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Health-related quality of life in a sample of HIVinfected South Africans Karl Peltzer & Nancy Phaswana-Mafuya Published online: 11 Nov 2009.

To cite this article: Karl Peltzer & Nancy Phaswana-Mafuya (2008) Health-related quality of life in a sample of HIVinfected South Africans, African Journal of AIDS Research, 7:2, 209-218, DOI: 10.2989/AJAR.2008.7.2.6.523 To link to this article: http://dx.doi.org/10.2989/AJAR.2008.7.2.6.523

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Health-related quality of life in a sample of HIV-infected South Africans Karl Peltzer1* and Nancy Phaswana-Mafuya2 Social Aspects of HIV/AIDS and Health, Human Sciences Research Council, Private Bag X41, Pretoria 0001, South Africa, and the University of the Free State, PO Box 339, Bloemfontein 9300, South Africa 2 Human Sciences Research Council, and the University of the Western Cape, 10 Nederburgh Crescent, Tulbagh, Port Elizabeth 6025, South Africa * Corresponding author, e-mail: [email protected]

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The study aims to assess the health-related quality of life and HIV symptoms of a sample of people living with HIV (PLHIV) in South Africa. The sample included 607 PLHIV from all districts of the Eastern Cape Province, recruited either through a health facility, from the community through key informants, or through support groups. At the time of the study, 66% of the respondents reported having been given an AIDS diagnosis (advanced stage of HIV disease), 48% were on antiretroviral therapy (ART), and 35% were receiving a disability grant. The findings indicate a low degree of overall quality of life, with a mean score of 13.4 on the WHOQOL-HIV measure. Among the WHOQOLHIV BREF subscales, logistic regression identified spirituality, environment, psychological health, and level of independence as predictors for overall quality of life. Among medical variables and HIV symptoms, CD4 cell count and having fewer HIV symptoms but not an AIDS diagnosis were identified as predictors for overall quality of life; among socio-economic variables, having sufficient food and a higher educational level were identified as predictors. The results highlight the need for better access to psychosocial support and medical services for PLHIV in South Africa, as well as the need to consider a patient’s general health perceptions during the course of ART. Keywords: antiretroviral treatment, assessment methods, HIV symptoms, people living with HIV/AIDS, psychosocial aspects, self-reporting, socio-economic factors, statistical analysis, questionnaires

Introduction HIV and AIDS is one of the main challenges facing South Africa today. Of approximately 39.5 million people living with HIV worldwide in 2006, more than 63% were estimated to be from sub-Saharan Africa (UNAIDS, 2007). About 5.54 million people were estimated to be living with HIV in South Africa in 2005, with 18.8% of the adult population (aged 15–49) and about 12% of the general population infected. Women are disproportionately affected, accounting for approximately 55% of HIV-positive people in South Africa (Department of Health [South Africa], 2007). Women in the age group 25–29 are the worst affected, with HIV prevalence among them as high as 40%, while among men peak prevalence occurs in older age groups (Department of Health, 2007). South Africa instituted antiretroviral therapies (ART) in the public health sector in 2003, although HIV prevention remains a public health priority. People living with HIV can now expect to live longer, and while they continue to pursue the normal activities of daily living, their health-related quality of life is expected to improve. Only two studies have investigated health-related quality of life (HRQoL) among people living with HIV or AIDS (PLHIV) in an urban setting in South Africa, and little is known about HRQoL among PLHIV in rural, resource-poor settings in South Africa. Hughes, Jelsma, Maclean , Darder & Tinise (2004) found that, by self-report, HRQoL was severely comprised in

people in WHO clinical stages 3 or 4 of disease, while limitations in four domains: mobility, usual activities, pain/discomfort and anxiety/depression, constituted major problems for PLHIV. Jelsma, Maclean, Hughes, Tinise & Darder (2005) investigated HRQoL of individuals receiving highly active antiretroviral therapy (HAART) in Cape Town and found that even in a resource-poor urban environment HRQoL was greatly improved by HAART, and the possible side effects of antiretroviral drugs seemed to have a negligible impact on the wellbeing of the subjects. Health-related quality of life (HRQoL) is a multidimensional concept that includes global health perspectives, symptom status, functional status, biological and physical variables, individual and environmental characteristics, and general health perceptions (Wilson & Cleary, 1995). Many different instruments have been developed to describe and quantify HRQoL. These include HIV-specific instruments such as the Medical Outcomes Study–HIV (Smith, Feldman, Kelly, DeHovitz, Chirgwin & Minkoff, 1996), the HIV Overview of Problems-Evaluation System (HOPES) (O’Leary, Ganz, Wu, Coscarelli & Petersen, 1998) and the World Health Organization’s Quality of Life Instrument module (WHOQOL) for international assessment of HIV/ AIDS (The WHOQOL-HIV Group, 2003). O’Connell, Saxena & Skevington (2004) describe the analysis of the WHOQOL-HIV field-test instrument, which was given

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to 1 334 PLHIV from six culturally diverse centres (i.e. Australia, Brazil, Italy, Thailand, Ukraine and India). The instrument demonstrated good psychometric properties (alpha values for the domains were between 0.70 and 0.90) and good discriminant validity, with poorest quality of life (QoL) measured among those who reported they felt least healthy. Men had tended to report poorer physical wellbeing and level of independence, while women had more often reported poorer environment, social support and spirituality. Older people (aged 34+) had demonstrated poorer QoL according to measures of physical wellbeing and levels of independence, while younger people had scored lower in the domains of environmental and spiritual wellbeing. Thus, the WHOQOL-HIV instrument provides a promising means for QoL assessment for PLHIV in diverse cultural settings. Wilson & Cleary (1995) described a symptom as a person’s perception of an abnormal physical, emotional or cognitive state. Symptoms are perceived indicators of change in an individual’s normal functioning as experienced by that person (Hegyvary, 1991). Persons infected with HIV may report myriad symptoms that indicate disease progression. For example, in a study describing the symptoms experienced by 743 men and women living with HIV or AIDS, from Botswana, Lesotho, South Africa and Swaziland, the patients commonly reported constitutional, neurological, digestive, pulmonary, cognitive, musculo-skeletal, genitourinary, and gynecological symptoms — symptoms involving most major organ systems — and they also reported severe psychological distress (Makoae, Seboni, Molosiwa, Moleko, Human, Sukati & Holzemer, 2005). The aim of this study was to explore HRQoL and self-reported HIV symptoms in a group of PLHIV residing in resource-poor communities in the Eastern Cape Province, South Africa. It has a population size of approximately seven million, representing 16% of the South African population. The non-urban population amounts to nearly 4 100 000, and dense concentrations of rural and peri-urban settlements occur in various districts and areas (Statistics South Africa [StatsSA], 2005). The province is largely rural, with two-thirds of the population living outside the urban areas (StatsSA, 2004). Although, since 1994, there have been general improvements in terms of households’ access to electricity, flush or chemical toilets, and regular refuse removal, the Eastern Cape remains one of the country’s poorest provinces and has the highest rate of unemployment (StatsSA, 2004). Women and children generally make up the majority of the population in the rural areas; in 2001, almost 54% of the total population were women (StatsSA, 2004). The age distribution of the population shows relatively few young adults in the province compared to the national pattern, and over one-third of the province’s population are children under 15 years old (StatsSA, 2004). Since 1994, the healthcare system has been undergoing transformation. There has been a concerted effort to strengthen and upgrade the primary healthcare (PHC) system. Access to the basic package of PHC facilities has improved, and more integrated services are being provided. PHC services are rendered through 47 district hospitals and 18 provincially aided hospitals. There is one hospital managed by a private company and there are 751

Peltzer and Phaswana-Mafuya

provincially administered clinics, besides 256 municipal clinics and 32 community health centres (Eastern Cape Department of Health [ECDoH], 2007). However, people living in areas of the former homelands typically have difficulty accessing PHC services because of poor roads and lack of transportation (Skinner, Mfecane, Gumede, Henda & Davids, 2005). The strengthening of the provincial health system is important for the integration and delivery of a comprehensive national HIV/AIDS programme that is responsive to the needs of the population. The current range of HIV-prevention strategies includes voluntary counselling and testing (VCT), prevention of mother-to-child transmission (PMTCT) services, post-exposure prophylaxis (PEP), syndromic management of sexually transmitted infections, tuberculosis management, provision of barrier methods (free condoms), lifeskills training programmes, and an information, education and communication campaign that is in line with the national HIV-prevention strategy (ECDoH, 2007). Some of these strategies are critical entry points for HIV treatment and care interventions. In 2006 the Eastern Cape Department of Health estimated that 21 294 adults and 1 220 paediatric patients were receiving ARV therapy (ECDoH, 2006). Methods Sample and procedures The study involved 607 PLHIV sampled from all districts of the Eastern Cape Province: Amathole (81; 13.3%), Cacadu (83; 13.7%), Chris Hani (120; 19.8%), Nelson Mandela (80; 13.2%), OR Tambo (120; 19.8%), Alfred Nzo (82; 13.5%) and Ukhalamba (41; 6.8%); they were recruited through convenience sampling by other PLHIV at health facilities (42%), key informants in the community (44.1%) and support groups (13.9%). Fifteen locally based PLHIV (males and females) with a matric qualification were appointed and trained as data collectors to conduct face-to-face interviews in the districts. The 15 interviewers were asked to recruit respondents from their own local environment. Those interviewers who worked in a clinic or who were a member of a support group at a clinic consecutively approached PLHIV known to them at the different clinic sites. In case of recruitment through key informants, the interviewers contacted someone in their community who was well known to them. Also, the interviewers could recruit from their own support group in the community. The criteria for inclusion were PLHIV who were at least 18 years old and who were able to respond to an interviewer-administered questionnaire. The English version of the questionnaire was translated into Xhosa, the province’s predominant language. Back-translation procedures were performed in order to keep the translated version in concordance with the original and to adapt it to South African culture. The interviewers (themselves PLHIV) approached other PLHIV known to them and obtained the participant’s informed consent before conducting a face-to-face interview in a private place at the interview site. Completed questionnaires were regularly checked by field supervisors.

African Journal of AIDS Research 2008, 7(2): 209–218

The study was approved by the Human Sciences Research Council’s ethics committee and the Eastern Cape Department of Health. All participants consented to the survey, which was conducted in 2007. Assessment measures

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Demographic and health-status characteristics of the participants Information was gathered regarding the respondents’ age, years of education completed, income level, socio-economic status, household situation, race, the month and year they had tested HIV-seropositive, whether they had been diagnosed with an AIDS case-defining condition, their use of antiretroviral medications, time since HIV diagnosis, and their self-reported CD4 cell count at the time of the interview. The Revised Sign and Symptom Checklist for Persons with HIV Disease (SSC-HIVrev) The SSC-HIVrev is a 72-item checklist of HIV/AIDS-specific physical and psychological symptoms (Holzemer, Hudson, Kirksey, Hamilton & Bakken, 2001). Since it includes eight gynaecological problems not relevant to men, our analysis included only the other 64 physical and psychological symptoms on the checklist. The symptom-related survey items were scored using the following scale: 0 = not checked (or ‘not present today’), 1 = ‘mild,’ 2 = ‘moderate’ and 3 = ‘severe.’ Calculations included the total number of symptoms checked as ‘present today’ (with a range of 0–64), and the total symptom-intensity is a weighting of the symptoms checked according to the 1 to 3 rating of mild, moderate, or severe (see Holzemer et al., 2001). The validity and reliability of the survey instrument have previously been reported for a sample in the United States (see Holzemer et al., 2001) as well as samples from various African countries, including South Africa (see Makoae et al., 2005). Reliability estimates were calculated using Cronbach’s alpha, which was 0.94 in this sample for the 64-item checklist. Health-related quality of life (HRQoL) The WHOQOL-HIV BREF is based on the WHOQOL-HIV measure, one of the two World Health Organization’s Quality-of-Life Instruments for use with HIV-infected populations (see O’Connell, Skevington & Saxena, on behalf of the WHOQOL-HIV Group, 2003; O’Connell, Saxena & Skevington, for the WHOQOL-HIV Group, 2003). This instrument is intended for cross-cultural use and is meant to be accessible to researchers in low-income countries without incurring the financial costs associated with acquiring copyright permission for the use of survey instruments developed in economically richer nations. Various versions of the WHOQOL-HIV (including the 31-item WHOQOL-HIV BREF utilised in this study) have been used in India (Chandra et al., 2003), Italy (Starace, Cafaro, Abrescia, Chirianni, Izzo, Rucci & Girolamo, 2002), Rwanda (Hakuzimana, Burgoyne & Lambert, 2006), Taiwan (Fang, Hsiung, Yu, Chen & Wang, 2002) and Zimbabwe (Sebit, Chandiwana, Latif, Gomo, Acuda, Makoni & Vushe, 2000). Quality-of-life (QoL) domains embedded in the WHOQOL-HIV scales include the categories physical,

211

psychological, social and environmental. Of the 31 items, 26 are identical to those of the generic WHOQOL-HIV BREF, thus enabling comparison of scores with those of healthy populations. One item concerns the individual respondent’s overall QoL: ‘How would you rate your quality of life?’ The response options are: 1 = ‘very poor,’ 2 = ‘poor,’ 3 = ‘neither poor nor good,’ 4 = ‘good,’ and 5 = ‘very good.’ One item measures the respondent’s general health perception: ‘How satisfied are you with your health?’ The response options range from 1 = ‘very dissatisfied’ to 5 = ‘very satisfied.’ The WHOQOL-HIV BREF produces six domain scores, which denote an individual’s subjective perception of their own QoL in the following domains: physical, psychological, level of independence, social relationships, environment, and spirituality. The individual items are rated on a 5-point Likert scale where 1 indicates ‘low, negative perceptions’ and 5 indicates ‘high, positive perceptions.’ There is one item to present each facet, and two items that examine general QoL. Domain scores are scaled in a positive direction, where higher scores denote higher perceived QoL. Items are organised by type of response-scale (capacity, frequency, intensity or satisfaction). The mean score of items within each domain is used to calculate the domain score; mean scores are then multiplied by 4, so that the domain scores range between 4 and 20 (World Health Organization, 2002). Reliability estimates were calculated using Cronbach’s alpha, which was 0.72 for this sample. Data analysis The data were analysed using the Statistical Package for the Social Sciences (SPSS) for Windows, Version 14.0. Basic statistical analyses were undertaken, such as descriptive statistics and cross-tabulations. Scores for all negatively phrased items were reversed so that high scores represent a better perceived QoL. Student t-tests and one-way analysis of variance (ANOVA) was performed to reveal significant associations between the clinical categories and the socio-demographic variables on the QoL domains. Logistic regression was used to assess associations between the WHOQOL-HIV BREF subscales, HIV symptoms and medical variables, socio-economic variables, and overall QoL (recoded as: 1 = very good or good,’ versus 0 = ‘very poor, poor or neither poor nor good’). All independent variables for each WHOQOL-HIV BREF subscale, HIV symptoms and medical variables, socioeconomic variables respectively were analysed in bivariate and multivariate analyses with overall QoL. Results Demographics Most of the participating PLHIV were in the age group 26–45 years (75.6%), more than 78% were women, and nearly 97% were black. Almost half came from a rural area (48.1%) and slightly less came from an urban area (43.4%); about 74% had more than a Grade-7 education, 70.5% had never been married, and the average number of a participant’s own children was two (Table 1).

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Socio-economic status More than half the participants (53.4%) indicated that they were unemployed and looking for work, 15% felt sick or disabled and unable to work, and 8.4% were employed full-time or part-time. The main source of household income among this sample of PLHIV was a government pension or grants (42.5%), followed by contributions from adult family members or relatives (20.3%) and formal salary earnings (5.3%). Responding to a question asking if they had ever gone without enough food to eat in the past 12 months, 40.6% said ‘never or rarely,’ 47.3% indicated ‘sometimes’ and 12% said ‘often.’ Thirty-nine percent indicated that they had ever been on a disability grant, 35% were currently receiving a disability grant, and 13% said that they had been stopped from receiving a disability grant since they no longer fulfilled the criteria, often due to improved health following ART. Severity of illness Three in five PLHIV (60%) in the sample had been diagnosed with HIV infection within the last four years (sometime since 2004), about 66% classified themselves as Table 1: Personal characteristics of the participants (n = 607 PLHIV)

Females Males Age (years): 18–25 26–35 36–45 46+ Race: Black Coloured White Locality: Rural Informal settlement Urban District: Amathole Cacadu Chris Hani Nelson Mandela OR Tambo Alfred Nzo Ukhahlamba Years of education: Grade 7 or less Grades 8 to 11 Grade 12 or above Marital status: Never married Married/cohabiting Separated/divorced/ widowed Data missing Mean number of own children

n 475 132

% 78.3 21.7

80 274 187 66

13.2 44.8 30.8 10

588 17 2

96.9 2.6 0.3

290 51 262

48.1 8.5 43.4

81 83 120 80 120 82 41

13.3 13.7 19.8 13.2 19.8 13.5 6.8

159 296 152

26.1 48.8 25

428 108 67

70.5 17.8 11

4 2.0 (SD = 1.7)

0.7

having received an AIDS diagnosis, about 32% self-reported a CD4 cell count of less than 200, and 48% were currently receiving ART (Table 2). HIV symptoms Overall, the participants reported that on the day of the interview they were experiencing an average of 26.1 symptoms (SD = 13.7) out of a possible 64. The ten most-reported symptoms were: headaches, fever, thirst, fatigue, weakness, painful joints, nausea, muscle aches, fears and worries, and dizziness. Perceived health-related quality of life (QoL) Mean scores for perceived quality of life (QoL), from lowest to highest, within the six domains were: environment = 12.2, level of independence = 12.6, physical health = 13.2, psychological health = 13.9, spirituality = 14.4, and social relationships = 14.0. Men’s perceived overall QoL, general health perceptions, and psychological QoL (in particular bodily image and appearance) were lower than the women’s. The mean score on the WHOQOL-HIV was 13.4 (range 4 to 20, with a higher score indicating higher perceived quality of life) (Table 3). The WHOQOL-HIV BREF and HIV symptoms related to medical variables Disease status Comparisons of the WHOQOL-HIV BREF between groups of AIDS- and non-AIDS-diagnosed participants found an association between the spiritual/religion/personal beliefs, social relationships and psychological domains as well as the HIV-symptoms index (Table 4). Those with an AIDS diagnosis scored higher in the domains of spiritual/religion/ personal beliefs, social relationships and psychological

Table 2: Severity of illness of the participants (n = 607 PLHIV)

Year known HIV-positive: 1988–1997 1998–2001 2002–2003 2004–2005 2006 onwards AIDS diagnosis: ‘Yes’ ‘No’ Most recent CD4 cell count: 350 Missing data/’Don’t know’ Currently on ART Commenced ART (among those on ART): Less than 3 months ago 3–6 months ago 6 months to 1 year ago 1–2 years ago More than 2 years

n

%

24 65 152 206 157

4 10.8 25.2 34.1 26

395 200

66.4 33.6

196 145 169 97 292

32.3 23.9 27.8 16 48.1

18 39 52 59 64

7.8 16.8 22.4 25.4 27.6

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Table 3: The WHOQOL-HIV BREF descriptive statistics according to sex of the participants (mean values ± standard deviation) Total Men Women t Overall quality of life 2.8 ± 1.0 2.6 2.8 –2.35* General health perceptions 3.1 ± 1.0 2.8 3.1 –2.88** Physical domain: 13.2 ± 3.2 12.9 13.2 –0.83 1. Pain and discomfort (r) 3.3 ± 1.0 3.2 3.3 –0.35 2. Energy and fatigue 2.9 ± 1.1 2.9 3.0 –0.63 3. Sleep and rest 3.5 ± 1.0 3.5 3.5 –0.36 50. HIV-related symptoms (r) 3.4 ± 1.1 3.3 3.4 –1.07 Psychological domain: 13.9 ± 2.8 13.4 14.0 –2.16* 4. Positive feelings 3.2 ± 1.0 3.1 3.3 –1.9 5. Thinking, learning, memory and concentration 3.3 ± 0.8 3.4 3.4 –0.25 6. Self-esteem 3.6 ± 1.0 3.5 3.7 –1.99 7. Bodily image and appearance 3.4 ± 1.2 3.2 3.6 –2.65** 8. Negative feelings (r) 3.6 ± 0.9 3.7 3.6 0.49 Level of independence domain: 12.6 ± 3.1 12.4 12.7 –1.16 9. Mobility 3.4 ± 1.0 3.4 3.4 0.09 10. Activities of daily living 3.2 ± 0.9 3.2 3.3 –1.63 11. Dependence on medication or treatments (r) 2.6 ± 1.1 2.6 2.7 –0.48 12. Work capacity 3.2 ± 0.9 3.1 3.3 –1.91 Social relationships domain: 14.0 ± 2.8 13.8 14.1 –1.14 13. Personal relationships 3.5 ± 0.9 3.5 3.6 –0.78 14. Social support 3.9 ± 0.8 3.8 3.9 –0.48 15. Sexual activity 3.2 ± 1.1 3.2 3.2 0.01 51. Social inclusion 3.3 ± 1.2 3.3 3.4 –0.61 Environment domain: 12.2 ± 2.2 12.0 12.3 –1.01 16. Physical safety and security 3.2 ± 0.9 3.2 3.3 –1.20 17. Home environment 3.4 ± 1.0 3.4 3.4 0 18. Financial resources 1.6 ± 0.9 1.8 1.6 2.02* 19. Health and social care: accessibility and quality 3.6 ± 0.9 3.6 3.6 –0.40 20. Opportunities for acquiring new information and skills 3.4 ± 1.0 3.3 3.5 –1.81 21. Participation in and opportunities for recreation/leisure activities 2.8 ± 1.0 2.9 2.9 0.20 22. Physical environment (pollution/noise/traffic/climate) 3.1 ± 1.0 3.1 3.1 –0.46 23. Transport 3.0 ± 1.0 3.0 3.0 –0.01 Spirituality/religion/personal beliefs domain: 14.4 ± 3.5 13.9 14.6 –1.82 24. Meaningful life 3.4 ± 1.0 3.4 3.5 –1.47 52. Forgiveness and blame (r) 3.8 ± 1.3 3.7 3.9 –1.36 53. Concerns about the future (r) 3.5 ± 1.2 3.6 3.5 1.19 54. Death and dying (r) 3.6 ± 1.3 3.5 3.6 –1.21 r = Reverse score; items 50−54 are specific to PLHIV and as such have been added to the original WHOQOL-HIV Instrument; items’ mean scores range from 1 to 5, with 5 indicating the highest, most positive perceptions of quality of life; domain scores range from 4 to 20, with 20 indicating the highest, most positive perceptions; *p < 0.05; **p < 0.01

wellbeing, and lower on the HIV-symptoms index, than those with no AIDS diagnosis. No significant differences were seen regarding scores for the other domains in the WHOQOL-HIV BREF and the overall QoL and general health perceptions. CD4 values Comparison of the three categories of CD4-cell-count ranges (i.e. 350) showed a statistically significant association in relation to the domains psychological health, physical functioning, physical health, level of independence and the HIV-symptoms index. Those with higher CD4 cell count values scored higher in the domains: overall QoL, psychological health, physical health and independence level, and they scored lower on the HIV-symptoms index than those with lower CD4 cell counts. No associations were seen regarding the other domains in the WHOQOL-HIV BREF and general health perceptions (Table 4).

Antiretroviral treatment (ART) On comparing persons treated with antiretroviral medication at the time of the study versus those who were not on ART, no differences regarding all WHOQOL-HIV BREF domains (except for general health perceptions) and the HIV-symptoms index were found. General health perceptions appeared significantly more satisfied in those PLHIV receiving ART as compared to those not on ART. However, for those who had been receiving ART for at least one year, general health perceptions appeared no longer significantly more satisfied than among those who were not on ART. Furthermore, comparing those who were on ART for a year or more, with those who were on ARVs for less than a year, people in the former group indicated a lower score on the HIV-symptoms index than those in the latter (Table 5).

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The WHOQOL-HIV BREF and HIV symptoms related to socio-economic variables

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Disability grant On comparing participants who were receiving a disability grant (due to advanced HIV disease) at the time of the study with those who were not receiving a disability grant, the former group scored significantly higher on the domains: overall quality of life, general health perceptions, psychological health, physical health, level of independence and environment, as well as lower sores on the HIV-symptoms index (Table 6). Educational level and marital status The comparison of the WHOQOL-HIV BREF subscales and HIV symptoms index regarding educational level found that higher educational levels were associated with higher scores for perceived overall QoL, general health perceptions, psychological health, level of independence, social relationships and environment, and lower scores on the HIV-symptoms index. Marital status was not associated with any of the WHOQOL-HIV BREF subscales and HIV symptoms index, except for being single, which was associated with greater psychological health (Table 6).

Among WHOQOL-HIV BREF subscales, multivariate logistic regression identified spirituality, environment, psychological health and level of independence as major predictors for overall quality of life. Among medical variables and HIV symptoms, CD4 cell count and having fewer HIV symptoms but not an AIDS diagnosis were identified as predictors for overall quality of life; among socio-economic variables, having enough food to eat and a higher educational level were identified as predictors for overall quality of life (Table 7). Discussion and conclusions This study among 607 PLHIV in the Eastern Cape found overall low levels of quality of life (QoL) among the domains in the WHOQOL-HIV BREF: environment (12.2), level of independence (12.6), physical health (13.2), psychological health (13.9), social relationships (14.0) and spirituality (14.4), compared to the results of other surveys among PLHIV (cf. WHOQOL-HIV Group, 2004). Among outpatients in North India, Wig, Lekshmi, Pal, Ahuja, Mittal & Agarwal (2006) also found low levels of QoL in the two domains environment (11.7) and physical health (17.7), and, in South India, Chandra, Ghandi, Satishchandra, Kamat, Desai,

Table 4: Quality of life (QoL) and health variables by AIDS diagnosis and CD4 cell count values

Overall quality of life (QoL) score General health perceptions Domains: Physical health

AIDS diagnosis

No AIDS diagnosis

2.8 (0.9) 3.0 (1.0)

2.8 (1.1) 3.1 (1.0)

13.2 (3.2)

13.0 (3.3)

CD4 count 350

F

–0.17 –0.72

2.6 (1.0) 3.0 (1.1)

2.9 (1.1) 3.2 (1.1)

2.9 (1.1) 3.2 (1.1)

3.78* 1.30

–0.78

12.6 (3.3)

t-value

13.41 13.71 6.16** (3.1) (3.1) Psychological health 14.0 (2.6) 13.5 (3.0) –2.10* 13.5 (2.8) 14.31 14.51 7.77*** (2.7) (2.6) Level of independence 12.6 (3.1) 12.7 (3.1) 0.34 12.2 (3.0) 12.91 (3.2) 13.41 (3.0) 7.63*** Social relationships 14.2 (2.8) 13.6 (2.8) –2.57** 14.0 (2.8) 14.4 (2.9) 14.3 (2.6) 0.84 Environment 12.3 (2.0) 12.0 (2.6) –1.89 12.2 (2.2) 12.3 (2.1) 12.7 (2.1) 2.23 Spiritual/religious/personal beliefs 14.9 (3.3) 13.5 (3.7) –4.52*** 14.5 (3.5) 15.0 (3.5) 14.3 (3.1) 1.46 HIV-symptoms index 27.5 (13.0) 23.6 (14.4) 3.33*** 28.41 (13.4) 26.2 23.7 5.24*** (13.7) (14.1) *p < 0.05; **p < 0.01; ***p < 0.001; superscript ‘1’ denotes the value is significantly higher compared to the lower values based on Bonferroni post-hoc comparisons Table 5: Quality of life (QoL) and health variables by ART status

Overall QoL General health perceptions Domains: Physical health Psychological health Level of independence Social relationships Environment Spiritual/religion/personal beliefs HIV symptom index *p < 0.001; **p < 0.05

On ART

Not on ART

2.8 (1.1) 3.2 (1.1)

2.7 (1.0) 2.9 (1.1)

13.3 (3.2) 14.0 (2.7) 12.7 (3.1) 14.2 (2.8) 12.2 (2.2) 14.6 (3.5) 25.9 (13.0)

13.1 (3.2) 13.8 (2.8) 12.6 (3.1) 13.9 (2.8) 12.2 (2.2) 14.3 (3.5) 26.2 (14.3)

t-value 1.57 3.42* 0.69 0.55 0.55 1.22 –0.23 1.04 –0.26

On ART (1 year or more) t-value 1.19 –0.06 –0.73 –0.83 1.47 –0.79 –0.43 –1.19 –2.23**

African Journal of AIDS Research 2008, 7(2): 209–218

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Table 6: Quality of life (QoL) and health variables by socio-economic variables Disability grant status

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Overall perceived quality of life (QoL) General health perceptions Domains: Physical health

Formal educational level

Receiving a grant

Not receiving a grant

t-value

2.9 (1.1)

2.6 (1.1)

2.35*

3.2 (1.1)

2.7 (1.3)

4.08*** 2.9 (1.1)

13.5 (3.1)

12.4 (3.5)

2.85**

2.6 (1.1)

2.7 (1.0) 3.0 (1.1)

3.21 (1.0) 3.41 (1.0)

Marital status Never married

Married/ cohabitating

t-value

17.66*** 2.8 (1.1)

2.7 (0.9)

0.89

8.08*** 3.1 (1.1)

3.0 (1.0)

0.68

F

13.0 13.0 13.7 2.91 13.2 (3.2) 12.9 (3.2) 0.88 (3.2) (3.1) (3.4) Psychological health 14.2 (2.6) 13.4 (3.1) 2.50* 13.6 13.6 14.71 8.38*** 14.0 (2.8) 13.4 (2.6) 2.04* (2.7) (2.8) (2.5) Level of 13.1 (3.1) 12.2 (3.4) 2.46* 12.3 12.4 13.51 8.56*** 12.7 (3.1) 12.3 (2.6) 1.26 independence (3.3) (2.9) (3.1) Social relationships 14.3 (3.0) 13.7 (3.0) 1.69 13.8 13.9 14.5 3.31* 14.1 (2.8) 13.7 (2.6) 1.41 (2.9) (2.9) (2.7) Environment 12.4 (2.1) 11.8 (2.5) 2.43* 12.2 12.0 12.81 7.15*** 12.3 (2.2) 11.9 (2.2) 1.42 (2.1) (2.1) (2.4) Spiritual/religious/ 14.6 (3.3) 13.8 (3.9) 1.75 14.4 14.4 14.6 0.22 14.5 (3.4) 13.9 (3.5) 1.76 personal beliefs (3.7) (3.4) (3.4) HIV-symptoms index 25.5 (13.1) 31.3 (15.0) –3.60*** 30.01 26.1 22.2 12.98*** 25.9 27.1 (14.1) –0.77 (14.5) (13.3) (12.6) (13.7) *p < 0.05; **p < 0.01; ***p < 0.001; superscript ‘1’ denotes that the value is significantly higher compared to the lower values based on Bonferroni post-hoc comparisons

Table 7: Bivariate and multivariate logistic regression between domains of quality of life (QoL), HIV symptoms and medical variables and socio-economic variables with overall QoL

WHOQOL-HIV BREF subscales Level of independence Psychological health Environment Physical health Spirituality Social relationships

HIV symptoms and medical variables HIV-symptoms index AIDS diagnosis CD4 cell count

Adjusted by sex and age

95% CI

1.49 1.67 1.59 1.34 1.83 1.19

1.31–1.54 1.50–1.76 1.45–1.74 1.24–1.45 1.61–2.08 1.12–1.26

Adjusted by sex and age

95% CI

0.93 1.05 1.26

0.91–0.94 0.71–1.53 1.06–1.50

Socio-economic variables

Adjusted by sex and age

95% CI

Educational level Enough food to eat Receiving a disability grant Disability grant stopped

1.26 1.68 2.07 0.70

1.14–1.40 1.39–2.02 1.19–3.61 0.39–1.29

p-value 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001

p-value 0.0001 0.82 0.009

p-value 0.0001 0.0001 0.01 0.25

Adjusted by sex, age and 95% CI WHOQOL-HIV BREF domains 1.12 1.01–1.24 1.21 1.06–1.39 1.19 1.06–1.34 1.03 0.93–1.14 1.36 1.16–1.59 0.99 0.91–1.08 Nagelkerke r 2 (effect of size) = 0.42 Adjusted by sex, age, HIV 95% CI symptoms and CD4 counts 0.93 0.91–0.95 1.15

0.94–1.41 Nagelkerke r 2 = 0.25

Adjusted by sex, age and socio-economic variables 1.17 1.36 1.75

95% CI 1.01–1.34 1.06–1.75 1.11–3.41

Nagelkerke r 2 = 0.12

p-value 0.035 0.007 0.003 0.531 0.0001 0.832

p-value 0.0001 0.17

p-value 0.03 0.02 0.06

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Ravi et al. (2006) found that QoL dimensions were modest, ranging from 12.5 (for the spiritual domain) to 15.2 (for the environmental domain). Among WHOQOL-HIV BREF subscales, logistic regression identified spirituality, environment, psychological health and level of independence as major predictors for perceived overall QoL. There were slight differences in the scores for men and women; men had lower scores for perceived overall QoL, general health perceptions, and psychological health (in particular bodily image and appearance) than did women. In comparison, the WHOQOL-HIV Group (2004) found larger sex differentials in the scores: men scored poorer than women in the domains of physical wellbeing and level of independence, and women scored poorer in the domains of environment, social support and spiritual beliefs. Surprisingly, the group of participants with an AIDS diagnosis scored higher in the spiritual/religious/personal beliefs, social relationships and psychological domains, and lower on the HIV-symptoms index, than those with no AIDS diagnosis. O’Keefe & Wood (1996) also found among HIV-patients in Cape Town that most of the decline in physical function took place early in HIV disease (i.e. WHO clinical stages 1 and 2), when many symptoms have not yet appeared. These findings indicate that HIV infection impacts early and on all aspects of QoL. Health workers must not neglect the needs of patients with early HIV disease and must support them at a primary-care level. Similar to the results of other studies (e.g. Eriksson, Nordström, Berglund & Sandström, 2000; Wig et al., 2006), we found that PLHIV with higher CD4-cell-count values scored higher in the domains: overall quality of life, psychological health, physical health and independence level, and lower on the HIV-symptoms index, than those with lower CD4-cell-count values. Phaladze, Human, Dlamini, Hulela, Hadebe, Sukati et al. (2005) also found relatively good, perceived QoL in terms of overall functional ability and control over symptom intensity among PLHIV in four southern African countries. Chandra et al. (2006) also found significant associations between low CD4 cell counts and the psychological and social relationships domains among HIV patients in South India. Among medical variables and HIV symptoms, CD4 cell count and fewer HIV symptoms without an AIDS diagnosis were identified as predictors for perceived overall QoL. Among the socio-economic variables, having sufficient food to eat, a higher educational level, and receiving a disability grant were identified as predictors for overall QoL. Kovacević, Vurusić, Duvancić & Macek (2006) examined health-related QoL among Croatian HIV-infected individuals and found that health status, a ‘currently ill’ status, and educational level were related to QoL. Eriksson et al. (2000) found in a Swedish sample that CD4 cell count was a poor predictor of how the HIV-infected respondents stated their health-related QoL. This study found that on comparing persons receiving ART at the time of the study versus those who were not receiving ART, there were no significant associations regarding all WHOQOL-HIV BREF domains (except for general health perceptions) and the HIV-symptoms index. Eriksson et al. (2000) also found among a Swedish sample that patients on ART scored significantly lower on some

Peltzer and Phaswana-Mafuya

HRQoL measures, namely physical functioning, mobility, and satisfaction with physical ability. In this study, general health perceptions were significantly more satisfied in those PLHIV on ART as compared to those not on ART. However, for those PLHIV who had been on ART for a year or more, general health perceptions were no longer significantly more satisfied than those who were not on ART. There are inconsistent results from other studies concerning this; for example, Eriksson et al. (2000) found worse perceived health in treatment-inexperienced patients, while Lenderking, Testa, Katzenstein & Hammer (1997) found better perceived health in patients experienced in ART, compared with patients inexperienced in this treatment. These results highlight the need for better access to psychosocial support and medical services for people living with HIV or AIDS in South Africa as well as the need to consider a patient’s general health perceptions during the course of ART. Limitations of the study Because non-probability sampling was used, the findings are not generalisable to the entire population of PLHIV in the Eastern Cape Province. Another limitation of the study is that CD4 cell counts were assessed by self-report data and not confirmed with clinical records. Even though about 32% of the patients reported a CD4 cell count less than

Table 8: Distribution of demographic characteristics of the 607 PLHIV in this study compared to a representative sample of 173 PLHIV cited in the last population-based survey in the Eastern Cape Province, South Africa (Shisana et al., 2005)

Characteristics

Females Males Age (years): 18–25 26–35 36–45 46+ Race: Black Coloured White Geolocality: Rural Informal settlement Urban Years of education: Grade 7 or less Grades 8 to 11 Grade 12 or above Marital status: Never married Married/cohabiting Separated/divorced/ widowed Data missing

% 78.3 21.7

Sample of 173 PLHIV (Shisana et al., 2005) % 76.7 23.3

13.2 44.8 30.8 10

41.6 25.7 17.7 14.9

96.9 2.6 0.3

98.7 1 0.4

48.1 8.5 43.4

61.8 15.9 14.5

26.1 48.8 25

30.5 44 24.5

70.5 17.8 11

61.6 26.8 10.4

0.7

1.1

This study of 607 PLHIV (2007)

African Journal of AIDS Research 2008, 7(2): 209–218

200, the group as a whole seemed to be extremely ill: about 66% self-reported to have been given an AIDS diagnosis. This may reflect the limitation in self-reporting of CD4 cell counts and/or an AIDS diagnosis because the data fail to reflect how ill the patients are. Table 8 shows that our study sample of PLHIV is similar (in terms of sex, race and educational level) but dissimilar (in terms of more urban bias in the sample, with participants tending to be older and more often married) to that of the 2005 representative populationbased survey of people with an HIV-positive status in the Eastern Cape (see Shisana, Rehle, Simbayi, Parker, Zuma, Bhana et al., 2005) (Table 8).

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Acknowledgements — This study was funded by the Eastern Cape Socio-Economic Consultative Council and the Eastern Cape AIDS Council, South Africa. The authors — Karl Peltzer (PhD, DrHabil) is a research director with the Social Aspects of HIV/AIDS and Health Programme at the Human Sciences Research Council; he is also an Extraordinary Professor in psychology at the University of the Free State. As a prevention researcher and evaluator, he has over 20 years of experience in the study of health promotion, risk behaviour and disease prevention, and socio-behavioural interventions. He has published extensively on health behaviour and health interventions (13 books and 300 articles) while working extensively in numerous areas of public health (alcohol and tobacco use, cancer, tuberculosis and HIV control, nutrition, physical activity, hypertension, mental health, injury and violence prevention, and health systems). Nancy Phaswana-Mafuya holds a PhD in health social work from the University of the North. She is currently a research director at the Human Sciences Research Council, based in the Social Aspects of HIV/AIDS and Health Research Programme and she is an Extraordinary Visiting Professor in the Faculty of Community Health Sciences at the University of the Western Cape. Her research interests are: the social determinants of health, HIV/AIDS, injury prevention, substance use and misuse, environmental health, and social work applied to health.

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