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Epidemiology and Social

Aging and the evolution of comorbidities among HIV-positive individuals in a European cohort

Pelchen-Matthews, Annegreta; Ryom, Leneb; Borges, Álvaro H.b; Edwards, Simonc; Duvivier, Claudined; Stephan, Christophe; Sambatakou, Helenf; Maciejewska, Katarzynag; Portu, José Joaquính; Weber, Jonathani; Degen, Olafj; Calmy, Alexandrak; Reikvam, Dag Henrikl; Jevtovic, Djordjem; Wiese, Lotharn; Smidt, Jelenao; Smiatacz, Tomaszp; Hassoun, Gamalq; Kuznetsova, Anastasiiar; Clotet, Bonaventuras; Lundgren, Jensb; Mocroft, Amandaa for the EuroSIDA study

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doi: 10.1097/QAD.0000000000001967
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The availability of potent combination antiretroviral therapy (cART) and improved treatment and linkage to care now allow people living with HIV (PLWHIV) to achieve life expectancies close to or the same as those for the general population [1–3] and led to concomitant aging of the HIV-positive population. In high-income countries in Europe and North America, it is estimated that approximately a third of HIV-positive adults are now aged at least 50 years [4,5]. Increases in life expectancy have been accompanied by increases in the prevalence of non-AIDS-related comorbidities such as cardiovascular disease (CVD), chronic kidney disease (CKD) or diabetes in PLWHIV [6–8]. Several cohort studies have described increases in comorbidities, particularly in CVD, CKD, osteoporosis and frailty in the older PLWHIV population [9–12] compared with the general population. This has been attributed to aging and life-style related factors, but also as consequences of HIV infection and the associated immune exhaustion, inflammation [7,13,14] and/or effects of the antiretroviral drugs themselves [15,16]. Certain antiretroviral drugs may affect the risk of CVD or myocardial infarction [17,18], whereas tenofovir disoproxil fumarate (TDF) and some boosted protease inhibitors have been shown to adversely affect kidney function and increase the risk of CKD [19–21]. A better understanding of the evolution of comorbidities may help to improve the clinical management of PLWHIV, including screening for risk factors and optimal selection of ART to balance HIV outcomes and reduce renal and cardiovascular risks [22].

To characterize the evolution of the prevalence of comorbidities and related risk factors in the aging PLWHIV population in Europe, we analysed data from individuals under follow-up in the EuroSIDA cohort during 2006 and 2014. We evaluated demographic and clinical characteristics to determine the prevalence of risk factors and comorbidities as the population aged and used modelling to investigate associations with the prevalence of two common comorbidities, which share many risk factors, CKD and CVD.


Study population and data collection

EuroSIDA is a multinational prospective cohort, which has systematically collected epidemiological, clinical, biological and therapeutic data for nearly 23 000 HIV-positive individuals in 35 European countries and in Israel and Argentina since 1994 [23,24]. Data collection at 6-month intervals is performed by the treating clinicians and constitutes details and dates of all antiretroviral prescriptions, CD4+ cell count and viral load measurements, laboratory data and clinical events, including both AIDS and non-AIDS events.

For this analysis, two cross-sectional analyses were conducted with individuals under active follow-up during 2006, when creatinine measurements became widely available, and 2014, representing a period with state-of-the art ART. Individuals were included if they were recruited before 1 January 2007 or 1 January 2015 for the 2006 and 2014 analyses, whereas participants who were lost to follow-up before 01 January 2006 or 01 January 2014, respectively, or those with a current age less than 16 (calculated at the mid-year, i.e. 1 July 2006 or 2014) were excluded. Variables considered were sex, ethnic group, mode of infection and region of Europe, categorized as South (Greece, Italy, Portugal, Spain, Israel and Argentina), West/Central (Austria, Belgium, France, Germany, Luxembourg and Switzerland), North (Denmark, Finland, Iceland, Ireland, the Netherlands, Norway, Sweden and the United Kingdom) and East (Belarus, Bosnia-Herzegovina, Bulgaria, Croatia, the Czech Republic, Estonia, Georgia, Hungary, Latvia, Lithuania, Poland, Romania, the Russian Federation, Serbia, Slovakia, Slovenia and the Ukraine). BMI (weight divided by the square of height) was categorized as underweight (<18.5), normal (18.5–24.9), overweight (25–29.9) or obese (>30 kg/m2). Recent HIV diagnosis or recent start of cART (taking at ≥3 antiretroviral drugs from any class) were defined as occurring during the 2 years prior to the mid-year of interest. Individuals who had a positive hepatitis C virus (HCV) antibody test, RNA test, genotype assay or received HCV treatment prior to mid-2006 or 2014 were considered co-infected with HCV. Hypertension was defined as SBP at least 140 mmHg and/or DBP at least 90 mmHg and/or taking hypertensive medications. Dyslipidaemia was defined as total cholesterol at least 6.2 mmol/l, high-density lipoprotein (HDL) 0.9 mmol/l or less or triglycerides at least 2.3 mmol/l. Estimated glomerular filtration rates (eGFR) were calculated from serum creatinine levels using the CKD-Epidemiology Collaboration creatinine equation [25], and CKD was a confirmed (two measurements >3 months apart) eGFR of less than 60 ml/min per 1.73 m2. Diabetes was based on clinical diagnosis and/or the use of antidiabetics or insulin; CVD included myocardial infarction, stroke or any invasive cardiovascular procedures. The Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) 5-year risk scores for CKD were calculated as in Mocroft et al.[26] and categorized as low (score <0), moderate (1–4), high (>5), whereas 5-year D:A:D CVD risk scores were categorized as low (<1%), medium (1–5%), high (5–10%) or very high (>10%, see Friis-Moller et al.[27]). Antiretroviral use was defined as none, use in the current year or past use, and antiretroviral exposure was categorized as none or exposure for up to 18 months, 19–36 months or more than 36 months. Age, BMI, smoking status, CD4+ cell count and nadir CD4+, viral load and exposure to antiretroviral were calculated at the latest date before mid-2006 or mid-2014, whereas prevalence of risk factors and comorbidities were included prior to 01 January 2007 for the 2006 or 01 January 2015 for the 2014 cohort.

Statistical methods and modelling

Analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, North Carolina, USA). Baseline characteristics are reported as proportions. To model trends in the odds of CKD or CVD between 2006 and 2014, we used logistic regression with generalized estimating equations with binomial distribution and logit link function to account for correlations between observations for individuals included in both cohorts. Adjusted odds ratios (aOR) are presented based on multivariable adjustment for calendar year (2006 versus 2014), age group, sex, ethnic group, region of Europe, mode of HIV infection, viral load, CD4+ cell counts in the year and CD4+ cells at nadir, HCV coinfection, BMI, smoking status, dyslipidaemia, hypertension and diabetes. Models estimating the odds of CKD also took into account prior use of TDF, atazanavir, boosted atazanavir, lopinavir (LPV/r) or use of boosted protease inhibitors, and CVD. Models estimating the odds of CVD considered prior use of LPV/r, indinavir, abacavir and prior CKD. P less than 0.05 were considered significant.


There were 9798 individuals under follow-up in EuroSIDA during 2006 and 12 882 during 2014; 7180 individuals contributed to both cohorts. Characteristics for those included in the 2006 or 2014 cohorts are shown in Table 1. Between 2006 and 2014, the population aged (median age in 2006: 43.1 years, IQR 37.2–50.0; compared with 2014: median age 48.6 years, IQR 40.3–55.1), and the proportion of individuals aged at least 50 years increased from 25% in 2006 to 44% in 2014. Participants were mainly men, of white/Caucasian ethnicity, with the main mode of infection through MSM. The 2014 cohort had better immunologic characteristics – the proportion of individuals with more than 500 CD4+ cells/μl increased from 43% in 2006 to 59% in 2014 – and better virological control, with the proportion with undetectable viral load (defined as <500 copies of HIV RNA/ml) increasing from 70% in 2006 to 86% in 2014.

Table 1:
Demographic and clinical characteristics of individuals in the 2006 and 2014 cohorts.

Prevalence of risk factors and comorbidities

The prevalence of risk factors and comorbidities for the 2006 and 2014 cohorts is summarized in Table 1 and Fig. 1. Apart from smoking, where the number of current smokers decreased from 51% in 2006 to 44% in 2014, the prevalence of risk factors and comorbidities generally increased in the older age groups. There was a similar high prevalence of dyslipidaemia (about 70%) in 2006 and 2014, whereas the prevalence of diabetes increased from 5.4% in 2006 to 6.3% in 2014. There was a small increase in the proportion of individuals who were overweight (BMI 25–29.9; 21% in 2006 and 23% in 2014) or obese (BMI ≥30; 4.1% in 2006 and 6.0% in 2014), and a larger increase in the proportion of those with hypertension (47 vs. 60% in 2006 and 2014, respectively). The largest increase in prevalence was observed for CKD (4.1% in 2006 to 6.9% in 2014), particularly in older individuals, where the proportion with CKD increased from 5.2% in 2006 to 7.2% in 2014 in the 50–60-year age group, and from 18.5% in 2006 to 23.2% in 2014 in individuals aged at least 60 years. The prevalence of CVD increased overall from 3.7% in 2006 to 5% in 2014, with the highest prevalence in individuals aged 50–60 years (7%) and those at least 60 years old (16%).

Fig. 1:
Prevalence of risk factors (a) and comorbidities/diseases (b) in the cohorts of 2006 (light grey) and 2014 (dark grey), stratified by age group (1, <30 years; 2, 30 to <40 years; 3, 40 to <50 years; 4, 50 to <60 years; and 5, ≥60 years).Bars show the proportions of individuals in each age group who have the risk factor or disease. For CKD, percentages are for those who had an eGFR measurement available (in 2006, 7608 individuals, of whom 326, 1743, 3327, 1516 and 696 were aged <30, 30–40, 40–50, 50–60 and ≥60 years, respectively; in 2014, 11 441 individuals of whom 396, 2218, 3629, 3443 and 1755 were <30, 30–40, 40–50, 50–60 and ≥60 years old). CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate.

Risk factor scores

The D:A:D 5-year risk scores for developing CKD are shown in Fig. 2a. Estimated GFR measurements, based on serum creatinine levels, were available for 7608 individuals in 2006 and 11 441 in 2014. The proportion of individuals with a high 5-year CKD risk score (>5 points) increased from 44% in 2006 to 53% in 2014. This was because of very high proportions of individuals with a high CKD risk score in the older age groups (in 2006, 69% of 50–60 year olds and 96% of those aged ≥60, and in 2014, 75% in the 50–60 and 98% in the ≥60 age groups).

Fig. 2:
D:A:D 5-year risk scores for chronic kidney disease (a) and cardiovascular disease (b) by age group, in 2006 and 2014.(a) D:A:D 5-year risk scores for CKD were calculated based on age, sex, mode of HIV infection, HCV co-infection, eGFR, nadir CD4+ cell count, hypertension, prior CVD, diabetes and use of tenofovir, atazanavir, lopinavir or of other boosted protease inhibitors (see [26]), and classified as low (score <0), moderate (1–4) or high (>5). Numbers are for those who had an eGFR measurement available (7608 individuals in 2006 and 11 441 individuals in 2014). (b) D:A:D 5-year CVD risks calculated from age, sex, family history of CVD, smoking status, diabetes, cholesterol levels, blood pressure and use of indinavir, lopinavir or abacavir, and classified as low (<1%), medium (1–5%), high (5–10%) or very high (>10%) [27]. Numbers are for individuals with eGFR measurements and all other relevant data (6222 individuals in 2006 and 9654 individuals in 2014). Total numbers of individuals in each age group and cohort are shown above the bars. CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate.

The D:A:D 5-year CVD risk scores were calculated only for individuals who had eGFR measurements available to allow comparison between those assessed for CKD and CVD risk (Fig. 2b). Overall the distribution of those with low, medium, high or very-high CVD risks in the five age groups was similar in 2006 and 2014 (Fig. 2b). As the number of individuals in the oldest age groups (50–60 and ≥60 years) increased between 2006 and 2014, there was an overall increase in the proportion of individuals with a very high CVD risk (>10%, from 16% in 2006 to 24% in 2014). The Framingham 10-year CVD risk factors [28] showed a similar distribution to the D:A:D CVD risk factors (not shown).

Factors associated with chronic kidney disease and cardiovascular disease and changes over calendar time

Univariable logistic regression modelling showed that individuals in the 2014 cohort had more than 2.5× higher odds of CKD compared with those in 2006 (unadjusted OR 2.62, CI 2.30–2.99, P < 0.0001). After adjusting for age group, the aOR for CKD for 2014 was 1.56 (CI 1.38–1.77, P < 0.0001), but after adjusting for other factors including demographic variables, viral load and CD4+ counts, HCV infection, smoking status, comorbidies and use of antiretrovirals, the year of the cohort was no longer associated with CKD (aOR 1.07, CI 0.92–1.25, P = 0.37; Fig. 3). Older individuals had significantly increased odds of CKD, and after adjustment, women were twice as likely to have CKD compared with men. Those with lower CD4+ cell counts had higher odds of CKD (Fig. 3), whereas high viral load (>500 copies RNA/ml) was associated with lower odds of CKD. Individuals with low BMI had a small but nonsignificant increase in the odds for CKD, whereas those who were overweight or obese had somewhat lower odds for CKD, compared with those with normal BMI. Individuals with other risk factors or comorbidities (dyslipidaemia, hypertension, diabetes or CVD) had up to two-fold higher odds for CKD (Fig. 3).

Fig. 3:
Adjusted odds ratios for factors associated with chronic kidney disease in the cohorts of 2006 and 2014, taking account of repeated observations for some individuals.There were 315 cases of CKD in 2006 and 791 in 2014. Multivariable adjustment was for the variables shown and in addition for ethnic group (Caucasian or other), region of Europe (South, West/Central, North or East), mode of infection (MSM, intravenous drug users, heterosexual contact or other), CD4+ cell numbers at nadir (categorized as ≤200 cells/μl, >200 cells/μl or unknown), HCV coinfection, family history of CVD and antiretroviral drug use (TDF use, stratified as none, use in the current year or past use of TDF; or prior exposure to lopinavir, atazanavir, boosted atazanavir or other boosted protease inhibitors, all categorized as no prior exposure, or exposure for up to 18 months, 19–36 months or >36 months). ARV, antiretroviral; CKD, chronic kidney disease; CVD, cardiovascular disease; HCV, hepatitis C virus.

Figure 4 shows the factors associated with having CVD for individuals who had eGFR measurements available (to allow comparison with the analysis of CKD). In univariable analysis, individuals in the 2014 cohort had higher odds of CVD compared with those in 2006 (unadjusted OR 1.88, CI 1.68–2.10, P < 0.0001), but after adjusting for age group, the odds of CKD were similar in 2006 and 2014 (aOR 1.06, CI 0.96–1.18, P = 0.24). After multivariable adjustment for age group, sex, region of Europe, mode of infection, viral load, CD4+ counts, prior use of abacavir, LPV/r and indinavir, HCV coinfection, BMI, smoking status, hypertension, dyslipidaemia, diabetes, family history of CVD and CKD, the year of the cohort was also not associated with CVD (aOR 0.94, CI 0.83–1.06; P = 0.29; Fig. 4). Older individuals had higher odds for CVD (aOR 5.05, CI 3.53–7.23 for those aged 50–60 years and aOR 9.34, CI 6.4–13.65 for those ≥60) and women were less likely to have CVD. Current and past smokers had higher odds compared with those who had never smoked and the odds for CVD were also increased among those with hypertension (aOR 2.72, CI 2.23–3.31), diabetes (aOR 1.85, CI 1.52–2.24) or CKD (aOR 1.63, CI 1.35–1.97; Fig. 4). There was no evidence that the relationship between cohort year and CVD or CKD differed across age groups (test for interaction P = 0.33 for CKD and P = 0.34 for CVD).

Fig. 4:
Adjusted odds ratios for factors associated with cardiovascular disease in the cohorts of 2006 and 2014, taking account of repeated observations for some individuals.Only individuals with available eGFR measurements were included in the analysis (337 cases of CVD among 7608 individuals in the 2006 cohort, and 619 cases of CVD among 11 441 individuals in the 2014 cohort). Multivariable adjustment was for the variables shown as well as region of Europe (South, West/Central, North or East), mode of infection (MSM, intravenous drug users, heterosexual contact or other), CD4+ cell numbers at nadir, HCV coinfection and antiretroviral drug use (use of lopinavir, indinavir and abacavir, all stratified as no prior use, use in the current year or past use). CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate.


We compared two cross-sectional cohorts of individuals under active follow-up in EuroSIDA in 2006 and 2014 to capture changes in the prevalence of comorbidities in PLWHIV. Over time, individuals aged, and in the 2014 cohort 44% of participants were at least 50 years old. In parallel, there was an increase in the prevalence of age-related risk factors including hypertension and obesity, and more individuals had higher calculated 5-year risk scores for CKD and CVD. The prevalence of diabetes, CKD and CVD was also higher in 2014 compared with the 2006 cohort. Although unadjusted analyses suggested an increase in the odds of both CVD and CKD over time, the increase in CVD was explained by aging of the population. After adjusting for age group, the increased odds of CKD in 2014 were reduced but still higher compared with 2006; but after multivariable adjustment for additional comorbidities and confounding factors, there was no significant difference in the odds of CKD in 2014 and 2006.

Several cohort studies have investigated the prevalence of risk factors and comorbidities in PLWHIV compared with the general population and many have identified similar increases of comorbidities in the HIV-positive population, driven by increases in hypertension, dyslipidaemia and obesity. In this study, the prevalence of hypertension increased between 2006 and 2014, and was somewhat higher than previously reported [29,30], possibly because of the older age of those included here. More recent studies report a higher burden of hypertension compared with uninfected populations [10,31–33]. We also observed high prevalence of dyslipidaemia, based on total and HDL cholesterol and triglyceride levels, in 2006 and 2014. This is comparable with several studies in the USA, which reported dyslipidaemia in 58–80% of participants [32–34]. Some of this variation may be explained by different definitions, for example, whether triglyceride levels are included or whether lipid levels are based on fasting blood samples. The low prevalence of obesity was similar to data reported for the AgehIV [31] and the Swiss cohort [10], although considerably lower than seen in cohorts of PLWHIV in the USA [32–35], probably because of life-style factors and different demographics as the European cohorts are dominated by MSM.

We observed a small increase in the prevalence of diabetes between 2006 and 2014, similar to that reported in the Swiss HIV cohort [10]. Diabetes appears strongly correlated with age [9], with lower prevalence reported for younger cohorts [30,36], whereas higher prevalence of diabetes (12–18%) was reported in studies in the USA [32–35]. The prevalence of CKD also increased from 4% in 2006 to 6.9% in 2014, and the odds of CKD increased with time, though this was explained by aging and other risk factors. The increase in CKD is broadly similar to that observed in other European cohorts (e.g. 4.7% in the AgehIV cohort [31,37]); by comparison, a lower prevalence of CKD was observed in earlier studies with younger cohorts (2% in the Danish study [11]), whereas Guaraldi et al.[9] reported 9% CKD in HIV-positive patients aged >50 years.

There has been a focus on CVD in PLWHIV, as HIV infection per se as well as certain antiretrovirals may contribute to CVD risk [17,18,20], and there is a strong association of CVD risk with age. Here we observed an increase in the prevalence of CVD (including myocardial infarction, stroke or invasive cardiovascular procedures) from 3.7% in 2006 to 5% in 2014. This is comparable to the prevalence of cardiovascular conditions reported in other studies. The Danish HIV cohort study reported a prevalence of 3% for myocardial infarction and 4% for stroke [11], whereas CVD prevalence of 6% has been reported in individuals greater than 50 years old in Italy [9], and 10% in the AgehIV cohort [31,37]. Although the unadjusted odds of CVD were strongly associated with year of cohort, after multivariable adjustment, the year was no longer significantly associated with CVD. Increasing age was strongly associated with higher odds of CVD, which is of concern with an aging population of PLWHIV. For younger individuals, the decreased odds of CVD are potentially related to reduced exposure to antiretrovirals that are known to increase CVD risk [17].

The increase in the prevalence of multiple risk factors and non-AIDS-related comorbidities between 2006 and 2014 is in keeping with what has been observed in many other cohorts [9–12], and also reflects the increase in individuals presenting with multiple conditions. Many of the conditions are interrelated; for example, hypertension has been shown to contribute to the risk of developing diabetes, CKD or CVD, diabetes is a risk factor for CKD, and both diabetes and CKD increase the risk of CVD [38,39]. This highlights the need to address these risk factors and comorbidities together through appropriate medical and lifestyle interventions. Further, as persons are aging and living longer, careful consideration should be given to clinical management of the older PLWHIV population who face additional risks associated with HIV infection, immunosuppression and immune inflammation as well as effects of the antiretrovirals [40] and the need to avoid drug-interactions and polypharmacy [7,41,42].

There are a number of limitations to this study. EuroSIDA is an observational cohort following individuals engaged in care, and the prevalence of comorbidities may be different to other studies of PLWHIV. Given that patient care and treatments are decided by clinicians, there is a possibility of confounding by indication where individuals with poorer prognosis or higher risk factors for certain comorbidities are selected for suitable interventions or specific antiretrovirals. Analyses were restricted to well defined risk factors and comorbidities as information on other age-related comorbidities such as osteoporosis and frailty, lung conditions or neurocognitive status was not available, whereas lack of data on proteinuria, diet and physical activity may represent residual confounding. Identification of CKD was only possible for individuals where serum creatinine measurements were available and our analysis of factors associated with CKD and CVD was restricted to those individuals. The proportion of individuals with eGFR available varied between 2006 and 2014 (89% of individuals in the 2014 cohort had eGFRs, but in 2006, there were only 78% with eGFR and measurements were not available for 66% of those aged <30 years), which might introduce bias. However, similar odds for CVD were seen in a sensitivity analysis when all individuals were included. These is also likely to be some variation in clinical practice and treatment between the centres and regions in EuroSIDA. Among the strengths of the study is the size of the cohort, covering most countries in the European region. Data collection is consistent across all regions with standardized follow-up, quality assurance and low rates of loss to follow-up [43]. Comparable groups of individuals were followed in 2006 and 2014 (73% of those in the 2006 cohort were still under follow-up in 2014), providing an overview of the population of PLWHIV in Europe.

In conclusion, our analysis of risk factors and comorbidities in a large cohort of HIV-positive individuals in Europe has shown an increase in the prevalence of non-AIDS comorbidities, including diabetes, CKD and CVD, along with increased prevalence of hypertension and a high prevalence dyslipidaemia, which was largely explained by the aging of persons included. Higher prevalence of comorbidities was particularly evident for individuals at least 50 years old, highlighting the increase in non-AIDS-related conditions in the aging PLWHIV population. This shows a need for careful management not only to control HIV through optimal selection of ART, but also to address the effect of aging, including screening and regular monitoring of the major comorbidities and risk modification measures and should lead to continued improvement of health outcomes and quality of life in PLWHIV.


The EuroSIDA Study Group

Argentina: M. Losso, M. Kundro, Hospital JM Ramos Mejia, Buenos Aires. Austria: B. Schmied, Otto Wagner Hospital, Vienna; R. Zangerle, Medical University Innsbruck, Innsbruck. Belarus: I. Karpov, A. Vassilenko, Belarus State Medical University, Minsk; V.M. Mitsura, Gomel State Medical University, Gomel; D. Paduto, Regional AIDS Centre, Svetlogorsk. Belgium: N. Clumeck, S. De Wit, M. Delforge, Saint-Pierre Hospital, Brussels; E. Florence, Institute of Tropical Medicine, Antwerp; L. Vandekerckhove, University Ziekenhuis Gent, Gent. Bosnia-Herzegovina: V. Hadziosmanovic, Klinicki Centar Univerziteta Sarajevo, Sarajevo. Croatia: J. Begovac, University Hospital of Infectious Diseases, Zagreb. Czech Republic: L. Machala, D. Jilich, Faculty Hospital Bulovka, Prague; D. Sedlacek, Charles University Hospital, Plzen. Denmark: G. Kronborg, T. Benfield, Hvidovre Hospital, Copenhagen; J. Gerstoft, T. Katzenstein, Rigshospitalet, Copenhagen; C. Pedersen, I.S. Johansen, Odense University Hospital, Odense; L. Ostergaard, Skejby Hospital, Aarhus, L. Wiese, N.F. Moller, Sjællands Universitetshospital, Roskilde; L.N. Nielsen, Hillerod Hospital, Hillerod. Estonia: K. Zilmer, West-Tallinn Central Hospital, Tallinn; Jelena Smidt, Nakkusosakond Siseklinik, Kohtla-Järve. Finland: M. Ristola, I. Aho, Helsinki University Central Hospital, Helsinki. France: J.-P. Viard, Hôtel-Dieu, Paris; P.-M. Girard, Hospital Saint-Antoine, Paris; C. Pradier, E. Fontas, Hôpital de l’Archet, Nice; C. Duvivier, Hôpital Necker-Enfants Malades, Paris. Germany: J. Rockstroh, Universitäts Klinik Bonn; G. Behrens, Medizinische Hochschule Hannover; O. Degen, University Medical Center Hamburg-Eppendorf, Infectious Diseases Unit, Hamburg; H.J. Stellbrink, IPM Study Center, Hamburg; C. Stephan, JW Goethe University Hospital, Frankfurt; J. Bogner, Medizinische Poliklinik, Munich; G. Fätkenheuer, Universität Köln, Cologne. Georgia: N. Chkhartishvili, Infectious Diseases, AIDS & Clinical Immunology Research Center, Tbilisi. Greece: H. Sambatakou, Ippokration General Hospital, Athens; G. Adamis, N. Paissios, Athens General Hospital ‘G Gennimatas’ Hungary: J. Szlávik, Szent Lásló Hospital, Budapest. Iceland: M. Gottfredsson, Landspitali University Hospital, Reykjavik. Ireland: F. Mulcahy, St. James's Hospital, Dublin. Israel: I. Yust, D. Turner, M. Burke, Ichilov Hospital, Tel Aviv; E. Shahar, G. Hassoun, Rambam Medical Center, Haifa; H. Elinav, M. Haouzi, Hadassah University Hospital, Jerusalem; D. Elbirt, Z.M. Sthoeger, AIDS Center (Neve Or), Jerusalem. Italy: A. D’Arminio Monforte, Istituto Di Clinica Malattie Infettive e Tropicale, Milan; R. Esposito, I. Mazeu, C. Mussini, Università Modena, Modena; F. Mazzotta, A. Gabbuti, Ospedale S Maria Annunziata, Firenze; V. Vullo, M. Lichtner, University di Roma la Sapienza, Rome; M. Zaccarelli, A. Antinori, R. Acinapura, M. Plazzi, Istituto Nazionale Malattie Infettive Lazzaro Spallanzani, Rome; A. Lazzarin, A. Castagna, N. Gianotti, Ospedale San Raffaele, Milan; M. Galli, A. Ridolfo, Osp. L. Sacco, Milan. Latvia: B. Rozentale, Infectology Centre of Latvia, Riga. Lithuania: V. Uzdaviniene, Vilnius University Hospital Santaros Klinikos, Vilnius; R. Matulionyte, Centro poliklinika, Vilnius, Vilnius University Hospital Santaros Klinikos, Vilnius. Luxembourg: T. Staub, R. Hemmer, Centre Hospitalier, Luxembourg. Netherlands: P. Reiss, Academisch Medisch Centrum bij de Universiteit van Amsterdam, Amsterdam. Norway: D.H. Reikvam, A. Maeland, J. Bruun, Oslo University Hospital, Ullevaal. Poland: B. Knysz, J. Gasiorowski, M. Inglot, Medical University, Wroclaw; E. Bakowska, Centrum Diagnostyki i Terapii AIDS, Warsaw; R. Flisiak, A. Grzeszczuk, Medical University, Bialystok; M. Parczewski, K. Maciejewska, B. Aksak-Was, Medical University, Szczecin; M. Beniowski, E. Mularska, Osrodek Diagnostyki i Terapii AIDS, Chorzow; T. Smiatacz, M. Gensing, Medical University, Gdansk; E. Jablonowska, J. Kamerys, K. Wojcik, Wojewodzki Szpital Specjalistyczny, Lodz; I. Mozer-Lisewska, Poznan University of Medical Sciences, Poznan. Portugal: L. Caldeira, Hospital Santa Maria, Lisbon; K. Mansinho, Hospital de Egas Moniz, Lisbon; F. Maltez, Hospital Curry Cabral, Lisbon. Romania: R. Radoi, C. Oprea, Carol Davila University of Medicine and Pharmacy Bucharest, Victor Babes Clinical Hospital for Infectious and Tropical Diseases, Bucharest. Russia: A. Panteleev, O. Panteleev, St Petersburg AIDS Centre, St Peterburg; A Yakovlev, Medical Academy Botkin Hospital, St Petersburg; T Trofimora, Novgorod Centre for AIDS, Novgorod, I Khromova, Centre for HIV/AIDS & and Infectious Diseases, Kaliningrad; E Kuzovatova, Nizhny Novgorod Scientific and Research Institute of Epidemiology and Microbiology named after Academician I.N. Blokhina, Nizhny Novogrod; E Borodulina, E Vdoushkina, Samara State Medical University, Samara. Serbia: (D Jevtovic), The Institute for Infectious and Tropical Diseases, Belgrade. Slovenia: J. Tomazic, University Clinical Centre Ljubljana, Ljubljana. Spain: J.M. Gatell, J.M. Miró, J. Mallolas, E. Martinez, F. Garcia, J.L. Blanco, M. Laguno and M. Martinez-Rebollar, Hospital Clinic – IDIBAPS University of Barcelona, Barcelona; S. Moreno, J.M. Rodriguez, Hospital Ramon y Cajal, Madrid; B. Clotet, A. Jou, R. Paredes, C. Tural, J. Puig, I. Bravo, Hospital Germans Trias i Pujol, Badalona; P. Domingo, M. Gutierrez, G. Mateo, M.A. Sambeat, Hospital Sant Pau, Barcelona; J.M. Laporte, Hospital Universitario de Alava, Vitoria-Gasteiz. Sweden: K. Falconer, A. Thalme, A. Sonnerborg, Karolinska University Hospital, Stockholm; C.J. Treutiger, Venhälsan-Sodersjukhuset, Stockholm; L Flamholc, Malmö University Hospital, Malmö. Switzerland: A. Scherrer, R. Weber, University Hospital Zurich; M. Cavassini, University Hospital Lausanne; A. Calmy, University Hospital Geneva; H. Furrer, University Hospital Bern; M. Battegay, University Hospital Basel; P. Schmid, Cantonal Hospital St. Gallen. Ukraine: A Kuznetsova, Kharkov State Medical University, Kharkov; G. Kyselyova, Crimean Republican AIDS centre, Simferopol; M. Sluzhynska, Lviv Regional HIV/AIDS Prevention and Control CTR, Lviv. United Kingdom: B. Gazzard, St. Stephen's Clinic, Chelsea and Westminster Hospital, London; A.M. Johnson, E. Simons, S. Edwards, Mortimer Market Centre, London; A. Phillips, M.A. Johnson, A. Mocroft, Royal Free and University College Medical School, London (Royal Free Campus); C. Orkin, Royal London Hospital, London; J. Weber, G. Scullard, Imperial College School of Medicine at St. Mary's, London; A. Clarke, Royal Sussex County Hospital, Brighton; C. Leen, Western General Hospital, Edinburgh.

Steering Committee: I. Karpov, M. Losso, J. Lundgren, J. Rockstroh, I. Aho, L.D. Rasmussen, V. Svedhem, G. Wandeler, C. Pradier, N. Chkhartishvili, R. Matulionyte, C. Oprea, J.D. Kowalska, J. Begovac, J.M. Miro, G. Guaraldi, R. Paredes. Chair: J. Rockstroh. Study Co-leads: A. Mocroft, O. Kirk.

Coordinating Centre Staff: O. Kirk, L. Peters, A. Bojesen, D. Raben, D. Kristensen, K. Laut, J.F. Larsen, D. Podlekareva, B. Nykjær.

Statistical Staff: A. Mocroft, A. Phillips, A. Cozzi-Lepri, L. Shepherd, S. Amele, A. Pelchen-Matthews.

Author contributions: A.M., J.L., L.R. and A.H.B. conceived the study and planned the analysis. A.P.-M. performed statistical analysis and data interpretation. A.P.-M. produced the first draft of the manuscript. S.E., C.D., C.S., H.S., K.M., J.J.P., J.W., O.D., A.C., D.H.R., D.J., L.W., J.S., T.S., G.H., A.K. and B.C. contributed to patient recruitment and data collection, and interpretation and presentation of results. A.M. supervised the project. All authors reviewed and approved the manuscript.

Funding: EuroSIDA was supported by the European Union's Seventh Framework Programme for research, technological development and demonstration under EuroCoord grant agreement n° 260694. Current support includes unrestricted grants by ViiV Healthcare LLC, GlaxoSmithKline R&D Limited, Janssen Scientific Affairs, Janssen R&D, Bristol-Myers Squibb Company, Merck Sharp & Dohme Corp, and Gilead Sciences. The participation of centres from Switzerland was supported by The Swiss National Science Foundation (Grant 148522). The study is also supported by a grant (grant number DNRF126) from the Danish National Research Foundation and by the International Cohort Consortium of Infectious Disease (RESPOND).

This analysis was funded by Gilead Sciences who did not influence the analyses presented or the decision to publish study findings.

Conflicts of interest

There are no conflicts of interest.


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aging; chronic cardiovascular diseases; comorbidity; HIV infections; renal insufficiency

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