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Factors associated with health-related quality of life in people living with HIV in Norway



Despite the advances in the treatment of HIV, people living with HIV (PLHIV) still experience impairment of health-related quality of life (HRQOL). The aim of the study was to explore factors associated with HRQOL in a well-treated Norwegian HIV population.


Two hundred and forty-five patients were recruited from two outpatient clinics to participate in this cross-sectional study of addiction, mental distress, post-traumatic stress disorder, fatigue, somatic health, and HRQOL. The latter was measured using the 36-Item Short Form Health Survey (SF-36). Stepwise multiple linear regression analysis was used to examine the adjusted associations between demographic and disease-related variables and HRQOL.


The study population was virologically and immunologically stable. Their mean age was 43.8 (SD = 11.7) years, 131 (54%) were men, and 33% were native Norwegians. Compared with the general population (published in previous studies), patients reported worse SF-36 scores for five of eight domains: mental health, general health, social function, physical role limitation, and emotional role limitation (all p < 0.001). Compared with men, women reported better SF-36 scores within the domains vitality (63.1 (23.6) vs. 55.9 (26.7), p = 0.026) and general health (73.4 (23.2) vs. 64.4 (30.1), p = 0.009). In the multivariate analyses, higher SF-36- physical component score values were independently associated with young age (p = 0.020), being employed, student, or pensioner (p = 0.009), low comorbidity score (p = 0.015), low anxiety and depression score (p = 0.015), being at risk of drug abuse (p = 0.037), and not being fatigued (p < 0.001). Higher SF-36-mental component score values were independently associated with older age (p = 0.018), being from a country outside Europe or from Norway (p = 0.029), shorter time since diagnosis, low anxiety and depression score (p < 0.001), answering ‘no’ regarding alcohol abuse (p = 0.013), and not being fatigued (p < 0.001).


HRQOL was poorer in PLHIV than in the general population in Norway. It is important to focus on somatic and mental comorbidities when delivering health-care services in the ageing population of PLHIV to improve HRQOL even among a well-treated group of PLHIV as found in Norway.


HIV care has improved markedly over the years in locations with access to highly active antiretroviral treatment. HIV disease has changed from being a deadly infection to a chronic disease with a life expectancy approaching that of the general population [1]. Access to treatment is both life-saving for people living with HIV (PLHIV) and important from a public health perspective by preventing HIV transmission [2]. A change in focus for the treatment of ageing population of PLHIV requires knowledge of antiretroviral management as well as expertise in the prevention and management of comorbidities typically associated with ageing [3]. Despite the global awareness and improvement in HIV care, the extent to which the stigma and discrimination that remain adversely affect health-related quality of life (HRQOL) in (PLHIV) needs investigation.

The Joint United Nations Programme on HIV/AIDS launched its getting to zero vision as ‘zero new HIV-infections, zero HIV-related deaths, and zero HIV-related discrimination’ in 2011 [4]. Since then, the ‘90–90–90 treatment for all’ programme was established in 2017 to help end the AIDS epidemic by focusing on rapid diagnostics and adequate treatment [5]. The awareness and recognition of the importance of an integrated and people-centred health service of chronic care for PLHIV have led to a proposal by Lazarus et al. for a ‘fourth 90’ to focus on the quality of life (QOL) [6]. For people with chronic diseases who require lifelong treatment and care, QOL becomes a key point of care, and it is important to identify factors that influence QOL [7]. When focusing QOL in a health context, the concept HRQOL is often used.

It is generally accepted that HRQOL is a multidimensional concept that incorporates factors such as physical, cognitive, emotional, and social functioning, each of which can affect one’s disease and/or treatment [8]. Several assessment tools have been established to measure HRQOL among PLHIV [9]. Although various factors associated with HRQOL have been identified, there is no consensus about the main determinants within the socio-demographic, clinical, psychological, and behavioural factors [10]. Even well-treated PLHIV have reported poorer HRQOL compared with healthy controls [11], and PLHIV report poorer mental HRQOL than other with chronic diseases [12].

To our knowledge, identify factors associated with HRQOL among PLHIV residing in Norway have not been identified. The aim of this study was to explore the associations between HRQOL and gender, socio-demographic, mental, and somatic health variables in well-treated PLHIV residing in Norway.

Material and methods

Study population

All PLHIV older than 18 years who were registered at the HIV outpatient clinics at the Southern Hospital of Norway (SSHF) and University Hospital of North Norway (UNN) were eligible to participate in this cross-sectional study regardless of their language and literacy. The nurse-facilitated survey, Mental health and quality of life among people living with HIV in Northern and Southern Norway, was completed in October 2015 and included questionnaires containing 147 questions about socio-demographic background, fatigue, HRQOL, addiction, and somatic and mental health. Patients pre-diagnosed with a severe mental disorder or cognitive impairment that would make them incapable of answering the questions were excluded (n = 10). However, solely illicit drug use was not an exclusion criterion.

The study was approved by the Regional Committee for Medical Research Ethics (ref 2011/1925 REK Nord).

Demographic and clinical data and questionnaires

The demographic data representing the independent variables included age, gender, hospital, education, cohabitation, and employment. The HIV-related variables were time since diagnosis, transmission route, openness about diagnosis, virus suppression, CD4+ cell count, antiretroviral therapy (ART), and treatment failure. The other health-related variables were, bodily pain, trouble sleeping, anaemia, and comorbidities (renal failure, thyroid disease, diabetes, cardiovascular disease, osteoporosis, arthritis, physical impairment, cancer, stroke, asthma, hepatitis C virus or chronic obstructive pulmonary disease). Comorbidity was defined as the presence of extra conditions beyond HIV. Data on medication, comorbidities, and blood test results were extracted from the medical records.

All participants completed seven validated instruments and a general informational scheme, conducted as a formalized interview with a trained nurse. The interviews were in English (n = 10), French (n = 2), or Norwegian (n = 224), or in another language with a professional interpreter if needed (n = 9). To explore anxiety and depression, the well-established Hopkins Symptom Checklist-25 (HSCL-25) was used [13]. This instrument has 10 items related to anxiety symptoms and 15 items to assess depression. The response options range from 1 to 4: ‘not at all’, ‘a little’, ‘quite a bit’, and ‘extremely’. The mean sum scores are calculated for the 10 anxiety items and for the 15 depression items, and a total score (average of all 25 items) is calculated. The HSCL-25 is a validated questionnaire that is useful as a screening tool in various settings, including in PLHIV [14].

To confirm depression, Beck’s Depression Inventory version 2 (BDI-II) was completed for participants with an HSCL-25 score above the cut-off of 1.75. BDI-II is a 21-question inventory designed to measure the severity of depression and comprises four statements for the time frame of two weeks. The answers are scored 0 to 3, and the responses are summed to yield a score that ranges from 0 to 63. A higher score indicates greater depression symptomatology, minimal depression (0–13), mild depression (14–19), moderate depression (20–28), severe depression (29–63) [15,16,17].

Diagnosing post-traumatic stress disorder (PTSD) can be challenging, and we used the Posttraumatic Stress Scale-16 (PTSS-16) as the screening instrument. The PTSS-16 comprises 16 questions about the frequency of symptoms after stressful life experiences during the past week. The answers are ‘not at all’, ‘a little bit’, ‘quite a bit’, and ‘almost always’, which are scored 1–4, respectively. A total mean score > 2.5 is defined as PTSD [18].

To explore risky alcohol consumption, the Alcohol Use Disorder Identification Test (AUDIT) was used. It is a widely used questionnaire of 10 items, each of which is scored as 0 to 4, and the higher score indicates greater alcohol consumption. We used the AUDIT score > 8 for men and > 6 for women to indicate risky consumption [19, 20]. The Drug Use Disorder Identification Test (DUDIT) is an 11-item questionnaire, each of which is scored as 0 to 4. Similar to the AUDIT, a higher score indicates at risk of drug abuse. DUDIT defines drugs as the misuse of legal drugs not prescribed by a doctor or the use of illicit drugs. The cut-off for at risk of drug abuse was a score of ≥ 6 for men and > 1 for women [21, 22].

The validated 11-item Chalder Fatigue Scale (FQ-11) contains two components, one to measure mental fatigue and the other to measure physical fatigue. Each item is scored on a 4-point Likert scale, and the total score is 0 to 11. Fatigue is defined as a score of ≥ 4 points [23,24,25].

HRQOL was assessed using the 36-item Short Form Health Survey questionnaire (SF-36), a self-reported and generic questionnaire that includes eight domains: general health, bodily pain, physical function, role limitations (physical), mental health, vitality, social function, and role limitations (emotional). The eight domains can be combined into a physical and mental sum scale that reflects physical and mental health. The physical component summary (SF-36-PCS) and the mental component summary (SF-36-MCS) scales were used in this study [26]. The SF-36 scales were scored according to published scoring procedures, and each scale was expressed using values from 0 to 100, with 100 representing excellent health [27,28,29,30].

Statistical analyses

Statistical analyses were performed using IBM SPSS Statistics version 27 [31]. Continuous variables are presented as mean and standard deviation (SD), and categorical variables as numbers and percentages (%). The chi-squared test and Student’s t test were used to compare differences between subgroups. When comparing HRQOL of our study population with previous published data from the aged matched general Norwegian population [32, 33] we used GraphPad. In the GraphPad we included mean (SD) scores for the eight SF-36 domains from both populations, the number of participants and used Independent t test for comparison.

Stepwise multiple linear regression analysis (backward procedure) was used to examine the adjusted associations between demographic and disease-related variables and HRQOL (SF-36-PCS and SF-36-MCS scores) (PIN = 0.05 and POUT = 0.20). Assumptions for linear regression were checked and fulfilled. The independent variables in the multiple analyses were chosen based on univariate associations with HRQOL and clinical experience/relevance and included age, gender, cohabitation, native continent, employment status, comorbidities, HIV viral load, at risk of drug or alcohol abuse, and fatigue scores [34]. The final tested variables are listed in Table 3. For robustness, we also tested the models using forward multiple regression analyses. The level of significance was set at p < 0.05.


Demographic and disease-related characteristics

The SSHF had 121 registered PLHIV and the UNN 158. Of the total of 279 PLHIV, 245 completed the survey, giving a response rate of 87.8%. The mean age of the participants was 43.8 (SD = 11.7) years; 131 (54%) were men and 33% were native Norwegians. Close to 60% had < 13 years of education, and 30% were either unemployed, undergoing rehabilitation, or disabled. The time since the diagnosis of HIV was a mean 9.4 (SD = 7.4) years; 86% had a viral load < 50 copies/mL, and their average CD4+ count was 0.53 × 109/L (SD = 0.26). Fifty-three (22%) of the participants were not open about their HIV status to their closest family or partner. There was a significant difference between PLHIV in northern and southern Norway (p = 0.01), however there were no significant gender differences. Thirty-five (14%) of the study population were open about their HIV status in the public, i.e. at work. Though, there were no significant differences among gender or hospital. The socio-demographic characteristics of the cohort are presented in Table 1, which shows the similarities and differences between men and women and hospital in age, native country, employment status, educational level, cohabitation status, and fatigue levels.

Table 1 Demographic and clinical variables among people living with HIV in Southern (n = 109) and Northern (n = 136) Norway (n = 245)


Comparison of PLHIV treated at the two hospitals showed that those treated at UNN had better scores for two SF-36 domains: mental health (76.2 (20.4) vs. 70.1 (23.7), p = 0.033) and social function (82.6 (27.7) vs. 74.8 (30.1), p = 0.037). PLHIV treated at the UNN also had a higher SF-36-MCS (48.0 (13.3) vs. 43.6 (14.1), p = 0.015). The PLHIV at both hospitals were part of the study, so in further analyses the patients were considered as one group despite some small differences (data not shown).

Compared with men, women reported better SF-36 scores within the domains vitality (63.1 (23.6) vs. 55.9 (26.7), p = 0.026) and general health (73.4 (23.2) vs. 64.4 (30.1), p = 0.009) (Table 2). Comparison between PLHIV and with data from an age matched general Norwegian population [32, 33] showed that PLHIV had worse SF-36 scores for five of the eight domains: mental health, general health, social function, physical role limitations, and emotional role limitations (all p < 0.001) (data not shown).

Table 2 Health-related quality of life in people living with HIV using the 36-item Short Form Health Survey questionnaire (n = 245)

Adjusted associations between demographic and clinical variables and HRQOL

In the multivariate analyses (Table 3), lower SF-36-PCS values were independently associated with old age (B = -0.12 (95% CI [− 0.21; − 0.02], p = 0.020), being unemployed/undergoing rehabilitation/disabled (B = − 6.79 (95% CI [− 6.00; − 0.98)], p = 0.007), higher comorbidity score (B = − 2.46 (95% CI [− 4.04 to 0.88)], p = 0.015), higher HSCL-25 score (B = − 3.18 (95% CI [− 5.73; − 0.62)], p = 0.015), and being fatigued (B = − 6.79 (95% CI [− 9.62; − 3.96)], p < 0.001), while higher SF-36 PCS values was associated with being at risk of drug abuse (B = 3.14 (95% CI [0.20;6.09)], p = 0.037). Lower SF-36-MCS values were independently associated with being from Europe except from Norway (B = − 5.14 (95% CI [− 9.75; − 0.54], p = 0.029), longer time since diagnosis (B = − 0.16 (95% CI [− 0.32;0.00)], p = 0.046), higher HSCL-25 score (B = − 15.01 (95% CI [− 17.49; − 12.53]), p < 0.001), being at risk of alcohol abuse (B = − 4.14 (95% CI [− 7.41; − 0.88)], p = 0.013), and being fatigued (B = − 5.49 (95% CI [− 8.36; − 2.61], (p < 0.001), while higher SF-36 MCS values was associated with lower age (B = 0.12 (95% CI [0.02;0.23)], p = 0.018). The demographic and clinical variables included in the full model explained 34.2% of the variance for the SF-36-PCS, in the final model 35.2%. The independent variables in the full model explained 61.9 of the variance for the SF-26-MCS, in the final model 62.9%. The same results were seen when the multivariate models were run forwards and if including hospital in the model (data not shown).

Table 3 Stepwise multivariate regression model of the adjusted associations between demographic and clinical variables, and physical and mental components of Health-related quality of life in people living with HIV (n = 245)


In this cross-sectional survey of 245 well-treated PLHIV residing in Norway, PLHIV had a poorer HRQOL than the general population [32, 33]. This observation is consistent with the results of other recently published cross-sectional surveys of HRQOL in PLHIV [7, 11].

The study population was recruited from two hospitals and differed significantly on two HRQOL domains (mental health and social function) as well as the SF-36-MCS. This finding was surprising for two reasons. First, all residents in Norway have access to free, high-quality health-care services and other social support systems [35]. Second, the SSHF has established a user-driven HIV clinic within their hospital facilities to provide optimal holistic health care and treatment, and to empower PLHIV [36]. The differences in HRQOL seen in the two hospitals in our study may reflect the fact that 42% of those living in northern Norway had full-time work compared with only 27% of those living in southern Norway. An association between employment and HRQOL on both the SF-36-PCS and SF-36-MCS has been reported in several studies [37,38,39,40,41,42]. A recent study among Swedish adults, showed that unemployment is strongly related to a poorer HRQOL [43]. However, unemployment hits groups of individuals differently and should be considered when prioritizing labour market measures [34]. The study is of interest, especially in a Norwegian setting, due to our common Scandinavian welfare and social model. In addition, the population in southern Norway more often lived alone, had a lower educational level, less open regarding the HIV to closest relatives or partner, and were more often disabled pensioners compared with the population living in northern Norway. These factors may influence HRQOL, as previously reported by Degroote and colleagues [10].

We explored whether age was associated with higher SF-36-MCS and SF-36-PCS scores. Several studies have reported that old age is associated with lower physical health scores [41, 44,45,46,47,48,49]; which may indicate poorer physical functioning and more comorbidities because of older age. Like previous studies that have reported a positive correlation between increasing age and better mental health, we found that older PLHIV reported better mental health and MCS scores [40, 47]. However, the literature is inconsistent regarding the relationship between age and mental health [50,51,52].

Another demographic variable associated with mental health was the native continent of the PLHIV in this study; that is, coming from a country outside Europe or from Norway was associated with a higher score at SF-36-MCS. A considerable number of our European study population were from Eastern Europe or the former Soviet Union, which may have contributed to their low SF-36-MCS-scores. Studies from this region have reported the need to focus on health and social care to improve HRQOL and QOL [39, 53,54,55]. A recent publication by Kuznetsov and colleagues, focused on treatment and health challenges among PLHIV residing in the Russian Federation [56], where especially HIV stigma makes a great challenge [57]. Our findings might be a result of previous experiences of living with HIV, despite the fact that they are now living in Norway.

Along with age, comorbidity was another variable that was significantly associated with lower SF-36-PCS scores in our study population. We defined comorbidity as the sum of somatic conditions, but not including mental distress, addiction, or fatigue, which were independent variables in our multivariate regression model. However, a significant association between somatic comorbidity and SF-36-MCS was not seen. Our comorbidity results are consistent with the results of several other studies [12, 58,59,60]. The population of PLHIV, is an ageing population with comorbidities [61, 62], and this must be addressed in the clinical setting to improve HRQOL in PLHIV.

In our study, low mental distress measured by the HSCL-25 was strongly associated with high SF-36-PCS and SF-36-MCS scores. Studies reported in the review by Degroote and colleagues show that depression and anxiety have a negative impact on HRQOL [10]. Another significant factor associated with HRQOL in our study was addiction, as measured with the DUDIT and AUDIT. Increased alcohol intake was significantly associated with lower SF-36-MCS, which suggests that alcohol consumption is associated with impaired mental HRQOL. By contrast, drug use was associated with improved physical HRQOL. This finding was not expected, and may reflect the exclusion of intravenous drug users with cognitive and mental disorders from this study. Few studies have focused on HRQOL and substance abuse in PLHIV [10]. In our study, fatigue was also associated with poorer mental and physical HRQOL, an observation that has been reported previously [63, 64]. Taken together, previous research and our findings highlight the importance of focusing on comorbidity/multimorbidity in the treatment of PLHIV.

Strengths and limitations

The strengths of our study are the high response rate, the fact that few participants were excluded, and that no variables were missing from the regression analyses. Further recruitment through scheduled clinical follow-ups and data collection by trained nurses likely increased the data accuracy as compared with data obtained from self-referral and self-report. The inclusion of PLHIV in Norway who do not speak the national language and people with poor reading and writing skills likely helped to improve the study’s external validity. Another strength of our study is that our study population is approximately 8% of the PLHIV residing in Norway. The northern and the southern counties in Norway have PLHIV from urban and rural settings with a similar socio-demographic characteristic as PLHIV in Norway [65].

The study’s cross-sectional design means that causality cannot be established. Another limitation is the number of variables that could be entered into the final regression model because we had 245 participants and, in turn, some estimates had wide confidence intervals. To limit the possible effects of confounding variables, all variables identified previously as confounders and independent variables were adjusted in the final regression model.

It might also be considered as a weakness that some of the questions included in the different PROMS, e.g. HSCL-25 and the questions included in the SF-36 MCS score, could be considered to be quite similar. However, to measure the concepts in focus of our study (e.g. anxiety/depression and the mental part of HRQOL) we choose to keep the original, well validated, questionnaires to do so. Another limitation in our study, is the fact that we did not include a validated questionnaire to measure stigma and discrimination in relation to living with HIV. However, we included two questions regarding openness.

Implications and future research

In the comparison between the PLHIV and the general population, patients reported worse scores for five of eight domains of the SF-36. The findings of this study contribute to knowledge about how age, employment status, somatic and psychological comorbidities, addiction, and fatigue are associated with HRQOL among PLHIV in a developed country. The study population was a well-treated population of PLHIV residing in Norway. Our findings emphasize the importance of focusing on comorbidities in the ageing PLHIV to optimize their HRQOL. Further studies using a longitudinal design are needed to increase the knowledge of HRQOL among PLHIV in the global setting.


We found poorer HRQOL among PLHIV in Norway than in the general population. HRQOL was influenced by several concurrent variables associated with poorer mental and physical HRQOL. It is important to focus on somatic and mental comorbidities in the delivery of health-care services for the ageing population of PLHIV to improve QOL, even among the virologically and immunologically stable group of PLHIV as in Norway.

Availability of data and materials

The datasets used and/or analysed during the current study are not publicly available because of the General Data Protection Regulation laws of Norway but are available from the corresponding author on reasonable request and with permission from the Norwegian Centre for Research Data.


  1. Lohse N, Obel N. Update of survival for persons with HIV infection in Denmark. Ann Intern Med. 2016;165(10):749–50.

    Article  PubMed  Google Scholar 

  2. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Grinsztejn B, Pilotto JH, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365(6):493–505.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Deeks SG, Lewin SR, Havlir DV. The end of AIDS: HIV infection as a chronic disease. Lancet. 2013;382(9903):1525–33.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Unicef WU: GLOBAL HIV/AIDS RESPONSE-Epidemic update and health sector progress towards Universal Access. In; 2011.

  5. UNAIDS: 90-90-90 An ambitious treatment target to help end the AIDS epidemic. In; 2017.

  6. Lazarus JVS-H, Barton SE, Costagliola D, Dedes N, Del Amo Valero J, Gatell JM, Baptista-Leite R, Mendao L, Porter K, Vella S, Rockstroh JK. Beyond viral suppression of HIV—the new quality of life frontier. BMC Med. 2016;14(1):94.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Pedersen KK, Eiersted MR, Gaardbo JC, Pedersen M, Gerstoft J, Troseid M, Nielsen SD. Lower self-reported quality of life in HIV-infected patients on cART and with low comorbidity compared with healthy controls. J Acquir Immune Defic Syndr. 2015;70(1):16–22.

    Article  PubMed  Google Scholar 

  8. Megari K. Quality of life in chronic disease patients. Health Psychol Res. 2013;1(3): e27.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cooper V, Clatworthy J, Harding R, Whetham J. Measuring quality of life among people living with HIV: a systematic review of reviews. Health Qual Life Outcomes. 2017;15(1):220.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Degroote S, Vogelaers D, Vandijck DM. What determines health-related quality of life among people living with HIV: an updated review of the literature. Arch Public Health. 2014;72(1):40.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Miners A, Phillips A, Kreif N, Rodger A, Speakman A, Fisher M, Anderson J, Collins S, Hart G, Sherr L, et al. Health-related quality-of-life of people with HIV in the era of combination antiretroviral treatment: a cross-sectional comparison with the general population. Lancet HIV. 2014;1(1):e32-40.

    Article  PubMed  Google Scholar 

  12. Engelhard EAN, Smit C, van Dijk PR, Kuijper TM, Wermeling PR, Weel AE, de Boer MR, Brinkman K, Geerlings SE, Nieuwkerk PT. Health-related quality of life of people with HIV: an assessment of patient related factors and comparison with other chronic diseases. AIDS (London, England). 2018;32(1):103–12.

    Article  PubMed  Google Scholar 

  13. Derogatis LRL, Rickels K, Uhlenhuth EH, Covi L. The Hopkins symptom checklist (HSCL): a self-report symptom inventory. Behav Sci. 1974;19(1):1–15.

    Article  CAS  PubMed  Google Scholar 

  14. Kaaya SF, Fawzi MC, Mbwambo JK, Lee B, Msamanga GI, Fawzi W. Validity of the Hopkins Symptom Checklist-25 amongst HIV-positive pregnant women in Tanzania. Acta Psychiatr Scand. 2002;106(1):9–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Beck AT, Steer RA, Garbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clin Psychol Rev. 1988;8(1):77–100.

    Article  Google Scholar 

  16. Beck AT, Steer RA. Beck depression inventory manual. San Antonio: Psychological Corporation; 1993.

    Google Scholar 

  17. Beck AT, Baruch E, Balter JM, Steer RA, Warman DM. A new instrument for measuring insight: the Beck Cognitive Insight Scale. Schizophr Res. 2004;68(2–3):319–29.

    Article  PubMed  Google Scholar 

  18. Raphael B, Lundin T, Weisaeth L. A research method for the study of psychological and psychiatric aspects of disaster. Acta Psychiatr Scand Suppl. 1989;353:1–75.

    Article  CAS  PubMed  Google Scholar 

  19. The Alcohol Use Disorders Identification Test.

  20. Berman AH, Wennberg P, Källmén H. Audit och Dudit – Identifiera problem med alkohol och droger. Stockholm: Gotia förlag; 2012.

    Google Scholar 

  21. Berman AH, Bergman H, Palmstierna T, Schlyter F. DUDIT. The drug use disorders identification test manual. Stockholm: Karolinska Institutet; 2002.

    Google Scholar 

  22. Suonpera E, Matthews R, Milinkovic A, Arenas-Pinto A. Risky alcohol consumption and associated health behaviour among HIV-positive and HIV-negative patients in a UK sexual health and HIV clinic: a cross-sectional questionnaire study. AIDS Behav. 2020;24(6):1717–26.

    Article  PubMed  Google Scholar 

  23. Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, Wallace EP. Development of a fatigue scale. J Psychosom Res. 1993;37(2):147–53.

    Article  CAS  PubMed  Google Scholar 

  24. Jackson C. The chalder fatigue scale (CFQ 11). Occup Med. 2014;65(1):86–86.

    Article  Google Scholar 

  25. Langseth R, Berg RC, Rysstad O, Sørlie T, Lie B, Skogen V: Prevalence and predictors of fatigue among people living with HIV in Norway. AIDS Care 2021;1–6.

  26. Lins L, Carvalho FM. SF-36 total score as a single measure of health-related quality of life: scoping review. SAGE Open Med. 2016;4:2050312116671725.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kvien TK, Kaasa S, Smedstad LM. Performance of the Norwegian SF-36 Health Survey in patients with rheumatoid arthritis. II. A comparison of the SF-36 with disease-specific measures. J Clin Epidemiol. 1998;51(11):1077–86.

    Article  CAS  PubMed  Google Scholar 

  28. Loge JH, Kaasa S, Hjermstad MJ, Kvien TK. Translation and performance of the Norwegian SF-36 Health Survey in patients with rheumatoid arthritis. I. Data quality, scaling assumptions, reliability, and construct validity. J Clin Epidemiol. 1998;51(11):1069–76.

    Article  CAS  PubMed  Google Scholar 

  29. Ware JE Jr, Kosinski MA, Keller SD. SF-36 physical and mental health summery scale: a user’s manual. Boston: New England Medical Centre, The Health Institute; 1994.

    Google Scholar 

  30. Ware JE Jr, Snow KK, Kosinski MA, Gandek MS. SF-36 Health survey manual and interpretation guide. Boston: New England Medical Centre, The Health Institute; 1993.

    Google Scholar 

  31. IBM: IBM SPSS Statistics for Windows, Version 27.0. In. Armonk, NY: IBM Corp; 2020.

  32. Garratt AM, Stavem K. Measurement properties and normative data for the Norwegian SF-36: results from a general population survey. Health Qual Life Outcomes. 2017;15(1):51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Jacobsen EL, Bye A, Aass N, Fosså SD, Grotmol KS, Kaasa S, Loge JH, Moum T, Hjermstad MJ. Norwegian reference values for the Short-Form Health Survey 36: development over time. Qual Life Res. 2018;27(5):1201–12.

    Article  PubMed  Google Scholar 

  34. Fayers PM, Machin D. Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. Chichester: Wiley; 2007.

    Book  Google Scholar 

  35. Whittaker R, Case KK, Nilsen Ø, Blystad H, Cowan S, Kløvstad H, van Sighem A. Monitoring progress towards the first UNAIDS 90-90-90 target in key populations living with HIV in Norway. BMC Infect Dis. 2020;20(1):451.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Berg RC, Gamst A, Said M, Aas KB, Songe SH, Fangen K, Rysstad O. True user involvement by people living with HIV is possible: description of a user-driven HIV clinic in Norway. J Assoc Nurses AIDS Care. 2015;26(6):732–42.

    Article  PubMed  Google Scholar 

  37. George S, Bergin C, Clarke S, Courtney G, Codd MB. Health-related quality of life and associated factors in people with HIV: an Irish cohort study. Health Qual Life Outcomes. 2016;14(1):115.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Rueda S, Raboud J, Mustard C, Bayoumi A, Lavis JN, Rourke SB. Employment status is associated with both physical and mental health quality of life in people living with HIV. AIDS Care. 2011;23(4):435–43.

    Article  PubMed  Google Scholar 

  39. Rüütel K, Pisarev H, Loit HM, Uusküla A. Factors influencing quality of life of people living with HIV in Estonia: a cross-sectional survey. J Int AIDS Soc. 2009;12:13.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Murri R, Fantoni M, Del Borgo C, Visona R, Barracco A, Zambelli A, Testa L, Orchi N, Tozzi V, Bosco O, et al. Determinants of health-related quality of life in HIV-infected patients. AIDS Care. 2003;15(4):581–90.

    Article  CAS  PubMed  Google Scholar 

  41. Ruiz Perez I, Rodriguez Baño J, Lopez Ruz MA, del Arco JA, Causse Prados M, Pasquau Liaño J, Martin Rico P, de la Torre LJ, Prada Pardal JL, Lopez Gomez M, et al. Health-related quality of life of patients with HIV: impact of sociodemographic, clinical and psychosocial factors. Qual Life Res. 2005;14(5):1301–10.

    Article  CAS  PubMed  Google Scholar 

  42. Degroote S, Vogelaers DP, Vermeir P, Mariman A, De Rick A, Van Der Gucht B, Pelgrom J, Van Wanzeele F, Verhofstede C, Vandijck DM. Socio-economic, behavioural, (neuro)psychological and clinical determinants of HRQoL in people living with HIV in Belgium: a pilot study. J Int AIDS Soc. 2013;16(1):18643.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Norström F, Waenerlund A-K, Lindholm L, Nygren R, Sahlén K-G, Brydsten A. Does unemployment contribute to poorer health-related quality of life among Swedish adults? BMC Public Health. 2019;19(1):457.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kowal J, Overduin LY, Balfour L, Tasca GA, Corace K, Cameron DW. The role of psychological and behavioral variables in quality of life and the experience of bodily pain among persons living with HIV. J Pain Symptom Manag. 2008;36(3):247–58.

    Article  Google Scholar 

  45. Fleming CA, Christiansen D, Nunes D, Heeren T, Thornton D, Horsburgh CR Jr, Koziel MJ, Graham C, Craven DE. Health-related quality of life of patients with HIV disease: impact of hepatitis C coinfection. Clin Infect Dis. 2004;38(4):572–8.

    Article  PubMed  Google Scholar 

  46. Préau M, Marcellin F, Carrieri MP, Lert F, Obadia Y, Spire B. Health-related quality of life in French people living with HIV in 2003: results from the national ANRS-EN12-VESPA Study. AIDS (London, England). 2007;21(Suppl 1):S19-27.

    Article  PubMed  Google Scholar 

  47. Gibson K, Rueda S, Rourke SB, Bekele T, Gardner S, Fenta H, Hart TA. Mastery and coping moderate the negative effect of acute and chronic stressors on mental health-related quality of life in HIV. AIDS Patient Care STDS. 2011;25(6):371–81.

    Article  PubMed  Google Scholar 

  48. Protopopescu C, Marcellin F, Spire B, Préau M, Verdon R, Peyramond D, Raffi F, Chêne G, Leport C, Carrieri MP. Health-related quality of life in HIV-1-infected patients on HAART: a five-years longitudinal analysis accounting for dropout in the APROCO-COPILOTE cohort (ANRS CO-8). Qual Life Res. 2007;16(4):577–91.

    Article  PubMed  Google Scholar 

  49. Liu C, Johnson L, Ostrow D, Silvestre A, Visscher B, Jacobson LP. Predictors for lower quality of life in the HAART era among HIV-infected men. J Acquir Immune Defic Syndr. 2006;42(4):470–7.

    Article  PubMed  Google Scholar 

  50. Jang HJ, Satre DD, Leyden W, Leibowitz A, Silverberg MJ. Mental and physical quality of life by age groups in people living with HIV. J the Assoc Nurses AIDS Care. 2019;30(5):500–10.

    Article  Google Scholar 

  51. Liu H, He X, Levy JA, Xu Y, Zang C, Lin X. Psychological impacts among older and younger people living with HIV/AIDS in Nanning, China. J Aging Res. 2014;2014: 576592.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Chen WT, Barbour R. Life priorities in the HIV-positive Asians: a text-mining analysis in young vs. old generation. AIDS Care. 2017;29(4):507–10.

    Article  PubMed  Google Scholar 

  53. Karkashadze E, Gates MA, Chkhartishvili N, DeHovitz J, Tsertsvadze T. Assessment of quality of life in people living with HIV in Georgia. Int J STD AIDS. 2017;28(7):672–8.

    Article  PubMed  Google Scholar 

  54. Balayan T, Sudfeld CR. Health-related quality of life among adults living with HIV: a cross-sectional survey in Armenia. AIDS Care. 2021;33(1):20–30.

    Article  PubMed  Google Scholar 

  55. Zhakipbayeva BT, Nugmanova ZS, Tracy M, Birkhead GS, Akhmetova GM, DeHovitz J. Factors influencing the quality of life in persons living with human immunodeficiency virus infection in Almaty, Kazakhstan. Int J STD AIDS. 2019;30(13):1318–28.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Kuznetsov S, Eremin A, Zaytseva E, Young B, Basova A, Paice A, Marin O, de Los Rios P, Okoli C. Treatment challenges and health conditions among people living with HIV with or without substance use disorder in the Russian Federation. AIDS care, 1–6 Advance online publication 2021.

  57. Balabanova Y, Coker R, Atun RA, Drobniewski F. Stigma and HIV infection in Russia. AIDS Care. 2006;18(7):846–52.

    Article  CAS  PubMed  Google Scholar 

  58. Rodriguez-Penney AT, Iudicello JE, Riggs PK, Doyle K, Ellis RJ, Letendre SL, Grant I, Woods SP. Co-morbidities in persons infected with HIV: increased burden with older age and negative effects on health-related quality of life. AIDS Patient Care STDS. 2013;27(1):5–16.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Zeluf-Andersson G, Eriksson LE, Schönnesson LN, Höijer J, Månehall P, Ekström AM. Beyond viral suppression: the quality of life of people living with HIV in Sweden. AIDS Care. 2019;31(4):403–12.

    Article  PubMed  Google Scholar 

  60. Nobre N, Pereira M, Roine RP, Sintonen H, Sutinen J. Factors associated with the quality of life of people living with HIV in Finland. AIDS Care. 2017;29(8):1074–8.

    Article  PubMed  Google Scholar 

  61. Althoff KN, Smit M, Reiss P, Justice AC. HIV and ageing: improving quantity and quality of life. Curr Opin HIV AIDS. 2016;11(5):527–36.

    Article  PubMed  PubMed Central  Google Scholar 

  62. De Francesco D, Sabin CA, Reiss P. Multimorbidity patterns in people with HIV. Curr Opin HIV AIDS. 2020;15(2):110–7.

    Article  PubMed  Google Scholar 

  63. Marcellin F, Préau M, Ravaux I, Dellamonica P, Spire B, Carrieri MP. Self-reported fatigue and depressive symptoms as main indicators of the quality of life (QOL) of patients living with HIV and Hepatitis C: implications for clinical management and future research. HIV Clin Trials. 2007;8(5):320–7.

    Article  PubMed  Google Scholar 

  64. Davis S. Clinical sequelae affecting quality of life in the HIV-infected patient. JANAC J Assoc Nurses AIDS Care. 2004;15(5):28S-33S.

    Article  PubMed  Google Scholar 

  65. BM. B: Årsrapport for 2015 med plan for forbedringstiltak. Oslo: NORHIV; 2016.

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We acknowledge the participants in this study for taking the time to complete the interviews and the nurses at the outpatient clinics at UNN and SSHF for supporting the research processes and implementation.


Open access funding provided by UiT The Arctic University of Norway (incl University Hospital of North Norway) This study was financially supported by the Norwegian Directorate of Health, Department of Infectious Diseases, Division of Internal Medicine, University Hospital of North Norway, and University of Tromsø–The Arctic University of Norway. This report presents independent research and the views expressed in this publication are those of the authors and not those of the funder of the project.

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All authors contributed to the study conception and design. VS was responsible for the data collection along with RL. Data analysis was performed by GER. The first draft of the manuscript was written by VS, GER, RL, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Vegard Skogen.

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All procedures performed in the study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Regional Committee for Medical Research Ethics (2011/1925 REK Nord). The participants received written information and provided informed consent. The data used in the study were anonymized.

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The authors declare that they have no competing interests.

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Skogen, V., Rohde, G.E., Langseth, R. et al. Factors associated with health-related quality of life in people living with HIV in Norway. Health Qual Life Outcomes 21, 14 (2023).

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  • HIV
  • Health-related quality of life
  • Short Form 36
  • Mental health
  • Somatic health