Frailty, HIV Infection, and Mortality in an Aging Cohort of
Injection Drug Users
Damani A. Piggott1,2*, Abimereki D. Muzaale1,2, Shruti H. Mehta2, Todd T. Brown1,2, Kushang V. Patel3,
Sean X. Leng1, Gregory D. Kirk1,2
1Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America, 2Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,
United States of America, 3University of Washington School of Medicine, Seattle, Washington, United States of America
Background: Frailty is associated with morbidity and premature mortality among elderly HIV-uninfected adults, but the
determinants and consequences of frailty in HIV-infected populations remain unclear. We evaluated the correlates of frailty,
and the impact of frailty on mortality in a cohort of aging injection drug users (IDUs).
Methods: Frailty was assessed using standard criteria among HIV-infected and uninfected IDUs in 6-month intervals from
2005 to 2008. Generalized linear mixed-model analyses assessed correlates of frailty. Cox proportional hazards models
estimated risk for all-cause mortality.
Results: Of 1230 participants at baseline, the median age was 48 years and 29% were HIV-infected; the frailty prevalence
was 12.3%. In multivariable analysis of 3,365 frailty measures, HIV-infected IDUs had an increased likelihood of frailty (OR,
1.66; 95% CI, 1.24–2.21) compared to HIV-uninfected IDUs; the association was strongest (OR, 2.37; 95% CI, 1.62–3.48)
among HIV-infected IDUs with advanced HIV disease (CD4,350 cells/mm3 and detectable HIV RNA). No significant
association was seen with less advanced disease. Sociodemographic factors, comorbidity, depressive symptoms, and
prescription drug abuse were also independently associated with frailty. Mortality risk was increased with frailty alone (HR
2.63, 95% CI, 1.23–5.66), HIV infection alone (HR 3.29, 95% CI, 1.85–5.88), and being both HIV-infected and frail (HR, 7.06;
Conclusion: Frailty was strongly associated with advanced HIV disease, but IDUs with well-controlled HIV had a similar
prevalence to HIV-uninfected IDUs. Frailty was independently associated with mortality, with a marked increase in mortality
risk for IDUs with both frailty and HIV infection.
Citation: Piggott DA, Muzaale AD, Mehta SH, Brown TT, Patel KV, et al. (2013) Frailty, HIV Infection, and Mortality in an Aging Cohort of Injection Drug Users. PLoS
ONE 8(1): e54910. doi:10.1371/journal.pone.0054910
Editor: Alan Landay, Rush University, United States of America
Received September 19, 2012; Accepted December 19, 2012; Published January 31, 2013
Copyright: ? 2013 Piggott et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the National Institutes of Health (grants RC1-AI-086053, R01-DA-04334, and R01-DA-12568). The funders had no role in
study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
Frailty is a clinical syndrome which increases in prevalence with
age and identifies older persons at higher risk for falls, disability,
institutionalization, and death [1,2]. Conceptualized as a state of
diminished reserves due to deficits across multiple physiologic
systems, frailty leads to an increased vulnerability and limited
adaptability to internal and external stressors [1,2]. A frailty
phenotype, operationalized by Fried and colleagues, predicts
adverse clinical outcomes in geriatric populations [3,4].
Since the advent of highly active antiretroviral therapy
(HAART), improved survival of HIV-infected individuals has led
to an increasing prevalence of older persons living with HIV [5,6].
However, several studies suggest that even with guideline
concordant care, HIV-infected persons have reduced life expec-
tancy relative to the general population and to HIV-uninfected
controls with similar behavioral risk [7,8].
An estimated 3.4 million persons in the U.S. report injecting
drugs at some time in their lifetime and this population of injection
drug users (IDUs) has also been aging . IDUs have decreased
survival attributable to HIV and to other behaviorally-associated
comorbid disease [10,11,12].
Limited data exist regarding the determinants of frailty among
HIV-infected and drug using populations. A higher prevalence of
a modified frailty-related phenotype was observed for HIV-
infected men who have sex with men (MSM) compared to HIV-
uninfected MSM . An increased prevalence of frailty was also
seen among HIV-infected women with limited immunological
recovery , while in an urban HIV clinic setting, frailty was
associated with prior opportunistic infections . To date, no
studies have examined frailty in an IDU population. Moreover,
while frailty increases mortality risk in older HIV-uninfected
persons, the effect of frailty on mortality among HIV-infected and
at risk IDUs is unknown.
Ensuring the healthy aging of HIV-infected and at-risk persons
may be facilitated by earlier interventions among persons at
greatest risk for adverse age-associated clinical outcomes. In the
PLOS ONE | www.plosone.org1 January 2013 | Volume 8 | Issue 1 | e54910
current study, we postulated that frailty may be an appropriate
phenotype to identify this high-risk subset. Incorporating the
objective criteria originally proposed by Fried, we sought to
characterize the demographic, behavioral, and clinical correlates
of frailty in an aging cohort of HIV-infected and HIV-uninfected
IDUs, and to assess the impact of frailty on mortality in this
The AIDS Linked to the IntraVenous Experience (ALIVE)
cohort has prospectively followed persons with a history of
injecting drugs in a community-recruited cohort since 1988. IDUs
aged 18 years or older were recruited through street-based efforts
from 1988 through 2008 as previously detailed [16,17]. The
ALIVE study has been continually approved by the Johns Hopkins
Institutional Review Board, and all participants provided written
At semi-annual visits, ALIVE participants completed standard-
ized questionnaires and underwent clinical examination. Detailed
information obtained at each follow-up visit included socioeco-
nomic, behavioral, and clinical parameters for the prior 6 month
period. Substance use including alcohol, tobacco and illicit
injection and non-injection drug use were assessed by participant
self report of behaviors in the prior 6 month period. Comorbid
conditions ascertained included obesity (defined as a body mass
index [BMI] $30) and participant self-report of any provider
diagnosis of diabetes, hypertension, or cerebrovascular, cardiovas-
cular, renal, chronic lung, malignant, or liver disease. Hazardous
alcohol use was assessed using the Alcohol Use Disorders
Identification Test (AUDIT) . Depressive symptoms were
assessed using the Center for Epidemiological Studies Depression
Scale (CES-D) . Prescription drug abuse was by participant
self report of abuse of drugs prescribed to them by a physician in
the last year . HAART was defined as use of at least 3
antiretroviral drugs, 1 of which was a nonnucleoside reverse-
transcriptase inhibitor, tenofovir, abacavir, or a protease inhibitor
and was reflective of use in the prior 6 months .
At each visit, HIV-uninfected persons had antibodies to HIV-1
assayed by enzyme-linked immunosorbent assay, with Western
blot confirmation. CD4 cell counts were measured on HIV-
infected persons at each visit using flow cytometry, and plasma
HIV-1 RNA levels determined using reverse-transcriptase PCR
methods. Mortality was assessed through linkage to the National
Death Index (NDI) with review of death certificates to confirm
Frailty was assessed using the 5 original Fried criteria: slow gait,
decreased grip strength (weakness), poor endurance (exhaustion),
low physical activity, and physical shrinking (weight loss) (Table
S1) . Frailty assessment was routinely performed in ALIVE at
six month intervals from July 2005 through the study period (91%
of person-visits assessed), except that in March 2007 the
assessment interval was altered to an annual basis until funding
was secured to allow semi-annual assessment again in January
2008. For the physical activity domain, in lieu of the Minnesota
Activity assessment of kilocalorie expenditure utilized by Fried, we
incorporated the self-reported response to a standardized question
on physical limitations as previously characterized in the
Multicenter AIDS Cohort Study (MACS) [13,22]. Physical
shrinking at each visit was defined as measured weight loss of
$5% body weight from the prior study visit. For analysis, we
included weight assessments that were 5 to 12 months from the last
measurement (95% of all measurements). Each frailty parameter
was considered as a binary variable (0, 1) and summed to obtain a
frailty score; $3 was considered frail, 1 or 2 considered prefrail,
and scores of 0 considered robust.
We compared participant characteristics by HIV status and by
frailty status at baseline and by person-visits. For each person-visit,
frailty was treated as a 3 category outcome (robust, prefrail, frail).
Using all person-visits, generalized linear mixed models estimated
associations of sociodemographic, behavioral, and clinical factors
with the frailty phenotype, comparing frail to robust and prefrail to
robust. To account for the intra-person correlation within the
repeated frailty measures, participants were incorporated as
random effects, with other covariates considered fixed effects
. Age was included as a continuous variable. Given the
predominance of African Americans in the cohort, self-reported
race was dichotomized as African American versus other.
Depressive symptomatology was assessed using a modified version
of the CES-D scale, removing the 2 items included in the frailty
assessment and adjusting the score to consider $21 as indicative of
depressive symptoms. In sensitivity analyses using variable CES-D
cutpoints or including the frailty-associated items, findings were
not significantly changed. An AUDIT score of $8 was considered
to be indicative of hazardous alcohol use . In sensitivity
analyses excluding the period of annual frailty assessment, no
substantive changes to the covariate associations with prefrailty
and frailty were observed.
To evaluate the relationship between prefrailty and frailty with
all-cause mortality, Kaplan-Meier survival analyses and Cox
proportional hazards regression models were performed. The
index (baseline) visit, defined as the first visit for which frailty was
measured, was the time origin with observation until date of death
or for those remaining alive, December 31, 2008. Frailty status,
CD4 count, and HIV viral load were considered as time-varying
covariates. To evaluate the independent and joint effects of HIV
and frailty on mortality, we constructed a 4-category variable
combining HIV status (positive/negative) with frailty status (frail if
score $3; nonfrail if score 0–2). Given the lack of association of
prefrailty (frailty score 1–2) with increased risk of mortality relative
to the robust group, we combined the robust group with the
prefrail group to create the ‘‘nonfrail’’ group for this 4-category
variable. Unadjusted hazard ratios were estimated, with multivar-
iable models constructed based on inclusion of variables found to
be associated with the outcome and of variables considered a priori
to be important predictors of mortality. The proportional hazards
assumption was found to be reasonable by graphical assessment.
Analyses were performed using STATA (version 11; Stata Corp.,
College Station, TX).
A total of 1230 ALIVE participants contributed 3365 person-
visits (median of 3 frailty measurements; IQR, 2–4). At initial
frailty assessment, the median age of participants was 48 years
(IQR, 42.9, 52.5), 89% were African American, 66% were male
and 29% were HIV-infected. Of the 3365 person-visits (Table 1),
31% were among HIV-infected persons, with a median CD4 cell
count of 296 (IQR, 168, 475) cells/uL, and a median viral load of
2.7 (IQR, 1.6, 4.4) log10 copies/ml. Recent HAART use was
reported at 54% of visits.
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org2 January 2013 | Volume 8 | Issue 1 | e54910
At the index visit, 12.3% of participants were classified as frail
and 62.1% as prefrail. Among all 3365 person-visits, 12.4% (417
person-visits) met criteria for frailty and 60% (2020 person-visits)
criteria for prefrailty. Univariate and multivariate associations with
frailty and prefrailty are shown in Table 2. In multivariable
analysis, frailty was significantly associated with older age, female
gender, lower educational attainment, absence of a cohabitating
partner, depressive symptoms, and increased number of comorbid
conditions (Table 2). In univariate analysis, frailty was associated
with hazardous alcohol use, being homeless, and non-injection use
of illicit drugs. However, these associations did not retain
significance in multivariable analyses. HIV infection was associ-
ated with a 66% greater likelihood of frailty (OR, 1.66; 95% CI,
1.24–2.21) (Table 2, Model A). In further analysis of HIV disease
status (Table 2, Model B), having both immunosuppression (CD4
count ,350 cells) and a detectable viral load was significantly
associated with frailty (OR, 2.37; 95% CI, 1.62–3.48). There was
no significant difference in frailty between HIV-uninfected person-
visits and those of HIV-infected persons with a CD4 count $350
cells and an undetectable viral load while modest, but non-
significant associations were seen for HIV-infected IDUs with
either lower CD4 counts only or detectable viral load only. In joint
analysis of current and nadir CD4 count, current CD4 count but
not CD4 nadir was found to be significantly associated with frailty
(data not shown). In separate adjusted models, HIV-infected IDUs
not receiving HAART had a substantially greater likelihood of
frailty (OR, 1.91; 95% CI, 1.32–2.75) compared to HIV-
uninfected IDUs, although this association was substantially
attenuated but remained significant with recent HAART usage
(OR, 1.45; 95% CI, 1.01–2.07) (Table 2, Model C). In models
stratifying by severity of HIV disease, frailty was consistently
associated with advanced (but not less advanced) HIV disease
irrespective of HAART use.
In adjusted analysis of prefrailty, factors significantly associated
with frailty generally remained similarly associated, but the
associations were more modest in magnitude (Table 2), with the
exception that comorbidity was not associated with prefrailty.
HIV-infected IDUs had a 38% greater likelihood of prefrailty
compared to HIV-uninfected IDUs (OR, 1.38; 95% CI, 1.11–
1.70), and having a CD4 count,350 and detectable HIV viral
load was significantly associated with prefrailty (OR, 1.79; 95%
During prospective evaluation of the relationship of frailty and
prefrailty with mortality, we observed 73 deaths over 2644 person-
years for a mortality rate of 2.8 per 100 person-years. Overall, frail
persons had substantially higher mortality compared to persons
that were either prefrail or robust (Figure 1). Adjusting for
sociodemographic factors in Cox proportional hazards models,
frailty (HR, 2.77; 95% CI, 1.32–5.81), having 3 or more comorbid
conditions (HR, 2.97; 95%CI, 1.65–5.35) and HIV infection (HR,
3.05; 95%CI, 1.89–4.93) were independently associated with
mortality (Table 3, Model A). Controlling for frailty status and
comorbidity, HIV-infected IDUs with advanced disease had
notably increased mortality risk (HR, 5.83; 95% CI, 3.48–9.74),
with no significantly increased risk of death for those with less
advanced HIV disease compared to HIV negatives (Table 3,
Model B). The prefrail state was not a significant predictor of
death in these models. In models with HIV-uninfected, nonfrail
persons as the referent group (Figure 2; Table 3, Model C) being
HIV-infected or being frail conferred an increased mortality risk
with an approximately 3-fold magnitude for each. Persons that
were both HIV-infected and frail had an over 7-fold increased risk
of death (HR, 7.06; 95% CI, 3.49–14.3).
In this study, we incorporated standardized assessment of frailty
into a community cohort of HIV-infected and epidemiologically-
comparable HIV-uninfected IDUs. We identified a frailty
prevalence of 12.3% and found that HIV infection, particularly
advanced disease stage with lower CD4 cell counts and the
absence of ART or virological suppression, was strongly associated
with frailty. Despite our cohort being relatively young compared to
geriatric populations where frailty has been shown to presage
adverse clinical outcomes, frailty was independently associated
with increased mortality risk in prospective analysis even after
accounting for sociodemographic variables, comorbidity, and HIV
infection. Moreover, the combined effect of frailty and HIV on
mortality appeared to exceed what one would expect from the
additive effect of the individual exposures. In summary, these
findings suggest that frailty is a useful phenotype for investigating
aging among HIV-infected IDUs and could potentially identify
individuals at high-risk for adverse outcomes among these highly
vulnerable groups. Our data also raise the possibility that optimal
Table 1. Characteristics of 1230 ALIVE Participants at 3365
Study Visits, by HIV Statusa.
N=2306 visitsN=1059 visits
No. (%) No. (%)
Age, median (IQR), y49.3 (44.2, 54.0)48.7 (44.6, 52.8)
Female 751 (32.6) 388 (36.6)
African American 2074 (89.9)1017 (96.0)
Less than high school education1318 (57.2) 682 (64.9)
Not married/common law2109 (91.5)1004 (95.4)
280 (12.2)112 (10.6)
Hazardous alcohol useb
530 (23.0)196 (18.5)
Recent injection drug useb
925 (40.1) 331 (31.3)
Any non-injection drug useb
1055 (45.8)345 (32.6)
Recent tobacco useb
1894 (82.2)851 (80.7)
Prescription drug abusec
244 (10.6)58 (5.5)
491 (21.3) 212 (20.0)
# Comorbid Conditionsd
0–11636 (72.2)770 (73.8)
2 373 (16.5)173 (16.6)
$3 257 (11.3)101 (9.7)
CD4+cell count, median (IQR)296 (168, 475)
HIV RNA, median (IQR), log10copies/ml
Median CD4+nadir (IQR)
2.66 (1.60, 4.43)
135 (53, 230)
Abbreviations: HAART, highly active antiretroviral therapy; IQR, interquartile
range; y, years; Hazardous alcohol use, score of $8 on the AUDIT; Depressive
symptoms, score of $21 on the CES-D.
aData are no. (%) of participants, unless otherwise indicated.
bReflect characteristics within the previous 6 months.
cReflect characteristics within the prior year.
dDiabetes, Hypertension, Cerebrovascular accident, Cardiovascular disease,
Renal disease, Chronic obstructive pulmonary disease, Cancer, Obesity, Liver
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org3 January 2013 | Volume 8 | Issue 1 | e54910
Table 2. Factors Associated with Frailty and Prefrailty among 3365 ALIVE Study Person-Visitsa.
Model A. Odds of Frailty and Prefrailty by Sociodemographic, Behavioral, and Clinical Risk Factorsb
OR (95% CI) OR (95% CI) OR (95% CI)OR (95% CI)
Age (per year) 1.00 (0.99, 1.01) 1.02 (1.00, 1.03)1.03 (1.01, 1.05) 1.05 (1.03, 1.07)
Female 1.24 (1.02, 1.51)1.17 (0.95, 1.45) 1.62 (1.23, 2.13)1.44 (1.07, 1.94)
African American0.72 (0.52, 1.00) 0.72 (0.50, 1.04) 0.76 (0.47, 1.23)0.67 (0.40, 1.13)
Less than high school education 1.27 (1.05, 1.54)1.25 (1.03, 1.52)1.43 (1.09, 1.87) 1.48 (1.12, 1.95)
Not married/common law1.56 (1.08, 2.23)1.57 (1.08, 2.29)1.77 (1.02, 3.06) 2.05 (1.16, 3.60)
1.23 (0.93, 1.61)– 1.49 (1.06, 2.11)–
Hazardous alcohol used
1.20 (0.98, 1.48)– 1.47 (1.12, 1.92)–
Recent injection drug used
1.04 (0.87, 1.23)– 1.00 (0.79, 1.27)–
Any non-injection drug used
1.21 (1.01, 1.44)– 1.38 (1.09, 1.75)–
Recent tobacco used
1.11 (0.88, 1.41)– 1.32 (0.94, 1.85)–
Prescription drug abusee
1.66 (1.20, 2.29)1.50 (1.05, 2.14) 2.14 (1.45, 3.14)1.70 (1.11, 2.59)
2.23 (1.77, 2.81) 2.11 (1.66, 2.69) 4.70 (3.58, 6.16)4.40 (3.31, 5.84)
# Comorbid conditionsf
0–1 RefRef Ref Ref
2 1.08 (0.85, 1.38)1.05 (0.82, 1.35) 1.87 (1.40, 2.49)1.70 (1.26, 2.30)
$3 1.18 (0.87, 1.60)1.10 (0.80, 1.51) 2.67 (1.84, 3.87)2.06 (1.39, 3.05)
HIV negativeRef RefRef Ref
HIV positive1.34 (1.09, 1.64) 1.38 (1.11, 1.70)1.53 (1.15, 2.02)1.66 (1.24, 2.21)
Model B. Odds of Frailty and Prefrailty by CD4 and VL Stratac
Prefrail PrefrailFrail Frail
OR (95% CI)OR (95% CI) OR (95% CI)OR (95% CI)
HIV negativeRef Ref RefRef
CD4$350, VL UD1.10 (0.79, 1.55) 1.18 (0.82, 1.69) 1.03 (0.64, 1.65)1.09 (0.67, 1.77)
CD4,350, VL UD 1.23 (0.82, 1.84)1.33 (0.89, 2.00) 1.35 (0.81, 2.25)1.47 (0.86, 2.51)
1.06 (0.71, 1.58)1.04 (0.69, 1.56) 1.33 (0.80, 2.22) 1.37 (0.80, 2.36)
1.76 (1.33, 2.33)1.79 (1.33, 2.39) 2.12 (1.46, 3.07)2.37 (1.62, 3.48)
Model C. Odds of Frailty and Prefrailty by HAART statusc
OR (95% CI) OR (95% CI)OR (95% CI) OR (95% CI)
HIV negativeRefRef Ref Ref
1.30 (1.01, 1.67) 1.40 (1.08, 1.81)1.27 (0.90, 1.80)1.45 (1.01, 2.07)
1.38 (1.07, 1.80)1.35 (1.03, 1.77)1.87 (1.31, 2.65) 1.91 (1.32, 2.75)
Abbreviations : HAART, highly active antiretroviral therapy; VL, HIV viral load; UD, undetectable, ,50 HIV RNA copies/ml; Hazardous alcohol use, score of $8 on the
AUDIT; Depressive symptoms, score of $21 on the CES-D.
– Not included in final model/not significant in adjusted analyses.
aData are given as unadjusted and adjusted odds ratios (95% confidence interval).
bAdjusted for age, gender, race, education, marital status, prescription drug abuse, depressive symptoms, # comorbid conditions and HIV status.
cAdjusted for age, gender, race, education, marital status, prescription drug abuse, depressive symptoms, and # comorbid conditions.
dReflect characteristics within the previous 6 months.
eReflect characteristics within the prior year.
fDiabetes, Hypertension, Cerebrovascular accident, Cardiovascular disease, Renal disease, Chronic obstructive pulmonary disease, Cancer, Obesity, Liver disease.
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org4 January 2013 | Volume 8 | Issue 1 | e54910
HIV care with virological suppression could attenuate the
development of frailty.
Aberrant inflammation and immune dysregulation have been
hypothesized to characterize the natural process of aging as well as
underlie the pathogenesis of chronic HIV disease . Based on
emerging epidemiologic, clinical, and mechanistic evidence,
inflammation and immune dysfunction are postulated to play a
central role in frailty pathophysiology among older HIV-uninfect-
ed adults [25,26,27]. We find that HIV-infected IDUs with well-
controlled HIV disease are no more likely to be frail than similar
individuals without HIV infection. In contrast, the likelihood of
frailty was significantly higher with advanced HIV disease with
inadequate virologic control. These results suggest that HIV
infection without effective treatment may represent a significant,
modifiable risk factor for frailty. Thus, together with data from
other HIV cohorts [13,14], these findings suggest a putative role
Figure 1. Survival by Frailty Status in the ALIVE cohort. Kaplan Meier Survival Curve Estimates for 1230 ALIVE Participants from July 2005 to
December 2008. Robust participants had a frailty score of 0; prefrail participants had a frailty score of 1–2; frail participants had a frailty score of 3–5.
Figure 2. Survival by Frailty and HIV Status in the ALIVE cohort. Kaplan Meier Survival Curve Estimates for 1230 ALIVE Participants from July
2005 to December 2008. Frail- participants had a frailty score of 0–2; Frail+ participants had a frailty score of 3–5.
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org5 January 2013 | Volume 8 | Issue 1 | e54910
for HAART in arresting the progression to frailty. HAART has
been shown to have a significant impact on morbidity and
mortality for HIV-infected populations in general and HIV-
infected IDUs specifically [28,29,30,31,32]. The negative impact
of late initiation of care and premature interruption of HAART on
survival has also been well defined [7,33,34]. Engagement in care
and adherence to antiretroviral regimens continue to be a
daunting challenge for the HIV-infected population . These
effects are exacerbated among IDUs, who tend to have later
diagnosis, poorer access to care, lower HAART uptake, more
limited adherence, and frequent treatment interruptions with
significant consequences for HIV-related morbidity and mortality
[17,36,37,38,39,40,41]. With less successful navigation of the HIV
care continuum, HIV-infected IDUs remain at higher risk for
HIV/AIDS progression, and by extension may suffer increased
progression to frailty with its consequent adverse outcomes. Future
investigations will need to elucidate the underlying mechanisms of
frailty development in the setting of HIV and determine whether
earlier ART may be effective for frailty prevention.
We found that frailty was independently associated with an
increased risk of death among HIV-infected and at risk IDUs.
These findings are particularly notable given that the median age
of this cohort was 48 years. Frailty has been primarily linked to
mortality and other adverse outcomes in significantly older cohorts
(predominantly 65 years of age and older) [3,4]. Consistent with
our data, a frailty related construct has demonstrated increased
mortality risk in younger populations in 2 recent studies [22,42].
As comprehensive treatment for HIV infection evolves beyond a
focus primarily on viral suppression and broadens to consider
management of multiple chronic conditions to achieve healthy
aging, assessment tools beyond HIV RNA and CD4 counts will be
increasingly needed. Frailty may improve risk stratification and
inform appropriate clinical management for aging, complex care
patients living with HIV. Further, the joint impact of frailty and
HIV infection on mortality suggests that efforts to reduce mortality
risk through both frailty and HIV targeted interventions may
translate into significant survival benefit.
Besides HIV disease markers, we found that depressive
symptoms and prescription drug abuse were associated with both
frailty and prefrailty. Previously, we have documented self-
medication with ‘street’ drugs for symptoms in this population
. Although directionality of these associations cannot be
determined in the current analysis, it will be important to examine
whether frailty interventions alleviate associated pain or other
symptoms and lead to improved health-related quality of life.
Consistent with studies of frailty in HIV-uninfected older adults
[3,44], we observed that advancing age, female gender, lower
educational attainment, and increased number of comorbid
conditions were associated with frailty within this IDU population.
The absence of a cohabiting life partner may be a putative
measure of social isolation with which frailty has also been
previously associated . As with HIV, dysregulated inflammation
hasbeen associated withage
[24,45,46,47]. Further, hormonal influences have been postulated
to play an important role in age-associated changes in inflamma-
tion among women [48,49]. Whether hormonally mediated
changes in inflammation account for sex-specific differences in
frailty prevalence remains to be determined. However, inflamma-
tion may be a predominant pathway by which these factors could
contribute to progression to a frail state.
Prefrailty is considered to be an intermediate state that presages
progression to frailty in geriatric populations . Therefore, the
prefrail state may provide a window of opportunity when
interventions could mitigate adverse clinical outcomes. We
observed consistent, although attenuated, associations of prefrailty
with HIV disease and other frailty risk factors; however, prefrailty
was not predictive of mortality. A larger study size or longer
duration may allow identification of incremental mortality risk
with prefrailty. Further follow-up also is needed to define the
likelihood of transition from prefrailty to frailty among HIV-
infected persons. These data will be vital to inform development of
interventions to reverse or slow progression to frailty. The high
prevalence of almost two-thirds of our participants with prefrailty
is consistent with other studies and provides a large target
population for intervention [3,4].
Table 3. Mortality Risk associated with Frailty and HIV among
HR (95% CI)HR (95% CI)
Age (per year) 1.05 (1.01, 1.08)1.04 (1.00, 1.08)
Female 1.55 (0.98, 2.46) 1.23 (0.74, 2.02)
African American 1.03 (0.45, 2.38)0.76 (0.33, 1.77)
Less than high school education 0.86 (0.54, 1.37)0.79 (0.49, 1.27)
# Comorbid conditions
2 1.77 (0.95, 3.28)1.39 (0.73, 2.63)
$3 4.10 (2.39, 7.03) 2.97 (1.65, 5.35)
HIV positive 2.83 (1.78, 4.49)3.05 (1.89, 4.93)
Prefrail 1.46 (0.74, 2.86) 1.24 (0.63, 2.45)
Frail4.38 (2.16, 8.90)2.77 (1.32, 5.81)
HIV negativeRef Ref
CD4$350, VL UD0.68 (0.16, 2.83) 0.60 (0.14, 2.55)
CD4,350, VL UD1.05 (0.25, 4.39)1.18 (0.28, 4.95)
1.12 (0.34, 3.65)1.38 (0.42, 4.54)
4.89 (3.01, 7.97) 5.83 (3.48, 9.74)
Prefrail1.46 (0.74, 2.86) 1.13 (0.57, 2.22)
Frail4.38 (2.16, 8.90)2.20 (1.03, 4.68)
HIV negative/nonfrail Ref Ref
HIV negative/frail3.45 (1.67, 7.12) 2.63 (1.23, 5.66)
HIV positive/nonfrail2.85 (1.62, 5.04) 3.29 (1.85, 5.88)
HIV positive/frail 8.31 (4.25, 16.3)7.06 (3.49, 14.3)
aData are given as unadjusted and adjusted hazard ratios (95% confidence
bAdjusted for age, gender, race, education, # comorbid conditions, HIV status
and frailty status.
cAdjusted for age, gender, race, education and # comorbid conditions.
dRobust participants had a frailty score of 0; prefrail participants had a frailty
score of 1–2; frail participants had a frailty score of 3–5; nonfrail participants had
a frailty score of 0–2.
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org6 January 2013 | Volume 8 | Issue 1 | e54910
Our study had several limitations. Debate persists on the
optimal criteria for defining frailty . The frailty phenotype
employed in this study closely approximated the original Fried
criteria, with objective measurement of weight loss, gait speed, and
grip strength. Consistent with prior studies, we substituted a self-
reported measure of low physical activity [13,22]. Our weight loss
parameter did not discern intentionality; however, similarly
constructed frailty constructs had predictive validity roughly
equivalent to the original Fried phenotype in elderly HIV-
uninfected persons [4,51]. As we used weight loss of $5% since
last study visit (median of 6 months), our threshold for meeting this
criteria required greater weight loss than the original criteria.
Given the observational nature of the study and lack of
temporality for HIV-frailty associations, caution is needed
regarding inferences of causality. Our cohort is a predominantly
African American, urban IDU cohort and as such, our findings
may not be fully generalizable to other HIV-infected populations.
However, significant relationships between frailty (and a frailty-
related phenotype) and advanced HIV disease have been noted in
several non-IDU cohorts [13,14,15]. Further, we have observed a
similar relationship between frailty and non-HIV-related factors in
our population as reported from older HIV-uninfected popula-
tions [3,44]. Whether similar biological mechanisms underlie the
development of frailty for these different groups needs to be further
investigated. Nevertheless, this population does represent those
individuals particularly vulnerable to disparities in access to care
and key adverse health care outcomes for whom appropriately
targeted frailty interventions could have substantial clinical impact.
Improved understanding of frailty in high-risk populations may
translate into clinical utility as well as strengthen our scientific
understanding of the aging process. Despite improving survival
and recent aging trends, HIV-infected and at risk IDUs continue
to experience marked socioeconomic challenges with persistent
disparities in treatment access, morbidity and mortality outcomes
[10,11,17,21,52]. Frailty assessment may prove useful in identify-
ing those persons at greatest risk for premature death and allow
appropriate intervention. Whether HIV infection and frailty share
a single common pathway to premature death remains to be
determined. However, elucidation of the mechanisms underlying
frailty development may provide substantial opportunities for
realizing the healthy aging of HIV-infected and drug using
populations, with potential additional benefit to the general aging
the AIDS Linked to the IntraVenous Experience (ALIVE)
Characterization of the Frailty Phenotype in
Edited and critically revised the manuscript: DP AM SM TB KP SL GK.
Conceived and designed the experiments: DP AM SM TB KP SL GK.
Performed the experiments: DP SM KP GK. Analyzed the data: DP AM
GK. Contributed reagents/materials/analysis tools: SM GK. Wrote the
paper: DP GK.
1. Fried LP, Ferrucci L, Darer J, Williamson JD, Anderson G (2004) Untangling
the concepts of disability, frailty, and comorbidity: implications for improved
targeting and care. J Gerontol A Biol Sci Med Sci 59: 255–263.
2. Xue QL (2011) The frailty syndrome: definition and natural history. Clin
Geriatr Med 27: 1–15.
3. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, et al. (2001) Frailty in
older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 56:
4. Bandeen-Roche K, Xue QL, Ferrucci L, Walston J, Guralnik JM, et al. (2006)
Phenotype of frailty: characterization in the women’s health and aging studies.
J Gerontol A Biol Sci Med Sci 61: 262–266.
5. High KP, Brennan-Ing M, Clifford DB, Cohen MH, Currier J, et al. (2012) HIV
and aging: state of knowledge and areas of critical need for research. A report to
the NIH Office of AIDS Research by the HIV and Aging Working Group.
J Acquir Immune Defic Syndr 60 Suppl 1: S1–18.
6. Mills EJ, Barnighausen T, Negin J (2012) HIV and aging–preparing for the
challenges ahead. N Engl J Med 366: 1270–1273.
7. Losina E, Schackman BR, Sadownik SN, Gebo KA, Walensky RP, et al. (2009)
Racial and sex disparities in life expectancy losses among HIV-infected persons
in the united states: impact of risk behavior, late initiation, and early
discontinuation of antiretroviral therapy. Clin Infect Dis 49: 1570–1578.
8. Lohse N, Hansen AB, Pedersen G, Kronborg G, Gerstoft J, et al. (2007) Survival
of persons with and without HIV infection in Denmark, 1995–2005. Ann Intern
Med 146: 87–95.
9. Armstrong GL (2007) Injection drug users in the United States, 1979–2002: an
aging population. Arch Intern Med 167: 166–173.
10. Wolfe D, Carrieri MP, Shepard D (2010) Treatment and care for injecting drug
users with HIV infection: a review of barriers and ways forward. Lancet 376:
11. Degenhardt L, Hall W, Warner-Smith M (2006) Using cohort studies to estimate
mortality among injecting drug users that is not attributable to AIDS. Sex
Transm Infect 82 Suppl 3: iii56–63.
12. Kohli R, Lo Y, Howard AA, Buono D, Floris-Moore M, et al. (2005) Mortality
in an urban cohort of HIV-infected and at-risk drug users in the era of highly
active antiretroviral therapy. Clin Infect Dis 41: 864–872.
13. Desquilbet L, Jacobson LP, Fried LP, Phair JP, Jamieson BD, et al. (2007) HIV-
1 infection is associated with an earlier occurrence of a phenotype related to
frailty. J Gerontol A Biol Sci Med Sci 62: 1279–1286.
14. Terzian AS, Holman S, Nathwani N, Robison E, Weber K, et al. (2009) Factors
associated with preclinical disability and frailty among HIV-infected and HIV-
uninfected women in the era of cART. J Womens Health (Larchmt) 18: 1965–
15. Onen NF, Agbebi A, Shacham E, Stamm KE, Onen AR, et al. (2009) Frailty
among HIV-infected persons in an urban outpatient care setting. J Infect 59:
16. Vlahov D, Anthony JC, Munoz A, Margolick J, Nelson KE, et al. (1991) The
ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users:
description of methods and characteristics of participants. NIDA Res Monogr
17. Salter ML, Lau B, Go VF, Mehta SH, Kirk GD (2011) HIV infection, immune
suppression, and uncontrolled viremia are associated with increased multi-
morbidity among aging injection drug users. Clin Infect Dis 53: 1256–1264.
18. Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M (1993)
Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO
Collaborative Project on Early Detection of Persons with Harmful Alcohol
Consumption–II. Addiction 88: 791–804.
19. Weissman MM, Sholomskas D, Pottenger M, Prusoff BA, Locke BZ (1977)
Assessing depressive symptoms in five psychiatric populations: a validation study.
Am J Epidemiol 106: 203–214.
20. Skinner HA (1982) The drug abuse screening test. Addict Behav 7: 363–371.
21. Mehta SH, Kirk GD, Astemborski J, Galai N, Celentano DD (2010) Temporal
trends in highly active antiretroviral therapy initiation among injection drug
users in Baltimore, Maryland, 1996–2008. Clin Infect Dis 50: 1664–1671.
22. Desquilbet L, Jacobson LP, Fried LP, Phair JP, Jamieson BD, et al. (2011) 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.
23. Rabe-Hesketh S, Skrondal A (2008) Multilevel and Longitudinal Modeling
Using Stata. College Station, TX: Stata Press.
24. Deeks SG (2011) HIV infection, inflammation, immunosenescence, and aging.
Annu Rev Med 62: 141–155.
25. Yao X, Li H, Leng SX (2011) Inflammation and immune system alterations in
frailty. Clin Geriatr Med 27: 79–87.
26. Leng SX, Xue QL, Tian J, Walston JD, Fried LP (2007) Inflammation and
frailty in older women. J Am Geriatr Soc 55: 864–871.
27. Walston J, McBurnie MA, Newman A, Tracy RP, Kop WJ, et al. (2002) Frailty
and activation of the inflammation and coagulation systems with and without
clinical comorbidities: results from the Cardiovascular Health Study. Arch
Intern Med 162: 2333–2341.
28. Detels R, Munoz A, McFarlane G, Kingsley LA, Margolick JB, et al. (1998)
Effectiveness of potent antiretroviral therapy on time to AIDS and death in men
with known HIV infection duration. Multicenter AIDS Cohort Study
Investigators. JAMA 280: 1497–1503.
29. Hammer SM, Squires KE, Hughes MD, Grimes JM, Demeter LM, et al. (1997)
A controlled trial of two nucleoside analogues plus indinavir in persons with
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org7 January 2013 | Volume 8 | Issue 1 | e54910
human immunodeficiency virus infection and CD4 cell counts of 200 per cubic Download full-text
millimeter or less. AIDS Clinical Trials Group 320 Study Team. N Engl J Med
30. Murphy EL, Collier AC, Kalish LA, Assmann SF, Para MF, et al. (2001) Highly
active antiretroviral therapy decreases mortality and morbidity in patients with
advanced HIV disease. Ann Intern Med 135: 17–26.
31. Vlahov D, Galai N, Safaeian M, Galea S, Kirk GD, et al. (2005) Effectiveness of
highly active antiretroviral therapy among injection drug users with late-stage
human immunodeficiency virus infection. Am J Epidemiol 161: 999–1012.
32. Wood E, Hogg RS, Lima VD, Kerr T, Yip B, et al. (2008) Highly active
antiretroviral therapy and survival in HIV-infected injection drug users. JAMA
33. Kitahata MM, Gange SJ, Abraham AG, Merriman B, Saag MS, et al. (2009)
Effect of early versus deferred antiretroviral therapy for HIV on survival.
N Engl J Med 360: 1815–1826.
34. Giordano TP, Gifford AL, White AC Jr, Suarez-Almazor ME, Rabeneck L, et
al. (2007) Retention in care: a challenge to survival with HIV infection. Clin
Infect Dis 44: 1493–1499.
35. Gardner EM, McLees MP, Steiner JF, Del Rio C, Burman WJ (2011) The
spectrum of engagement in HIV care and its relevance to test-and-treat
strategies for prevention of HIV infection. Clin Infect Dis 52: 793–800.
36. Wood E, Hogg RS, Harrigan PR, Montaner JS (2005) When to initiate
antiretroviral therapy in HIV-1-infected adults: a review for clinicians and
patients. Lancet Infect Dis 5: 407–414.
37. Nijhawan A, Kim S, Rich JD (2008) Management of HIV infection in patients
with substance use problems. Curr Infect Dis Rep 10: 432–438.
38. Arnsten JH, Demas PA, Grant RW, Gourevitch MN, Farzadegan H, et al.
(2002) Impact of active drug use on antiretroviral therapy adherence and viral
suppression in HIV-infected drug users. J Gen Intern Med 17: 377–381.
39. Celentano DD, Vlahov D, Cohn S, Shadle VM, Obasanjo O, et al. (1998) Self-
reported antiretroviral therapy in injection drug users. JAMA 280: 544–546.
40. Kavasery R, Galai N, Astemborski J, Lucas GM, Celentano DD, et al. (2009)
Nonstructured treatment interruptions among injection drug users in Baltimore,
MD. J Acquir Immune Defic Syndr 50: 360–366.
41. Mathers BM, Degenhardt L, Ali H, Wiessing L, Hickman M, et al. (2010) HIV
prevention, treatment, and care services for people who inject drugs: a
systematic review of global, regional, and national coverage. Lancet 375:
42. Rockwood K, Song X, Mitnitski A (2011) Changes in relative fitness and frailty
across the adult lifespan: evidence from the Canadian National Population
Health Survey. CMAJ 183: E487–494.
43. Khosla N, Juon HS, Kirk GD, Astemborski J, Mehta SH (2011) Correlates of
non-medical prescription drug use among a cohort of injection drug users in
Baltimore City. Addict Behav 36: 1282–1287.
44. Szanton SL, Seplaki CL, Thorpe RJ Jr, Allen JK, Fried LP (2010)
Socioeconomic status is associated with frailty: the Women’s Health and Aging
Studies. J Epidemiol Community Health 64: 63–67.
45. Carroll JE, Cohen S, Marsland AL (2011) Early childhood socioeconomic status
is associated with circulating interleukin-6 among mid-life adults. Brain Behav
46. Nazmi A, Victora CG (2007) Socioeconomic and racial/ethnic differentials of C-
reactive protein levels: a systematic review of population-based studies. BMC
Public Health 7: 212.
47. Koster A, Bosma H, Penninx BW, Newman AB, Harris TB, et al. (2006)
Sci Med Sci 61: 284–290.
48. Joseph C, Kenny AM, Taxel P, Lorenzo JA, Duque G, et al. (2005) Role of
endocrine-immune dysregulation in osteoporosis, sarcopenia, frailty and fracture
risk. Mol Aspects Med 26: 181–201.
49. Singh T, Newman AB (2011) Inflammatory markers in population studies of
aging. Ageing Res Rev 10: 319–329.
50. Rodriguez-Manas L, Feart C, Mann G, Vina J, Chatterji S, et al. (2012)
Searching for an Operational Definition of Frailty: A Delphi Method Based
Consensus Statement. The Frailty Operative Definition-Consensus Conference
Project. J Gerontol A Biol Sci Med Sci.
51. Ensrud KE, Ewing SK, Taylor BC, Fink HA, Cawthon PM, et al. (2008)
Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and
death in older women. Arch Intern Med 168: 382–389.
52. Crystal S, Akincigil A, Sambamoorthi U, Wenger N, Fleishman JA, et al. (2003)
The diverse older HIV-positive population: a national profile of economic
circumstances, social support, and quality of life. J Acquir Immune Defic Syndr
33 Suppl 2: S76–83.
Frailty, HIV and Mortality among Aging IDUs
PLOS ONE | www.plosone.org8 January 2013 | Volume 8 | Issue 1 | e54910