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AIDS:
doi: 10.1097/QAD.0000000000000032
Epidemiology and Social

Educational attainment and risk of HIV infection, response to antiretroviral treatment, and mortality in HIV-infected patients

Legarth, Rebeccaa; Omland, Lars H.a; Kronborg, Gitteb; Larsen, Carsten S.c; Pedersen, Courtd; Gerstoft, Jana; Obel, Nielsa

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Author Information

aDepartment of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet

bDepartment of Infectious Diseases, Copenhagen University Hospital, Hvidovre

cDepartment of Infectious Diseases, Aarhus University Hospital, Aarhus

dDepartment of Infectious Diseases, Odense University Hospital, Odense, Denmark.

Correspondence to Rebecca A. Legarth, Department of Infectious Diseases, Rigshospitalet, Blegdamsvej 9, DK2100 Copenhagen Ø, Denmark. Tel: +45 35347726; fax: +45 35456648; e-mail: Rebeccalegarth@gmail.com

Received 24 June, 2013

Revised 13 August, 2013

Accepted 14 August, 2013

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Abstract

Objective: To estimate association between educational attainment and risk of HIV diagnosis, response to HAART, all-cause, and cause-specific mortality in Denmark in 1998–2009.

Design: Prospective, population-based cohort study including 1277 incident HIV-infected patients without hepatitis C virus or intravenous drug abuse identified in the Danish HIV Cohort Study and 5108 individually matched population controls.

Methods: Data on educational attainment, categorized as low, medium, or high, were identified in The Danish Attainment Register. Logistic and Poisson regression were used to estimate odds ratios (ORs) and mortality rate ratios (MRRs).

Results: OR of HIV diagnosis was 1.7 (95% confidence interval, CI 1.3–2.3) among heterosexual individuals with low educational attainments, but no associations between educational attainment and time to HAART initiation, CD4+ cell count, or viral suppression were identified. All-cause MRRs were 1.8 (95% CI 1.0–3.2) and 1.8 (1.1–2.8) for HIV-infected patients and population controls with low educational attainment compared with medium and high educational attainment. MRRs for smoking and alcohol-related deaths were 3.6 (95% CI 1.5–8.9) for HIV-infected patients and 2.0 (95% CI 1.2–3.4) for population controls with low educational attainment compared with medium and high educational attainment.

Conclusion: With free and equal access to healthcare, low educational attainment might increase risk of HIV infection among heterosexual individuals, but was not associated with late/very late presentation of HIV, time to HAART initiation, or HAART response. However, low educational attainment substantially increased lifestyle-related mortality, which indicates that increased mortality in HIV-infected patients with low educational attainments stems from risk factors unrelated to HIV.

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Introduction

Studies have demonstrated an adverse relation between socioeconomic status (SES) and mortality in patients diagnosed with chronic diseases including cardiovascular disease and cancer [1,2]. Education is closely related to other socioeconomic measure such as income or employment, but the association between educational attainment and mortality seems to be strong when adjusted for income and employment [3,4].

Several studies have shown an association between socioeconomic measure and mortality among HIV-infected patients particularly in the years following the introduction of antiretroviral treatment [5–7]. Some studies have suggested that educational attainment could be associated with delayed HIV diagnosis and delayed initiation of treatment [8].

In a Danish setting where healthcare is tax-funded and provided free of charge, we aimed to estimate the association between educational attainment and risk factors for acquisition and prognosis of HIV infection

We used a nationwide, population-based cohort of HIV-infected patients and a comparison cohort from the background population to estimate the association between educational attainments and risk of HIV diagnosis, late or very late presentation at HIV diagnosis, timely initiation of HAART, viral and immunological response to HAART, and all-cause mortality and cause-specific mortality.

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Methods

Setting

The study period was from 1 January 1998 until 31 December 2009. Denmark had a population of 5.5 million as of 31 December 2009 [9], with an estimated HIV prevalence of approximately 0.09% in the adult population. HIV-infected patients are treated in eight specialized HIV centers, and are seen on an outpatient basis at intended intervals of 12–24 weeks. HAART is provided free of charge to all HIV-infected residents of Denmark.

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Data sources

We used the unique 10-digit civil registration number assigned to all Danish residents [9,10] to link the following registries.

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The Danish HIV Cohort Study

The Danish HIV Cohort Study (DHCS) is a population-based nationwide cohort study of all HIV-infected individuals treated at Danish HIV centers since 1 January 1995. Individuals are consecutively enrolled. Data include demographics, date of HIV diagnosis, route of transmission, AIDS-defining events, and antiretroviral treatment. CD4+ cell counts and HIV RNA measurements are extracted electronically from laboratory data files. Data are updated annually [10].

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The Attainment Register

The Attainment Register, established in 1981, covers the entire Danish population and includes data on successfully completed educational attainments. Data on educational attainment are collected on the basis of information reported directly from all Danish educational institutions and are updated annually [11]. Ninety seven percent of the ethnic Danish population has nonmissing education information in The Attainment Register, and the estimated misclassification is between 0 and 3% [12].

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Civil Registration System

Civil Registration System (CRS) contains information on vital status, country of origin, and migration for all Danish residents and is updated continuously [9].

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Danish National Registry of Causes of Death

The Danish National Registry of Causes of Death contains information on date and causes of death on all dead Danish citizens. Causes of death are registered according to the International Classification of Diseases, 10th Revision (ICD-10), and are updated annually [13].

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Description and categorization of exposure variables, outcomes, and covariates
Exposure variables

From the Attainment Register, we extracted data on the highest educational attainment obtained by the study population in the calendar year of the index date. Educational attainments were grouped into the following three categories: low educational attainment (LEA) covering mandatory education of up to 9 years, medium educational attainment (MEA) covering mandatory and vocational education of 9–12 years, and high educational attainment (HEA) covering formal education of more than 12 years. In the cause-specific mortality analyses, HIV-infected patients and population controls with MEA and HEA were merged into one group (M/HEA), resulting in two levels of education: M/HEA and LEA.

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Outcomes

Late and very late presentation was characterized by CD4+ cell counts less than 350 cells/μl and less than 200 cells/μl, respectively at HIV diagnosis and/or diagnosed with an AIDS-defining disease at or within 14 days after date of HIV diagnosis regardless of CD4+ cell count [14].

In line with the national treatment guidelines published by the Danish Infectious Diseases Society, HIV-infected patients were considered eligible for start of HAART when fulfilling one of the following criteria: acute HIV infection, an AIDS-defining event, CD4+ cell count less than 300 cells/μl, HIV RNA more than 100 000 copies/ml (until 1 January 2002), and pregnancy (estimated as 257 days before delivery).

HAART was defined as a treatment regimen of at least three antiretroviral drugs that included a nonnucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor, and/or abacavir, or a treatment regimen with a combination of a NNRTI and a boosted protease inhibitor.

HIV RNA less than 500 copies/ml was categorized as undetectable viral load as this was the detection limit in the initial study period.

Causes of death were categorized as natural and unnatural according to ICD-10 codes. Unnatural causes of deaths included suicide, accidents, injury, murder, or drug overdose (ICD-10 T00-W99). Natural causes of death were categorized as AIDS-related (ICD-10 codes A07.2–07.3, A31, A81.2, B00, B20–25, B37–39, B45, B58, C46, C53, C83.4, C83.9, F02.4), smoking-related and alcohol-related (ICD-10 F10, K70, K74, K852, X45, X65, Y15,ICD-10 C33-C34, C00-C15, C35, J20-J22, J40-J44, J47), and other natural deaths (ICD-10 A00-R99 excluding AIDS-related and smoking-related and alcohol-related) [15–17].

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Covariates

Following covariates were included in the adjusted analyses: calendar year of index date, age (time updated variable at 5 years of interval), and gender.

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Study populations

We included HIV-1-infected patients from the DHCS who were of Danish origin, more than 25 years old at date of HIV diagnosis, diagnosed with HIV after 1 January 1998, who were registered in CRS, and were living in Denmark at index date. We excluded all HIV-infected patients with intravenous drug use (IDU) as route of transmission and all HIV-infected patients coinfected with hepatitis C at index date, as these subpopulations of predominantly IDUs differed in respect to all outcome variables compared with the general HIV-infected population [18,19]. Six hundred and forty-seven HIV-infected patients of non-Danish origin, and five HIV-infected patients with missing educational data were excluded.

Index date was defined as date of HIV diagnosis. For each HIV-infected patient, four controls individually matched on age and gender were identified from CRS to constitute a background population cohort. All population controls were of Danish origin, had data on educational attainment, were living in Denmark at the index date of their corresponding HIV-infected patient, and were assigned the same index date as their corresponding HIV-infected patient.

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Statistics
Risk of HIV diagnosis

In a nested case–control study, HIV-infected patients were cases, population controls were controls, and educational attainment was exposure. Logistic regression was used to estimate unadjusted and adjusted odds ratios (ORs) and (95% confidence interval, CI) of HIV diagnosis.

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Risk of late and very late presentation of HIV diagnosis

In a nested case–control study, educational attainment was exposure, HIV-infected patients presenting with late or very late HIV diagnosis were cases, and HIV-infected patients not presenting with late or very late HIV diagnosis were controls. Logistic regression was used to estimate unadjusted and adjusted OR (and 95% CI) of late and very late presentation at HIV diagnosis.

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Time to HAART start

In a cohort study including the HIV-infected population, outcome was time to start of HAART. Time was calculated from date of fulfillment of HAART criteria until date of start of HAART, death, emigration, date of last clinical visit, or 1 year from HAART criteria fulfillment, whichever came first. Cumulative incidence function was used to estimate absolute risk estimates of HAART start, with death as competing risk.

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Response to HAART

Treatment response was evaluated graphically as the proportion of HIV-infected patients with undetectable viral load and median CD4+ cell counts after initiating HAART according to educational attainment, as described previously [20].

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All-cause and cause-specific mortality

In a cohort study including the HIV-infected and control populations, outcome was time to death. Time was calculated from index date to date of death, emigration, or 31 December 2009. The mortality analyses covered two periods: less than 1 year from index date and more than 1 year from index date to account for lead-in mortality among HIV-infected patients. All-cause mortality rates [per 1000 person years (PYR)] were estimated both for HIV-infected patients and population controls. Unadjusted and adjusted all-cause mortality rate ratios (MRRs) for time to death were estimated using Poisson regression for HIV-infected patients with MEA and LEA compared with HIV-infected patients with HEA; population controls with MEA and LEA compared with population controls with HEA; and HIV-infected patients compared with population controls stratified by educational attainment. All-cause MRRs were further stratified by route of transmission and gender for the HIV-infected population. Cause-specific mortality rates (per 1000 PYR) were estimated for HIV-infected patients with M/HEA and LEA; and population controls with M/HEA and LEA. Unadjusted and adjusted cause-specific MRRs were estimated using Poisson regression model for HIV-infected patients with LEA compared with HIV-infected patients with M/HEA; population controls with LEA compared with population controls with M/HEA; and HIV-infected patients compared with population controls stratified by M/HEA and LEA.

The study was approved by the Danish Data Protection Agency. Data analyses were performed using SPSS statistical software, version 19.0 (Norusis; SPSS Inc., Chicago, Illinois, USA), R version 2.14.2., and STATA software, version 12.0 (STATA Corporation, College Station, Texas, USA).

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Results

We identified 1277 HIV-infected patients, who fulfilled the inclusion criteria and who were followed for a total of 6938 PYR (Table 1). Among the HIV-infected patients, 143 (11.2%) died, 61 (1.6%) emigrated, and none were registered as lost to follow-up. We identified 5738 population controls who were followed for a total of 29 813 PYR, 190 (3.7%) died, 134 (0.9%) emigrated, and two were recorded lost to follow-up.

Table 1
Table 1
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Risk of HIV diagnosis

Compared to individuals with HEA, individuals with medium (MEA) or LEA did not have increased risk of HIV diagnosis [unadjusted/adjusted OR: 1.1 (95% CI 0.9–1.3)/1.1 (95% CI 0.9–1.3) and 1.1 (95% CI, 0.9–1.3)/1.1 (95% CI 0.9–1.3, respectively]. When only including HIV-infected patients with heterosexual transmission and their corresponding population controls, unadjusted/adjusted ORs were 1.3 (95% CI 0.97–1.6)/1.3 (95% CI 0.97–1.6) for MEA and 1.7 (95% CI 1.3–2.3)/1.7 (95% CI 1.3–2.3) for LEA compared with HEA. When only including women, unadjusted/adjusted ORs were 1.0 (95% CI 0.6–1.6)/1.0 (95% CI 0.6–1.6) for MEA and 1.9 (95% CI 1.1–3.0)/1.9 (95% CI 1.2–3.1) for LEA compared with HEA.

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Risk of late and very late presentation at HIV diagnosis

Unadjusted and adjusted ORs for late presentation at HIV diagnosis were 1.1 (95% CI 0.9–1.5)/1.2 (95% CI 0.9–1.6) for HIV-infected patients with MEA and 1.2 (95% CI 0.9–1.7)/1.2 (95% CI 0.9–1.6)) for HIV-infected patients with LEA compared with HIV-infected patients with HEA. Unadjusted and adjusted odd ratios for very late presentation were 1.0 (95% CI 0.8–1.4)/1.1 (95% CI 0.8–1.5) for HIV-infected patients with MEA and 1.3 (95% CI 0.9–1.8)/1.3 (95% CI 0.9–1.8) for HIV-infected patients with LEA compared with HIV-infected patients with HEA.

When only including HIV-infected women, unadjusted/adjusted ORs for late presentation were 1.6 (95% CI 0.7–4.0)/1.6 (95% CI 0.7–4.0) for MEA and 0.9 (95% CI 0.4–2.0)/0.8 (95% CI 0.4–2.0) for LEA compared with HEA. For very late presentation in women, unadjusted/adjusted ORs were 1.7 (95% CI 0.7–4.2)/1.8 (95% CI 0.7–4.4) for MEA and 1.3 (95% CI 0.5–3.1)/1.2 (95% CI 0.5–3.0) for LEA compared with HEA. Sensitivity analyses with very late presentation defined as CD4+ cell counts below 100 or 50 cells/μl did not substantially change the results.

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Time to initiation of HAART

A total of 947 HIV-infected patients fulfilled the criteria for start of HAART (222 HEA, 471 MEA, and 254 LEA), of whom 900 started HAART during the study period. Time to start of HAART stratified by educational attainment is shown in Fig. 1. Cumulative incidences 1 year from fulfillment of HAART criteria were 86.0% (95% CI: 80.6–90.0), 86.6% (95% CI: 83.2–89.4), and 83.5% (95% CI: 78.3–87.6) for HIV-infected patients with HEA, MEA, and LEA.

Fig. 1
Fig. 1
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CD4+ cell counts and viral load response to HAART

A total of 1178 HIV-infected patients were started on HAART during the study period (273 HEA, 569 MEA, and 336 LEA). We observed no substantial differences in median CD4+ cell count and proportion with undetectable viral load stratified by educational attainment after start of HAART (Fig. 2).

Fig. 2
Fig. 2
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All-course and cause-specific mortality

Absolute (mortality rate) and relative risk (MRR) of all-cause mortality and cause-specific mortality are shown in Table 2.

Table 2
Table 2
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Forty eight HIV-infected patients died during the first year after HIV diagnosis, 35 were AIDS-related, and all-cause mortality was more than 10-fold increased among the HIV-infected patients compared with the population controls, most pronounced among HIV-infected patients with LEA.

After the first year from HIV diagnosis, all-cause mortality was 1.8-fold increased among HIV-infected patients with LEA compared with HIV-infected patients with HEA and two-fold increased among HIV-infected patients compared with population controls with the corresponding educational attainment.

Among HIV-infected patients reporting homosexual route of transmission, unadjusted and adjusted MRRs were 0.7 (0.4–1.5)/0.8 (0.4–1.5) and 1.1 (0.5–2.4)/0.9 (0.4–2.1) for MEA and LEA compared with HEA, respectively. Among HIV-infected patients with heterosexual transmission, unadjusted and adjusted MRRs were 2.6 (0.8–8.7)/2.4 (0.7–8.0) and 3.6 (1.1–12.1)/3.3 (1.0–11.0) for HIV-infected patients with MEA and LEA compared with HEA, respectively. Unadjusted and adjusted all-cause MRRs were 1.1(0.6–2.0)/1.1(0.6–2.0) and 1.9(1.0–3.4)/1.7 (0.9–3.0) for male HIV-infected patients with MEA and LEA, respectively. We could not stratify on female gender as only nine female HIV-infected patients died during follow-up.

As the differences in risk of death between individuals with MEA and HEA were small both in the HIV population and the control population, these groups were merged into one group (M/HEA) in analyses of cause-specific mortality, as illustrated in Fig. 3.

Fig. 3
Fig. 3
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Among the cause-specific deaths, we found a substantially increased risk of smoking and alcohol-related mortality among HIV-infected patients with LEA compared with HIV-infected patients with M/HEA.

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Discussion

In this nationwide, population-based study, we observed no association between educational attainments and late or very late presentation at HIV diagnosis, time to start of HAART, or viral load, or CD4+ response to HAART. We did not find an overall increased risk of being diagnosed with HIV related to educational attainment, but found an increased risk of being diagnosed with HIV among heterosexual men and women with LEAs. Further we found that HIV-infected patients with LEA and MEA had increased mortality compared with HIV-infected patients with HEA, but a similar association was observed in the background population. The increased risk of death among HIV-infected patients with LEA mainly stemmed from smoking-related and alcohol-related mortality.

To our knowledge, this is the first nationwide study to estimate impact of educational attainment on risk of HIV acquisition in the general population and time to initiation of and response to HAART among HIV-infected patients. Also our study includes a comparison cohort from the background population matched on age, gender, and country of origin with complete data on educational attainments. A major strength of this study is the high quality and coverage of the Danish registries, the population-based design with long and nearly complete follow-up, and access to valid data on educational attainment for the HIV-infected as well as the control population.

We excluded HIV-infected patients coinfected with hepatitis C and HIV transmission through IDU, as these groups differed in all outcomes [10,18,19,21,22]. The estimated number of active IDUs in Denmark is approximately 13 000 individuals [23] and the prevalence of hepatitis C infection in Denmark is approximately 0.38% [24], which makes combined subpopulations of IDU and hepatitis C infected small in a Danish population of 5.5 million.

Only individuals of Danish origin were included to minimize confounding from differences in migrations. However, the HIV-infected population in Denmark is multiform in respect to ethnicity [10], and the social disparity identified in this study may be different in a multiethnic setting. As the data are registry-based, it was not possible to adjust for smoking and alcohol consumption, and the limited numbers of events restricted the numbers of explanatory variables included in the adjusted analyses.

We did not find an overall increased risk of HIV among non-IDU individuals with LEA, but we found an increased risk of HIV diagnosis among heterosexual men and women with LEA. As Table 1 indicates, the educational attainments among homosexually infected HIV patients is higher than among heterosexually infected HIV patients in our study population, and this is in line with the findings of other studies, which have found a higher educational level among Danish MSM than compared with the general population [25].

In a recent study among Spanish HIV patients, Sobrino-Vegas et al.[8] found an increased risk of delayed HIV diagnosis among men with LEA, and among women with HEA, but in our study educational attainment had no impact on risk of late vs. very late presentation at HIV diagnosis when stratified by gender.

Further, Thorsteinsson et al.[26] did not detect any differences in time to initiation of HAART or overall response to HAART attributed to gender among Danish HIV patients when excluding pregnant women from their study population.

Larsen et al. [18] identified an increased risk of delayed initiation of HAART and a significant lower HIV RNA and CD4+ cell response to HAART among IDUs, and poor adherence was suggested as main explanation for these findings. We did not identify any significant differences in time to initiation of HAART or response to HAART related to educational attainment, indicating that poor adherence is a minor problem among HIV-infected patients with LEA.

Previous studies have addressed a growing social disparity in mortality among HIV-infected patients, especially in the years following the introduction of HAART in 1995–1996 [5,6]. A major part of the excess mortality in HIV-infected populations have been attributed to the HIV-infected IDUs [19,21,27,28]. Even though IDUs were excluded from the study, we found an increased all-cause mortality among HIV-infected patients with LEA compared with HIV-infected patients with HEA.

We detected a 10-fold increased lead-in mortality in all-cause mortality in the year following HIV diagnosis. Excess mortality following a HIV diagnosis has been described elsewhere [29,30], along with the fact that HIV infection may be detected during contact with the healthcare system caused by other heath-related problems [31,32].

We did not find a significant increased risk of AIDS-related mortality among HIV-infected patients with LEA compared with HIV-infected patients with M/HEA. This contrasts previous studies that have identified SES as a strong independent predictor of AIDS-related mortality in the post-HAART era [33]. Nondifferential misclassification might contribute to excess reporting of AIDS-related deaths, especially early in the study period, and thereby leading to an educational disparity in AIDS-related mortality that merely reflects an underlying educational disparity in all-cause mortality among HIV-infected patients [33,34].

In a study covering the entire Danish population, Juel and Koch [17] estimated a decline in excess all-cause mortality among individuals with LEA compared with individuals with HEA of 0.3 when alcohol-related and smoking-related deaths were excluded. In our study, we detected a 3.6-fold increased risk of smoking-related and alcohol-related mortality among HIV-infected patients with LEA compared with HIV-infected patients with M/HEA, and an 2.0-fold increased risk of smoking-related and alcohol-related mortality among population controls with LEA compared with M/HEA. This indicates that the HIV-infected population smokes and consumes alcohol more heavily than population controls, and that especially the HIV-infected patients with LEA have greater consumption of alcohol and tobacco. There has been a shift in smoking and alcohol habits in Denmark both across social status and gender [15,35], but even though these sociodemographic changes may influence the results, the HIV-infected population in our study had significant increased smoking-related and alcohol-related mortality. Our findings are in line with the findings by Helleberg et al.[36] who observed a more than four-fold increased all-cause mortality among HIV-infected patients who were current smokers compared with HIV-infected patients who never smoked.

We conclude that in a setting with free and equal access to healthcare, LEA might be associated with increased risk of HIV infection among heterosexual individuals, but no association among homosexual individuals was found. Educational attainment was not associated with late or very late presentation of HIV diagnosis, delayed initiation, or lower response to HAART. However, in the HIV and non-HIV-infected populations, LEA is associated with substantially and equipotent increased lifestyle-related mortality, which indicates that the increased mortality among HIV-infected patients with LEAs does not stem from HIV-related risk factors.

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Acknowledgements

None.

The funding source had no role in the design, conduct, or analysis of the study or the decision to publish the article.

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Conflicts of interest

N.O. has received research funding from Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, GlaxoSmithKline, Abbott, Boehringer Ingelheim, Janssen-Cilag, and Swedish Orphan. C.P. has received research funding from Abbott, Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, GlaxoSmithKline, Swedish Orphan, Jansen Pharma/Tibotec, and Boehringer Ingelheim. J.G. has received research funding from Abbott, Roche, Bristol-Myers Squibb, Merck Sharp & Dohme, ViiV, Swedish Orphan and Gilead. R.L., G.K., C.S.L., and L.H.O. report no conflicts of interest.

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Keywords:

education; HIV infection; mortality; response to HAART

© 2014 Lippincott Williams & Wilkins, Inc.

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