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Obesity on the rise in African American women on anti-HIV treatment
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Authors conclude:.... Our data suggest that being overweight or obese is common in an urban HIV population....
NEW YORK (Reuters Health) - In the modern HIV therapeutic era, obesity is more common than wasting and women, especially African American women, appear to be particularly at high risk, research suggests.
In the August 15th Journal Acquired Immune Deficiency Syndromes, the study team voices concern that obesity "might add to the metabolic abnormalities associated with HIV or its treatment and contribute to morbidity, as patients with HIV live longer."
Dr. Valerianna Amorosa and colleagues from the University of Pennsylvania explored the prevalence of overweight and obesity in 1689 HIV-infected individuals from Philadelphia.
Among them, 31% of subjects were overweight with a BMI of 25 to 29 and 14% were obese with a BMI of 30 or higher. In contrast, just 9% suffered from wasting.
Obesity and overweight were prevalent in this HIV-infected population but not more so than in the general population, the authors note.
While the prevalence of overweight was similar in women and men (30% vs 31%), women far surpassed men in the prevalence of obesity (28% vs 11%, p < 0.001).
Among women, African American race and a CD4 count of 200 cells per microliter or greater were associated with overweight and obesity with odds ratios of 1.8 and 2.8, respectively. Among men, only a CD4 count of 200 cells per microliter or greater was associated with increased BMI, with an odds ratio of 1.6.
Among a subset of patients for whom lipid and glucose values were available, BMI was positively correlated with cholesterol, triglyceride, and glucose levels, which "suggests an elevated prevalence of metabolic syndrome in our overweight population," the researchers point out.
The fact that 46% of study subjects were smokers is also noteworthy, they write. "Given the potentially increased risk of vascular disease and malignancy in HIV, the high prevalence of smoking in the cohort may be of even more deleterious consequences than obesity," they suggest.
J Acquir Immune Defic Syndr 2005;39:557-561.
A Tale of 2 Epidemics: The Intersection Between Obesity and HIV Infection in Philadelphia
JAIDS Journal of Acquired Immune Deficiency Syndromes: Volume 39(5) 15 August 2005
Amorosa, Valerianna MD*; Synnestvedt, Marie MSEd; Gross, Robert MD, MSCE*; Friedman, Harvey MD*; MacGregor, Rob Roy MD*; Gudonis, Debie LPN*; Frank, Ian MD*; Tebas, Pablo MD*
From the *Division of Infectious Diseases, University of Pennsylvania, Philadelphia, PA; and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA.
Greater than 20.0% of American adults fulfill the National Institutes of Health (NIH) definition of obesity, with a body mass index (BMI) ≥30 kg/m2, whereas more than half of US adults are considered overweight, with a BMI ≥25 kg/m2.1-4 Beyond obesity, the metabolic syndrome, characterized by truncal obesity, hypertension, hypertriglyceridemia, insulin resistance, and concomitant increased cardiovascular risk, is extremely common in the United States, with an overall 22% prevalence.5 Studies that have directly addressed obesity in HIV-infected patients quantify the relatively slower progression to AIDS and the survival advantage afforded by elevated BMI in the era before successful chronic viral suppression.9-11 Now, in the highly active antiretroviral therapy (HAART) era, although some HIV-infected patients are still afflicted with wasting,12 we have observed that obesity is a significant issue in our HIV-infected population, especially among women.
The purpose of this cross-sectional study was to explore the prevalence of overweight and obesity in an HIV population receiving care at 4 affiliated hospitals in urban Philadelphia. To begin to evaluate the association between weight and metabolic abnormalities, we analyzed the relation between BMI and serum cholesterol, triglycerides, and glucose levels.
Abstract
Background: Obesity and HIV infection are ongoing epidemics in the United States. Obesity predisposes to diabetes and cardiovascular disease, which are complications also associated with HIV and/or its treatment.
Objective: To determine the prevalence and risk factors for overweight and obesity in HIV-infected individuals.
Design and Setting: Retrospective cross-sectional study in which 1689 patients enrolled in the University of Pennsylvania Center for AIDS Research Adult/Adolescent Database at 1 university hospital clinic, 2 affiliated practices, and 1 Veterans Administration clinic in Philadelphia had demographic, social, and medical data collected prospectively since 1999.
Participants: Body mass index (BMI) data were available for 1669 HIV-infected subjects: 78% were men, and 60% were African American. The median CD4 count was 381 cells/mL, 47% of subjects had a viral load <400 copies/mL, and 9% of subjects were treatment naive.
Main Outcome Measures: The prevalence and risk factors for overweight (BMI: 25-29.9 kg/m2) and obesity (BMI ≥30 kg/m2) in HIV-infected subjects.
Results: Obesity and overweight were more prevalent than wasting (14%, 31%, and 9%, respectively; P < 0.0005), but they were not more common than in the general population. Although women and men were equally overweight (30% vs. 31%), women were more obese than men (28% vs. 11%; P < 0.001). Among women, African American race (odds ratio [OR] = 1.8, 95% confidence interval [CI]: 1.1-2.9) and a CD4 count ≥200 cells/mL (OR = 2.8, 95% CI: 1.6-4.9) were associated with overweight and obesity. Among men, only a CD4 count ≥200 cells/mL (OR = 1.6, 95% CI: 1.04-2.4) was associated with increased BMI. In men and women, smoking was associated with decreased obesity and overweight (OR = 0.59, 95% CI: 0.47-0.74 and OR = 0.65, 95% CI: 0.43-0.98, respectively). Age, income, employment, education, past or current intravenous drugs, being on HIV treatment, and viral load were not associated with obesity in the multivariate model. There was a positive correlation between BMI and total cholesterol, triglycerides, and glucose.
Conclusion: Obesity is more common than wasting in this therapeutic era. Women, particularly those of African American race, are at high risk. Obesity might add to metabolic abnormalities associated with HIV or its treatment and contribute to morbidity, as patients with HIV live longer.
AUTHOR DISCUSSION
Our data suggest that being overweight or obese is common in an urban HIV population, a reflection of the obesity epidemic in Philadelphia. Although the prevalences of overweight and obesity were not more common than in the general population, the prevalence of frank obesity was increased among HIV-infected women compared with men in our cross-sectional cohort. Female sex, CD4 cell count, and nonsmoking status correlated with obesity and overweight within the overall group. A CD4 count ≥200 cells/mL was the only factor significantly associated with obesity and overweight in men and women in the multivariate model. Among the subset of patients for whom lipid and glucose laboratory data were available, the positive correlation of BMI with cholesterol, triglyceride, and glucose levels suggests an elevated prevalence of the metabolic syndrome in our overweight population. Although not proving causation, because of the cross-sectional nature of the study design, these data suggest that overweight or obesity may contribute to the dyslipidemia and insulin resistance in our population of HIV-infected patients. Of note, 46% of our subjects were smokers. Given the potentially increased risk of vascular disease and malignancy in HIV, the high prevalence of smoking in the cohort may be of even more deleterious consequence than obesity.
Women far surpassed men in prevalence of obesity, even when factoring other risks, including the women's earlier stage of disease as assessed by CD4+ cell count, their lower overall income level, and their lower overall education level. Frank obesity was 2.6 times as common in women in comparison with the overall population of Philadelphia, in which obesity is 1.2 times as common in women. To our knowledge, this is the first study directly addressing risk factors for obesity in HIV-infected patients and directly comparing men and women. In young women, obesity can be associated with poor self-esteem and, subsequently, less negotiation of condom use,15 which could lead to an increased risk of HIV infection among overweight and obese women. This is a potential explanation for the HIV-infected cohort's dramatically wider gender disparity in obesity compared with the general population. Because of the association of AIDS with progressive and dramatic wasting, despite potential morbidities, some HIV-infected patients may favor maintaining elevated weight to serve as a protective cushion against future wasting or may believe that being overtly overweight masks their disease from friends or acquaintances. Further study may refine our understanding of this potential barrier to maintaining a healthy weight.
For the patients in whom specific antiretroviral regimens were known, no correlation was seen between BMI and being antiretroviral naive, being on HAART currently, or PI use. Because we did not examine longitudinal data in patients initiating treatment with specific agents, we were unable to assess whether certain antiretroviral regimens are associated with more weight gain than others. Although others have demonstrated changes in body composition in patients on PIs,16 increases in total fat mass specifically associated with certain drugs have not been published.
Given that our population is from a single US city with a high prevalence of obesity, our results may not be reflective of HIV patients throughout the United States, much less the world. A limitation in our analysis of the relation between BMI and lipid and glucose levels is our lack of data on the subjects' fasting state at the time of phlebotomy and additional anthropometric measurements; it is possible that the overweight and obese subjects might have been more likely to be nonfasting at phlebotomy than the others, which would influence their higher triglyceride and glucose levels. Longitudinal follow-up rather than cross-sectional data could elucidate associations not noted here for associations of obesity and overweight with particular antiretroviral regimens.
Because the major consequences of obesity take years to emerge, further longitudinal data are needed to quantify adverse sequelae within the HIV-infected population. Although BMI is an adequate tool to study obesity on the population-based level, differences in body habitus, particularly the presence of abdominal obesity, the degree of metabolic derangement, and an individual's family history, are better markers of risk in a given patient. In an obese patient with abnormal metabolic characteristics, lifestyle modification and weight loss interventions to achieve a healthy weight are likely to be beneficial. Optimum intervention strategies need to be established.
RESULTS
The Penn CFAR-AAD included 1689 patients 18 years of age or older whose first encounter occurred before June 1, 2003, with BMI data available on 1669 patients. The database questionnaire was modified in October 2002 to include current antiretroviral medications; therefore, 1132 patients were included in the analyses of obesity and overweight and treatment.
Table 1 shows the overall characteristics of the study population. Most were male. Women were younger and more likely to be African American and had a higher median CD4 count than men (402 cells/mL, interquartile range [IQR]: 222-402 cells/mL vs. 378 cells/mL, IQR: 223-581 cells/mL; P < 0.001). BMI was normally distributed for each sex. The mean BMI in men was 24.9 kg/m2 (95% CI: 24.7-25.1 kg/m2), and in women, it was 27.5 kg/m2 (95% CI: 26.8-28.3 kg/m2). The prevalence of obesity in women was 28.3% versus 10.7% in men (OR = 3.3, 95% CI: 2.4-4.4; Fig. 1A). The combined prevalence of overweight and obesity in women was 58.2% versus 42.3% in men (OR = 1.9, 95% CI: 1.5-2.4). Obesity was most common in African American women, with a 30% prevalence, whereas the prevalence in African American men was 13.4% (OR = 2.8, 95% CI: 2.0-3.8). In contrast, the prevalence of overweight in African American women was 31.4%, and it was 29.7% in African American men (OR = 1.1, 95% CI: 0.81-1.5). Of non-African American women, 22.5% were obese compared with 7.5% of non-African American men (OR = 3.6, 95% CI: 1.9-6.6), whereas 25% were overweight compared with 33.9% of men (OR = 0.65, 95% CI: 0.38-1.1).
We performed stratified analyses to determine factors associated with obesity and overweight. In a univariate analysis, factors correlating with obesity and overweight in men were CD4 count ≥200 cells/mL (OR = 1.8, 95% CI: 1.4-2.5) and undetectable viral load (relative risk [RR] = 1.3, 95% CI: 1.02-1.6). Current cigarette smoking was protective (OR = 0.59, 95% CI: 0.47-0.74). Among women, being African American (OR = 1.8, 95% CI: 1.1-2.9) and having a CD4 count of ≥200 cells/mL (OR = 2.8, 95% CI: 1.6-4.9) were significantly associated with obesity, and cigarette smoking was also protective (OR = 0.65, 95% CI: 0.43-0.98). No significant correlation was found for employment status, education status, yearly income, history of IVDU or NIVDU, being antiretroviral naive, currently being on HAART, currently being on a PI, or, among women, HIV viral load. There was no significant correlation between BMI and age for men or women.
The multivariate models for obesity included potential confounding factors, such as age, employment status, education level, IVDU and NIVDU, naive status, current HAART use, current PI use, and HIV viral load in addition to factors found significant in the univariate models: sex, race, CD4 cell count, and smoking status. In the multivariate analysis in men, having a CD4 count ≥200 cells/mL remained associated with obesity and overweight (OR = 1.6, 95% CI: 1.04-2.40), whereas cigarette smoking remained protective (OR = 0.61, 95% CI: 0.44-0.83). In women, being African American (OR = 4.6, 95% CI: 1.9-11.1) and having a CD4 count ≥200 cells/mL (OR = 3.2, 95% CI: 1.1-8.8) were associated with obesity and overweight.
We compared the age-adjusted prevalence of obesity and overweight within our cohort with that of Philadelphia at large, stratified by sex, race, and age group. In African American men, the city rate was 27% greater than in the HIV-infected cohort: 20% greater in non-African American men and 10.8% greater in African American women (all P < 0.001). In non-African American women, the rate was 48% compared with the 46% city rate (P > 0.5). In the age-stratified comparison with Philadelphia, the prevalence of obesity and overweight in the cohort was similar to that of the overall Philadelphia population in those aged 18 to 29 years (P = 0.43) and those aged 65 years or greater (P = 0.41). Obesity and overweight were less prevalent in the cohort than in the Philadelphia population in those aged 30 to 44 years and those aged 45 to 64 years (P = 0.0001 and P < 0.0001, respectively).
Data on lipids within 90 days of the weight used to calculate the BMI were available in 349 patients (20% of the cohort, 280 men and 69 women), and data on glucose in were available in 744 patients (44% of the cohort, 522 men and 222 women). Lipid data were more commonly available for patients who were nonsmokers on PIs having higher CD4+ cell counts and higher BMIs than the group as a whole (all P < 0.01). Glucose levels were checked more frequently in older women of low income (P < 0.01). There were weak positive correlations between BMI and total cholesterol, non-HDL cholesterol, triglycerides, and glucose overall (p = 0.14, 95% CI: 0.04-0.24; p = 0.17, 95% CI: 0.0-0.27; p = 0.14, 95% CI: 0.4-0.24; and p = 0.15, 95% CI: 0.08-0.22, respectively). Among men, there were also weak positive correlations between BMI and total cholesterol, non-HDL cholesterol, triglycerides, and glucose (p = 0.17, 95% CI: 0.06-0.28; p = 0.18, 95% CI: 0.07-0.29; p = 0.17, 95% CI: 0.06-0.28; and p = 0.16, 95% CI: 0.07-0.25, respectively). In women, probably because of the small sample size, there were no statistically significant correlations between BMI and cholesterol, non-HDL cholesterol, triglycerides, or glucose (p = -0.03, 95% CI: -0.27-0.21; p = 0.08, 95% CI: -0.16-0.32; p = 0.12, 95% CI: -0.08-0.32; and p = 0.13, 95% CI: -0.01-0.27, respectively).
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