Associations among Body Composition, Androgen Levels, and Human Immunodeficiency Virus Status in Adolescents

Journal of Adolescent Health 39 (2006) 164 –173

Original article

Associations among Body Composition, Androgen Levels, and Human Immunodeficiency Virus Status in Adolescents Anna-Barbara Moscicki, M.D.a,*, Jonas H. Ellenberg, Ph.D.b, Debra A. Murphy, Ph.D.c, and Xu Jiahong, M.P.H.d b

a Department of Pediatrics, University of California, San Francisco, San Francisco, California Division of Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania c Department of Psychiatry, University of California, Los Angeles, Los Angeles, California d Westat, Rockville, Maryland Manuscript received August 31, 2005; manuscript accepted November 8, 2005

Abstract

Purpose: To investigate whether factors influencing body composition may be unique for male and female adolescents with horizontal transmission of human immunodeficiency virus (HIV). Methods: HIV infected and uninfected youth (aged 13–18 years) participating in the multi-center project REACH (Reaching for Excellence on Adolescent Health Care) had at baseline anthropomorphic measurements including height, weight, bicep, tricep, subscapular and suprailiac skinfold measurements and midarm circumference. Body mass index, muscle mass, fat free body mass, and fat mass were calculated and predictors of these measures were assessed using multiple variable linear regression. Predictors included contraception, HIV status and related variables (CD4 counts, treatment status, and viral load), substance use, androgen levels as well as appetite changes, and bone age. Results: In multiple variable linear regression analysis, female adolescents’ body composition was associated with HIV status, CD4 ⫹ T cell counts, and free testosterone levels. HIV status was found associated with higher fat and lean body mass, however lower CD4⫹T cell counts were associated with lower fat and lean body mass. Higher testosterone levels were associated with higher lean and fat mass. For adolescent males, higher total testosterone levels but not free testosterone levels were associated with lower lean and fat mass. Conclusions: HIV status was not associated with a lower muscle or fat mass. Different factors influenced body composition for females than males. Higher testosterone levels may be protective against loss in lean and fat mass in females. © 2006 Society for Adolescent Medicine. All rights reserved.

Keywords:

Body composition; Androgen levels; Adolescents; Human immunodeficiency virus

The negative effect of human immunodeficiency virus (HIV) on body composition in children and adults has been well documented. In turn, these negative changes have been associated with hastened disease progression and death [1–3] even in patients on highly active antiretroviral therapy [4]. Although wasting is considered an acquired immune *Address correspondence to: Dr. Anna-Barbara Moscicki, University of California San Francisco, 3333 California Street, Suite 245, San Francisco, CA 94118. E-mail address: [email protected]

deficiency syndrome (AIDS)-defining condition, there is considerable controversy about the appropriate definition. Several parameters have been used to define wasting including loss of weight, lean muscle mass and fat [5– 8]. The proportions of fat and lean tissue lost depend on a variety of factors [6,8,9] including appetite loss, changes in metabolic needs, and testosterone deficiency [5,10 –13]. In the pre-HAART (highly active anti-retroviral therapy) era, hypogonadism had been described in up to 50% of men with HIV infection [10 –12]. Although hypogonadism has been associated with undernutrition, chronic illness, and anti-

1054-139X/06/$ – see front matter © 2006 Society for Adolescent Medicine. All rights reserved. doi:10.1016/j.jadohealth.2005.11.020

A.-B. Moscicki et al. / Journal of Adolescent Health 39 (2006) 164 –173

viral medication, 25% of HIV infected men with hypogonadism appear to have primary (idiopathic) hypogonadism [13]. Similar to men, testosterone deficiency has found to be associated with wasting in HIV-infected women [5]. With the advent of HAART, the wasting syndrome has experienced a decrease in prevalence [14,15]. On the other hand, alteration of body composition has been attributed to complications of HAART, including the described lipodystrophy syndrome, making association with body composition more difficult to interpret [16,17]. Little information is available on body composition and the effect of HIV when acquired during adolescence. A longitudinal study in transfusion-infected boys found that age-adjusted testosterone levels decreased with decreasing immune function and, subsequently, delayed pubertal development and growth failure [18]. It is possible that HIV acquired during times of pubertal growth may accelerate wasting because of increased metabolic needs from both HIV and puberty. In addition, HIV infections have been associated with hypothalamus-pituitary-gonadal (HPG) dysfunction [13,19]. Adolescents may be particularly vulnerable to hormonal changes because the HPG axis has not yet fully matured. On the other hand, adolescents may be relatively protected from wasting because the sharp rises in estrogen and testosterone cause strong anabolic effects. The objective of the study was to examine the body composition, using measures of lean and fat mass, in a population of HIV-infected youth participating in the observational study, REACH (Reaching for Excellence in Adolescent Health Care) project and to compare their body composition to HIV-uninfected youth controls. In addition, factors associated with lower lean and fat mass among both groups were sought. Factors included androgen levels, Tanner stage, bone age, hormonal contraceptive use, socioeconomic factors, tobacco and substance use, loss of appetite, and depression. Methods Study population Study subjects were enrolled in the REACH Project of the Adolescent Medicine HIV/AIDS Research Network (AMHARN). REACH was an observational study of HIV disease progression in HIV-positive adolescents aged 12–18 years, infected as teens, primarily through sexual behaviors. The study also recruited HIV-negative girls and boys of comparable age and high-risk behaviors (i.e., sexual activity, substance use) in a pre-planned ratio of 2:1 (HIV infected:uninfected). A detailed description of the national REACH study objectives and procedures has been previously published [20]. The primary REACH study objectives address biomedical outcomes, requiring physical examination and specimen collection. Therefore, recruitment was restricted to adolescents who were engaged in primary care.

165

In the HIV-infected subgroup, only adolescents who were infected through sex or drug-taking behaviors were eligible for study participation, and those infected through perinatal transmission or contaminated blood products were excluded. In the high-risk noninfected subgroup, only adolescents who were at risk for HIV were eligible for study participation; subjects were selected based on a history of high-risk behaviors that increase the possibility of exposure to HIV. Informed consent The study protocol was reviewed and approved by the institutional review board at each of the participating sites. All subjects were informed of study requirements and gave written consent. Parental permission was obtained where required by local site review boards. Assessment interview Data obtained for this analysis were all baseline and were obtained from four sources: direct face-to-face interview; audio computer-assisted self-administered interview (ACASI) for obtaining sensitive information (i.e., substance use, sexual behavior); physical examination; and laboratory testing [20]. Anthropormorphic measurements Body composition was defined using anthropormorphic measurements garnered from the literature. These included measurements for body mass index (BMI), fat mass, and lean body mass (muscle mass and fat free mass) [21]. Height and weight were obtained on a stadiometer and single scale, respectively, at each site. All weights were obtained in a patient gown without undergarments. Using Lagne Precision Calipers, skinfold measurements of the biceps, tripceps, subscspular and supraliliac were obtained in triplicate. Each of the measures biceps, triceps, subscapular and suprailiac were taken as the mean of the three measurements. Mid-arm circumference (MAC) of the upper arm was also obtained. All individuals obtaining skinfold measurements and MAC were centrally trained using standard collection criteria [22]. The following are the equations used for muscle mass, fat free body mass and fat mass: Muscle Mass was computed as [21]: Muscle Mass 共mm2兲 ⫽

兵mid upper arm circumference 共mm兲 ⫺ ␲ ⫻ triceps skinfold 共mm兲其2 4⫻␲

where ␲ ⫽ 3.14 Fat free body mass was computed as weight minus fat mass, where: Fat Mass (Kg) ⫽ Weight (Kg) ⫻ [94.95/D ⫺ 4.95] and D ⫽ 1.1620 ⫺ .0630 ⫻ S for males, and D ⫽ 1.1549 ⫺ .0678 ⫻ S for females, and

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S ⫽ log10 {biceps (mm) ⫹ triceps (mm) ⫹ subscapular (mm) ⫹suprailiac (mm)} Standardized BMI and muscle mass percentiles were developed from the NHANES III [23] cohort defined by the ⬍5th and ⱖ 5th (10th, 25th, 50th, 75th, 90th, 95th, and 100th) percentile boundaries for age, gender and race. Pubertal staging of the genitals and breasts using Tanner I–V categories were performed by a principle investigator at each site and recorded. Laboratory Quantitative immunophenotyping of CD4⫹ T-cell lymphocytes counts were determined at the individual clinical sites in certified laboratories using AIDS Clinical Trials Group (ACTG) standardized flow cytometry protocols. Initially, HIV plasma viral loads were performed at a centralized laboratory using 200 ␮l of plasma assayed with Nucleic Acid Sequence Base Amplification (NASBA, Organon Technika, Rockville, Maryland); however, this method was changed to NucliSens (Organon Technika) in 1998. Time for blood draws was not standardized; however, time of draw was noted. Sera were sent to a central laboratory at the University of Alabama at Birmingham for analysis of total and free testosterone for males and females, and for females, dehydroepiandrostenedone-sulfate (DHEA-S) and androstenedione [20]. Bone age All subjects were requested to a have a hand-wrist bone age performed at their local radiology department at baseline to assess their stage of growth development. Due to variability in bone age interpretation, we requested that all immature subjects (aged 16 years or younger) have their radiographs sent to a centralized institute for assessment of skeletal age using the FELS method [24]. For various reasons (i.e., films lost, patient refused release), 33 (18.8%) of immature subjects’ baseline skeletal readings were not sent for central reading. A linear regression model of centralized FELS evaluation of bone age was developed using all children who did have centrally read X-rays in addition to the local evaluation. The model was used to impute the FELS result for those without centralized readings. Statistical methods and evaluation The distribution of data for body mass index, muscle mass, fat mass and fat free body mass were examined visually and using the Kolmogorov-Smirnov test to assess departures from normality that might significantly affect the statistical tests [25]. As a result, fat mass and fat free body mass were transformed using a log10 transformation to address potential deviations from normality. Androgen levels were not corrected for time of day. However, for 90% of the specimens where time of blood draw (A.M. vs. P.M.) was available, no difference in the mean values for A.M. and

P.M. was found for DHEA-S, total or free testosterone. This was most likely due to the pubertal maturity of the adolescent population. For each of the several anthropometric measures considered, the potential predictors included Tanner stage, bone age, race, behavioral variables (alcohol use in the last three months, illicit drug use in the last three months, smoking), hormonal contraceptive use (oral contraceptive use, Depo, Depo-Provera, Norplant), endocrinologic measurement (testosterone total, testosterone free, DHEA-S, androstenedione, polycystic ovary syndrome defined as an elevation of any of the androgen levels and reported irregular menses), past pregnancy, irregular period, and HIV-related indicators and its treatment (CD4⫹ T cell counts, viral load, antiretroviral treatment). These were assessed in univariate analysis, using one-way nonparametric analysis of variance (PROC NPAR1WAY) or parametric t-tests using PROC TTEST, as appropriate, and multiple variable linear regression using PROC GLM [26]. Comparisons of subgroups within larger groups for categorical variables in linear regression analyses were undertaken only when the statistical test for the larger group comparison was significant at the p ⬍ .05 level (Type III SS test). No additional techniques to adjust for multiple comparisons were used in the initial analyses to avoid missing the chance of observing clinically important associations [27]. No data were available on time on specific anti-retroviral regimens. Predictor variables for each anthropometric measure judged as important based on the results of univariate analyses, as well as potential covariates supported by other studies in the literature (e.g., depression, appetite loss and socioeconomic status defined by maternal education level), were introduced into classical multiple variable regression models to assess predictive value adjusted for relevant covariates, and provide least squares means. The backward elimination, stepwise and R-square selection procedures were used to determine covariate inclusion in the models. R square and Adjusted R square were used to assess total model fit. Variables with p value of ⬎ .05 were eliminated. Results Data were available from 519 subjects, with 137 males and 382 females in the REACH master data file as of March 2001. Among all subjects in this cohort, 326 were HIVinfected and 193 were HIV-uninfected adolescents. The demographic characteristics of the cohort are given in Table 1, by gender and HIV status. For females, there were more black, non-Hispanics in the HIV-positive group (79% vs. 67%; p ⫽ .006) A significantly greater percent of male youth had bisexual or homosexual experience at the entry of the study (67.21%) when compared with female youth (8.33%). All females had begun menarche and 10.9% were breast Tanner stage IV and 87.5% were breast Tanner stage V. About 8%

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Table 1 Demographic characteristics of study cohort at baseline Characteristic

Female (n ⫽ 382) HIV negative (n ⫽ 146)

Continuous variablesa Age (years) Weight (kg) Total testosterone (ng/dL) Inter-quartile range by gender Free testosterone (ng/dL) Inter-quartile range by gender Categorical variablesb Standardized BMIc ⬍ 5th percentile ⱖ 5th percentile Standardized muscle massc ⬍ 5th percentile ⱖ 5th percentile Race White/other nonHispanic Hispanic Black, non-Hispanic Cumulative Depo Provera use No Yes: ⱕ 1 year ⬎ 1 year Cumulative Norplant use No Yes: ⱕ 1 year ⬎ 1 year Cumulative oral contraceptive use No Yes: ⱕ 1 year ⬎ 1 year Irregular menstrual periodd No Yes Past pregnancye No Yes Time since diagnosis of HIV ⬍⫽ 2 Years ⬎ 2 Years CD4 ⬍ 200 200–499 ⱖ 500 Viral load ⱕ 10,000 ⬎ 10,000 Current ART No Yes

Male (n ⫽ 137) HIV positive (n ⫽ 236)

p Value

HIV negative (n ⫽ 47)

.048ⴱ .2539 .3157

16.85 (1.23) 17.20 (.95) 68.78 (15.81) 68.49 (16.13) 335.27 (146.25) 321.02 (150.07) 242.00–415.00

.0943 .9195 .5029

.40 (.31)

.2587

5.10 (3.31) 4.90 (2.87) 3.12–6.23

.5120

6 (4%) 138 (96%)

1 (.4%) 229 (99.6%)

.0145ⴱ

4 (9%) 43 (91%)

7 (8%) 83 (92%)

.8809

7 (5%) 134 (95%)

8 (3%) 222 (97%)

.4805

7 (15%) 40 (85%)

19 (21%) 70 (79%)

.3626

19 (13%)

22 (9%)

.0209ⴱ

8 (17%)

9 (10%)

.3813

29 (20%) 96 (67%)

27 (11%) 187 (79%)

16 (34%) 23 (49%)

27 (30%) 53 (60%)

106 (74%) 30 (21%) 8 (6%)

164 (69%) 50 (21%) 22 (9%)

.4013

143 (99%) 0 (0%) 1 (1%)

235 (99.6%) 1 (.4%) 0 (0%)

.3247

82 (57%) 49 (34%) 13 (9%)

146 (62%) 61 (26%) 29 (12%)

.1932

88 (79%) 24 (21%)

132 (71%) 55 (29%)

.1297

71 (49%) 73 (51%)

105 (44%) 131 (56%)

.3612

16.55 (1.27) 16.80 (1.15) 68.98 (21.22) 71.50 (20.67) 42.86 (37.72) 41.35 (58.80) 22.00–51.00 .53 (.69) .21–.54

HIV positive (n ⫽ 90)

185 (81%) 43 (19%)

76 (87%) 11 (13%)

18 (8%) 97 (42%) 117 (50%)

11 (12%) 48 (53%) 31 (34%)

164 (70%) 70 (30%)

46 (52%) 43 (48%)

141 (60%) 95 (40%)

54 (60%) 36 (40%)

p Value

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Table 1 Continued Characteristic

Female (n ⫽ 382) HIV negative (n ⫽ 146)

Current HAART including a PI No Yes

Male (n ⫽ 137) HIV positive (n ⫽ 236)

196 (83%) 40 (17%)

p Value

HIV negative (n ⫽ 47)

HIV positive (n ⫽ 90)

p Value

70 (78%) 20 (22%)

For continuous variables, means and standard deviations provided; p values from t-test (ⴱp ⬍ .05). For categorical variables, frequencies and percentages provided; p values from chi-square test. The frequencies may not sum to the total sample size due to missing values (ⴱp ⬍ .05). c Standardized BMI and muscle mass percentiles were developed from the NHANES III [27] cohort defined by the ⬍ 5th and ⱖ 5th (10th, 25th, 50th, 75th, 90th, 95th and 100th) percentile boundaries for age, gender and race. d Irregular menstrual period defined as females having skipped (0 days) or prolonged period (⬎ 7 days) in the past three months. Data were missing for 83 female subjects. e The proportions having past pregnancy among HIV-untreated and HIV-uninfected females are 57% (78/137) and 51% (73/144), respectively, (p value of .2944). a

b

of males were rated genital Tanner stage IV and 91.2% were at genital Tanner stage V. Similar to the reproductive maturity states of the youth, closure of epiphysis (bone age ⬎ 16 years) was seen in 97.6% of males and 95.2% of females at baseline. Preliminary analyses addressed the univariate relationships between the results of anthropomorphic studies (BMI, muscle mass, fat mass, and fat free body mass) and HIV status, CD4⫹ T cell count, and viral load, by gender (Table 2). Overall, BMI and fat mass were greater for females than for males (p ⬍ .0001), whereas muscle mass and fat free body mass were greater for males than females (p ⬍ .0001). Further assessment between HIV-positive and HIV-negative within the same gender separately, indicated that fat free body mass for HIV-positive females was significantly greater than that for HIV-negative females (48.17 vs. 46.18; p ⫽ .03). Because muscle mass and BMI were age-standardized measures, we examined the number of subjects with values suggestive of wasting (⬍ 5th percentile). About 21% (19/ 89) and 3.5% (8/230) of the HIV-infected males and females, respectively, had muscle mass less than the 5th percentiles based on the age- and race-adjusted NHANES III data [23] compared to 15% (7/47) and 5% (7/144) of the HIV-uninfected (HIV-infected vs. HIV-uninfected: p ⫽ .36 for males; p ⫽ .48 for females) . Eight percent (7/90) and .4% (1/230) of the HIV-infected males and females had BMI less than 5th percentile compared to 9% (4/47) and 4% (6/144) of the HIV-uninfected males and females, respectively (HIV-infected vs. HIV-uninfected: p ⫽ .88 for males; p ⫽ .01 for females). Higher CD4⫹ T cell count among females was associated with higher anthropomorphic values (p ⫽ .016 for BMI, p ⫽ .012 for muscle mass, and p ⫽ .023 for fat mass) except for fat free body mass. No univariate associations between viral load and anthropomorphic values were seen.

We next examined the univariate association of anthropomorphic indicators with anti-retroviral therapy by gender among HIV-positive youth. The use of anti-retroviral therapy (with or without a protein inhibitor therapy) at the time of the anthropometric measurements was not an important predictor of any body composition variables in univariate analysis. Multiple variable linear regression analyses Based on the preliminary analyses, females were seen to demonstrate associations that differed from their male counterparts, and multiple variable regression analyses were, therefore, completed within the male and female cohorts separately. The outcomes utilized in the multiple variable regression analyses were the actual raw scores for BMI and muscle mass, and the log transformed values of fat mass and fat free body mass. The results of the linear regression models by gender are shown in Table 3. Body mass index (BMI) and fat mass Among females in the multiple variable regression model, a higher BMI was associated with a higher free testosterone level, a lower androstenedione level, a higher CD4⫹ T cell count, and a positive HIV status. Comparison of HIV-negative females with HIV-infected females without treatment shows a statistically significant higher BMI among the HIV-infected women, suggesting that the HIV status difference for BMI above is not a reflection of treatment. For females, free testosterone, CD4⫹ T cell counts and HIV status had similar associations with fat mass as those described for BMI. Among males in the multiple variable regression model, a higher BMI and a greater fat mass were associated with a lower total testosterone. Race was associated with fat mass

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169

Table 2 Mean anthropomorphic measurements by gendera Female (n ⫽ 382) Total BMI (kg/m2) Muscle mass (mm2) Fat mass (kg) Fat free body mass (kg)

By HIV status BMI (kg/m2) Muscle mass (mm2) Fat mass (kg) Fat free body mass (kg)

By CD4 Counts (HIV⫹ only) BMI (kg/m2) Muscle mass (mm2) Fat mass (kg) Fat free body mass (kg)

Male (n ⫽ 137)

27.1 (7.4) 4497 (1666) 22.6 (10.9) 47.4 (10.5)

p

23.2 (4.9) 5023 (1251) 11.9 (7.6) 56.6 (9.7)

HIV negative

HIV positive

p

HIV negative

HIV positive

26.7 (7.8) 4379 (1674) 21.8 (11.1) 46.2 (10.5)

27.3 (7.1) 4569 (1661) 23.1 (10.8) 48.2 (10.5)

.1242 .0693 .0960 .0328*

23.6 (5.3) 4999 (1507) 12.1 (7.2) 56.7 (10.1)

22.9 (4.7) 5035 (1102) 11.7 (7.8) 56.6 (9.6)

CD4 ⱖ 500

CD4 ⬍ 500

p

CD4 ⱖ 500

CD4 ⬍ 500

27.9 (8.1) 4691 (1827) 23.9 (11.9) 48.4 (11.4)

25.2 (5.0) 4137 (1246) 19.9 (7.8) 45.5 (8.1)

.0169* .0123* .0229* .1300

23.6 (4.9) 4972 (1452) 12.7 (7.0) 56.9 (10.2)

22.7 (4.9) 5084 (956) 10.9 (8.2) 56.2 (9.3)

Viral load ⱕ 10,000

Viral load ⬎ 10,000

p

Viral load ⱕ 10,000

Viral load ⬎ 10,000

27.4 (7.8) 4563 (1751) 22.90 (11.4) 47.80 (11.0)

25.8 (5.2) 4214 (1213) 21.21 (8.4) 45.82 (8.0)

.5274 .2704 .8055 .3811

23.5 (5.2) 5055 (1356) 12.49 (8.0) 57.0 (10.4)

22.5 (4.2) 4963 (1019) 10.4 (6.5) 56.0 (8.2)

⬍.0001 ⬍.0001 ⬍.0001 ⬍.0001 p

.4503 .7836 .6939 .8764 p

.1638 .4296 .0192* .7067 p

By viral load (HIV⫹ only) BMI (kg/m2) Muscle mass (mm2) Fat mass (kg) Fat free body mass (kg)

.4582 .9868 .1998 .7589

Mean and standard deviations are provided (x៮ ⫾ SD). The n’s are the maximum sample size. The calculation of the mean and standard deviation may not be based on the maximum number of observations due to missing values. The Kruskal-Wallis test was used for comparing the means among groups. * (p ⬍ .05). a

in males; non-Hispanic black males had a lower fat mass than for white and Hispanic males. Muscle mass and fat free mass For females, greater muscle mass was associated with a higher free testosterone, lower androstenedione level, higher CD4⫹ T cell counts and HIV-positive status. NonHispanic black females had greater muscle mass than Hispanic females. Among HIV-positive females, muscle mass tended to be significantly greater among females with no anti-retroviral treatment compared to those with treatment. As with muscle mass, females with higher free testosterone levels, higher CD4⫹ T cell counts, and positive HIV status had greater fat free body mass. Use of medroxyprogesterone was associated with greater fat free body mass. Among HIV-infected females, those on anti-retroviral therapy had lower fat free body mass compared to those without any treatment; similar to that reported for muscle mass. Males with lower total testosterone levels tended to have higher fat free mass, a relationship not seen for muscle mass. We assessed the interaction between androstenendione and free testosterone for BMI and muscle mass infection

using the final models: the results indicate that the interaction was not significant in the model (for BMI: p ⫽ .4668, for Muscle Mass: p ⫽ .3917). Because Polycystic Ovarian Syndrome is defined by high androgen levels, obesity, and irregular periods, we explored the relationship between androgen levels and fat mass and muscle mass by examining the frequency of irregular periods among women with lower (⬍ 25th percentile) and higher (⬎75th percentile) testosterone levels. The frequency of irregular periods (defined as any skipped period and prolonged period ⬎ seven days in the past three months) did not differ between females with ⬎ 75% free testosterone (25%) and ⬍ 75% (28%). Discussion Although wasting is commonly described for adults, we found that wasting was not a predominant characteristic of the REACH HIV-infected boy or girl cohorts as measured by fat or lean body mass. Although the majority of adolescents were within two years of diagnosis, the exact timing of infection remains unknown, similar to adult studies. HIV status did influence body composition among girls but in a direction not expected. The boys enrolled in the study were

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Table 3 Linear regression of predictors of anthropomorphic measurements, by gender adjusted least squares means for statistically significant predictorsa,b,c (nmale ⫽ 137, nfemale ⫽ 382)

Female BMI

Testosterone-total (ng/dL)d 25% (male ⫽ 252, female ⫽ 22) 50% (male ⫽ 291, female ⫽ 33) 75% (male ⫽ 435, female ⫽ 57) Testosterone free (ng/dL)d 25% (male ⫽ 3.5, female ⫽ .2) 50% (male ⫽ 4.3, female ⫽ .4) 75% (male ⫽ 6.2, female ⫽ .6) Androstenedioned 25% (female ⫽ 585.00) 50% (female ⫽ 944.51) 75% (female ⫽ 1349.00) CD4 counts ⬍ 200 200–500 ⱖ 500 (ref)e Hormone contraceptive use Medroxyprogesterone only OC only No contraceptive (ref)e Race Hispanic White and others Black non-Hispanic (ref)e Bone age Unknown ⬎ 17 years old ⱕ 17 years old (ref)e HIV and treatment status On HAART w/ PI On ART Not on treatment HIV⫺ (ref)e (HIV⫹) ⫺ (HIV⫺)f (HIV⫹, No Rx) ⫺ (HIV⫹, ART or HAART)f

24.4**** 26.1**** 27.7****

Male Log10 fat mass

11.9**** 12.7**** 13.6****

Log10 FFM

42.1** 43.2** 44.3**

19.8*** 19.0*** 18.1*** 21.3*** 24.2*** 27.4

Muscle mass

BMI

Log10 fat mass

Log10 FFM

23.8*** 22.7*** 21.7***

12.5**** 9.9**** 8.0****

55.8*** 54.1*** 52.3***

24.3* 23.4 22.0

10.7*** 10.7* 7.7

Muscle mass

3981**** 4294**** 4607**** 3120** 2976** 2813**

15.1** 17.0** 20.0

44.7 45.7** 47.9

3431* 3710*** 4441

46.8ⴱ 46.7 44.2 3630* 3757 4194 25.3ⴱ 25.2** 22.3

17.0 18.6** 16.2

24.2 24.2 25.9*** 22.8 2.0* 1.7

17.8 17.0 19.1*** 15.5 1.2*

1.1

3959 4096* 3526 45.7 45.7 49.0*** 43.7 1.1*

8.7 11.2* 9.1

5259 5124* 4358

3850 3739 4244** 3610 334 450*

1.1*

*p ⬍ .05; **p ⬍ .01; ***p ⬍ .001; ****p ⬍ .0001; blank cells indicate the variables are not in the final model (p ⬎ .05) for corresponding outcome. See methods for list of potential predictors and covariates. c Covariates for food consumption, depression and socioeconomic status were adjusted in the multiple variable regression models when they were significant at alpha level of .05. For males, lower maternal education was associated with lower BMI (p ⬍ .01). For females, loss of appetite was associated with lower BMI (p ⬍ .05). d Among the predictors, total testosterone, free testosterone and androstenedione were used as continuous variables in the model. For these predictors, the Least Square Means for each outcome are given for the gender-specific 25th, 50th, and 75th percentile values of the predictors. e (ref) means reference group. For pairwise comparison among two groups for HIV and treatment status, the differences of least square means were provided. BMI ⫽ body mass index; FFM ⫽ fat free body mass; TRT ⫽ treatment; ART ⫽ current ART therapy without HAART; (HAART w/ PI) ⫽ HAART therapy with protease inhibitor. The interaction terms between CD4⫹ T cell counts and testosterone (both total and free) were tested, they were not statistically significant. f Differences of the least square means between two groups were compared using the contrast procedure in GLM for the categories: HIV-positive vs. HIV-negative; HIV-positive without treatment vs. treatment. a

b

relatively thin with low muscle mass, for both HIV-positive and -negative participants, consistent with the multiple variable regression result that HIV status did not influence either BMI or muscle mass. Studies in adults have suggested that HIV infection in men is predominantly associated with

muscle wasting, whereas fat loss appears to be more predominant in women [5,7,28]. More recent data suggest that these differences are not real and it is the starting mass that is more important in predicting wasting [6,9]. HIV-infected females not on treatment had greater fat and lean body mass

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than the HIV-uninfected group. A similar observation was also made by Mulligan et al [29], who reported a higher rate of obesity among HIV-infected adult women than general populations. Mulligan et al [29] hypothesized that this association may reflect differences in body composition in minority at-risk groups. Subtle differences in other sociodemographic factors related to income and types of food available may have been present and not measured in our study. Despite the greater fat mass and lean body mass in the HIV-infected females, low CD4⫹ T cell counts did negatively influence both fat and lean body mass as found in adult women [3,5]. One of the interesting findings among the females was the independent association between higher testosterone levels and higher fat mass and lean body mass. Although low levels of androgens are known to be associated with muscle wasting, none of the levels measured in this study were considered pathologically low or high. However, because adolescence is a time of rapid hormonal changes, we hypothesize that higher androgen levels, even at the higher end of normal for women, may be associated with gains in fat and muscle mass. Androgen replacement studies in HIVinfected women have shown that therapy results in a predominant gain in fat mass, including visceral fat [11,30,31]. On the other hand, central adiposity is associated with elevated androgren levels in women [32,33]. Kirschner et al [34] observed that obese young women have lower steroid hormone binding globulin, resulting in higher free testosterone levels. Unfortunately, we did not measure central adiposity in this study. Polycystic ovary syndrome (PCOS) also did not explain our findings because androgen levels were not associated with reported irregular menses nor was PCOS found to be associated with body composition in this cohort. The lower level of adrenostenedione in the women with greater BMI and muscle mass was significant and not well explained. Enhanced peripheral conversion to estrone or testosterone found in obese individuals may explain this finding. Use of exogenous steroids such as the hormone contraceptive medroxyprogesterone is associated with weight gain, primarily fat [35]. Progesterone-only contraceptives have androgenic (as well as anti-androgenic) properties that can cause increase in appetite with resulting increases in weight gain. The finding of higher fat free body mass for adolescents on medroxyprogesterone suggests that the androgenic components of hormonal contraceptives may also be protective against muscle loss. Studies have repeatedly shown that metabolic disorders are common among HIV-infected children and adolescents on highly active (HA)ART regimens [17]. Of specific relevance to body composition is the lipodystrophy syndrome characterized by peripheral wasting and relative truncal obesity, dyslipidemia, insulin resistance, and impaired glucose tolerance. We were unable to examine this syndrome in our study because we did not measure truncal fat adiposity

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nor any of the metabolic disturbances. However, muscle mass, which is a reflection of mid-arm circumference and triceps skinfold thickness, was decreased among HIVinfected females on HAART compared to those on no treatment even after correcting for CD4⫹ T-cell counts. Body composition in males gave a very different picture than girls. First, we noted that total testosterone in the males was inversely related to fat mass as well as lean body mass as measured by fat free mass. This finding is in contrast to adult studies and may be due to pubertal changes not relevant to adult males. Testosterone control is under the sensitive feedback of follicle-stimulating hormone, which has dramatic fluctuations during adolescence. In addition, total testosterone is a reflection of free testosterone and steroid binding globulin (SBG). Our results suggest that disorders with SBG occur in HIV-infected males, reflecting an inverse relationship seen between total testosterone and fat free mass, yet no associations are seen for free testosterone levels. Although exogenous androgen use was not measured in our study, another explanation may be the use of exogenous androgens in order to increase lean body mass among the males. Commonly taken androgens taken among gay males include nandralone and oxymetholone (personal communication, K. Mulligan 2005). Synthetic androgens are known to suppress endogenous testosterone [36,37]. Consequently, exogenous androgen use would result in greater lean body mass with lower endogenous testosterone, consistent with our results. Unfortunately, we had no information on exogenous hormone use in our population. The lack of association of body composition with CD4⫹ T-cell counts, HIV status, or treatment regimen among adolescent males compared with older men may reflect basic biological differences in HIV infection with age. Infection with HIV during adolescence for males may be somewhat protective against fat or muscle wasting. On the other hand, the sample size of this population limits any general conclusions. We acknowledge that the conclusions of this study remain limited because of the relatively crude measures used to define body composition. Although crude, skinfold thickness remains a reasonable reflection of body composition and is reflective of measurements used in much of the available literature. Attempting to overcome the problems with skinfold thickness measures, we incorporated the use of several mathematical models. We believe that measures of fat free mass using the mathematical model gave us more sensitive information than muscle mass alone. Unfortunately, measurements of lean body mass using skinfold thickness are greatly limited when used in obese individuals. We noted that the females in our cohort were generally heavier with higher BMI and fat mass and lower lean body mass than the males, which is not surprising because females have a greater amount of fat but less muscle aquisi-

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tion than males during and after puberty [38]. This was true for both the HIV-infected and -uninfected, suggesting that the clinic demographics were typical of national data referencing urban females. Interestingly, bone age but not chronological age was an independent predictor of muscle and fat mass. Our finding suggests that charts for body composition based on chronological age such as BMI are limited. The finding was even more pronounced because bone age variability was relatively restricted to mature and almost mature. In conclusion, significant differences in body composition were found between adolescent boys and girls infected with HIV. However, in this cohort, wasting was rare among the HIV-infected group. The associations with testosterone levels are intriguing because testosterone deficiencies have been associated with wasting. Both greater fat and lean body mass were associated with higher end of normal values, suggesting that androgens may allow some protection against HIV wasting in those individuals with higher values. In males, the inverse relationship between total but not free testosterone and lean body mass is not well explained and may reflect unique features of pubertal maturation in HIVinfected males. Longitudinal studies will give better insight into important factors associated with lean and fat mass loss in HIV-infected youth. Acknowledgments This study was funded by grant U01-HD32830 from the National Institute of Child Health and Human Development with co-funding from the National Institutes on Drug Abuse, Allergy and Infectious Diseases, and Mental Health. This work was also supported in part by NCI R01 CA 51323. The authors acknowledge the contributions of the investigators and staff of the Adolescent Medicine HIV/ AIDS Research Network (1994 –2001) and the youth who participated in the research. The authors would like to thank Anthony Kung for assistance in manuscript preparation. References [1] Palenicek JP, Graham NMH, He YD, et al. Weight loss prior to clinical AIDS as predictor of survival. J Acquir Immune Defic Syndr Hum Retrovirol 1995;10:366 –73. [2] Guenter P, Muurahaninen N, Simons G, et al. Relationships among nutritional status, disease progression, and survival in HIV infection. J Acquir Immune Defic Syndr 1993;6:1130 – 8. [3] Wheeler DA, Gibert CL, Launer CA, et al. Weight loss as a predictor of survival and disease progression in HIV infection; Terry Beirn Community Programs for Clinical Research on AIDS. J Acquir Immune Defic Syndr Hum Retrovirol 1998;18:80 –5. [4] Tang AM, Forrester J, Spiegelman D, et al. Weight loss and survival in HIV-positive patients in the era of highly active antiretroviral therapy. J Acquir Immune Defic Syndr 2002;31:230 – 6. [5] Grinspoon S, Corcoran C, Miller K, et al. Body composition and endocrine function in women with acquired immunodeficiency syndrome wasting. J Clin Endocrinol Metab 1997;82:1332–7.

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