Share this article on:

Relationship of physical function and quality of life among persons aging with HIV infection

Erlandson, Kristine M.; Allshouse, Amanda A.; Jankowski, Catherine M.; Mawhinney, Samantha; Kohrt, Wendy M.; Campbell, Thomas B.

doi: 10.1097/QAD.0000000000000384
Clinical Science: Concise Communication

Objective: Physical function impairments are seen among aging, HIV-infected persons on effective antiretroviral therapy (ART). The impact of physical function impairments on health-related quality of life (QoL) during ART is unknown.

Design: This was a cross-sectional study including 359 HIV-infected patients, aged 45–65 years, on ART for more than 6 months.

Methods: Patients completed the SF-36 QoL questionnaire, 400-m walk, 5-time chair rise, and grip strength. HIV-associated mortality risk was calculated using the Veterans Aging Cohort Study (VACS) Index. Physical function, physical activity (>500 versus ≤500 kcal/week), and VACS scores were used to estimate QoL in multivariable linear regression.

Results: For every 1 m/s increase in gait speed, we saw an estimated 11.8 [95% confidence interval (CI) 8.4, 15.2] point increase in the physical function scale with smaller differences across all subscales. For every 1 rise/s faster chair rise pace, we saw an estimated 16.0 (95% CI 9.1, 22.9) point increase in the physical function scale with smaller differences across all subscales. SF-36 scores were between 2.8 and 5.7 points higher among more physically active compared to less active patients. A 1 kg increase in grip strength was associated with a 0.2 (95% CI 0.01, 0.3) higher mental health score, but there were no differences in other subscales. VACS scores did not improve the model.

Conclusions: Faster gait speed and chair rise time, and greater physical activity were associated with greater QoL, independent of HIV-related mortality risk. Targeted exercise programs to increase physical activity and improve speed and power should be evaluated as interventions to improve QoL during ART.

Supplemental Digital Content is available in the text

University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.

Correspondence to Kristine M. Erlandson, 12700 E. 19th Avenue, Mail Stop B168, Aurora, CO 80045, USA. Tel: +1 303 724 4941; fax: +1 303 724 4926; e-mail:

Received 9 May, 2014

Revised 10 June, 2014

Accepted 11 May, 2014

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

Back to Top | Article Outline


Antiretroviral therapy (ART) has dramatically extended the life expectancy of those living with HIV and is changing the demographics of the HIV epidemic. Currently, nearly one-half of the people living with HIV in the United States are aged 50 or older [1]. The success of ART is partially offset by a higher-than-expected prevalence of age-associated complications including neurocognitive decline [2], osteoporosis and fractures [3–5], impaired physical function [6–8], frailty [9–13], and falls [14], conditions that can have a detrimental effect on an individual's quality of life (QoL). Maintaining independence, preventing functional decline, and preserving health-related QoL are considered the tenets of care for older adults, and overarching goals of the Healthy People 2020 [15]. Thus, a comprehensive understanding of the impact of HIV, ART, and age-associated comorbidities on QoL and physical function of persons aging with HIV is needed to improve HIV treatment in the coming decades.

Among older, HIV-uninfected adults, better performance on objective physical function tests including gait speed [16–19] and handgrip [18,20,21] or leg-extensor strength [20] is associated with higher QoL, oftentimes independent of underlying comorbidities. Furthermore, persons with greater self-reported or objectively measured physical activity tend to report higher QoL [18,22].

Physical function limitations are seen in older adults with effectively treated HIV infection [6–8] and are associated with underlying comorbidity. Similarly, underlying morbidity and mortality are strong predictors of health-related QoL, but the effects on QoL may differ between persons aging with or without HIV infection [23–25]. We hypothesized that impairment in objective measures of physical function and greater HIV-related morbidity or mortality would be associated with lower QoL.

Back to Top | Article Outline


Study population

The study population has been previously described [8]. Briefly, persons who received HIV-1 care in the Infectious Diseases Clinic at the University of Colorado Hospital within 12 months prior to February 2010 were evaluated for participation. Eligibility criteria included: 45–65 years of age; able to consent and participate in procedures; and taking effective combination (two or more) ART for at least 6 months with one undetectable plasma HIV-1 RNA (<48 copies/ml) and no plasma HIV-1 RNA above 200 copies/ml in the prior six months. Approval was obtained from the Colorado Multiple Institutional Review Board, and informed consent was obtained from all participants.

Back to Top | Article Outline

Clinical assessment

A single study visit included medical record review, standardized interview, health-related QoL questionnaire [short form (SF)-36 Health Survey], physical activity questionnaire [2-week recall of Minnesota Leisure Time Physical Activity (LTPA) questionnaire], and a physical function assessment [8]. The SF-36 yields eight subscales of health and well being that range from 0 (poorest) to 100 (highest) quality of life [26]. Activity metabolic index (AMI) units/week were computed from the LTPA questionnaire by combining light, moderate, and heavy activities, and provided an estimation of kcal/week [27,28]. An equivalent weekly activity of five 20-min walks for pleasure (500 kcal/week) or greater was used to dichotomize physical activity.

Grip strength was assessed by the average of three dominant hand-grip measurements using a single Lafayette dynamometer. Chair rise time was measured by five repetitions of sit-to-stand without use of the arms and reported as rises/second (i.e. pace). The 400-m gait speed was measured on a set walking course by asking the participant to walk as quickly as possible to complete the distance. The outcome was reported as gait speed in meters/second with a 0 assigned for a failure to walk 400 m.

The Veterans Aging Cohort Study (VACS) Index was calculated using the following parameters, as previously described: CD4+ cell count, viral load, age, aspartate aminotransferase, alanine aminotransferase, platelets, hemoglobin, hepatitis C, and estimated glomerular filtration rate [29]. Laboratory values were the most recent values available in the medical record. Time since HIV diagnosis and CD4+ lymphocyte nadir were by self-report and confirmed by medical records if available. Of a possible 164 points, higher values indicate greater mortality risk, and scores of 34 or less are associated with the lowest mortality [29]. All participants in the current study had plasma HIV-1 RNA viral load below 500 copies/ml; thus the highest possible VACS score was 150.

Back to Top | Article Outline

Statistical analysis

Data were collected and managed with Research Electronic Data Capture (REDCap) hosted at the University of Colorado [30]. Analyses were performed in SAS v9.3; SAS Institute Inc., Cary, North Carolina, USA). Study population characteristics were summarized with frequency and percentage for categorical measures, and mean with SD (or median with 25th and 75th percentiles) for continuous measures. Correlations between each SF-36 domain and measures of physical function were described with Pearson (400-m walk, chair rise, grip) or Spearman (physical activity, VACS Index) coefficients. For each SF-36 subscale, a multivariable linear regression model was estimated parameterized with the following covariates: 400-m gait speed, chair rise pace, grip strength, dichotomized physical activity, and VACS Index.

Back to Top | Article Outline


A total of 359 participants completed the study visit, of whom 85% were men, 74% Caucasian, 18% Hispanic or Latino, 65% were men who have sex with men, 21% reported prior intravenous drug use, and less than 1% reported current intravenous drug use. Mean age was 52 ± 5.2 years, the mean CD4+ lymphocyte count was 594 ± 303 cells/μl, and 95% had plasma HIV-1 RNA below the limits of detection. Other characteristics of the study population are provided in Table 1.

Table 1

Table 1

Mean grip strength was 39.0 ± 9.3 kg, mean chair rise pace was 0.51 ± 0.19 rise/s, and mean 400-m walk time was 1.43 ± 0.37 m/s. Eleven participants (3%) were unable to complete the 400-m walk and assigned a pace of 0. Eleven percentage reported no leisure-time physical activity in the prior 2 weeks, 19% had at least some physical activity but averaged less than 500 kcal/week, 42% reported 500–2500 kcal/week, and 29% reported more than 2500 kcal/week. VACS Index scores were calculated for each participant and ranged from 0 to 78 (mean 18.2 ± 0.7).

Median SF-36 QoL subscale scores are summarized in Table 2. Physical health summary scores were weakly to moderately correlated with gait speed [r = 0.50, 95% confidence interval (CI) 0.42, 0.57], chair rise pace (r = 0.44, 95% CI 0.35, 0.52), grip strength (r = 0.14, 95% CI 0.04, 0.24), physical activity (r = 0.39, 95% CI 0.29, 0.47), and VACS Index score (r = −0.16; 95% CI −0.26, −0.06) (all P < 0.003). Mental health summary scores were weakly to moderately correlated with gait speed (r = 0.24, 95% CI 0.14, 0.33), chair rise pace (r = 0.26, 95% CI 0.16, 0.35), grip strength (r = 0.22, 95% CI 0.12, 0.32), and physical activity (r = 0.32, 95% CI 0.22, 0.41) (all P < 0.001), but not VACS Index score (r = −0.002; 95% CI −0.11, 0.10).

Table 2

Table 2

The impact of demographics, HIV characteristics, physical function, physical activity, and morbidity/mortality risk (VACS Index) on QoL was assessed in univariate (Supplemental Table, models. The final multivariable linear regression models included physical function, physical activity, and the VACS Index (Table 2). The 400-m gait speed was a significant predictor in all of the eight multivariable models for the SF-36 subscales (Table 2). For every 1 m/s increase in gait speed on the 400-m walk, there was an estimated 11.8 point mean increase in the physical function subscale and an 8.4 point mean increase in the role physical subscale.

Chair rise pace and physical activity were significant in seven of the subscale models. For every increase of 1 rise/s on chair rise pace, there was an estimated 16.0 point increase in physical function scores and 15.0 point increase in social function scale with weaker but significant relationships across all subscales. Participants reporting greater physical activity had QoL scores between 2.8 and 5.7 points higher than those with lower physical activity.

In all eight models, estimates of the effect of grip strength and VACS Index were small in magnitude, and had narrow 95% CIs including zero. Thus, for this population, grip strength and the VACS Index were not predictive of QoL outcomes (Table 2).

Back to Top | Article Outline


Although impairments in physical function have been reported among older adults with HIV infection, no prior studies have evaluated the impact of physical function impairments on QoL, independent of mortality risk. Similar to studies among older adults without HIV infection, we found significant correlations between gait speed, chair rise time, and grip strength with both physical and mental QoL. In regression models, the association between gait speed and chair rise time with both physical and mental health QoL domains remained stronger than demographic or HIV variables (VACS Index).

Our findings highlight several important issues among persons aging with HIV infection. First, we demonstrate that gait speed is a key measure of health and wellness among adults aging with HIV infection, similar to older HIV-uninfected adults in whom self-selected gait speed is a strong predictor of loss of independence, disability, and mortality [31–35]. Second, although closely related [25,36,37], mortality risk is not correlated to QoL, as demonstrated by the strong association of QoL with gait speed or chair rise, but not VACS Index. This finding is reassuring because gait speed and chair rise time may be improved by exercise or strength training interventions. Conversely, many measures of the VACS Index are nonmodifiable. Next, physically active older adults have greater QoL in both physical and mental health domains, independent of physical function. Lastly, our findings demonstrate that objective physical function measures provide an assessment of QoL in aging adults beyond the mortality risk estimated by the VACS Index.

Our study describes a large cohort of well characterized middle-aged men and women on effective ART, but does have several limitations. First, as a cross-sectional study, we are unable to demonstrate causality in the relationships between QoL and physical function or physical activity. The range of VACS Index scores was relatively small; thus the findings may not be applicable to persons with higher VACS Index scores. Similarly, the age range of 20 years may have limited our ability to detect associations with age and QoL seen in the youngest and oldest patients. Alternatively, the lack of association with age and QoL may illustrate ‘decreasing aspiration’, where increasing age is associated with lower health expectations [38]. The physical activity assessment in our study was by self-report, and persons with higher QoL may report higher levels of physical activity.

In summary, faster gait speed and chair rise time, and greater physical activity were associated with greater QoL among adults aging with effectively controlled HIV, independent of HIV-related mortality risk. Our findings suggest that measures of physical function and mortality risk may provide a complementary and more inclusive assessment of health and disease, although longitudinal studies are needed to confirm these relationships over time. Targeted exercise programs to increase physical activity and improve lower-extremity muscle speed and power should be evaluated as interventions to improve QoL in adults aging with HIV infection.

Back to Top | Article Outline


K.M.E. developed and led the study protocol. A.A.A., C.M.J., S.M., W.M.K., and T.B.C. assisted with study development and implementation. A.A.A. and S.M. conducted the study analysis. K.M.E. assisted with the data analysis plan and prepared the initial draft of the manuscript. All authors reviewed and edited the manuscript.

The study was supported by funding through the Hartford Foundation Center of Excellence, and the National Institutes of Health R03AG040594 and UL1 TR001082.

Back to Top | Article Outline

Conflicts of interest

The contents are the authors’ sole responsibility and do not necessarily represent official NIH views.

Back to Top | Article Outline


1. 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.
2. Sacktor N, Skolasky RL, Cox C, Selnes O, Becker JT, Cohen B, et al. Longitudinal psychomotor speed performance in human immunodeficiency virus-seropositive individuals: impact of age and serostatus. J Neurovirol 2010; 16:335–341.
3. Womack JA, Goulet JL, Gibert C, Brandt C, Chang CC, Gulanski B, et al. Increased risk of fragility fractures among HIV infected compared to uninfected male veterans. PLoS One 2011; 6:e17217.
4. Young B, Dao CN, Buchacz K, Baker R, Brooks JT. Increased rates of bone fracture among HIV-infected persons in the HIV Outpatient Study (HOPS) compared with the US general population. Clin Infect Dis 2011; 52:1061–1068.
5. Walker Harris V, Brown TT. Bone loss in the HIV-infected patient: evidence, clinical implications, and treatment strategies. J Infect Dis 2012; 205 (Suppl 3):S391–398.
6. Oursler KK, Sorkin JD, Smith BA, Katzel LI. Reduced aerobic capacity and physical functioning in older HIV-infected men. AIDS Res Hum Retroviruses 2006; 22:1113–1121.
7. Richert L, Dehail P, Mercie P, Dauchy FA, Bruyand M, Greib C, et al. High frequency of poor locomotor performance in HIV-infected patients. AIDS 2011; 25:797–805.
8. Erlandson KM, Allshouse AA, Jankowski CM, Duong S, Mawhinney S, Kohrt WM, et al. Comparison of functional status instruments in HIV-infected adults on effective antiretroviral therapy. HIV Clin Trials 2012; 13:324–334.
9. Desquilbet L, Jacobson LP, Fried LP, Phair JP, Jamieson BD, Holloway M, et al. HIV-1 infection is associated with an earlier occurrence of a phenotype related to frailty. J Gerontol A Biol Sci Med Sci 2007; 62:1279–1286.
10. Desquilbet L, Jacobson LP, Fried LP, Phair JP, Jamieson BD, Holloway M, et al. A frailty-related phenotype before HAART initiation as an independent risk factor for AIDS or death after HAART among HIV-infected men. J Gerontol A Biol Sci Med Sci 2011; 66:1030–1038.
11. Desquilbet L, Margolick JB, Fried LP, Phair JP, Jamieson BD, Holloway M, et al. Relationship between a frailty-related phenotype and progressive deterioration of the immune system in HIV-infected men. J Acquir Immune Defic Syndr 2009; 50:299–306.
12. Onen NF, Agbebi A, Shacham E, Stamm KE, Onen AR, Overton ET. Frailty among HIV-infected persons in an urban outpatient care setting. J Infect 2009; 59:346–352.
13. Terzian AS, Holman S, Nathwani N, Robison E, Weber K, Young M, et al. Factors associated with preclinical disability and frailty among HIV-infected and HIV-uninfected women in the era of cART. J Womens Health 2009; 18:1965–1974.
14. Erlandson KM, Allshouse AA, Jankowski CDS, MaWhinney S, Kohrt WM, Campbell TB. Risk factors for falls in HIV-infected persons. J Acquir Immune Defic Syndr 2012; 61:484–489.
15. Older Adults. 2020 topics and objectives. [Accessed 3 January 2014]
16. Jylha M, Guralnik JM, Balfour J, Fried LP. Walking difficulty, walking speed, and age as predictors of self-rated health: the women's health and aging study. J Gerontol A Biol Sci Med Sci 2001; 56:M609–617.
17. Horder H, Skoog I, Frandin K. Health-related quality of life in relation to walking habits and fitness: a population-based study of 75-year-olds. Qual Life Res 2013; 22:1213–1223.
18. Wanderley FA, Silva G, Marques E, Oliveira J, Mota J, Carvalho J. Associations between objectively assessed physical activity levels and fitness and self-reported health-related quality of life in community-dwelling older adults. Qual Life Res 2011; 20:1371–1378.
19. Ekstrom H, Dahlin-Ivanoff S, Elmstahl S. Effects of walking speed and results of timed get-up-and-go tests on quality of life and social participation in elderly individuals with a history of osteoporosis-related fractures. J Aging Health 2011; 23:1379–1399.
20. Takata Y, Ansai T, Soh I, Awano S, Yoshitake Y, Kimura Y, et al. Quality of life and physical fitness in an 85-year-old population. Arch Gerontol Geriatr 2010; 50:272–276.
21. Sayer AA, Syddall HE, Martin HJ, Dennison EM, Roberts HC, Cooper C. Is grip strength associated with health-related quality of life? Findings from the Hertfordshire Cohort Study. Age Ageing 2006; 35:409–415.
22. Martin CK, Church TS, Thompson AM, Earnest CP, Blair SN. Exercise dose and quality of life: a randomized controlled trial. Arch Intern Med 2009; 169:269–278.
23. Oursler KK, Goulet JL, Crystal S, Justice AC, Crothers K, Butt AA, et al. Association of age and comorbidity with physical function in HIV-infected and uninfected patients: results from the Veterans Aging Cohort Study. AIDS Patient Care STDS 2011; 25:13–20.
24. Oursler KK, Goulet JL, Leaf DA, Akingicil A, Katzel LI, Justice A, et al. Association of comorbidity with physical disability in older HIV-infected adults. AIDS Patient Care STDS 2006; 20:782–791.
25. Rodriguez-Penney AT, Iudicello JE, Riggs PK, Doyle K, Ellis RJ, Letendre SL, et al. Co-morbidities in persons infected with HIV: increased burden with older age and negative effects on health-related quality of life. AIDS Patient Care STDS 2013; 27:5–16.
26. McHorney CA, Ware JE Jr, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 1993; 31:247–263.
27. Pereira MA, FitzerGerald SJ, Gregg EW, Joswiak ML, Ryan WJ, Suminski RR, et al. A collection of Physical Activity Questionnaires for health-related research. Med Sci Sports Exerc 1997; 29:S1–205.
28. Taylor HL, Jacobs DR Jr, Schucker B, Knudsen J, Leon AS, Debacker G. A questionnaire for the assessment of leisure time physical activities. J Chronic Dis 1978; 31:741–755.
29. Justice AC, Freiberg MS, Tracy R, Kuller L, Tate JP, Goetz MB, et al. Does an index composed of clinical data reflect effects of inflammation, coagulation, and monocyte activation on mortality among those aging with HIV?. Clin Infect Dis 2012; 54:984–994.
30. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap): a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42:377–381.
31. Vestergaard S, Patel KV, Walkup MP, Pahor M, Marsh AP, Espeland MA, et al. Stopping to rest during a 400-meter walk and incident mobility disability in older persons with functional limitations. J Am Geriatr Soc 2009; 57:260–265.
32. Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, et al. Gait speed and survival in older adults. J Am Med Assoc 2011; 305:50–58.
33. Newman AB, Simonsick EM, Naydeck BL, Boudreau RM, Kritchevsky SB, Nevitt MC, et al. Association of long-distance corridor walk performance with mortality, cardiovascular disease, mobility limitation, and disability. J Am Med Assoc 2006; 295:2018–2026.
34. Diehr PH, Thielke SM, Newman AB, Hirsch C, Tracy R. Decline in health for older adults: five-year change in 13 key measures of standardized health. J Gerontol A Biol Sci Med Sci 2013; 68:1059–1067.
35. White DK, Neogi T, Nevitt MC, Peloquin CE, Zhu Y, Boudreau RM, et al. Trajectories of gait speed predict mortality in well functioning older adults: the Health, Aging and Body Composition study. J Gerontol A Biol Sci Med Sci 2013; 68:456–464.
36. Emlet CA, Fredriksen-Goldsen KI, Kim HJ. Risk and protective factors associated with health-related quality of life among older gay and bisexual men living with HIV disease. Gerontologist 2013; 53:963–972.
37. Balderson BH, Grothaus L, Harrison RG, McCoy K, Mahoney C, Catz S. Chronic illness burden and quality of life in an aging HIV population. AIDS Care 2013; 25:451–458.
38. Tornstam L. Health and self-perception: a systems theoretical approach. Gerontologist 1975; 15:264–270.

HIV; human; neuropsychological; physical activity; physical conditioning; psychiatry; psychosocial; quality of life

© 2014 Lippincott Williams & Wilkins, Inc.