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Peak Bone Mass in Young HIV-Infected Patients Compared With Healthy Controls

Negredo, Eugènia MD, PhD*; Domingo, Pere MD, PhD; Ferrer, Elena MD, PhD; Estrada, Vicente MD, PhD§; Curran, Adrià MD, PhD; Navarro, Antonio MD, PhD; Isernia, Valentina MD, PhD§; Rosales, Joaquim MD; Pérez-Álvarez, Núria*,#; Puig, Jordi*; Bonjoch, Anna MD, PhD*; Echeverría, Patricia MD*; Podzamczer, Daniel MD, PhD; Clotet, Bonaventura MD, PhD*,**

JAIDS Journal of Acquired Immune Deficiency Syndromes: February 1st, 2014 - Volume 65 - Issue 2 - p 207–212
doi: 10.1097/01.qai.0000435598.20104.d6
Clinical Science

Introduction: Peak bone mass (PBM) is the amount of bone present at the end of skeletal maturation. It is an important determinant of osteoporotic fracture risk. Data on the PBM in the HIV-infected population are lacking.

Design and Methods: We performed a multicenter (6 centers in Spain), case–control study to assess PBM using dual-energy x-ray absorptiometry. We studied HIV-infected patients aged 20–30 years and compared them with age- and gender-matched non–HIV-infected controls. We also assessed the predictive factors for a low PBM.

Results: We included 307 subjects: 232 HIV-infected patients and 75 non–HIV-infected controls. Bone mineral density was similar in both groups although differences were seen in the total femur T-score (−0.15SD versus +0.50SD, respectively, P = 0.018). The percentage of osteopenia and osteoporosis was higher in the HIV-infected patients (56.5% and 10.7%, respectively) than in the controls (50.7% and 4%, respectively; P = 0.019). Osteoporosis was more frequent in HIV-infected men than in control men and HIV-infected women (12.2% versus 5.5% and 4.8%, P = 0.033). Protease inhibitors and nadir CD4 T-cells were negatively associated with PBM, whereas fat and lean mass were positively associated with PBM.

Conclusions: Bone mineral density was similar between HIV-infected patients aged 20–30 years than in age- and gender-matched controls. However, lower femoral T-scores and higher rate of osteopenia and osteoporosis were seen in HIV-infected men. Therapy with protease inhibitors, nadir CD4 counts, and fat and lean mass were predictive factors of PBM. Given that these patients will be living with HIV infection for many years, every effort should be made to modify risk factors.

*Lluita Contra la Sida Foundation, Internal Medicine Department, Germans Trias i Pujol University Hospital, Autonomous University of Barcelona, Barcelona, Spain;

Internal Medicine Department, Hospital Sant Pau, Barcelona, Spain;

Internal Medicine Department, Hospital Bellvitge, Barcelona, Spain;

§Internal Medicine Department, Hospital Clínico San Carlos, Madrid, Spain;

Internal Medicine Department, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain;

CETIR, Grup Mèdic, Barcelona, Spain;

#Statistics and Operations Research, Technical University of Catalunya, Barcelona, Spain; and

**Irsicaixa Foundation, Germans Trias i Pujol University Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Correspondence to: Eugènia Negredo, MD, PhD, Lluita Contra la SIDA Foundation, Germans Trias i Pujol 08916 Badalona, Catalonia, Spain (e-mail:

D.P. received payment for consultation educational lectures of Boerhinger-Ingelheim ,ViiV, BMS, Abbott, Gilead, Jannsen-Cilag, Merck Sharp and Dohme (MSD), GlaxoSmithKline and Pfizer. A.N. received payment for lectures from Gilead. V.E. received fees for consultancy, grants or educational presentations from Abbott, MSD, Gilead, Abbott, Jannsen, MSD and GlaxoSmithKline. B.C. received payments for grants or consultancy from MSD, ViiV, Gilead, BMS, Jannsen and MSD. E.N. received payments for consultancy from Abbott, Pfizer, MSD, GlaxoSmithKline, Roche and Jannsen. A.C. received payment for lectures from Viiv, Jannsen, BMS, ViiV and Boerhinger ingelheim. A.B. received payment for consultation from Roche, Abbott, Merck and GlaxoSmithKline. All other authors have no other funding or conflicts of interest to disclose.

Received June 11, 2013

Accepted August 27, 2013

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Peak bone mass (PBM) is the amount of bone present in a person's body at the end of skeletal maturation.1 It can be used to measure bone development. A knowledge of the PBM in the pediatric and young adult population is of paramount importance, because this parameter is a determinant of osteoporotic fracture risk.

Although the first 2 decades of life are crucial for skeletal mineralization, bone mass increases mainly during puberty, when differences between genders appear. The PBM tends to be higher in men than in women,1–3 and up to 90% of bone mass is acquired by age 18 years in women and 20 years in men. By age 30, everyone would have acquired his or her PBM.

The PBM is influenced by a variety of environmental factors, and genetics could play an important role.4–7 Other factors affecting the PBM include estrogen and testosterone deficiency, nutrition (calcium, vitamin D, magnesium, or zinc deficiency), physical activity (lack of exercise or excessive exercise due to extremely low body weight and hormonal changes), and lifestyle (eg, smoking).2

In HIV-infected patients, low bone mineral density (BMD) is an emerging metabolic condition.8–12 Although the underlying mechanism is unknown, epidemiologic studies and clinical trials suggest that its etiology is multifactorial. The traditional risk factors associated with osteoporosis, such as smoking, alcohol, drugs, malnutrition, low body mass index (BMI), chronic disease, and inactivity, are more prevalent in the HIV-infected population.13,14 Additionally, HIV itself plays a direct role in bone demineralization, through the viral proteins, inflammatory effects,15–17 and antiretroviral therapy.

Given the knowledge that low PBM increases the risk of developing osteoporosis later in life and the available evidence that HIV-infected patients have an increased risk of osteoporosis and bone fracture,18–21 we assessed the PBM in our young adult HIV-infected patients.

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Study Design and Participants

We performed a multicenter (6 centers in Spain), observational case–control study to assess the PBM in young adult HIV-infected patients. The study was approved by the Institutional Ethics Committee of the coordinating center and the local health authorities.

The study population comprised patients diagnosed with HIV-1 infection who were receiving or not receiving antiretroviral therapy. All the patients had had a dual-energy x-ray absorptiometry (DXA) scan between the age of 20 and 30 years, performed as routine in clinical practice. Patients with a history of comorbidities that have a negative impact on bone metabolism (collected from the medical records) or a BMI <16 or >28 kg/m2 were excluded from the analysis. Non–HIV-infected individuals with available DXA scans matched for age and gender were included and considered healthy controls (3 cases per control). These subjects were students or staff from some of the participating centers.

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Study Objectives and Endpoints

The main objective of the study was to assess the PBM, that is, the amount of bone present in a person's body at the end of skeletal maturation. For this purpose, BMD and T-scores were recorded for the lumbar spine (L1–L4) and total femur and compared between HIV-infected patients and non–HIV-infected controls. The percentages of participants with osteopenia or osteoporosis were also compared between the groups according to the criteria of the World Health Organization. The same endpoints were compared between genders.

We also tried to identify the predictors of low PBM. We focused mainly on HIV-related factors and on the potential association between bone mass and lean and fat mass.

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Study Variables

DXA was performed using different devices, and all of them were calibrated daily (QDR-4500A Hologic, Inc, Waltham, MA; and GE LUNAR DPX PRO, version 12.3, DXA Prodigy model; GE Healthcare, Madison, WI). Findings were compared by correcting determinations to standardized BMD (from LUNAR or from Hologic to standardized values, for each area, L1–L4 and total femur) using equations described elsewhere.22

We recorded demographic data (gender, age, and race), BMI, and risk factors for low BMD (smoking habit, physical inactivity, alcohol or illicit drugs, and corticosteroid or antiepileptic drug use) from all the participants, if available. We also recorded data from the clinical history, as follows: data associated with HIV infection (time since HIV diagnosis, time on antiretroviral therapy, risk factors for HIV infection, clinical stage, history of opportunistic infections or tumors, and previous and current antiretroviral treatment), and immunologic and virologic data (viral load and CD4 cell count at the time of the DXA scan, nadir CD4 cell count).

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Statistical Analysis

Due to the difficulty in the recruitment of HIV-infected patients aged from 20 to 30 years evaluated by the DXA scan, a multicenter study was planned, including centers that usually perform DXA scans to their patients as a part of their clinical practice, to achieve a big sample size.

Clinical and demographic data were assessed. The numerical variables were expressed as the median and interquartile range (IQR) and compared using the Mann–Whitney test. For categorical variables, the number and percentages of patients were given and compared using the χ2 or Fisher exact test (as appropriate). Comparisons were made between HIV-infected patients and non–HIV-infected controls and according to the gender of the patient.

The minimum value of the T-score for L1–L4 and the total femur area was calculated and used as a marker of BMD.

Multivariate analysis was performed to assess the effect of clinical and epidemiological variables, mentioned before in the Study variables section, on BMD and T-scores. All the variables were included in a multivariate stepwise linear regression model.

Results were considered significant at P ≤ 0.05. All analyses were performed with SPSS 15 (SPSS, Inc, Chicago, IL).

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A total of 307 persons were included in the analysis: 232 HIV-infected patients and 75 non–HIV-infected controls.

Epidemiological and HIV-related characteristics are described in Table 1. The 2 groups were well balanced for gender, age, and BMI. The only differences we observed were in the body composition: in HIV-infected patients, the average lean mass was higher than in the controls (52,639 versus 46,732 g, respectively, P = 0.001) and the percentage of fat mass was lower (19.7% versus 23.4%, P = 0.022).



Risk factors for low BMD (described in the Methods section) were not available for all the participants, because data were recorded retrospectively. In concrete, complete data were recorded for 115 (49.6%) patients and 30 (40%) controls. As we expected, HIV-infected patients were smokers more frequently than controls (57% versus 13%, P = 0.012) and more regularly consumed illicit drugs (15% versus 3%, P = 0.173) or alcohol (20% versus 3%, P = 0.04), whereas control women used anticonceptive pills more frequently than HIV-infected women (20% versus 0%, P = 0.050) did. Other risk factors for low BMD were similar: 48% of HIV-infected patients practiced exercise versus 40% of controls (P = 0.742); no patients and no controls used corticosteroid or antiepileptic drugs (P = 0.123).

HIV-related data are also summarized in Table 1. Most patients were men who have sex with men (66.8%), and almost all were receiving therapy at the time of their DXA scan (94%). Although the mean time with infection and that for receiving antiretroviral treatment was 2 years, it is noteworthy that mother-to-child transmission was recorded in 6 patients (2.6%) (ie, mean time with HIV infection of 28 years); 10.8% of the participants had been infected for >10 years.

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Comparison Between HIV-Infected Patients and Non–HIV-Infected Controls

No differences in the BMD were found at any site between HIV-infected patients and controls (Table 2). When we repeated the analysis excluding those subjects who acquired HIV infection by vertical transmission (6 patients) to homogenize the study population, no differences in the BMD were seen between both populations, although the BMD was slightly lower in the HIV-infected group. The L1–L4 BMD was 1015 (892–1108) in HIV-infected patients and 1082 (977–1211) in controls (P = 0.210) and the total femur BMD was 1042 (934–1136) and 1045 (935–1130), respectively (P = 0.176).



Comparison of the T-scores revealed a difference for total femur, with a mean T-score of −0.2 in HIV-infected patients and 0.050 in controls (P = 0.018). No differences were seen for the lumbar spine (L1–L4; Table 2).

Osteoporosis was present in 23 HIV-infected patients (10.7%) and in 3 controls (4%), whereas osteopenia was present in 121 patients (56.5%) and 38 controls (50.7%). The normal BMD was present in 32.7% of HIV-infected patients and in 45.3% of controls (P = 0.019; Table 2).

Stratification by gender showed that osteoporosis was more frequently observed in HIV-infected men than in control men (12.2% versus 5.5%, P = 0.033), as was osteopenia (57% versus 45.5%, P = 0.014). The mean total femoral T-score was −0.3SD in HIV-infected men and 0.1 in control men (P = 0.03). We did not find any differences in the BMD, T-score, or percentage of osteopenia and osteoporosis between HIV-infected and control women (Table 3).



The BMD was higher at all sites in the HIV-infected men than in the HIV-infected women, although no significant differences in the T-score were found between the groups.

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Predictors of Low Peak Bone Mass

The low nadir CD4 T-cell count and therapy with protease inhibitors were associated with a lower PBM in the lumbar spine and total femur (Table 4) but not with the use of tenofovir. We also found a positive correlation between lean mass and PBM for any site and between fat mass and bone mass for the femur (Table 4).



Regression analyses have not been repeated including risk factors for low BMD (smoking, alcohol, physical inactivity, corticosteroids, etc) at the same time due to missingness and the underrepresentation of some categories. However, an analysis has been performed including a subgroup of potential confounders. No other new factors have been associated with a low PBM except for alcohol (P = 0.014 for femoral BMD and P = 0.009 for lumbar spine), and a trend was seen for smoking (P = 0.068 for lumbar BMD).

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A low BMD and fragility fractures are increasingly common among HIV-infected patients.9–12 A North American study comparing 8525 HIV-infected patients with 2,208,792 noninfected subjects found that the prevalence of osteoporotic fractures was 60% higher in the HIV-infected group.19 Similar results were observed in other cohorts.20,21 Available data reveal a 3.7-fold higher risk of developing osteoporosis in antiretroviral-naive HIV-infected patients.23 Lumbar spine and femoral BMD decrease by 2%–6% after the initiation of therapy.24–27 The effect of antiretroviral therapy seems to be associated with a decrease in the BMD during the first 2 years of treatment, followed by stabilization28,29 and a higher risk of typical fragility fractures.30

These data mean that HIV-infected patients are affected by factors other than traditional risk factors associated with bone mass loss, mainly viral replication and the prolonged use of antiretroviral drugs. Considering that many new HIV infections occur in very young adults, who will be affected by these additional factors for many years, it is important to assess the PBM, because it predicts the risk of developing osteoporosis. Because most people reach their PBM by the age of 20–30 years, we evaluated the BMD of HIV-infected patients in this age group and compared it with that of age- and gender-matched healthy controls. Surprisingly, no differences in the BMD were observed between patients and controls. Nevertheless, a significantly lower hip T-score was observed among HIV-infected men. Likewise, a higher proportion of them presented criteria of osteopenia and osteoporosis (56.5% and 10.7%, respectively) even considering that a substantial percentage of our control group presented osteopenia and osteoporosis (50.7% and 4%, respectively). An increasing number of children and adults are affected by a low BMD, probably because secondary forms are becoming more common as a result of lifestyle, diet, chronic illness, and medication.31–34 In fact, only 30.8% of HIV-infected men had a normal BMD in comparison with almost half of the control men (49.1%).

As for gender effects in the HIV-infected patients, men had lower T-scores than did women. The fact that men achieve the PBM later than women do could explain the higher prevalence of osteopenia and osteoporosis in this group; some of the men aged around 20 years in this study may not yet have attained their PBM. However, this finding seems to be consistent with the published data on the higher proportion of HIV-infected men with osteoporosis than HIV-infected women.9

Considering all our results, the lower femoral T-score in HIV-infected men with respect to women or controls could be associated with the higher proportion of smokers or people who consume illicit drugs or alcohol in this subgroup.

Because trabecular bone is more active and more subject to bone turnover and remodeling, we expected to find differences, especially in the lumbar spine. However, contrary to our expectations, the femur was the most affected area in HIV-infected patients, and no differences were observed for the lumbar spine, suggesting that HIV-related factors could have played a role in our findings.

Lower nadir CD4 T-cell count and therapy with protease inhibitors were correlated with a lower PBM. The recently reported association between protease inhibitors and low bone mass9 could be a consequence of increased osteoclastic activity in patients taking protease inhibitors. The negative effect of low nadir CD4 T-cell count on BMD could be explained by the high levels of immune activation and inflammation usually associated with severe immunodeficiency.35

Our finding that fat mass and lean mass were positively correlated with the BMD is consistent with those of other authors in both HIV-infected patients and the general population.36–39 Even considering that our HIV-infected patients had a higher lean mass than did healthy controls (probably as a consequence of the increased physical activity among young adult men who have sex with men), femoral T-score was lower. Although lean mass, fat mass, and bone density are affected by genetic factors, the association between the 3 is mediated mainly by environmental factors.40 Because lean mass is strongly related to physical activity, it is clear that exercise is an important component in the prevention of bone loss. Considering our data and previous data,36 these measures should be strongly recommended in HIV-infected patients from very early stages of the infection. Similarly, secondary causes of osteoporosis should be ruled out or treated to slow down bone loss.

Data on risk factors for low BMD values were only available for a subgroup of participants (40%–50%) owing to the retrospective study design. Although alcohol intake and probably smoking seem to be associated with a low BMD, incomplete data collected in our study limit the conclusions in this sense. The low number of HIV-infected women in our study could have prevented us from finding differences with control women. Additionally, the very low proportion of participants with mother-to-child transmission of HIV prevented us from investigating the long-term effect of the virus itself, although a considerable number of patients had been diagnosed with HIV infection for >5–10 years.

In summary, although fragility fractures depend on factors other than BMD (eg, bone microstructure), the PBM is a good predictor. Although no differences in the BMD were seen between our HIV-infected patients and controls, HIV-infected men showed a lower hip T score and a higher prevalence of osteopenia and osteoporosis than HIV-uninfected controls. PBM was inversely associated with nadir CD4 T-cell counts and the use of protease inhibitors, but directly associated with fat and lean mass. Considering that this young population will be living with HIV infection for many years, risk factors for osteoporosis should be modified, if possible.

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1. Bonjour JP, Theintz G, Law F, et al.. Peak bone mass. Osteoporos Int. 1994;4(suppl 1):7–13.
2. Ferrari S, Bianchi ML, Eisman JA, et al.. Osteoporosis in young adults: pathophysiology, diagnosis, and management. Osteoporos Int. 2012;23:2735–2748.
3. Rubin K, Schirduan V, Gendreau P, et al.. Predictors of axial and peripheral bone mineral density in healthy children and adolescents, with special attention to the role of puberty. J Pediatr. 1993;123:863–870.
4. Christian JC, Yu PL, Slemenda CW, et al.. Heritability of bone mass: a longitudinal study in aging male twins. Am J Hum Genet. 1989;44:429–433.
5. del Rio L, Carrascosa A, Pons F, et al.. Bone mineral density of the lumbar spine in white Mediterranean Spanish children and adolescents: changes related to age, sex, and puberty. Pediatr Res. 1994;35:362–366.
6. Krall EA, Dawson-Hughes B. Heritable and life-style determinants of bone mineral density. J Bone Miner Res. 1993;8:1–9.
7. Seeman E, Hopper JL, Bach LA, et al.. Reduced bone mass in daughters of women with osteoporosis. N Engl J Med. 1989;320:554–558.
8. Bedimo R, Maalouf NM, Zhang S, et al.. Osteoporotic fracture risk associated with cumulative exposure to tenofovir and other antiretroviral agents. AIDS. 2012;26:825–831.
9. Bonjoch A, Figueras M, Estany C, et al.. High prevalence of and progression to low bone mineral density in HIV-infected patients: a longitudinal cohort study. AIDS. 2010;24:2827–2833.
10. Brown TT, McComsey GA, King MS, et al.. Loss of bone mineral density after antiretroviral therapy initiation, independent of antiretroviral regimen. J Acquir Immune Defic Syndr. 2009;51:554–561.
11. Brown TT, Qaqish RB. Antiretroviral therapy and the prevalence of osteopenia and osteoporosis: a meta-analytic review. AIDS. 2006;20:2165–2174.
12. Knobel H, Guelar A, Vallecillo G, et al.. Osteopenia in HIV-infected patients: is it the disease or is it the treatment? AIDS. 2001;15:807–808.
13. Amorosa V, Tebas P. Bone disease and HIV infection. Clin Infect Dis. 2006;42:108–114.
14. Pollock E, Klotsas AE, Compston J, et al.. Bone health in HIV infection. Br Med Bull. 2009;92:123–133.
15. Fakruddin JM, Laurence J. HIV envelope gp120-mediated regulation of osteoclastogenesis via receptor activator of nuclear factor kappa B ligand (RANKL) secretion and its modulation by certain HIV protease inhibitors through interferon-gamma/RANKL cross-talk. J Biol Chem. 2003;278:48251–48258.
16. Fakruddin JM, Laurence J. HIV-1 Vpr enhances production of receptor of activated NF-kappaB ligand (RANKL) via potentiation of glucocorticoid receptor activity. Arch Virol. 2005;150:67–78.
17. Wei S, Kitaura H, Zhou P, et al.. IL-1 mediates TNF-induced osteoclastogenesis. J Clin Invest. 2005;115:282–290.
18. Guerri-Fernandez R, Vestergaard P, Carbonell C, et al.. HIV infection is strongly associated with hip fracture risk, independently of age, gender and co-morbidities: a population-based cohort study. J Bone Miner Res. 2013;28:1259–1263.
19. Triant VA, Brown TT, Lee H, et al.. Fracture prevalence among human immunodeficiency virus (HIV)-infected versus non-HIV-infected patients in a large U.S. healthcare system. J Clin Endocrinol Metab. 2008;93:3499–3504.
20. Womack JA, Goulet JL, Gibert C, et al.. Increased risk of fragility fractures among HIV infected compared to uninfected male veterans. PLoS One. 2011;6:e17217.
21. Young B, Dao CN, Buchacz K, et al.. Increased rates of bone fracture among HIV-infected persons in the HIV Outpatient Study (HOPS) compared with the US general population, 2000–2006. Clin Infect Dis. 2011;52:1061–1068.
22. Bonnick S. Bone density data. In: Bone Densitometry in Clinical Practice. Application and Interpretation. 2nd ed. New York, NY: Humana Press; 2004:111–126.
23. Gallant JE, Staszewski S, Pozniak AL, et al.. Efficacy safety tenofovir DF vs stavudine combination therapy antiretroviral-naive patients: a 3-year randomized trial. JAMA. 2004;292:191–201.
24. Grund B, Peng G, Gibert CL, et al.. Continuous antiretroviral therapy decreases bone mineral density. AIDS. 2009;23:1519–1529.
25. Hansen AB, Obel N, Nielsen H, et al.. Bone mineral density changes in protease inhibitor-sparing vs. nucleoside reverse transcriptase inhibitor-sparing highly active antiretroviral therapy: data from a randomized trial. HIV Med. 2011;12:157–165.
26. McComsey GA, Tebas P, Shane E, et al.. Bone disease in HIV infection: a practical review and recommendations for HIV care providers. Clin Infect Dis. 2010;51:937–946.
27. Stellbrink HJ, Orkin C, Arribas JR, et al.. Comparison of changes in bone density and turnover with abacavir–lamivudine versus tenofovir–emtricitabine in HIV-infected adults: 48-week results from the ASSERT study. Clin Infect Dis. 2010;51:963–972.
28. Bolland MJ, Grey AB, Horne AM, et al.. Bone mineral density is not reduced in HIV-infected Caucasian men treated with highly active antiretroviral therapy. Clin Endocrinol (Oxf). 2006;65:191–197.
29. Dolan SE, Kanter JR, Grinspoon S. Longitudinal analysis of bone density in human immunodeficiency virus-infected women. J Clin Endocrinol Metab. 2006;91:2938–2945.
30. Yin MT, Kendall MA, Wu X, et al.. Fractures after antiretroviral initiation. AIDS. 2012;26:2175–2184.
31. da Fonseca MA. Osteoporosis: an increasing concern in pediatric dentistry. Pediatr Dent. 2011;33:241–245.
32. Mesias M, Seiquer I, Navarro MP. Calcium nutrition in adolescence. Crit Rev Food Sci Nutr. 2011;51:195–209.
33. Roef G, Lapauw B, Goemaere S, et al.. Thyroid hormone status within the physiological range affects bone mass and density in healthy men at the age of peak bone mass. Eur J Endocrinol. 2011;164:1027–1034.
34. Shivane VK, Sarathi V, Lila AR, et al.. Peak bone mineral density and its determinants in an Asian Indian population. J Clin Densitom. 2012;15:152–158.
35. Massanella M, Negredo E, Perez-Alvarez N, et al.. CD4 T-cell hyperactivation and susceptibility to cell death determine poor CD4 T-cell recovery during suppressive HAART. AIDS. 2010;24:959–968.
36. Hinriksdottir G, Arngrimsson SA, Misic MM, et al.. Lean soft tissue contributes more to bone health than fat mass independent of physical activity in women across the lifespan. Maturitas. 2013. pii: S0378-5122(12)00409-4.
37. Park JH, Song YM, Sung J, et al.. The association between fat and lean mass and bone mineral density: the Healthy Twin Study. Bone. 2012;50:1006–1011.
38. Sharma A, Tian F, Yin MT, et al.. Association of regional body composition with bone mineral density in HIV-infected and HIV-uninfected women: women's interagency HIV study. J Acquir Immune Defic Syndr. 2012;61:469–476.
39. Waters DL, Vawter R, Qualls C, et al.. Long-term maintenance of weight loss after lifestyle intervention in frail, obese older adults. J Nutr Health Aging. 2013;17:3–7.
40. Nguyen TV, Howard GM, Kelly PJ, et al.. Bone mass, lean mass, and fat mass: same genes or same environments? Am J Epidemiol. 1998;147:3–16.

peak bone mass; bone mineral density; osteoporosis; HIV infection; antiretroviral therapy

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