected by HIV infection or antiretroviral therapy in overweight women. Journal of Acquired Immune Deficiency Syndromes, 39, 55-62. Dreschler, H., & Powderly, W. G. (2002). Switching effective antiretroviral therapy: A review. Clinical Infectious Diseases, 35, 1219-1230. Engleson, E. S., Kotler, D. P., Tan, Y., Agin, D., Wang, J., Pierson, R. N., et al. (1999). Fat distribution in HIV-infected patients reporting truncal enlargement quantified by wholebody magnetic resonance imaging. American Journal of Clinical Nutrition, 69, 1162-1169. Falutz, J., Allas, S., Blot, K., Potvin, D., Kotler, D., Somero, M., et al. (2007). Metabolic effects of a growth hormonereleasing factor in patients with HIV. New England Journal of Medicine, 357, 2359-2370. Ford, E. S., Giles, W. H., & Dietz, W. H. (2002). Prevalence of the metabolic syndrome among U.S. adults. Journal of the American Medical Association, 287, 356-359. Grundy, S. M., Brewer, H. B., Jr., Cleeman, J. I., Smith, S. C., Jr., & Lenfant, C. (2004). Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/ American Heart Association Conference on Scientific Issues Related to Definition. Circulation, 109, 433-438. Hadigan, C., Meigs, J. B., Corcoran, C., Rietschel, P., Piecuch, S., Basgoz, N., et al. (2001). Metabolic abnormalities and cardiovascular disease risk factors in adults with human immunodeficiency virus infection and lipodystrophy. Clinical Infectious Diseases, 32, 130-139.

Keithley et al. / Review of HIV Infection and Obesity Hadigan, C., Meigs, J. B., Wilson, P. W., D’Agostino, R. B., Davis, B., Basgoz, N., et al. (2003). Prediction of coronary heart disease risk in HIV-infected patients with fat redistribution. Clinical Infectious Diseases, 36, 909-916. Hadigan, C., Miller, K., Corcoran, C., Anderson, E., Basgoz, N., & Grinspoon, S. (1999). Fasting hyperinsulinemia and changes in regional body composition in human immunodeficiency virus-infected women. Journal of Clinical Endocrinology & Metabolism, 84, 1932-1937. Haskell, W. L., Lee, I. M., Pate, R. R., Powell, K. E., Blair, S. N., Franklin, B. A., et al. (2007). Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Medicine and Science in Sports Exercise, 39, 1423-1434. Heath, K. V., Hogg, R. S., Singer, J., Chan, K. J., O’Shaughnessy, M. W., & Montaner, J. S. (2002). Antiretroviral treatment patterns and incident HIV-associated morphologic and lipid abnormalities in a population-based cohort. Journal of Acquired Immune Deficiency Syndrome, 30, 440447. Hendricks, K. M., Willis, K., Houser, R., & Jones, C. Y. (2006). Obesity in HIV-infection: Dietary correlates. Journal of the American College of Nutrition, 25, 321-331. Hodgson, L. M., Ghattas, H., Pritchitt, H., Schwenk, A., Payne, L., & Macallan, D. C. (2001). Wasting and obesity in HIV outpatients. AIDS, 15, 2341-2342. Hollis, J. F., Gullion, C. M., Stevens, V. J., Brantley, P. J., Appel, L. J., Ard, J. D., et al. (2008). Weight loss during the intensive intervention phase of the weight-loss maintenance trial. American Journal of Preventive Medicine, 35, 118-126. Innes, K. E., Vincent, H. K., & Taylor, A. G. (2007). Chronic stress and insulin resistance-related indices of cardiovascular disease risk, part 2: A potential role for mind-body therapies. Alternative Therapies in Health and Medicine, 13, 44-51. Jacobson, D. L., Tang, A. M., Spiegelman, D., Thomas, A. M., Skinner, S., Gorbach, S. L., et al. (2006). Incidence of metabolic syndrome in a cohort of HIV-infected adults and prevalence relative to the U.S. population. Journal of Acquired Immune Deficiency Syndromes, 43, 458-466. Jones, C. Y., Hogan, J. W., Snyder, B., Klein, R. S., Rompalo, A., Schuman, P., et al. (2003). Overweight and human immunodeficiency virus (HIV) progression in women: Associations between HIV disease progression and changes in body mass index in women in the HIV epidemiology research study cohort. Clinical Infectious Diseases, 37(Suppl. 2), S69-S80. Jones, C. Y., Wilson, I. B., Greenberg, A. S., Shevitz, A., Knox, T. A., Gorbach, S. L., et al. (2005). Insulin resistance in HIV-infected men and women in the nutrition for healthy living cohort. Journal of Acquired Immune Deficiency Syndromes, 40, 202-211. Justman, J. E., Hoover, D. R., Shi, Q., Tan, T., Anastos, K., Tien, P. C., et al. (2008). Longitudinal anthropometric patterns among HIV-infected and HIV-uninfected women.

273

Journal of Acquired Immune Deficiency Syndromes, 47, 312-319. Kaplan, R. C., Kingsley, L. A., Sharrett, A. R., Li, X., Lazar, J., Tien, P. C., et al. (2007). Ten-year predicted coronary heart disease risk in HIV-infected men and women. Clinical Infectious Diseases, 45, 1074-1081. Khunnawat, C., Mukerji, S., Havlichek, D., Touma, R., & Abela, G. S. (2008). Cardiovascular manifestations in human immunodeficiency virus-infected patients. American Journal of Cardiology, 102, 635-642. Knowler, W. C., Barrett-Connor, E., Fowler, S. E., Hamman, R. F., Lachin, J. M., Walker, E. A., et al. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 364, 393-403. Kohli, R., Shevitz, A., Gorbach, S., & Wanke, C. (2007). A randomized placebo-controlled trial of metformin for the treatment of HIV lipodystrophy. HIV Medicine, 8, 420-426. Kotler, D. P., Rosenbaum, K., Wang, J., & Pierson, R. N. (1999). Studies of body composition and fat distribution in HIV-infected and control subjects. Journal of Acquired Immune Deficiency Syndrome and Human Retrovirology, 20, 228-237. Kumanyika, S. K., Obarzenek, E., Stettler, N., Bell, R., Field, A. E., Fortmann, S. P., et al. (2008). Population-based prevention of obesity: The need for comprehensive promotion of healthful eating, physical activity, and energy balance. Circulation, 118, 428-464. Lin, B., & Guthrie, J. E. (1999). Nutrient contribution of food away from home. Washington, DC: U.S. Department of Agriculture, Economic Research Service. Lo, J., You, S. M., Canavan, B., Liebau, J., Beltrani, G., Koutkia, P., et al. (2008). Low-dose physiological growth hormone in patients with HIV and abdominal fat accumulation: A randomized controlled trial. Journal of the American Medical Association, 300, 509-519. Mondy, K., Overton, E. T., Grubb, J., Tong, S., Seyfried, W., Powderly, W., et al. (2007). Metabolic syndrome in HIVinfected patients from an urban, midwestern U.S. outpatient population. Clinical Infectious Diseases, 44, 726-734. Moyle, G. J. (2005). Plastic surgical approaches for HIV-associated lipoatrophy. Current HIV/AIDS Reports, 2, 127-131. Mu, H., Chai, H., Lin, P., Yao, Q., & Chen, C. (2007). Current update on HIV-associated vascular disease and endothelial dysfunction. World Journal of Surgery, 31, 632-643. National Heart, Lung, and Blood Institute Education Initiative. (2000). The practical guide: Identification, evaluation, and treatment of overweight and obesity in adults. Washington, DC: National Institutes of Health. National Heart, Lung, and Blood Institute. (2008). Portion distortion. Retrieved September 23, 2008, from http:// hp2010.nhlbihin.net/portion/ Nieuwenhuizen, A. G., & Rutters, F. (2008). The hypothalamicpituitary-adrenal-axis in the regulation of energy balance. Physiology and Behavior, 94, 69-177. O’Brien, K., Nixon, S., Glazier, R. H., & Tynan, A. M. (2007). Progressive resistive exercise interventions for adults

274 JANAC Vol. 20, No. 4, July/August 2009 living with HIV/AIDS. Cochrane Database of Systematic Reviews, 2. Ogden, C. L., Carroll, M. D., Curtin, L. R., McDowell, M. A., Tabak, C. J., & Flegal, K. M. (2006). Prevalence of overweight and obesity in the United States, 1999-2004. Journal of the American Medical Association, 295, 1549-1555. Pao, V., Lee, G. A., & Grunfeld, C. (2008). HIV therapy, metabolic syndrome, and cardiovascular risk. Current Atherosclerosis Reports, 10, 61-70. Samaras, K., Wand, H., Law, M., Emery, S., Cooper, D., & Carr, A. (2007). Prevalence of metabolic syndrome in HIVinfected patients receiving highly active antiretroviral therapy using International Diabetes Foundation and Adult Treatment Panel III criteria. Diabetes Care, 30, 113-119. Shai, I., Schwarzfuch, D., Henkin, Y., Shahar, D., Witkow, S., Greenberg, I., et al. (2008). Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. The New England Journal of Medicine, 359, 229-241. Shaw, K., O’Rourke, P., Del Mar, C., & Kenardy, J. (2005). Psychological interventions for overweight or obesity. Cochrane Database of Systematic Reviews, 2, CD003818. Shevitz, A.H., & Knox, T.A. (2001). Nutrition in the era of highly active antiretroviral therapy. Clinical Infectious Diseases, 32, 1769–1775. Erratum in Clinical Infectious Diseases, 33, 1445. Shor-Posner, G., Campa, A., Zhang, G., Persaud, N., MiguezBurbano, M. J., Quesada, J., et al. (2000). When obesity is desirable: A longitudinal study of the Miami HIV-1-infected drug abusers (MIDAS) cohort. Journal of Acquired Immune Deficiency Syndromes, 23, 81-88. Shuter, J., Chang, C. J., & Klein, R. S. (2001). Prevalence and predictive value of overweight in an urban HIV care clinic. Journal of Acquired Immune Deficiency Syndromes, 26, 291-297. Tang, A. M., Jacobson, D. L., Spiegelman, D., Knox, T. A., & Wanke, C. (2005). Increasing risk of 5% or greater unintentional weight loss in a cohort of HIV-infected patients, 1995 to 2003. Journal of Acquired Immune Deficiency Syndromes, 40, 70-76. Torres, S. J., & Nowson, C. A. (2007). Relationship between stress, eating behavior, and obesity. Nutrition, 23, 887-894. Wohl, D. A., McComsey, G., Tebas, P., Brown, T. T., Glesby, M. J. M., Reeds, D., et al. (2006). Current concepts in the diagnosis and management of metabolic complications of HIV infection and its therapy. HIV/AIDS, 43, 645-653. World Health Organization. (1999). Definition, diagnosis and classification of diabetes mellitus and its complications: Report of a WHO consultation. Part 1: Diagnosis and classification of diabetes mellitus. Retrieved September 20, 2008, from http://www.staff.ncl.ac.uk/philip.home/who_dmc.htm