HIV Infection and Cardiovascular Disease in Women [618311]

HIV Infection and Cardiovascular Disease in Women
Julie A. Womack, CNM, APRN, PhD; Chung-Chou H. Chang, PhD; Kaku A. So-Armah, PhD; Charles Alcorn, MA; Jason V. Baker, MD;
Sheldon T. Brown, MD; Matthew Budoff, MD; Adeel A. Butt, MD, MS; Cynthia Gibert, MD; Matthew Bidwell Goetz, MD; John Gottdiener, MD;
Stephen Gottlieb, MD; Amy C. Justice, MD, PhD; David Leaf, MD, MPH; Kathleen McGinnis, PhD; David Rimland, MD; Maria C. Rodriguez-
Barradas, MD; Jason Sico, MD; Melissa Skanderson, MSW; Hilary Tindle, MD, MPH; Russell P. Tracy, MD; Alberta Warner, MD;Matthew S. Freiberg, MD, MSc
Background- —HIV infection is associated with increased risk of cardiovascular disease (CVD) in men. Whether HIV is an
independent risk factor for CVD in women has not yet been established.
Methods and Results- —We analyzed data from the Veterans Aging Cohort Study on 2187 women (32% HIV infected [HIV+]) who were
free of CVD at baseline. Participants were followed from their first clinical encounter on or after April 01, 2003 until a CVD event, death,
or the last follow-up date (December 31, 2009). The primary outcome was CVD (acute myocardial infarction [AMI], unstable angina,
ischemic stroke, and heart failure). CVD events were de fined using clinical data, International Classi fication of Diseases, Ninth
Revision, Clinical Modi fication codes, and/or death certi ficate data. We used Cox proportional hazards models to assess the
association between HIV and incident CVD, adjusting for age, race/ethnicity, lipids, smoking, blood pressure, diabetes, renal disease,
obesity, hepatitis C, and substance use/abuse. Median follow-up time was 6.0 years. Mean age at baseline of HIV+and HIV uninfected
(HIV/C0) women was 44.0 versus 43.2 years ( P<0.05). Median time to CVD event was 3.1 versus 3.7 years ( P=0.11). There were 86
incident CVD events (53%, HIV+): AMI, 13%; unstable angina, 8%; ischemic stroke, 22%; and heart failure, 57%. Incident CVD/1000
person-years was signi ficantly higher among HIV+(13.5; 95% con fidence interval [CI] =10.1, 18.1) than HIV/C0women (5.3; 95% CI =3.9,
7.3; P<0.001). HIV+women had an increased risk of CVD, compared to HIV/C0(hazard ratio =2.8; 95% CI =1.7, 4.6; P<0.001).
Conclusions- —HIV is associated with an increased risk of CVD in women. (J Am Heart Assoc . 2014;3:e001035 doi: 10.1161/
JAHA.114.001035)
Key Words: AIDS CVD risk factors Women
HIV infection has been associated with an increased risk
of cardiovascular disease (CVD) in women.1–3Whether
this association is driven by HIV-speci fic or traditional risk
factors remains unclear, given that gender-strati fied assess-
ments of the associations between risk factors and CVD have
not been performed consistently.1,3,4Where separate analy-
ses were done for men and women, important risk factors forCVD, including smoking, hepatitis C status, and alcohol andcocaine use, were not included.
2The inclusion of women
diagnosed early in the AIDS epidemic may also confound ourability to understand the impact of earlier analyses on women
in the current epidemic given that there are signi ficant
differences in the timing of antiretroviral therapy (ART)initiation, the antiretroviral medications available, and the
From the Yale School of Nursing, West Haven, CT (J.A.W.); University of Pittsburgh School of Medicine, Pittsburgh, PA (C.-C.H.C., A.A.B., H.T.); University of Pittsburgh
Graduate School of Public Health, Pittsburgh, PA (C.-C.H.C., C.A.); Yale University School of Medicine, New Haven, CT (K.A.S.-A., A.C.J., J.S.); University of MinnesotaDepartment of Medicine, Hennepin County Medical Center, Minneapolis, MN (J.V.B.); James J. Peters VA Medical Center, Bronx, NY (S.T.B.); Icahn School of Medicine at
Mt. Sinai, New York, NY (S.T.B.); Harbor-UCLA Medical Center and Los Angeles Biomedical Research Institute, Los Angeles, CA (M.B.); VA Pittsburgh Healthcare
System, Pittsburgh, PA (A.A.B.); Sheikh Khalifa Medical City, Abu Dhabi, UAE (A.A.B.); VA Medical Center and George Washington University School of Medicine,Washington, DC (C.G.); David Geffen School of Medicine, University of California Los Angeles, CA (M.B.G., D.L., A.W.); VA Greater Los Angeles Health Care System Los
Angeles, CA (M.B.G., D.L., A.W.); University of Maryland School of Medicine, Baltimore, MD (J.G., S.G.); Veterans Affairs Connecticut Health Care System, West Haven
Veterans Administration Medical Center, West Haven, CT (A.C.J., K.M., J.S., M.S.); Emory University School of Medicine and Atlanta VA Medical Center, Atlanta, GA(D.R.); Infectious Diseases Section Michael E. DeBakey VA Medical Center and Department of Medicine Baylor College of Medicine, Houston, TX (M.C.R.-B.); Universityof Vermont College of Medicine, Burlington, VT (R.P.T.), Vanderbilt University School of Medicine, Nashville, TN (M.S.F.).
Correspondence to: Julie A. Womack, CNM, APRN, PhD, Yale School of Nursing, Yale University West Campus, P.O. Box 27399, 300 Heffernan Dr, West Haven,
06516 CT. E-mail: julie.womack@yale.eduReceived July 30, 2014; accepted September 15, 2014.ă2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell. This is an open access article under the terms of the Creative
Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is
not used for commercial purposes.
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side effects experienced with treatment.1–3Finally, a number
of the previous analyses have included population compara-
tors who may differ in important ways, such as race and
substance use history, from HIV-infected women.1–3,5The
inclusion of women who are demographically similar, and fromthe same healthcare system, is of key importance.
We investigated whether HIV and ART are associated with
increased CVD events after adjusting for traditional risk
factors and substance use and abuse in a cohort of HIV-
infected and uninfected women veterans.
Methods
Sample
The Veterans Aging Cohort Study-Virtual Cohort (VACS-VC) isa prospective, longitudinal, observational cohort. Each HIV-
infected Veteran is matched on age, race/ethnicity, and
clinical site to 2 uninfected veterans enrolled in general
medicine clinics.
6Data for this cohort are extracted from
multiple Veterans Health Administration (VHA) sources,
including the immunology case registry, national patient care
database, and the VHA electronic medical record health factor
data set. Deaths were con firmed using the VHA vital status
file, the Social Security Administration death master file, the
Bene ficiary Identi fication and Records Locator Subsystem,
and the VHA Medical Statistical Analysis Systems inpatientdata sets. National Death Index data provided cause of death
information. This study was approved by institutional review
boards at the University of Pittsburgh, Yale University, and theVA Connecticut Healthcare System.
Our analysis was restricted to women. Baseline was
defined as the first clinical encounter on or after April 1, 2003.
All participants were followed from their baseline date to aCVD event, death, or the last follow-up date before December
31, 2009.
As reported in an earlier study, VHA data were merged with
data from Medicare, Medicaid, and the Ischemic Heart
Disease-Quality Enhancement Research Initiative.
7We
excluded participants with prevalent CVD as identi fied by
International Classi fication of Diseases, Ninth Revision, Clin-
ical Modi fication (ICD-9-CM) codes for acute myocardial
infarction (AMI), stable or unstable angina, cardiovascularrevascularization, stroke or transient ischemic attack, periph-
eral vascular disease, or heart failure (HF) on or before their
baseline date (n =66). After these exclusions, our final sample
included 2187 women veterans (32% HIV infected). Thosewomen excluded for prevalent CVD were signi ficantly older
than those without (47.3 /C67.8 vs. 43.8 /C67.7 years, P<0.001,
respectively), but did not differ by race (black 65.9%, white
26.1% among those with prevalent CVD, and black 60.0%,
white 30.2% in those without; P=0.59).Independent Variable
We identi fied HIV infection by the presence of at least 2
outpatient or 1 inpatient ICD-9-CM codes for HIV andconfirmation in the VHA immunology case registry.
6
Dependent Variables
Our primary outcome was total CVD defi ned as the presence
of AMI, unstable angina, ischemic stroke, or congestive HF.7
Despite the lack of data on etiology of HF (ischemic vs.nonischemic), we elected to include HF in the CVD outcome
because our earlier work demonstrates an association
between HIV and HF
8and because this approach also
maximizes power. All primary outcomes were defi ned using
VHA, Medicare, and death certi ficate data. For AMI events
within the VHA, we used adjudicated outcomes from the VHA
External Peer Review Program. To identify those AMI events
that occurred outside of the VHA in patients who were not
transferred to the VHA, a Medicare 410.xx ICD-9-CM code
was used. For unstable angina, HF, and ischemic stroke, we
used 1 inpatient and/or 2 or more outpatient ICD-9-CM
codes: unstable angina 411.xx; heart failure 428.xx, 429.3,
402.01, 402.11, 402.91, and 425.xx; stroke (inpatient)
433.x1, 434.x1, 436, and (outpatient) 438.xx. These CVD
ICD-9-CM codes were selected based on earlier validationwork within and outside the VHA healthcare system.
8,9
Covariates
We selected covariates a priori based on clinical relevance,
previous work7within the VACS-VC, and data availability. We
determined age, sex, and race/ethnicity using administrativedata. Hypertension (HTN), diabetes mellitus, renal disease,
and anemia were identi fied using outpatient and clinical
laboratory data collected closest to the baseline date. Serum
lipid concentrations (low-density lipoprotein [LDL], high-den-
sity lipoprotein [HDL], and triglycerides [TGs]) were identi fied
using clinical laboratory data. HMG-CoA (3-hydroxy-3-methyl-glutaryl-coenzyme A) reductase inhibitor and ART use were
identi fied using pharmacy data. Smoking and body mass index
(BMI; weight in kg/height in m
2) were identi fied in health
factor data that are collected in a standardized form within
the VHA.
HTN was categorized based on use of antihypertensive
medication and blood pressure ≥140/90 mm Hg derived
from the average of the 3 routine outpatient clinical
measurements closest to the baseline date. Diabetes was
diagnosed using a previously validated metric that includes
glucose measurements, antidiabetic agent use, and/or at
least 1 inpatient and/or 2 or more outpatient ICD-9-CM codes
for this diagnosis.10Abnormal serum lipid concentrations
were de fined as LDL ≥160, HDL <50, and TGs ≥150 mg/dL.
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The HMG-CoA reductase inhibitor use was within 180 days of
the baseline date. Hepatitis C virus (HCV) infection was
defined as a positive hepatitis C virus antibody test result or
at least 1 inpatient and/or 2 or more outpatient ICD-9-CMcodes for this diagnosis. Renal disease was defi ned as an
estimated glomerular filtration rate (eGFR) <60 mL/min per
1.73 m
2and was obtained from VA laboratory data. Anemia
was de fined as hemoglobin <12 g/dL. Current, past, and
never smoking and BMI were assessed using documentation
from the VHA electronic medical record health factor data set,which contains information collected from clinical reminders
that clinicians are required to complete for patients. Previous
work demonstrates high agreement between health factor
documentation and self-reported smoking survey data.
11
History of cocaine and alcohol abuse or dependence wasidenti fied using ICD-9-CM codes.
12We collected data on
baseline CD4+T-cell (CD4) counts and HIV-1 RNA values.
Baseline ART was categorized by drug class and types of
regimens documented within 180 days of the baseline
enrollment date. Antiretroviral regimens were de fined as
follows: protease inhibitors (PIs) plus nucleoside reverse
transcriptase inhibitors (NRTIs); non-nucleoside reverse trans-
criptase inhibitors (NNRTIs) plus NRTIs;, other; and no ART
use. We have previously demonstrated that 96% of HIV-
infected veterans obtain all of their ART medications from the
VHA.6Because the analytic sample was not perfectly matched
as a result of the exclusion of individuals with prevalent CVD,we also included variables on which the original cohort was
matched (age, race, and ethnicity).
Statistical Analysis
Descriptive statistics for all variables by HIV status wereassessed using 2-sample t tests or the nonparametric
counterparts for continuous variables, and the chi-square or
Fisher ’s exact tests for categorical variables. We calculated
the incidence of total CVD per 1000 person-years, as well asmedian age at time of CVD event, strati fied by HIV status. We
used Cox proportional hazards models to estimate hazardratios (HRs) and 95% con fidence intervals (CIs) to assess
whether HIV infection was associated with incident total CVD
after adjusting for age and race/ethnicity and then for
Framingham risk factors.
9,13In a third model, we adjusted for
demographic characteristics, Framingham risk factors, co-morbid disease, and substance abuse or dependence. We
conducted secondary analyses that compared uninfected
women to HIV-infected women strati fied by baseline CD4
+T-
cell count, baseline HIV-1 RNA level, and baseline ART status.On ART at baseline was de fined as on any ART regimen
(PI+NRTI, NNRTI +NRTI, or other ART medications) versus not
on any ART at baseline. We also examined the rates of CVDamong HIV-infected veterans who were on ART and not onART at baseline, compared to uninfected veterans. Missing
covariate data were included in the analyses using multiple
imputation techniques that generated 5 data sets with
complete covariate values to increase the robustness and
efficiency of the estimated HR.
Results
After restricting the VACS-VC sample to women (n =2253) and
excluding those with baseline CVD (n =66), our final sample
included 2187 women, of whom 710 (32%) were HIV infected.
Among the HIV-infected women, 248 (34.9%) were on ART atbaseline (Table 1). An additional 393 women initiated ART
within a median of 1.14 years (interquartile range [IQR], 0.28,
3.01) after entry into the cohort.
The prevalence of several cardiovascular risk factors
differed by HIV status. HIV-infected women veterans had a
higher prevalence of low HDL cholesterol, elevated TGs,
smoking, HCV infection, hemoglobin <12 g/dL, alcohol and
cocaine abuse/dependence, and a lower prevalence of HTNand obesity (BMI ≥30 kg/m
2;P<0.05 for all).
During a median follow-up of 6.0 years, there were 86
incident CVD events (53% HIV infected). Of these events, 13%were AMI, 8% were unstable angina, 22% were ischemic
stroke, and 57% were HF. All events occurred in unique
individuals. Median time to CVD event was 3.1 versus
3.7 years ( P=0.11) for HIV-infected, compared to uninfected,
women. Incident CVD per 1000 person-years was signi ficantly
higher among HIV-infected (13.5; 95% CI =10.1, 18.1), com-
pared to uninfected, women (5.3; 95% CI =3.9, 7.3; P<0.001;
Figure). The incidence of CVD excluding HF was also higher
among HIV-infected women, compared to uninfected controls(incidence rate ratio [IRR] [95% CI] =2.3 [1.2, 4.5]), as was the
incidence of HF excluding CVD (IRR [95% CI] =2.5 [1.5, 4.5]).
The median age at time of the CVD event for HIV-infected
versus uninfected women was (49.3 years vs. 52.1 years;
P=0.05). The median Framingham risk score was 3 for both
HIV-infected and uninfected women ( P=0.3).
After adjusting for Framingham risk factors (age, lipids,
smoking, blood pressure, and diabetes), other comorbidities(renal disease, obesity, HCV infection), substance use andabuse (cocaine and alcohol), and demographic factors, HIV-
infected women veterans had a signi ficantly increased risk of
total CVD, compared to uninfected women veterans (HR =2.8;
95% CI =1.7, 4.6; P<0.001; Table 2).
Compared to uninfected women, HIV-infected women had
a signi ficantly increased risk of CVD, regardless of CD4 count
at baseline ( ≥500, 200 to 499, and <200 cells/mm
3;
Table 3). Among HIV-infected women, there was a step-wise
increase in point estimates of CVD risk with decreasing
baseline CD4 count (HR =2.3 [95% CI =1.2, 4.4]; HR =2.9 [95%
CI=1.5, 5.7]; HR =3.8 [95% CI =1.9, 7.6], respectively), but
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Table 1. Characteristics of Women VACS Participants Strati fied by HIV Status*†
Characteristic Uninfected (N =1477) HIV Infected (N =710) PValue
Age at baseline, y 0.04
Mean (SD) 44.0 (7.7) 43.2 (7.7)
Median (IQR) 44.0 (40.0 to 48.0) 44.0 (39.0 to 48.0)
Race/ethnicity 0.57
African American 59.3 61.6
White 30.9 28.7
Other 9.8 9.7
Framingham risk score 0.26
Mean (SD) 3.1 (3.0) 3.2 (3.2)Median (IQR) 3 (1 to 5) 3 (1 to 5)
Framingham risk factors, %
Hypertension 28.0 22.9 0.02Diabetes mellitus 12.6 10.4 0.14
Lipids, mg/dL
LDL cholesterol ≥160 12.3 8.2 0.01
HDL cholesterol <50 41.1 53.8 <0.001
TGs≥150 23.4 33.6 <0.001
Smoking, % <0.001
Current 40.4 59.2
Past 12.3 10.2
Never 47.2 30.6
Other risk factors, %
Current HMG-CoA reductase
inhibitor use7.3 4.7 0.02
HCV infection 5.7 24.4 <0.001
eGFR <60 mL/min per
1.73 m
2,%3.7 5.6 0.048
Body mass index ≥30, % 44.5 25.3 <0.001
Hemoglobin <12 g/dL 17.3 29.7 <0.001
History of substance use, %
Alcohol abuse/dependence 5.0 13.8 <0.001
Cocaine abuse/dependence 3.6 13.5 <0.001
HIV-specific biomarkers
CD4 cell count, mm3
Mean (SD) 468 (352)
Median (IQR) 420 (212 to 654)
CD4 count ≤200 cells/mm3, % 24.2
HIV-RNA, copies/mLMean (SD) 57 866 (150 888)
Median (IQR) 1900 (325 to 30 600)
HIV-RNA ≥500 copies/mL, % 59.7
Continued
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these differences were not statistically signi ficant. In addition,
HIV-infected women with detectable HIV-1 RNA ( ≥500 cop-
ies/mL) were at greater risk for CVD, compared to uninfected
women (HR =3.7 [95% CI =2.1, 6.5]), although CVD risk did not
differ by level of HIV-RNA suppression ( P>0.05; Table 3).
Being on ART at baseline did not appear to change these
relationships (Table 3).
The rates of incident CVD per 1000 person-years among
HIV-infected women who were on ART at baseline, comparedto those who were not, were similar (12.8 [95% CI =8.0, 20.7]
vs. 14.0 [95% CI =9.7, 20.1], respectively) but were signi fi-
cantly higher than the rate of incident CVD among uninfected
women (5.3; 95% CI =3.9, 7.3; P<0.003).
HIV-infected women had a more than 2-fold increased risk
of death, compared to uninfected women (HR =2.6; 95% CI,
1.7 to 3.9; P<0.001). For 8 women (5 HIV
+), the underlying
cause of death was associated with CVD. Of those 8, only 3 (1HIV+) did not have an identi fied incident CVD event before
death. Causes of death for these 3 women included hemor-rhagic stroke (1 woman) and unstable angina (2 women). In a
secondary analyses that included CVD death as an outcome,the HR for HIV did not differ substantially from those in
primary analyses (HR =2.6; 95% CI, 1.6 to 4.3; P<0.01).
Discussion
HIV-infected women had higher rates and risks of total CVD,
compared to uninfected women. This increased risk persisted
after adjustment for demographic factors, Framingham risk
factors, other comorbidities, and substance (alcohol and
cocaine) use and abuse.
Although multiple earlier studies have linked HIV infection
to AMI, coronary heart disease, ischemic stroke, and HF, themajority of the participants in these studies were men.
7,14
Few studies have focused on women and even fewer includedCVD events. Our results are consistent with earlier studies
that linked HIV infection to an increased risk of CHD, ischemic
stroke, and subclinical atherosclerosis among women.
1,2,15
Our findings extend these results by examining this
association in a national sample of HIV-infected and unin-
fected women from the same healthcare system. In addition,we were able to adjust our analyses for demographic and
Framingham risk factors, as well as comorbid conditions,
smoking, and substance use and abuse variables (cocaine and
alcohol). We assessed incident CVD events and included
analyses strati fied by HIV-1 RNA, CD4 count, and ART use.
Our results are consistent with previous studies reporting
HIV infection as an independent risk factor for CVD in men,
suggesting that HIV infection increases the risk of CVD
regardless of gender. In addition, ART, Framingham risk
factors, and important comorbidities, such as HTN, renal
Table 1. Continued
Characteristic Uninfected (N =1477) HIV Infected (N =710) PValue
On HAART at baseline, % 34.9
ART regimen at baseline, %
PI+NRTI 15.2
NNRTI+NRTI 18.0
Other 5.9
No ART use 60.9
ART indicates antiretroviral therapy; BMI, body mass index; eGFR, estimated glomerular filtration rate; HAART, highly active antiretroviral therapy (3 or more antiretrovirals); HDL, high-
density lipoprotein; HMG-CoA, 3-hydroxy-3-methylglutaryl-coenzyme A; IQR, interquartile range; PI, protease inhibitors; NNRTI, non-nucleoside reverse transcriptase inhibitors NRTI,
nucleoside reverse transcriptase inhibitors; TGs, triglycerides; VACS, Veterans Aging Cohort Study.*P<0.05 for all comparisons by HIV status except race ( P=0.57), diabetes ( P=0.14), and median Framingham risk score ( P=0.30).
†All variables had complete data except hypertension (HIV/C0N=1446; HIV+N=702), LDL cholesterol (HIV/C0N=1054; HIV+N=537), HDL-cholesterol (HIV/C0N=1080; HIV+N=558), TGs (HIV/C0
N=1127; HIV+N=587), smoking (HIV/C0N=1388; HIV+N=679), eGFR (HIV/C0N=1282, HIV+N=662), BMI (HIV/C0N=1444; HIV+N=699), hemoglobin (HIV/C0N=1275, HIV+N=651), CD4 cell
count (HIV+N=512), HIV-1 RNA (HIV+N=539).
0.80 0.85 0.90 0.95 1.00
710 666 598 534 478 413 343 HIV infected1477 1418 1338 1224 1090 966 759 HIV uninfectedNumber at risk0 1 2 3 4 5 6
Years since enrollmentHIV infectedHIV uninfectedProbability of CVD- free survival
p<0.001
Figure. Unadjusted Kaplan-Meier ’s curves showing CVD-free
survival by HIV status. CVD indicates cardiovascular disease.
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Table 2. The Association Between HIV and Incident Total CVD*
Characteristic Model 1 (Demographics)Model 2 (Framingham
Risk Factors) Model 3 (All Predictors)
HIV 2.8 (1.8, 4.3) 3.1 (2.0, 4.9) 2.8 (1.7, 4.6)
Age (10-year increments) 2.1 (1.6, 2.7) 1.7 (1.3, 2.3) 1.7 (1.3, 2.3)
White 1.0 1.0 1.0
Black 1.4 (0.9, 2.3) 1.3 (0.8, 2.1) 1.3 (0.7, 2.2)
Other 0.5 (0.1, 1.6) 0.4 (0.1, 1.4) 0.4 (0.1, 1.4)
Hypertension 2.5 (1.6, 4.0) 2.4 (1.5, 3.8)
Diabetes 1.6 (1.0, 2.7) 1.6 (0.9, 2.7)
LDL≥160 mg/dL 1.3 (0.7, 2.4) 1.3 (0.7, 2.5)
HDL<50 mg/dL 0.9 (0.5, 1.5) 0.8 (0.5, 1.4)
TGs≥150 mg/dL 1.2 (0.7, 2.1) 1.2 (0.7, 2.1)
Nonsmoker 1.0 1.0
Current smoker 0.9 (0.6, 1.5) 1.0 (0.6, 1.7)
Past smoker 1.3 (0.7, 2.4) 1.3 (0.7, 2.5)
HMG-CoA reductase inhibitor 1.1 (0.5, 2.2)
Hepatitis C 1.1 (0.6, 2.0)
eGFR <60 mL/min per 1.73 m23.0 (1.5, 6.2)
BMI≥30 kg/m21.2 (0.7, 1.9)
Cocaine abuse/dependence 2.5 (1.1, 5.4)
Alcohol abuse/dependence 0.5 (0.2, 1.3)
Hemoglobin <12 g/dL 1.7 (1.0, 2.8)
BMI indicates body mass index; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; HMG-CoA, 3-hydroxy-3-methylglutaryl-coenzyme A;
LDL, low-density lipoprotein; TGs, triglycerides.*Hazard ratio (95% con fidence interval).
Table 3. Association Between HIV Status, Baseline HIV-Speci fic Covariates, and Incident Total CVD
Model HR (95% CI)*
A HIV/C01
HIV+, CD4+T-cell count ≥500 cells/mm32.3 (1.2, 4.4)†
HIV+, CD4+T-cell count 200 to 499 cells/mm32.9 (1.5, 5.7)†
HIV+, CD4+T-cell count <200 cells/mm33.8 (1.9, 7.6)†
B HIV/C01
HIV+, HIV-1 RNA <500 copies/mL 1.6 (0.6, 4.1)†
HIV+, HIV-1 RNA ≥500 copies/mL 3.7 (2.1, 6.5)†
C HIV/C01
HIV+, HIV-1 RNA <500 copies/mL, on HAART 1.6 (0.7, 3.9)†
HIV+, HIV-1 RNA ≥500 copies/mL, on HAART 4.4 (2.0, 9.9)†
HIV+, not on HAART 3.0 (1.8, 5.1)†
CI indicates con fidence interval; CVD, cardiovascular disease; HAART, highly active antiretroviral therapy (3 or more antiretrovirals); HDL, high-density lipoprotein; HR, hazard ratio; LDL,
low-density lipoprotein.
*Model HRs adjusted for age, race/ethnicity, hypertension, diabetes, LDL cholesterol, HDL cholesterol, triglycerides, HMG-CoA (3-hydroxy-3-methylglutaryl-coenzyme A) reductase use,
smoking, hepatitis C, estimated glomerular filtration rate, body mass index, cocaine and alcohol abuse or dependence, and hemoglobin.
†Tests for differences in CVD risk among the HIV-infected women were not statistically signi ficant ( P>0.05).
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disease, substance use, and anemia, may all contribute to
CVD in men and women.7Women with HIV-1 RNA ≥500 cop-
ies/mL appear to be at particularly high risk. This finding is
consistent with data from male veterans and emphasizes the
importance of viral suppression. Future studies should
investigate potential mechanisms linking viremia and CVD
risk. What remains to be established is whether or not HIV-
infected women are at greater risk for CVD than HIV-infected
men. Among HIV-infected women, whether those with lower
CD4 counts are at greater risk for CVD than those with higherCD4 counts remains unclear. Likewise, whether or not CVD
risk among HIV-infected women with fully suppressed HIV-1
RNA differs from that of uninfected women or from women
with detectable HIV-1 RNA should be investigated.
Although the exact mechanisms for increased CVD risk in
HIV-infected women are not known, earlier studies in men
have suggested in flammation, immune activation, immunode-
ficiency, altered coagulation, dyslipidemia, insulin resistance,
and endothelial dysfunction as potential mechanisms.
16–18
HIV-infected women also have increased immune activationmarkers (soluble CD163) that are associated with preclinicalCVD, compared to uninfected women.
19,20Previous studies
among uninfected women also suggest that depression21,22
(which has a higher prevalence among HIV-infected vs.
uninfected women22), earlier menopause23(which may be
more prevalent among HIV-infected vs. uninfected women24),
and other drivers of decreased estrogen, such as substance
use,24,25are all associated with incident CVD events.26
Whether these factors contribute to the excess risk of CVDamong HIV-infected women, however, is not known.
Currently, women represent 1 of every 4 people living with
HIV infection in the United States and 20% of all newinfections.
5Minority women are disproportionately affected
by the HIV infection epidemic. Heart disease and cerebrovas-cular disease are the first and third leading causes of death
among U.S. women ages 18 or older, respectively. For thesereasons, future studies will be needed to elucidate the
mechanisms of CVD in this high-risk population. Without this
knowledge, CVD risk strati fication strategies for HIV-infected
women will not be optimal.
There are several limitations to this study that warrant
discussion. First, unlike earlier studies in HIV-infected men,
we did not find signi ficant associations between several
traditional and HIV-speci fic risk factors and total CVD. The
lack of signi ficance likely re flects our relatively small number
of total events (n =86). However, when we compared these
results to our larger study among HIV-infected and unin-
fected male and female veterans,
7the associations between
the majority of these risk factors and CVD risk were of
similar direction and/or magnitude. We also did not havesufficient power to examine individual types of CVD events
separately in this analysis. However, previous studies amongmen have demonstrated that HIV is signi ficantly associated
with each component of our CVD variable (AMI, unstable
angina, ischemic stroke, and HF). Given the earlier associ-
ations of HIV with HF and nonadjudicated HF outcomes,
ascertainment bias by HIV status for this component of our
CVD outcome is possible. However, the HIV uninfected
women in this cohort also had important HF risk factors
present (eg, HTN or obesity) that could have precipitated a
workup for HF. On balance, this study presents data from
one of the few cohorts of HIV-infected women that includesCVD events, detailed information on comorbidities, sub-
stance use and abuse, HIV-speci fic biomarkers, and a
comparator group of uninfected women from the samenational healthcare system. Our study also incorporated
VHA, Medicare, and National Death Index cause-of-death
data to maximize our capture of incident CVD events. The
contribution of ART to CVD risk among women is an
important question that we are unable to assess given the
limited sample size and number of events. This is an
important question for future analyses.
In addition, it is dif ficult to know whether women in any
cohort are truly representative of U.S. women living with HIVinfection. Therefore, our findings should be replicated in
cross-cohort collaborations so that we can better understandthe association between HIV and CVD in women.
In summary, HIV-infected women have increased rates and
risk of incident CVD events, as compared to uninfected
women, after adjustment for demographic characteristics,
Framingham risk factors, other comorbidities, and substance
use and abuse. Future studies should focus on the identi fi-
cation of risk factors contributing to this excess risk of CVD
among HIV-infected women and strategies designed to
prevent CVD in this high-risk population.
Acknowledgments
The authors thank the Veterans for participating in the Veterans
Aging Cohort Study. Without their participation and the commitmentof the study’ s staff and coordinators, this research would not be
possible.
Sources of Funding
This work was supported by the Yale Center for Clinical
Investigation and the Clinical and Translational Science Award
Grant No. UL1 RR024139 from the National Center for
Research Resources; National Institute of Nursing Research
Grant No. K01 NR013437; National Heart, Lung and Blood
Institute Grant No. HL095136; and the National Institute onAlcohol Abuse and Alcoholism Grant Nos. AA013566-10,
AA020790, and AA020794, all components of the National
Institutes of Health (NIH).
DOI: 10.1161/JAHA.114.001035 Journal of the American Heart Association 7CVD in HIV-Infected Women Womack et alORIGINAL RESEACH
by guest on January 8, 2018 http://jaha.ahajournals.org/ Downloaded from

Disclosures
The NIH did not participate in the design and conduct of the
study; collection, management, analysis, or the interpretation
of the data; nor did the NIH prepare, review, or approve of this
manuscript. The views expressed in this article are those ofthe authors and do not necessarily re flect the position or
policies of the Department of Veterans Affairs.
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DOI: 10.1161/JAHA.114.001035 Journal of the American Heart Association 8CVD in HIV-Infected Women Womack et alORIGINAL RESEACH
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Alberta Warner and Matthew S. FreibergMaria C. Rodriguez-Barradas, Jason Sico, Melissa Skanderson, Hilary Tindle, Russell P. Tracy, Gottdiener, Stephen Gottlieb, Amy C. Justice, David Leaf, Kathleen McGinnis, David Rimland,Sheldon T. Brown, Matthew Budoff, Adeel A. Butt, Cynthia Gibert, Matthew Bidwell Goetz, John Julie A. Womack, Chung-Chou H. Chang, Kaku A. So-Armah, Charles Alcorn, Jason V. Baker,HIV Infection and Cardiovascular Disease in Women
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