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High frequency of poor locomotor performance in HIV-infected patients

Richert, Lauraa; Dehail, Patrickb,c; Mercié, Patricka,c; Dauchy, Frédéric-Antoinec; Bruyand, Mathiasa; Greib, Carinec; Dabis, Françoisa,c; Bonnet, Fabricea,c; Chêne, Genevièvea,c for the Groupe d'Epidémiologie Clinique du SIDA en Aquitaine (GECSA)

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doi: 10.1097/QAD.0b013e3283455dff
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Although HIV-infected patients treated by combination antiretroviral therapy (cART) experience longer survival [1,2], comorbidities such as cancer and cardiovascular, metabolic, renal and bone disorders have become a concern in their clinical care [3]. These comorbidities are associated with ageing in the general population, but are detected relatively early in life in HIV-infected patients who have a median age of approximately 40–50 years in industrialized countries [1,4].

In HIV-uninfected individuals, both muscle strength and muscle power decrease with advanced age, resulting in impairments of locomotor function [5], deterioration of functional ability and limitations in activities of daily living [6]. Poor lower limb muscle performance and balance disorders predict the risk of falls and disability in elderly community-dwelling individuals of the general population. Furthermore, low quadriceps strength is an independent risk factor for hip fracture and a predictor for mortality after fragility fracture [7,8].

In HIV-infected patients, data from a cross-sectional survey in 2002 suggest that up to 30% of HIV-infected patients have complaints concerning their locomotor function and balance [9]. Antiretroviral drugs, particularly exposure to d-drugs (didanosine, stavudine and zalcitabine) and to zidovudine, could have influenced locomotor performance in the early cART era through a pathway of peripheral neurotoxicity and adverse effects on the muscle [10,11].

There is a lack of data regarding prevalence of poor locomotor performance and associated factors, as studies based on objective measurements of different muscle function parameters are scarce in HIV-infected patients and mostly focused on central neuromuscular activation or cardiorespiratory fitness [12–14].

Several standardized locomotor tests have been validated in the general population and allow for assessing different functional parameters, such as balance, muscle performance and walking speed in the clinical care setting. To our knowledge, locomotor performance, measured by a broad range of standardized tests, has not been assessed in a large sample of HIV-infected patients, representative of the current situation regarding treatment and control of infection. Therefore, the objective of the present study was to provide up-to-date standardized assessments of locomotor function in the HIV-infected population, with a particular focus on lower limb muscle performance and balance and on the identification of potential determinants of impaired function.


Study population

The French Agency for AIDS and Hepatitis Research (ANRS) CO3 Aquitaine Cohort is an open prospective cohort of HIV-1-infected patients followed in six public hospitals of the Aquitaine region in France. The cohort was initiated in 1987 and includes adults with the following eligibility criteria: HIV-1 infection confirmed by Western blot, regardless of clinical stage, with either at least one follow-up after the first clinic visit or with a known date of death, and informed consent. Details of the cohort have been described elsewhere [15].

The present locomotor study enrolled patients between June 2007 and October 2009 in five HIV clinics of the Bordeaux University Hospital. Calendar enrolment periods were prespecified per clinic, allowing for alternating enrolment between sites. The protocol defined that study participation be proposed to each eligible patient attending a visit during a predefined enrolment period.

Patients were eligible for the locomotor study if they were HIV-1-infected adults (≥18 years), included in the Aquitaine Cohort, had neither acute opportunistic infection nor cancer under treatment, and able to stand and walk. The study was approved by the Ethics Committee of Bordeaux (CPP du Sud-Ouest et Outre Mer III) and written informed consent was obtained from all participants. The study procedures were in accordance with the standards of the Ethics Committee and with the Helsinki Declaration. The assessments were conducted as baseline measurements of a longitudinal study on locomotor function with ongoing follow-up.

Patient characteristics were extracted from the Aquitaine Cohort database and included the following variables: sex; age; anthropometric data; IDU; smoking and alcohol consumption; medical history and comorbidities; HIV-1 RNA level; CD4 cell count and nadir; HIV transmission category; date of HIV diagnosis; AIDS stage according to US Centers for Disease Control and Prevention (CDC) classification; hepatitis B and C co-infection status; history of lipodystrophy; history of polyneuropathy; antiretroviral treatment history; and medication intake. Exposure to zidovudine, and to didanosine, stavudine or zalcitabine was studied through a categorical variable (yes/no through the entire follow-up) and a quantitative variable (cumulative time of exposure). Hepatitis B co-infection was defined by at least one positive hepatitis B virus surface antigen measurement, and hepatitis C co-infection by at least one positive hepatitis C virus antibody measurement since inclusion in the cohort.

Locomotor tests

Locomotor assessment was performed by trained study staff according to standardized protocols and consisted in the following tests and measurements:

  1. Berg balance scale, assessing overall balance and equilibrium by the means of 14 functional tasks [16,17].
  2. Six-minute walk test, assessing global functional capacity and aerobic endurance [17,18]. The six-minute walk test measures the distance walked in 6 min at accelerated speed.
  3. Timed up and go test, assessing functional balance [17,19] and used to predict risk of fall in the elderly. This test measures the time taken by a participant to stand up from an armchair, walk a distance of 3 m, turn around, walk back to the chair and sit down.
  4. Functional reach test, assessing forward reach ability and dynamic balance [20]. This test measures the maximal distance that a participant can reach forward beyond arm's length while maintaining a fixed base of support in the standing position.
  5. One-leg standing with eyes closed test, assessing static balance [21] by measuring the time the participant can stand on one leg with the eyes closed.
  6. Five-times sit-to-stand (5STS) test, assessing lower limb muscle performance and balance [22,23]. The 5STS test measures the time required to complete five sit-to-stand-to-sit cycles at accelerated speed, recorded with a digital stopwatch. The participant sat on a standard armchair (height 45 cm) with the back against the chair and arms crossed in front of the chest. After one practice trial, the participant was instructed to rise, stand fully up and sit down again five consecutive times as fast as possible, without using the arms to push up from the chair.

Results of locomotor tests were interpreted on the basis of the data established in the general population, available in the literature. Whenever appropriate, age-specific distributions of test results were adopted in order to account for the age dependence of locomotor performance.

For the Berg balance scale, a score of less than 46 was considered as poor performance in all age categories [16]. For the interpretation of the six-minute walk distance, the reference formula proposed by Enright and Sherrill [18] was used to determine poor results, taking into account age, weight, height (continuous variables) and sex. For the 5STS test and the remaining locomotor tests, poor test performance was defined by a test result of more than 2 SD from the expected age-specific mean in the general population [21,24,25] in analogy to the criteria used to define HIV-associated dementia [26].

Statistical analyses

Descriptive analyses were performed and summary measures of results of each locomotor test were calculated. Possible differences between subgroups of participants were assessed by tests for independent samples using nonparametric methods when appropriate.

Univariable and multivariable logistic regression analyses were performed to explore the factors associated with poor 5STS performance. Variables with P-value less than 0.25 in univariable analyses were included in a full model. The final multivariable model was obtained using a backward stepwise modeling procedure, including interaction terms when appropriate. Sex and the following major HIV-related and cART-related characteristics were maintained in the final model as key variables for adjustment regardless of the significance level: transmission category, current CD4 cell count, exposure to zidovudine and HIV-1 RNA levels of at least 500 copies/ml during the past year.

Robustness analyses were performed by adding 1 s to the initial cut-off in each age category to define poor 5STS performance.

Fit of the final model was examined by Hosmer–Lemeshow goodness-of-fit test. For final results, P-values less than 0.05 were considered statistically significant. All statistical analyses were performed with SAS software, version 9.1 (SAS Institute, Cary, North Carolina, USA).


Of 3655 patients under active follow-up in the Aquitaine Cohort in 2007–2009, 2992 were followed at the University Hospital of Bordeaux and 324 were included in the present study. Median age of the participants was 47.6 years. A large majority of participants were men, on cART and had HIV-1 RNA levels of less than 500 copies/ml at time of the locomotor evaluation.

Compared with the characteristics of the patients not included in the present study, the patients participating in the locomotor evaluation were slightly older, more often men and on antiretroviral treatment, and more likely to have a history of polyneuropathy. Other characteristics of the study participants were similar to those of the patients under active follow-up at the University Hospital of Bordeaux (Table 1).

Table 1:
Characteristics of the study participants in the locomotor study compared with patients under active follow-up in the ANRS CO3 Aquitaine Cohort in 2007.

Table 2 summarizes the results of each locomotor test. Additional raw results of the tests can be consulted in the supplemental digital content (Table SDC1), The 5STS test was the most frequently altered test, with 172 of 323 [53.3%; 95% confidence interval (CI): 47.6, 58.8] patients having a poor performance in this test. The extent of poor 5STS results was confirmed in a robustness analysis with larger cut-offs defining poor test performance: even after adding 1 s to each cut-off, a poor 5STS performance was found in 39.3% (95% CI: 34.0, 44.9).

Table 2:
Distribution of locomotor test results and proportion of patients with poor test performance in the locomotor study, ANRS CO3 Aquitaine Cohort 2007–2009.

For the remaining locomotor tests, poor performance was detected with the following proportions: six-minute walk test, 23.6%; timed up and go test, 10.5%; one-leg standing test, 9.9%; functional reach test, 10.6%; and Berg balance scale, 1.5%.

Overall, 199 patients (61%; 95% CI: 56, 67) had poor performance in at least one of the six locomotor tests.

Associations between 5STS performance and other locomotor tests are shown in Table 3. Of 172 patients with poor 5STS performance, 90 had a poor result in at least one other locomotor test. Among the 151 patients with normal (i.e. not poor) 5STS performance, 125 had no other poor locomotor test result. When used to rule out poor locomotor performance in any other test, a normal 5STS result would, thus, have a negative predictive value of 83% (95% CI: 76, 88). Twenty-two patients with normal 5STS performance had a poor result in one of the other tests and only four patients had poor results in more than one of the other tests. The most frequently altered test in those patients was the six-minute walk test (poor performance in 12 patients with normal 5STS results). In order to improve the negative predictive value without the need to include another locomotor test result, we explored the incorporation of smoking habits, given the impact of smoking on cardiorespiratory fitness and the six-minute walk test. Indeed, when restricted to current nonsmokers (n = 167), the negative predictive value of a normal 5STS result was 94% (95% CI: 87, 98).

Table 3:
Association of five-times sit-to-stand performance with performance in other locomotor tests in the locomotor study, ANRS CO3 Aquitaine Cohort 2007–2009.

Eighty-four percent of patients with poor six-minute walk performance also had poor performance in the 5STS test. The further results, therefore, focus on the 5STS test.

Frequency of poor 5STS performance was significantly higher in patients aged below 50 years than in the older patients (64 vs. 36%, P < 0.0001), notwithstanding the use of age-specific cut-offs for the definition of poor performance. When examining the raw test results (time required to complete the test), there was no clinically relevant difference between the two age groups (median time 9.7 and 10.0 s, respectively), confirming the finding that the older patients had relatively good test results.

In univariable comparisons, patients with poor 5STS performance differed from those with normal test performance in terms of age, sex, smoking habits, BMI, HIV transmission category, time since HIV diagnosis, hepatitis C co-infection and exposure to d-drugs (Table 4). Polyneuropathy was not associated with poor test performance.

Table 4:
Univariable comparisons of patient characteristics according to five-times sit-to-stand performance in the locomotor study, ANRS CO3 Aquitaine Cohort 2007–2009.

In the final multivariable model, longer time since HIV diagnosis was independently associated with poor 5STS performance (Table 5). Moreover, a significant interaction was found between age and BMI: in younger patients, a lower BMI was significantly associated with poor test performance, whereas this association was inversed in the elderly patients. In Table 5, estimates of odds ratios (ORs) per kilogram per square meter BMI at selected ages (30, 50 and 70 years) illustrate this interaction. Analyzing BMI as a categorical variable (three categories: <20 kg/m2; 20–25 kg/m2; and ≥25 kg/m2) resulted in the same trend, although the interaction term was at the limit of statistical significance (P = 0.06), possibly due to limited statistical power.

Table 5:
Factors associated with poor five-times sit-to-stand performance in the final multivariable logistic regression model in the locomotor study, ANRS CO3 Aquitaine Cohort 2007–2009.

None of the other studied variables were independently associated with poor 5STS performance in the multivariable models. Particularly, no associations were found with current CD4 cell count and plasma HIV-1 RNA level or with exposure to antiretroviral drugs. Association with cumulative exposure to d-drugs was not significant after adjustment for time since HIV diagnosis in the multivariable model, although a trend could be suspected (OR 1.08 per year of exposure; 95% CI: 0.99, 1.18; P = 0.09).

The use of larger cut-offs to define poor 5STS performance (1 s added to each cut-off) did not change the conclusions drawn from the final model (data not shown).


In a comprehensive sample of 324 ambulatory HIV-infected patients, most of whom on cART and with controlled viral load, we show a very high prevalence of poor results in at least one of the standardized tests used to assess locomotor performance. By far, the most frequently altered test was the 5STS test, assessing lower limb muscle performance and balance, with poor performance in 53%. Poor performance in this test may put these patients at risk of falls [8,27] and ultimately contribute to a high risk of fractures. Six-minute walk distance, a marker of functional status and cardiorespiratory fitness, was below the age-specific threshold in 24%.

The definition for poor 5STS performance in our study was based on a unilateral cut-off at 2 SD from the age-specific mean in the general population. Therefore, one would expect a probability of a poor 5STS result in approximately 2–3% of the participants in all age categories. Hence, the frequency of poor 5STS performance was considerably higher in our sample than the expected frequency in the general population. With a median time required to complete the 5STS test of 9.8 s, raw test results of our study sample at a median age of 47.6 years equaled results expected at age higher than 60 years in the general population [24,28,29].

Although our study sample had, to a limited extent, different characteristics than the source population, there was no evidence that this could have contributed to an over-selection of patients with poor locomotor performance. Indeed, characteristics that were over-represented in the study sample were rather associated with normal test performance in the regression analyses.

We found a significant association between 5STS performance and time since HIV diagnosis in our final multivariable model. Neither current immunovirologic characteristics nor exposure to antiretroviral treatment were independently associated with 5STS performance. Particularly, no signal for an association with zidovudine exposure was detected in our analyses. A potential association with exposure to d-drugs did not reach significance in our study, but may warrant further exploration. Furthermore, one can hypothesize that other factors, such as nutrition, malabsorption and vitamin D status, may have an impact on the locomotor performance of HIV-infected patients.

In the final multivariable model, the relationship between BMI and 5STS performance varied with age: in younger patients, a lower BMI was associated with poor 5STS performance, whereas in older patients this relationship was reversed. Although no inference on temporal relationships and causality can be made due to the cross-sectional design of the study, it could be hypothesized that this finding might be due to changes in body composition with increasing age. Indeed, studies addressing the changes in body composition in the general population indicate that lean mass declines from the third to fourth decade onward, and particularly after the age of 50 years, whereas fat mass tends to increase [30–33]. Thus, for the same BMI, younger patients in our study might have had a higher amount of muscle mass, whereas older patients had a higher amount of fat mass. This could explain the observed interaction between BMI and age on the 5STS performance. However, our study did not include an assessment of body composition, which would allow for testing this hypothesis, and it may be warranted to confirm our findings in a study with prospective follow-up. Nevertheless, from a clinical perspective, it seems reasonable to encourage a sufficient level of physical activity to maintain muscle mass in HIV-infected patients.

In univariable comparisons, younger patients performed relatively worse on the 5STS test compared with older ones. Except for the interaction with BMI described above, no underlying factors explaining this finding could be identified. However, it cannot be excluded that primarily the fittest patients among the older ones were included in our study. It is also possible that our finding may reflect a real effect of selective survival of the fittest older HIV-infected patients.

The reference data for 5STS performance in the general population, derived from the literature [24], might have some limitations due to the fact that they were established in the United States and Canada. No other reference data across different age groups are available. Summary measures of test performance might vary between North America and France due to different population characteristics. Moreover, it cannot be excluded that the reference study favored the participation of relatively fit volunteers, therefore overestimating test performance in the general population. Nevertheless, robustness analyses with the use of a larger cut-off for poor performance still showed a considerable frequency of poor test performance in our study and did not alter the results of the final multivariable model.

Whatever the choice of the reference population, it remains methodologically difficult to attribute differences in performance between HIV-infected and HIV-uninfected populations directly to HIV infection, as the compared populations most likely always differ in terms of behavioral characteristics and other risk factors.

To the best of our knowledge, the present study is unique in being the largest investigation of locomotor function in the HIV-infected population using a broad range of standardized locomotor tests. The 5STS test is a functional assessment of lower limb muscle performance and balance [22,23] that can be easily performed in clinical practice. Given that the other balance tests used in our study were much less affected, one could speculate that poor 5STS performance in HIV-infected patients is primarily driven by lower limb muscle function.

Normal 5STS performance in current nonsmokers had a negative predictive value of 94% to exclude the presence of poor performance in any of the other locomotor tests. This finding suggests that the 5STS test may be useful on its own to screen HIV-infected patients for poor locomotor performance. In smokers and in patients with poor 5STS performance, further testing, particularly the six-minute walk test, could be warranted to determine locomotor performance.

Given the high frequency of poor 5STS performance found in whole study sample, we recommend to perform the 5STS test in standard care.

In conclusion, the high frequency of poor 5STS performance in our study suggests that lower limb muscle strength and power may be reduced in a large proportion of HIV-infected patients. 5STS performance is associated with risk of falls and disability in elderly community-dwelling individuals of the general population [8,27]. In the HIV-infected population, osteoporosis and osteopenia are highly prevalent [34]. Although assessments of fracture incidence have yielded variable results [35,36], several studies indicate that HIV-infected patients might have a higher fracture risk compared with uninfected individuals [37,38]. An increased risk of falls in HIV-infected patients could be detrimental given the coactions on fracture risk. The potential importance of this problem needs further evaluation. Longitudinal studies should be performed to assess the evolution of locomotor performance and the incidence of falls and their impact on fractures in the HIV-infected population.


This study was supported by grants from the French Agency for AIDS and Hepatitis Research (ANRS) and INSERM CIC-EC 7.

F.B. is receiving honoraria from Bristol-Myers Squibb, Gilead Sciences and ViiV healthcare. G.C. has received honoraria from Roche, and the author's institution has received funding from Gilead Sciences and Bohringer Ingelheim in the past.

For the remaining authors, no conflicts of interest are declared.

P.D., P.M., F.D., F.B. and G.C. participated in the design of the study. P.M., F.-A.D., C.G., and F.B. contributed to the recruitment of patients. P.D. had the responsibility for locomotor data acquisition. L.R., P.D., M.B., F.D. and G.C. overviewed the day-to-day conduct of the study. L.R. performed the statistical analysis and drafted the manuscript. G.C. provided advice on the statistical analysis. L.R., P.D., P.M., M.B., F.D., F.B. and G.C. were involved in interpretation of the data. All authors have read and approved the final version of the manuscript.

The authors wish to thank Charlotte Lewden who initiated this work, and the investigators and patients who participated in the study. The authors also acknowledge the work of Emma Bestaven, Sandrine Cerda and Guillaume Coldefy who carried out the locomotor assessments.

Members of the GECSA-COGLOC Study Group: M. Allard, H. Amieva, M. Auriacombe, S. Auriacombe, E. Bestaven, F. Bonnet, M. Bruyand, G. Catheline, G. Chêne, G. Coldefy, F. Dabis, J.-F. Dartigues, F.-A. Dauchy, S. Delveaux, P. Dehail, C. Greib, C. Lewden, J. Macua, F. Marquant, F. Matharan, P. Mercié, C. Milien, P. Morlat, N. Raoux, L. Richert

Composition of the Groupe d'Epidémiologie Clinique du SIDA en Aquitaine (GECSA), steering the ANRS CO3 Aquitaine Cohort:

Coordination: F. Dabis.

Epidemiology and Methodology: M. Bruyand, G. Chêne, F. Dabis, S. Lawson-Ayayi, R. Thiébaut.

Infectious Diseases and Internal Medicine: M. Bonarek, F. Bonnal, F. Bonnet, N. Bernard, O. Caubet, L. Caunègre, C. Cazanave, J. Ceccaldi, I. Chossat, F.A. Dauchy, M. Pillot-Debelleix, C. De La Taille, S. De Witte, M. Dupon, P. Duffau, H. Dutronc, S. Farbos, Y. Gerard, C. Greib, D. Lacoste, P. Lataste, S. Lafarie, E. Lazaro, P. Loste, D. Malvy, P. Mercié, P. Morlat, D. Neau, A. Ochoa, J.L. Pellegrin, T. Pistone, J.M. Ragnaud, M.C. Receveur, S. Tchamgoué, M.A. Vandenhende, J.F. Viallard.

Immunology: P. Blanco, J.F. Moreau, I. Pellegrin.

Virology: H. Fleury, M.E. Lafon, B. Masquelier. Pharmacology: D. Breilh.

Drug monitoring: G. Miremont-Salamé.

Data collection and processing: M.J. Blaizeau, M. Decoin, S. Delveaux, C. D'Ivernois, C. Hannapier, V. Jauvin, O. Leleux, B. Uwamaliya-Nziyumvira.

Computing and statistical analysis: S. Geffard, A. Kpozehouen, G. Palmer, D. Touchard.

Scientific committee: M. Dupon, M. Longy-Boursier, P. Morlat, J.L. Pellegrin, J.M. Ragnaud, F. Dabis.

Some data from this study were presented as an abstract at the 17th Conference on Retroviruses and Opportunistic Infections, 16–19 February 2010, San Francisco, USA.


1. Antiretroviral Therapy Cohort Collaboration. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies.Lancet 2008; 372:293–299.
2. Lewden C, Chene G, Morlat P, Raffi F, Dupon M, Dellamonica P, et al. HIV-infected adults with a CD4 cell count greater than 500 cells/mm3 on long-term combination antiretroviral therapy reach same mortality rates as the general population. J Acquir Immune Defic Syndr 2007; 46:72–77.
3. Deeks SG, Phillips AN. HIV infection, antiretroviral treatment, ageing, and non-AIDS related morbidity. BMJ 2009; 338:a3172.
4. Effros RB, Fletcher CV, Gebo K, Halter JB, Hazzard WR, Horne FM, et al. Aging and infectious diseases: workshop on HIV infection and aging – what is known and future research directions. Clin Infect Dis 2008; 47:542–553.
5. Doherty TJ. The influence of aging and sex on skeletal muscle mass and strength. Curr Opin Clin Nutr Metab Care 2001; 4:503–508.
6. Bean JF, Leveille SG, Kiely DK, Bandinelli S, Guralnik JM, Ferrucci L. A comparison of leg power and leg strength within the InCHIANTI study: which influences mobility more? J Gerontol A Biol Sci Med Sci 2003; 58:728–733.
7. Bliuc D, Nguyen ND, Milch VE, Nguyen TV, Eisman JA, Center JR. Mortality risk associated with low-trauma osteoporotic fracture and subsequent fracture in men and women. JAMA 2009; 301:513–521.
8. Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med 1995; 332:556–561.
9. Rusch M, Nixon S, Schilder A, Braitstein P, Chan K, Hogg RS. Impairments, activity limitations and participation restrictions: prevalence and associations among persons living with HIV/AIDS in British Columbia. Health Qual Life Outcomes 2004; 2:46.
10. Moyle G. Clinical manifestations and management of antiretroviral nucleoside analog-related mitochondrial toxicity. Clin Ther 2000; 22:911–936.
11. Scruggs ER, Dirks Naylor AJ. Mechanisms of zidovudine-induced mitochondrial toxicity and myopathy. Pharmacology 2008; 82:83–88.
12. Bauer LO, Ceballos NA, Shanley JD, Wolfson LI. Sensorimotor dysfunction in HIV/AIDS: effects of antiretroviral treatment and comorbid psychiatric disorders. AIDS 2005; 19:495–502.
13. Oursler KK, Katzel LI, Smith BA, Scott WB, Russ DW, Sorkin JD. Prediction of cardiorespiratory fitness in older men infected with the human immunodeficiency virus: clinical factors and value of the six-minute walk distance. J Am Geriatr Soc 2009; 57:2055–2061.
14. Scott WB, Oursler KK, Katzel LI, Ryan AS, Russ DW. Central activation, muscle performance, and physical function in men infected with human immunodeficiency virus. Muscle Nerve 2007; 36:374–383.
15. Thiebaut R, Morlat P, Jacqmin-Gadda H, Neau D, Mercie P, Dabis F, et al. Clinical progression of HIV-1 infection according to the viral response during the first year of antiretroviral treatment. Groupe d'Epidemiologie du SIDA en Aquitaine (GECSA). AIDS 2000; 14:971–978.
16. Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health 1992; 83(Suppl 2):S7–S11.
17. Steffen TM, Hacker TA, Mollinger L. Age- and gender-related test performance in community-dwelling elderly people: six-minute walk test, Berg balance scale, timed up & go test, and gait speeds. Phys Ther 2002; 82:128–137.
18. Enright PL, Sherrill DL. Reference equations for the six-minute walk in healthy adults. Am J Respir Crit Care Med 1998; 158:1384–1387.
19. Podsiadlo D, Richardson S. The timed ‘up & go': a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991; 39:142–148.
20. Duncan PW, Studenski S, Chandler J, Prescott B. Functional reach: predictive validity in a sample of elderly male veterans. J Gerontol 1992; 47:M93–M98.
21. Vereeck L, Wuyts F, Truijen S, Van de Heyning P. Clinical assessment of balance: normative data, and gender and age effects. Int J Audiol 2008; 47:67–75.
22. Lord SR, Murray SM, Chapman K, Munro B, Tiedemann A. Sit-to-stand performance depends on sensation, speed, balance, and psychological status in addition to strength in older people. J Gerontol A Biol Sci Med Sci 2002; 57:M539–M543.
23. Whitney SL, Wrisley DM, Marchetti GF, Gee MA, Redfern MS, Furman JM. Clinical measurement of sit-to-stand performance in people with balance disorders: validity of data for the five-times-sit-to-stand test. Phys Ther 2005; 85:1034–1045.
24. Bohannon RW, Shove ME, Barreca SR, Masters LM, Sigouin CS. Five-repetition sit-to-stand test performance by community-dwelling adults: a preliminary investigation of times, determinants, and relationship with self-reported physical performance. Isokinet Exerc Sci 2007; 15:77–81.
25. Demura S, Yamada T. Simple and easy assessment of falling risk in the elderly by functional reach test using elastic stick. Tohoku J Exp Med 2007; 213:105–111.
26. Antinori A, Arendt G, Becker JT, Brew BJ, Byrd DA, Cherner M, et al. Updated research nosology for HIV-associated neurocognitive disorders. Neurology 2007; 69:1789–1799.
27. Buatois S, Miljkovic D, Manckoundia P, Gueguen R, Miget P, Vancon G, et al. Five times sit to stand test is a predictor of recurrent falls in healthy community-living subjects aged 65 and older. J Am Geriatr Soc 2008; 56:1575–1577.
28. Butler AA, Menant JC, Tiedemann AC, Lord SR. Age and gender differences in seven tests of functional mobility. J Neuroeng Rehabil 2009; 6:31.
29. Lindsey C, Brownbill RA, Bohannon RA, Ilich JZ. Association of physical performance measures with bone mineral density in postmenopausal women. Arch Phys Med Rehabil 2005; 86:1102–1107.
30. Gallagher D, Ruts E, Visser M, Heshka S, Baumgartner RN, Wang J, et al. Weight stability masks sarcopenia in elderly men and women. Am J Physiol Endocrinol Metab 2000; 279:E366–E375.
31. Gallagher D, Visser M, De Meersman RE, Sepulveda D, Baumgartner RN, Pierson RN, et al. Appendicular skeletal muscle mass: effects of age, gender, and ethnicity. J Appl Physiol 1997; 83:229–239.
32. Janssen I, Heymsfield SB, Wang ZM, Ross R. Skeletal muscle mass and distribution in 468 men and women aged 18-88 yr. J Appl Physiol 2000; 89:81–88.
33. Kyle UG, Genton L, Hans D, Karsegard L, Slosman DO, Pichard C. Age-related differences in fat-free mass, skeletal muscle, body cell mass and fat mass between 18 and 94 years. Eur J Clin Nutr 2001; 55:663–672.
34. Cazanave C, Dupon M, Lavignolle-Aurillac V, Barthe N, Lawson-Ayayi S, Mehsen N, et al. Reduced bone mineral density in HIV-infected patients: prevalence and associated factors. AIDS 2008; 22:395–402.
35. Collin F, Duval X, Le Moing V, Piroth L, Al Kaied F, Massip P, et al. Ten-year incidence and risk factors of bone fractures in a cohort of treated HIV1-infected adults. AIDS 2009; 23:1021–1024.
36. Yin MT, Shi Q, Hoover DR, Anastos K, Sharma A, Young M, et al. Fracture incidence in HIV-infected women: results from the Women's Interagency HIV Study. AIDS 2010; 24:2679–2686.
37. Arnsten JH, Freeman R, Howard AA, Floris-Moore M, Lo Y, Klein RS. Decreased bone mineral density and increased fracture risk in aging men with or at risk for HIV infection. AIDS 2007; 21:617–623.
38. Triant VA, Brown TT, Lee H, Grinspoon SK. 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.

five-times sit-to-stand test; HIV infection; locomotion; muscle strength; physical function

Supplemental Digital Content

© 2011 Lippincott Williams & Wilkins, Inc.