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Quality of life of people living with HIV/AIDS and on highly active antiretroviral therapy in Ethiopia a

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Kebede Abera , Teferi Gedif , Ephrem Engidawork & Tsige Gebre-Mariam

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School of Pharmacy , Addis Ababa University , King George VI Street, PO Box 1176, Addis Ababa, Ethiopia Published online: 19 May 2010.

To cite this article: Kebede Abera , Teferi Gedif , Ephrem Engidawork & Tsige Gebre-Mariam (2010) Quality of life of people living with HIV/AIDS and on highly active antiretroviral therapy in Ethiopia, African Journal of AIDS Research, 9:1, 31-40, DOI: 10.2989/16085906.2010.484560 To link to this article: http://dx.doi.org/10.2989/16085906.2010.484560

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ISSN 1608–5906 EISSN 1727–9445 doi: 10.2989/16085906.2010.484560

Quality of life of people living with HIV/AIDS and on highly active antiretroviral therapy in Ethiopia Kebede Abera, Teferi Gedif*, Ephrem Engidawork and Tsige Gebre-Mariam

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School of Pharmacy, Addis Ababa University, King George VI Street, PO Box 1176, Addis Ababa, Ethiopia *Corresponding author, e-mail: [email protected]; [email protected] The Amharic version of the Short Form-36 Health Survey (SF-36) was used to measure quality of life among patients on highly active antiretroviral therapy (HAART) at selected governmental hospitals in central and southern Ethiopia. The study was cross-sectional and used SF-36-specific software for automatic scoring of the form’s scales and dimensions. Pearson bivariate correlations showed moderate correlation between the SF-36 scales, ranging from 0.2673 between ‘general health’ and ‘vitality,’ to 0.8583 between ‘role physical’ and ‘role emotional.’ Cronbach’s-α was >0.70 for six out of eight multi-item scales, with values ranging from 0.6500 to 0.8860 for all scales, thus indicating good internal reliability of the Amharic version of the SF-36. The independent variables shown to positively affect mean scores were: duration of treatment, CD4 cell count, and adherence to doses of antiretrovirals. Participants treated for >12 months had higher mean scores for all domains than those who had been treated for ≤12 months. Likewise, those with a CD4 cell count >200 cells/mm3 had better mean scores for all scales except ‘social functioning’ and ‘mental health’ than those with counts ≤200. Participants adhering to treatment (in the last 15 days, according to self-report) had better mean scores for all scales except ‘role physical,’ ‘bodily pain’ and ‘vitality’ in comparison to those who were not adherent. The findings suggest that the Amharic version of the SF-36 is a valid and reliable health survey instrument for use in Ethiopia to assess the quality of life of people living with HIV/AIDS on HAART. Keywords: adherence, Africa, assessment methods, CD4 count, HAART, quality of life, questionnaire design, questionnaires, Short Form 36

Introduction Since the first evidence of HIV in Ethiopia was detected in 1984, AIDS has claimed the lives of millions and has left behind hundreds of thousands of orphans (Ministry of Health, 2005). In response to the epidemic, the government of Ethiopia issued an HIV/AIDS policy in 1998 and has subsequently established the HIV/AIDS Prevention and Control Office (HAPCO) and the National AIDS Council. In turn, these agencies have taken several steps to prevent the spread of HIV and to increase accessibility to care, treatment and support for people living with HIV or AIDS (PLHIV) in Ethiopia (Ministry of Health, 2007a). According to the most recent estimates, about one million people in Ethiopia (2.2% of the adult population) were living with HIV in 2008. In the same year approximately 290 000 people needed antiretroviral therapy (ART) (Ministry of Health, 2007b). Ethiopia’s national policy on the supply and use of ARVs was developed in 2002, and treatment guidelines for adults and adolescents were first issued in 2003, and then revised in 2007 (Ministry of Health, 2007c). Initially, a fee-based ART programme was started in 2003; this gave way to a free ART programme by early 2005, owing to a number of initiatives undertaken to expand the availability of ART in Ethiopia, including those by the Global Fund, PEPFAR, the Ethiopian–North American Health Professionals Association, the Clinton Foundation, and the

Ethiopian Red Cross Society. This was followed by an ART roll-out plan guided by the 2004–2008 national strategic plan for a multisectoral response to HIV/AIDS and the ‘road maps’ for accelerated access to ART (see Ministry of Health, 2004 and 2007a). Consequently, since August 2006, ART services have been decentralised and are available in health centres and hospitals in the country (Ministry of Health, 2007d and 2008). With a decentralised and free ART programme, the number of patients who have ever started ART has increased from 900 at the beginning of 2005, to more than 150 000 by June 2008; and the number of patients enrolled for ART has increased from 2 700 initially to about 5 000 per month (Ministry of Health, 2008). Moreover, the proportion of women and children on ART increased from 25% in 2005 to 55% in 2008, and the number of clients receiving HIV counselling and testing services has increased considerably, from 448 000 (between mid-2004 and mid-2005) to more than 4.5 million (between mid-2007 and mid-2008) (Ministry of Health, 2008). In industrialised countries, questionnaire-based methods are used with increasing frequency to assess the health status, also referred to as health-related quality of life (HRQOL), of people with chronic diseases, including HIV or AIDS. These methods of evaluation of HIV therapeutics and research on health services have been rarely used in resource-poor settings, such as in Africa. The intensity

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of HIV in Africa, together with increasing expectations for the availability of HIV treatment and services, suggests a need for the assessment of quality of life in African populations (Mast, Kigozi, Wabwire Mangen, Black, Sewankambo, Serwadda et al., 2004). Medical outcome cannot be described fully by measurement of clinical outcome and clinical indicators alone (Eshaghi, Ramezani, Shahsanaee & Pooya, 2006). Not only do many factors such as pain, apprehension, financial situation have an influence on an individual’s health status, but subjective wellbeing also affects an individual’s health (Bowden & Fox-Rushby, 2003). Measures of HRQOL are commonly used in determining the effects of medical and community-based health interventions by comparing the general health of different populations and assessing their health needs (Bowden & Fox-Rushby, 2003). One of the generic measures of HRQOL is the Short Form-36 Health Survey (SF-36), which was originally developed as a way of measuring the outcome of different types of healthcare delivery in the United States (see Ware, 1993). Since its introduction in the early 1990s, the SF-36 has been translated into various languages and is now widely used in many countries in the world (Fuh, Wang, Lu, Juang & Lee, 2000). The SF-36 is a patient-rated instrument that includes assessment of physical function (PF), social function (SF), limitations in role due to physical health (or ‘role physical’) (RP), limitations in role due to emotions (or ‘role emotional’) (RE), mental health (MH), vitality (VT), bodily pain (BP), and general health (GH) (refer to Box 1 for abbreviations). Two summary scores can be calculated: a mental-health component summary score (MHS) and a physical-health component summary score (PHS) (see Ware, 1993; Shiely, Bayliss, Keller, Tsai & Ware, 1996; Mittal, Ahern, Flaster, Maesaka & Fishbane, 2001). The SF-36 is a generic measure as opposed to one that targets a specific age group, disease group, or treatment group. Accordingly, the SF-36 has been useful in comparing general and specific populations, by comparing the relative burden of diseases, differentiating the health benefits produced by a wide range of treatments, and screening individual patients (Shiely et al., 1996). The SF-36 can be self-administered or it can be used by an interviewer to solicit the information. It takes about 5 to10 minutes to

Abera, Gedif, Engidawork and Gebre-Mariam

complete and contains 36 items that yield eight scales when scored (see Box 1) (Ware, 1993). Highly active antiretroviral therapy (HAART) has greatly reduced the morbidity and mortality associated with HIV-1 infection (Palella, Delaney, Moorman, Loveless, Fuhrer, Satten, Aschman & Holmberg, 1998). The long-term success of HAART is dependent on a high level of adherence to the regimen prescribed. Adherence greater than 95% is needed to achieve virologic success, especially for regimens containing protease inhibitors. As adherence decreases, viral loads may increase sharply in a dose-response effect (Paterson, Swindells, Mohr, Brester, Vergis, Squier, Wagener & Singh, 2000). HAART adherence is a critical component for therapeutic success in HIV infection, while improved quality of life (QOL) has been recognised as an important outcome of treatment (Cohen, Revicki, Nabulsi, Sarocco & Jiang, 1998; Franchi & Wenzel, 1998). The relationship between QOL and adherence to HIV medications has not been well studied (Mannheimer, Matts, Telzak, Chesney, Child, Wu & Friedland, 2005). HAART adherence is known to contribute to improved clinical outcomes in HIV cases, which could result in a better QOL. QOL may also influence adherence, as persons with better QOL may have a greater ability to adhere to their HAART regimen (Mannheimer et al., 2005; Parsons, Braaten, Hall & Robertson, 2006). This study focused on evaluating the effect of HAART adherence on QOL and checking the validity and reliability of the Amharic version of the SF-36 for assessment of QOL of PLHIV on HAART in Ethiopia. The findings could provide policymakers and clinicians valuable information on the qualitative outcomes of HAART. Methods A cross-sectional study was conducted between August and October 2007 in Yirgalem, Hawassa and Shashemene hospitals, located in central and southern Ethiopia. These hospitals were selected because high numbers of patients had been treated in these facilities: at the time of the study, there were 1 001, 623 and 594 PLHIV on HAART in Yirgalem, Hawassa and Shashemene hospitals, respectively. Prior to data collection, a two-day training workshop was organised for the data collectors; this included an overview

Box 1: Abbreviations for measures of health-related quality of life (HRQOL) on the Short Form-36 Health Survey (SF-36) questionnaire (see Ware, 1993) The SF-36 contains 36 items that yield eight domains (scales) when scored: BP = bodily pain GH = general health MH = mental health PF = physical function RE = limitation in role due to emotions RP = limitation in role due to physical health SF = social function VT = vitality. Two summary scores can be calculated: MHS = mental-health component summary score PHS = physical-health component summary score.

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of the aim of the study and a detailed collective review of the research tools. The training was followed by pre-testing of the tools at the three hospitals’ ART units, among patients who were not involved in the study. Both the data collectors and the investigators discussed lessons learnt from pre-testing to help modify the tools and clarify some of the associated issues. Data on sociodemographics, psychosocial variables, and clinical parameters were collected using a pre-tested questionnaire and hospital records. In addition, the SF-36 was used to assess the QOL of the patients in the study. The self-report method with a 15-day recall period was employed for determining the participants’ adherence to their doses of ARVs. Optimal adherence was defined as ≥95% of the prescribed doses were taken by the patient. Adherence to schedules of ARVs was determined by using a subjective measure with four response categories: adhered all the time, adhered most of the time, adhered some of the time, or never adhered to the medications schedules. Eligible participants were selected using the following criteria: ARV users age 18 years and above, who were on HAART for at least three months preceding the survey time (as it is assumed that QOL scores for chronic-disease patients on drug treatment will change significantly after three months: Landgraf & Abety, 1996). Based on these criteria, a single population proportion formula was used to determine sample size (World Health Organization, 2001), thus determining a sample size of 422. Next, 200 participants from Yirgalem hospital, 111 from Hawassa hospital, and 111 from Shashemene hospital were selected. The selection of participants was made by systematic random sampling proportional to the number of PLHIV on HAART found at each study site. To perform the SF-36 measurements, the questionnaire was reformatted to make it more user-friendly without modifying the content of the original questions or the answer options. Following the standard procedures set by the developers of the instrument (see Ware, 1993), the original SF-36 was translated into Amharic. The translation tried to replicate the original instrument as much as possible for purposes of cross-cultural comparisons and to adapt the instrument to the local socio-economic and cultural setting. For such purposes, some of the questions in the original SF-36 were systematically modified during translation. One example is that the question that asks about ‘climbing stairs’ in the original SF-36 was translated to ‘climbing hills’ in the Amharic version. Each translation was reviewed by two independent healthcare providers who were proficient in both English and Amharic, and the accuracy of the translations was certified. There were no missing responses to the SF-36. All participants were able to answer the SF-36 questions within 5 to 10 minutes.

Data entry, cleaning and analysis The data were entered using SF-36 software (MS Excel 2003) and analysed according to the standard method for the SF-36 instrument (see Ware, 1993). Automatic scoring of the SF-36 scales and dimensions were performed using the software program designed by Zadeh, Kopple, Block & Humphreys (2001). Descriptive, bivariate and multivariate analyses were performed using SPSS, version 11.05. Multivariate logistic regression was used to control for possible confounders and to examine the association between the SF-36 scores and the independent variables. Percentage adherence from self-report (given a 15-day recall period) was calculated using the following formula (see Chesney, Ickovics, Chambers, Gifford, Neidig, Zwickl & Wu, 2000):

Study variables The independent variables were: sex, age, level of education, marital status, employment status, disclosure of HIV status, source of social support, CD4 cell count, duration of treatment and adherence to HAART. The dependent variables were the eight SF-36 QOL scales (refer to Box 1).

Validity and reliability of the SF-36 Amharic version The performance of the Amharic version of the SF-36 was evaluated by examining feasibility, reliability and evidence of validity. The feasibility of conducting measureof-QOL interviews in an Ethiopian setting was evaluated by examining the presence of missing item responses, interviewer-reported acceptability, and the time and ease of

% Adherence =

No. of doses patient should have taken – No. of doses missed × 100 No. of doses patient should have taken

Ethical considerations Approval was obtained from the School of Pharmacy’s ethics review committee at Addis Ababa University and the National Health Research Ethics Review Committee (ref. no. RDHE/95-77-2007). Written informed consent was obtained from each study participant after they were informed of the purpose, benefits and possible risks associated with the study. Results Demographics, psychosocial variables and clinical parameters About 56% of the study participants were females and 44% were males; mean age was 32.3 years (SD = 7.24). Married participants accounted for 38.4%, and unmarried ones 24.6%. Education-wise, 47.9% had attended junior secondary and secondary school (grades 7 to 12) and 22.7% had attended primary school (grades 1 to 6). The majority of the participants were unemployed (59%) and had disclosed their HIV status (69.9%). Regarding support, 44.8% reported getting support from family and 39.1% from non-family members. The values for the average and median CD4 cell counts of the participants at the initiation of HAART were 142 (SD = 65.67) and 143 cells/mm 3, respectively, and those values for the groups’ most-recent CD4 cell counts were 312 (SD = 146.29) and 290 cells/ mm3. Around 85% of the participants had been on treatment for 12 months of HAART had higher mean scores for all domains than

Table 2: Psychometric results of data from the SF-36 and the mean scores on the SF-36 scales (see Box 1 for abbreviations)

Scales PF RP BP GH VT SF RE MH PHS MHS

No. of items

Cronbach’s-α

10 4 2 5 4 2 3 5 – –

0.8474 0.8860 0.7795 0.6298 0.6500 0.7277 0.8716 0.7078 – –

Total participants (n = 422) Mean (SD) 86.67 (16.94) 79.26 (34.71) 85.26 (20.26) 74.94 (19.67) 68.77 (16.95) 88.96 (18.92) 76.70 (37.72) 64.10 (16.38) 78.86 (16.19) 74.72 (15.45)

Females (n = 238) Mean (SD) 84.39 (18.58) 75.31 (36.99) 83.36 (21.52) 74.99 (20.39) 67.77 (17.24) 88.37 (19.47) 73.52 (40.00) 63.22 (16.70) 77.05 (17.40) 73.61 (16.52)

Males (n = 184) Mean (SD) 89.61 (14.05) 84.37 (30.87) 87.71 (18.27) 74.88 (18.75) 70.08 (16.53) 89.73 (18.20) 80.81 (34.23) 65.23 (15.93) 81.20 (14.19) 76.15 (13.86)

Table 3: Mean scores on the SF-36 scales in relation to selected sociodemographic and psychosocial variables (see Box 1 for abbreviations)

Sex: Males Females Age (years): ≤35 36+ Education: Uneducated Grades 7–12 Marital status: Married Unmarried Employment: Employed Unemployed HIV disclosure: ‘Yes’ ‘No’ Support from family: ‘Yes’ ‘No’ Support from outside family: ‘Yes’ ‘No’

PF

RP

BP

GH

VT

SF

RE

MH

PHS

MHS

89.61 84.39

84.37 75.31

87.71 83.36

74.88 74.99

70.08 67.77

89.73 88.37

80.81 73.52

65.23 63.22

81.20 77.05

76.15 73.61

87.21 85.13

80.04 77.04

85.04 85.88

74.82 75.28

68.79 68.72

87.93 91.89

75.97 78.78

63.10 66.94

79.08 78.24

74.14 76.34

80.11 87.82

60.22 80.19

81.56 84.87

75.43 77.05

66.02 69.08

88.45 88.31

61.34 77.40

65.09 63.84

72.54 79.69

71.29 75.16

87.37 88.17

79.78 87.98

85.11 87.07

73.91 77.94

70.21 73.36

90.58 89.74

74.50 84.62

66.37 64.50

79.17 82.78

75.16 78.04

89.47 84.71

82.80 76.80

85.98 84.75

77.20 73.36

70.14 67.83

89.65 88.49

79.78 74.57

66.70 62.29

80.98 77.38

76.68 73.35

85.79 88.70

73.72 92.12

83.79 88.66

76.17 72.07

68.44 69.56

88.38 90.33

70.85 90.29

64.69 62.74

77.47 82.07

73.74 76.99

88.25 85.38

84.39 75.10

86.26 84.45

75.30 74.65

70.13 67.68

89.03 88.91

81.68 72.66

66.47 62.18

80.74 77.33

76.58 73.21

83.03 89.00

67.27 86.96

81.93 87.39

75.24 74.74

65.39 70.95

88.32 89.38

65.44 83.93

62.95 64.84

74.46 81.68

71.49 76.78

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Abera, Gedif, Engidawork and Gebre-Mariam

status were shown to have the same effect on the measured parameters. Married participants as well as those that had attained a secondary school education had better scores than the unmarried and uneducated participants in all scales except for SF and MH. Concerning the patient’s disclosure of HIV status to others, except for the GH and MH scales, those that had not disclosed their status to others had better mean scores than those that had disclosed. Employed participants and those that claimed to have support from family members had better mean scores for all SF-36 scales than those who were unemployed and those that did not get support. On the other hand, those who did not get support from non-family members had better mean scores for the SF-36 scales than those who were getting support, except for the GH scale (Table 3).

those with a duration of ≤12 months, with the exception of the ‘mental health’ (MH) scale. In the multivariate analysis, significant positive associations were observed between duration of treatment and scores of RP and RE (see Table 5). Concerning most recent CD4 cell count, as shown in Table 5, those participants with a CD4 cell count of >200 cells/mm3 had better mean scores in all domains except for SF and MH than those with a count of ≤200. In the multivariate analysis, CD4 cell count was positively associated with scores of ‘bodily pain’ (BP), RE and VT. Those who were adherent to their doses of ARVs had better mean scores than those who did not adhere, apart from scores of BP, RP and VT. Multivariate analysis showed an association between adherence to doses of ARVs and the PHS score. Moreover, those that always adhered to their schedule of ARVs had better mean scores than those that never adhered, with the VT scale being an exception. Adherence to schedule of ARVs was independently associated with scores of BP, GH, MH, PF, RE, RP, SF, MHS and PHS (see Table 6). Demographic factors were found to influence the different domains analysed to a varied extent. While participants aged ≤35 had better mean scores for scales of PF, RP and PHS, those aged 36 and above scored better for scales of GH, SF, RE, MH and MHS (see Table 3). Males were found to have better mean scores in all domains except the GH scale than did the females. Marital status and education

Discussion The SF-36 is a generic instrument to measure quality of life (QOL) and it has been widely tested in cross-cultural contexts (Ware, 1993). It has been used successfully in several countries for assessment of quality of life (QOL) of PLHIV (Call, Klapow, Stewart, Westfall, Mallinger, DeMasi et al., 2000). The validity and reliability of the Amharic version of the SF-36 has been previously demonstrated for assessing QOL of people suffering from mental illness in central rural Ethiopia (Kebede, Alem, Shibre, Negash,

Table 4: Pearson’s correlation coefficients for inter-scale association of the SF-36 scales (see Box 1 for abbreviations) Scale PF RP BP PF 1.0000 RP 0.6576* 1.0000 BP 0.5987* 0.5656* 1.0000 GH 0.4520* 0.3383* 0.4302* VT 0.2714* 0.2989* 0.3322* SF 0.5099* 0.3921* 0.6139* RE 0.5849* 0.8583* 0.5394* MH 0.3505* 0.2770* 0.2827* *Correlation is significant at the level of 0.01 (2-tailed test)

GH

VT

SF

RE

MH

1.0000 0.2673* 0.4423* 0.3583* 0.3878*

1.0000 0.3135* 0.2844* 0.4369*

1.0000 0.3789* 0.4227*

1.0000 0.2868*

1.0000

Table 5: Association between mean scores on the SF-36 scales and clinical parameters (bold type denotes reference group for odds ratio analysis) (see Box 1 for abbreviations) Clinical parameters Duration of treatment (months) (n = 364) Most recent CD4 cell count (cells/mm3) (n = 259) 3–12 12+ AOR 95% CI ≤200 >200 AOR 95% CI 83.95 87.65 0.566 PF 84.67 88.71 0.645 (0.250–1.662) (0.169–1.898) RP 72.33 86.83 0.337 75.44 82.43 0.614 (0.196–0.581)* (0.288–1.306) BP 83.88 88.64 0.453 82.91 86.85 0.246 (0.172–1.193) (0.078–0.775)** GH 74.18 75.44 0.842 71.79 75.11 0.626 (0.440–1.608) (0.260–1.504) VT 68.17 70.84 1.522 67.46 69.46 0.427 (0.853–2.716) (0.192–0.950)** SF 87.19 91.24 0.449 89.77 89.18 0.703 (0.200–1.009) (0.245–2.011) RE 70.22 84.65 0.399 73.68 77.74 0.277 (0.233–0.686)* (0.138–0.554)* MH 64.08 64.02 0.660 63.23 63.27 0.907 (0.386–1.131) (0.428–1.920) PHS 76.53 81.98 1.952 76.18 80.18 0.490 (0.870–4.379) (0.174–1.379) MHS 72.79 77.26 1.256 73.19 74.95 1.637 (0.560–2.817) (0.536–5.001) *p < 0.005; **p < 0.05; AOR = adjusted odds ratio; CI = confidence interval SF-36 scales

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Table 6: Association between SF-36 mean scores and adherence to HAART (bold type denotes reference group for odds ratio analysis) (see Box 1 for abbreviations) Adherence to HAART Adherence to doses of HAART (n = 422) Adherence to schedules of HAART (n = 422) Non-adherent Adherent AOR 95% CI Never adhere Always adhere AOR 95% CI 68.12 88.28 0.023 PF 81.90 87.02 0.687 (0.000–270.11) (0.003–0.176)* RP 80.17 79.20 0.627 48.43 76.30 0.066 (0.193–2.041) (0.015–0.288)* BP 86.03 85.21 4.135 66.50 86.37 0.087 (0.089–191.770) (0.015–0.508)** GH 71.59 75.19 1.941 54.68 78.20 0.081 (0.194–19.387) (0.023–0.288)* VT 70.17 68.68 0.376 63.12 70.26 0.316 (0.062–2.265) (0.095–1.053) SF 85.00 89.26 1.123 66.56 90.87 0.087 (0.144–8.756) (0.020–0.373)* RE 75.93 76.76 0.648 43.68 74.19 0.105 (0.131–3.193) (0.029–0.376)* MH 58.07 64.55 0.559 48.75 66.68 0.127 (0.238–1.314) (0.039–0.419)* PHS 77.83 78.94 0.006 59.93 79.76 0.025 (0.000–0.532)* (0.004–0.154)* MHS 72.13 74.91 0.549 55.43 76.07 0.035 (0.112–2.701) (0.007–0.176)* *p < 0.005; **p < 0.05; AOR = adjusted odds ratio; CI = confidence interval

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SF-36 scales

Deyassa & Beyero, 2004). This study has demonstrated that the Amharic version of the SF-36 is a reliable and valid instrument for the assessment of QOL in HIV/AIDS patients. With an interview-administered approach, 100% completion of the questionnaire was achieved for all patients, including those that lived in rural areas and had a poor educational background. Moreover, a satisfactory internal consistency of the SF-36 was documented in this study, with Cronbach’s-α exceeding 0.70 for six out of eight of the SF-36 scales. This study revealed that certain sociodemographic characteristics, namely male gender, younger age, being educated and being employed, were associated with better QOL among PLHIV on HAART. Mean values of the PHS scores declined with age, as compared with values related to MHS scores. Similar findings relating to SF-36 summary scores have been reported in other cross-sectional studies (e.g. Gandek, Ware, Aaronson, Apolone, Bjorner, Brazier et al., 1998; Bowling, Bond, Jenkinson & Lamping, 1999; Zadeh et al., 2001; Li, Wang & Shen, 2003; Eshaghi et al., 2006; Failde & Soto, 2006). The patients’ decline in physical health could be attributed to the natural aging process, although this reasoning has been challenged (Rowe & Kahn, 1987). This finding also supports the discriminant construct validity of the Amharic version of the SF-36 used in this study. The present study also pointed out differences between men and women on the SF-36 scores. On each scale a higher proportion of men attained the top score (except for the GH score). This is in line with the findings of many other studies (e.g. Sullivan & Karlsson, 1998; Aaronson, Muller, Cohen, Essink-Bot, Fekkes, Sanderman et al., 1998). The reasons for these differences are unclear, though Derogatis & Derogatis (1996) reported that women had a higher incidence of psychological symptoms and greater psychological distress than did men, and Wiklund, Herlitz, Johansson, Bengtson, Karlsson & Persson (1993) found that female patients with physical illnesses had worse scores than those of males in terms of symptoms and wellbeing. The employed participants also had better mean scores for all SF-36 scales. This is similar to findings from a study in Brazil among HIV patients initiating HAART (Campos,

César & Guimarães, 2009). This result may be attributable to the fact that employment status provides not only financial benefits but also a structure for social support and role identity. Notably, deterioration of ability to work after HIV infection is one factor influencing an HIV/AIDS patient’s QOL. Being educated also had a positive association with the scores measuring QOL, possibly because education is a means for getting better employment, which in turn is shown to positively influence QOL. This study also examined the impact of psychosocial factors (e.g. social support and HIV-status disclosure) on the patients’ QOL scores. We found that having support from family members was associated with the patients’ improved scores for QOL. A similar finding was reported by Swindells, Mohr, Justis, Berman, Squier, Wagener & Singh (1999) in a multiple-site longitudinal study of 138 HIV-infected patients. Additionally, in a cross-sectional study of 82 women living with HIV, Cowdery & Pesa (2002) demonstrated that social support was significantly associated with mental health, general health perception, and experience of bodily pain. By contrast, in this study, disclosure was noted to be negatively associated with the SF-36 scores of GH, PF, PR, RE, RP SF, VT, MHS and PHS. This might be due to the negative impact of disclosing one’s HIV status to others as it could result in stigma and discrimination (Meng, Li, Liu, Chen, Song & Qian, 2008). The current goals of therapy for HIV-infected individuals focus on the traditional outcomes of increased life expectancy, decreased disease-associated mortality, and decreased occurrence of opportunistic infections. However, as we shift toward a new paradigm in the treatment of HIV infection — focusing on the long-term management of a chronic illness — emphasis must be placed on patient-based outcomes (Call et al., 2000). Improvement of the QOL of patients receiving HAART is one of the main objectives of the treatment, as mentioned in therapeutic guides published throughout the world (Call et al., 2000). QOL has been shown to improve with HAART (Nieuwkerk, Gisolf, Reijers, Lange, Danner & Sprangers, 2001), though the effect may differ depending on the person’s baseline QOL (Nieuwkerk, Hillebrand, Vriesendorp, Frissen, De Wolf, Lange & Sprangers, 2002). While some aspects of QOL have been shown to have an

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impact on HAART adherence, little is known about the effect of HAART adherence on QOL. Limited data suggest that adherence to treatment affects QOL, but it is not known what degree of adherence is required to achieve QOL benefits (Mannheimer et al., 2005). To gain a better understanding of QOL in outpatient HIV-clinic settings and the relationship between QOL and HAART adherence, this study examined QOL and self-reported adherence among HAART-experienced participants. As a result, in multivariate analysis, taking the SF-36 scales as the dependent variable, it was observed that adherence to doses of HAART had a positive association only with PHS scores. On the other hand, adherence to schedules of ARVs had a positive association with scores for all SF-36 scales, with the association being significant in multivariate analysis. PLHIV on HAART for >12 months treatment duration experienced higher mean scores in seven of the eight SF-36 scales as well as the two summary scales. The likely explanation could relate to the patients’ better virological response, improvement in clinical variables, and adaptation to the side effects of HAART, which can all result in better QOL. This is in accord with the findings of Mannheimer et al. (2005). Here, the HAART patients with a CD4 cell count >200 were shown to have better mean scores in all SF-36 scales and the two summary scales, with the exception of the SF and MH scales. In multivariate analysis, significant associations were seen in the BP and VT scales. This result is similar to the findings of Call et al. (2000) and Mannheimer et al. (2005). While informative, this study has some limitations. The SF-36 is a general HRQOL measure and may not capture all HIV-specific dimensions of HRQOL, though studies of both generic and disease-specific HRQOL measures in populations of HIV-infected individuals have revealed several consistent observations. First, these measures appear to be associated with clinical symptoms of HIV disease (Wachtel, Piette, Mor, Stein, Fleishman & Carpenter, 1992; Wu, Hays, Kelly, Malitz & Bozzette, 1997). Next, these measures appear to be responsive to adverse-event occurrences. Finally, there is a correlation between HRQOL measures and most markers of HIV-disease severity (O’Keefe & Wood, 1996; Smith, Feldman, Kelly, DeHovitz, Chirgwin & Minko, 1996). It should also be noted that this study was not longitudinal and could not identify the long-term effect of HAART on QOL and hence on the SF-36 scores among the participants. Above all, baseline QOL data for the study participants was not available, and it could not be identified how much the QOL of the patients had changed since starting HAART. Lack of SF-36 scores for a HAART-naive group for comparison is also another limitation of the study. One more limitation is the concern that self-report may overestimate adherence to treatment (Chesney et al., 2000; Friedland & Andrews, 2001; Osterberg & Blaschke, 2005). Despite this concern, studies in developed countries have demonstrated a strong association between self-reported adherence to medication and QOL in HIV-infected patients (Mannheimer et al., 2005). In addition, the large sample size of the present study can, at least in part, offset the aforementioned limitations.

Abera, Gedif, Engidawork and Gebre-Mariam

Conclusions and recommendations This study clearly revealed that quality of life (QOL) of PLHIV on HAART has an association with sociodemographic and psychosocial factors as well as clinical parameters. Hence, understanding such an association can be used in alerting clinicians to the factors that should be assessed and modified early in the course of an HIV/AIDS patient’s treatment plan. Moreover, the QOL of patients could be increased over time through educational and counselling programmes for PLHIV and their family members, by enhancing support by family members as well as creating employment opportunities for PLHIV. It is also desirable to carefully consider clinical factors when developing interventions to improve the health-related quality of life (HRQOL) of PLHIV on HAART. The present study also showed that the Amharic version of the SF-36 is a valid and reliable health survey instrument to assess the QOL of PLHIV on HAART. Since multiple factors had been shown to be associated with QOL, the level and extent to which clinical parameters, psychosocial variables, and sociodemographic factors influence the HRQOL of PLHIV on HAART could be assessed using the SF-36 in the Ethiopian set-up. Such studies would enable analysis of the impact of sickness and the complex therapeutic strategies used and help in evaluating which dimensions of a patient’s life are most affected, and thereby to establish possible associations with different clinical, therapeutic and psychosocial factors. Future longitudinal research is recommended to strengthen the use of the SF-36 instrument for assessing the QOL of HIV-infected patients in an Ethiopian setting. Acknowledgments — This study was sponsored by the graduate program at Addis Ababa University and the School of Pharmacy– SIDA/SAREC adherence project.

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