Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa

Zanele Benedict Nomatshila; Laston Gonah; Guillermo Alfredo Pulido-Estrada; Monwabisi Faleni; Sibusiso Cyprian Nomatshila; Teke Ruffin Apalata

doi:10.12688/f1000research.174519.1

Home Browse Quality of Life of People Living with Virally Suppressed HIV in the...

ALL Metrics

-

Views

-

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa 

[version 1; peer review: awaiting peer review]

Zanele Benedict Nomatshila ^1-3, Laston Gonah¹, Guillermo Alfredo Pulido-Estrada¹, Monwabisi Faleni¹, Sibusiso Cyprian Nomatshila^1,4, Teke Ruffin Apalata^3,5

Zanele Benedict Nomatshila ^1-3, Laston Gonah¹, [...] Guillermo Alfredo Pulido-Estrada¹, Monwabisi Faleni¹, Sibusiso Cyprian Nomatshila^1,4, Teke Ruffin Apalata^3,5

PUBLISHED 09 Jun 2026

Author details Author details

¹ School of Public Health, Walter Sisulu University, Mthathja, Eastern Cape, 5117, South Africa
² Department of Social Work, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa
³ University of Stirling Faculty of Health Sciences and Sport, Stirling, Scotland, UK
⁴ WSU Society and Health Research Institute, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa
⁵ School of Pathology, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa

Zanele Benedict Nomatshila
Roles: Conceptualization, Investigation, Methodology, Visualization, Writing – Original Draft Preparation

Laston Gonah
Roles: Data Curation, Formal Analysis, Software, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Guillermo Alfredo Pulido-Estrada
Roles: Data Curation, Formal Analysis, Software, Validation

Monwabisi Faleni
Roles: Investigation, Project Administration

Sibusiso Cyprian Nomatshila
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Teke Ruffin Apalata
Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Supervision, Visualization

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

This article is included in the Global Public Health gateway.

Abstract

Background

Viral suppression in people living with HIV (PLH) positively affects their quality of life and lifespan due to long-term Antiretroviral Therapy (ART). However, this treatment can also lead to various issues, including metabolic, physical, psychosocial, and economic challenges. Many individuals who achieve viral suppression (VL) still face significant difficulties that adversely affect their overall quality of life.

Objectives

To measure Quality of Life (QoL) domains using the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) among People Living with Immunodeficiency Virus who achieved Viral Load Suppression.

Methods

A descriptive cross-sectional study of 244 HIV-virally suppressed adult participants was conducted across the Eastern Cape Province. The QoL was assessed using the WHOQOL-BREF questionnaire, where mean scores for each of the 4 domains were calculated and transformed to a 0–100 scale.

Results

The overall quality of life (QoL) assessment yielded a moderate general score of 50.5 (SD = 12.1) across four domains. Participants rated their physical health highest with a mean score of 55.9 (SD = 17.6), while scores for social relationships and psychological health were both 51.3 (SD = 20.1 and SD = 15.9, respectively), and the environmental domain scored the lowest at 43.6 (SD = 13.7). This was accompanied by moderate perceived overall self-rated health status, where higher educational level, employment, and higher income were significantly associated with higher scores for each of the four QoL domains (p < 0.05, respectively).

Keywords

Quality of life; HIV, viral suppression, physical health, psychological health; self-rated health. 

Corresponding author: Zanele Benedict Nomatshila

Competing interests: No competing interests were disclosed.

Grant information: The work reported herein was made possible through funding by the South African Medical Research Council through its Division of Research Capacity Development under the SAMRC Research Capacity Development Initiative (MRC-RFACC 01-2014), from funding received from the South African National Treasury. The content hereof is the sole responsibility of the authors and does not necessarily represent the official views of the SAMRC or the funders.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2026 Nomatshila ZB et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Nomatshila ZB, Gonah L, Pulido-Estrada GA et al. Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa  [version 1; peer review: awaiting peer review]. F1000Research 2026, 15:898 (https://doi.org/10.12688/f1000research.174519.1) First published: 09 Jun 2026, 15:898 (https://doi.org/10.12688/f1000research.174519.1) Latest published: 09 Jun 2026, 15:898 (https://doi.org/10.12688/f1000research.174519.1)

Introduction

Successful Human Immunodeficiency Virus (HIV) treatment through antiretroviral therapy (ART) is known to significantly contribute to viral suppression and consequently quality of life (QoL) improvements in people living with HIV. Existing research evidence has linked HIV treatment success and viral load suppression (VLS) to several benefits, including increased life expectancy, increased productivity and improved QoL domains - physical health, psychological, social relationships and environment domains.^1,2

According to UNAIDS, VLS is a significant indicator of ART treatment success, characterised by a reduction of viral load to undetectable levels (<1000 copies/mL) in HIV infected individuals.^3,4 The VLS results in reduced viral transmission, improved immunity, and increased life expectancy among HIV-infected individuals, thereby implying better productivity and better QoL across all domains.^1,2,5

According to the World Health Organization (WHO), QoL is a multidimensional measurement of an individual’s perceived well-being on several dimensions, including their physical and psychological health, environment, and social relationships.^2,6 The World Health Organisation Quality of Life Brief Version (WHOQOL-BREF) is a cross-culturally applicable and validated measurement tool that assesses QoL using 26 standardised questions on the four QoL domains, namely physical health, psychological, social relationships and environment, with 5-point Likert scale responses per question.^1,6,7

An estimated 30.7 million people out of 39.9 million PLH were accessing ART globally, and 72% of them were virally suppressed.^8,9 Sub-Saharan Africa is the region with the highest numbers of PLHIV (20.8 million out of 39.9 million), PLH on ART (84%) and viral suppression rate (76%), relative to other regions.^8,9 South Africa has been ranked among the top 5 countries with the highest HIV prevalence in the world, with 18.8% of the population living with HIV and 81.2% of those virally suppressed.^8,9 The Eastern Cape Province (ECP), where this study was conducted, is among the top 4 provinces with the highest HIV prevalence rate (18.8%) and highest HIV viral suppression rate (80.2%).¹⁰

During the 2014 International AIDS Conference held in Melbourne, the Joint United Nations Programme on HIV/AIDS introduced the 90–90-90 targets aimed at speeding up initiatives to eliminate the AIDS epidemic by the year 2030. These targets were reviewed in 2018 by the United Nations.¹¹ The 90–90-90 and 95–95-95 initiatives establish targeted health goals to be realized by the years 2020 and 2030, respectively. The aim is to ensure that by this time, at least 90% of individuals living with HIV (PLWH) will be diagnosed, a minimum of 90% of those diagnosed will be on antiretroviral therapy (ART), and at least 90% of those undergoing treatment will attain viral suppression. The WHO (2016), however, admits that this technique falls short of establishing a clear aim for quality of life. Therefore, it fails to address the needs of PLH who have achieved viral suppression yet continue to confront substantial non-communicable diseases, psychological distress, feelings of hopelessness, economic difficulties, and experiences or fears associated with HIV-related discrimination¹² Despite the high rates of viral suppression, research evidence on QoL of PLHIV following viral suppression is generally limited in South Africa and none in the Eastern Cape province. The study sought to evaluate Quality of Life (QoL) domains namely, physical health, psychological, social relationships and environment, using the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) among PLH who achieved VL in South Africa.

Methods

Research design

The study was a quantitative cross-sectional study.

Study setting

The study was conducted at eleven selected health facilities within four adjacent health districts of the predominantly rural coastal province called the Eastern Cape. The mid-2024 estimates indicated that the province mainly consists of a Black population (85% of an approximate total population of 7million) that is mired in unemployment and inequalities.¹³

Participants and sampling

The study was conducted among a random sample of 244 participants aged 18 years or older who were HIV virally suppressed and participating in the South African Medical Research Council Research Capacity Development Initiative (SAMRC-RCDI) project at Walter Sisulu University. Viral suppression (below 200 copies/mL) was verified from patient registers prior to enrolment into the study.

Data collection

Sampling and data collection occurred over a 6-month period: January – June 2023. A team of researchers conducted a simple random selection from a database of people living with HIV (PLHIV) who are receiving antiretroviral therapy (ART) and have achieved viral load suppression (defined as having a laboratory test result of less than 200 copies/ML). To be eligible for participation in this study, individuals have given consent to take part in future HIV-related research. The authors of the current study also contributed as co-investigators in the SAMRC-RCDI study. Those with cognitive impairments or who were unable to provide consent were excluded from the study.

Data was collected from the selected participants using the 26-item WHOQOL-BREF,¹⁴ which is a cross-culturally applicable and validated tool for evaluating quality of life across four major domains: physical health, psychological, social relationships, and environment. Mean scores for each of the four domains were calculated, and each of the mean scores was transformed to a 0–100 scale. A higher score indicated better quality of life for that domain. The WHOQOL-BREF was implemented by a team of three qualified Public Health Practitioners who were trained on questionnaire administration. Following written informed consent by the participant, data collection was conducted at healthcare facilities, where each questionnaire survey lasted 20–30 minutes.

Data analysis

Data entry and analysis was done using SPSS version 13® for windows. The Cronbach’s alpha was used to determine the reliability and internal consistency of the WHOQOL-BREF tool. Descriptive data were analysed and presented as frequencies, means, standard deviations and proportions in tables and figures, as appropriate. A repeated measures ANOVA was performed to assess whether there were significant differences in the mean scores across the four domains of the WHOQOL-BREF questionnaire and p-values were obtained. A p-value of less than 0.05 was considered statistically significant. A Bonferroni post-hoc test was performed to identify the specific sources of a significant overall difference in QoL domain scores. Wilk’s Lambda analysis was used to look at the overall error rate while testing different areas of quality of life (QoL).

The Cronbach’s alpha was used to determine the reliability and internal consistency of the WHOQOL-BRF questionnaire, where it showed a value of 0.808, indicating a good consistency for the WHOQOL-BEF questionnaire. The WHOQOL-REF questionnaire measures four domains of QoL.¹⁴ The physical domain assesses QoL in relation to the ability to perform daily activities, the capacity to work, energy levels, mobility, pain, and sleep quality. Whereas the psychological domain of QoL evaluates positive feelings, self-esteem, body image, sense of meaning in life, and negative emotions. The social domain of QoL measures satisfaction with personal relationships, special support from family and friends, and sexual life. The Environmental domain assesses the quality of life in relation to the physical environment, including aspects such as physical safety, home conditions, financial resources, access to health services and information, and leisure opportunities. Each domain was scored on a scale from 0 to 100, with higher scores indicating better quality of life.

Results

Participants characteristics

The study sample of 244 participants was predominantly female (57.0%), with the largest age group being 45–53 years (28.3%). Secondary education was most common (36.1%), and the majority were employed (61.5%). Nearly half resided in rural areas (46.3%), and most reported low income (66.8%). Christianity was the most prevalent religion (50.8%), followed by Muslim (30.3%) and African religion (15.6%). The socio-demographic information is summarised in Table 1.

Table 1. Socio-demographic information of study participants.

Sociodemographic variables	n	%	95% CI
Gender
Male	105	43.0	36.8–49.2
Female	139	57.0	50.8–63.2
Age group (years)
18–26	27	11.1	7.1–15.1
27–35	46	18.9	14.0–23.8
36–44	61	25.0	19.6–30.4
45–53	69	28.3	22.6–34.0
≥54	41	16.8	12.1–21.5
Educational level
None	32	13.1	8.9–17.3
Primary	62	25.4	19.9–30.9
Secondary school	88	36.1	30.0–42.2
Tertiary	62	25.4	19.9–30.9
Marital status
Single	89	36.5	30.4–42.6
Married	75	30.7	25.0–36.4
Separated	39	16.0	11.4–20.6
Divorced	21	8.6	5.1–12.1
Widowed	20	8.2	4.8–11.6
Employment status
Yes	150	61.5	55.4–67.6
No	94	38.5	32.4–44.6
Location
Rural	113	46.3	40.1–52.5
Urban	99	40.6	34.5–46.7
Informal settlement	32	13.1	8.9–17.3
Income
Low (R0–R5000/month)	163	66.8	60.9–72.7
Moderate (R5001–R15000/month)	72	29.5	23.8–35.2
High (≥R15000/month)	9	3.7	1.3–6.1
Religion
Christian	124	50.8	44.5–57.1
Muslim	74	30.3	24.6–36.0
African Religion	38	15.6	11.1–20.1
Other	8	3.3	1.1–5.5

Self-rated health status

Over half (55.3%) of the participants perceived their overall health status as either excellent or good, with the remainder self-rating as fair or bad, as shown in Figure 1 below.

Figure 1. Self-rated health status distribution among respondents.

Quality of life scores according to domains

Following listwise deletion, where any case with missing data for any item was excluded, a total of 186 cases were included in the final analysis from the initial sample size of 244. The physical domain scored the highest mean score (55.9), suggesting that participants rated their physical health relatively higher than the other domains. The general score represents an overall assessment of quality of life. The general mean score was just above 50, indicating an overall moderate level of perceived quality of life among the participants. Table 2 Summarises the QoL scores according to each of the four QOL domains that were assessed in this study.

Table 2. QoL Scores according to QoL domains for study participants.

Domains of WHOQOL BREEF Questionnaire (0 to 100 scale)	Mean score (SD)	Median score (IQR)
Physical	55.91 (17.59)	58.33 (25.00)
Psychological	51.30 (15.91)	50.00 (20.83)
Social	51.47 (20.27)	50.00 (33.34)
Environmental	43.57 (13.85)	43.75 (12.50)
General score	50.52 (12.07)	48.70 (13.93)

Repeated measures ANOVA and pairwise comparisons of mean score differences between WHOQOL-BREF domains

A repeated measures ANOVA was performed to assess whether there were significant differences in the mean scores across the four domains of QoL assessed by the WHOQOL-BREF questionnaire. There were statistically significant differences in how participants perceived their QoL with respect to their physical health, psychological, social relationships, and environment. The Wilk’s Lambda multivariate analysis showed statistically significant differences between the mean scores of the domains (F-value = 35.54; p < 0.001). Table 3 shows Bonferroni post-hoc test results of pairwise comparison of mean score differences between the four QoL domains, where the mean score difference between the physical health and psychological domain was the highest among the domain mean score differences (mean difference = 4.61; p = 0.001). In general, participants perceived their physical health better than their environmental conditions.

Table 3. Bonferroni post-hoc test results of pairwise comparison of mean score differences between the four QoL domains.

Domain	Domain	Mean difference	Std. Error	p value	95% Confidence interval for difference
Domain	Domain	Mean difference	Std. Error	p value	Lower limit	Upper limit
Physical	Psychological	4.61	1.20	0.001	1.42	7.8
Physical	Social	4.44	1.45	0.014	0.59	8.29
Physical	Environmental	12.34	1.23	0.000	9.08	15.6
Psychological	Social	−0.17	1.21	1.000	−3.38	3.04
Psychological	Environmental	7.73	1.14	0.000	4.69	10.77
Social	Environmental	7.90	1.36	0.000	4.27	11.53

Mean scores for the WHOQOL-BREF Domains by socio-demographic variables

Mean scores for the four QoL domains were analysed based on the socio-demographic variables of the study participants, as presented in Table 4.

Table 4. Mean scores for the WHOQOL-BREF Domains by socio-demographic variables.

Variables	Physical domain		Psychological domain		Social domain Mean		Environmental domain
Variables	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Age group
18–26	61.73	17.18	55.40	17.75	54.01	19.66	42.82	14.16
27–35	58.88	19.98	50.72	14.94	53.26	19.68	45.38	12.53
36–44	56.42	15.99	51.64	17.72	54.92	21.21	43.55	14.11
45–53	53.02	18.08	51.45	15.22	49.64	21.03	42.21	14.67
≥ 54	52.85	15.55	48.48	14.06	45.73	17.79	44.36	13.61
p-value	0.114		0.531		0.171		0.800
Gender
Male	55.24	15.73	49.01	15.28	51.35	18.92	42.56	14.32
Female	56.41	18.91	53.03	16.21	51.56	21.30	44.33	13.48
p-value	0.606		0.051		0.936		0.322
Educational level
None	48.70	16.41	44.79	12.79	43.49	17.29	44.14	16.87
Primary	50.40	14.66	48.39	13.65	43.82	18.78	39.11	13.62
Secondary school	59.56	18.85	52.98	16.49	56.63	20.10	42.33	12.01
Tertiary	59.95	16.72	55.17	17.36	55.91	20.10	49.50	13.02
p-value	0.000		0.007		0.000		0.000
Marital status
Single	58.33	20.53	55.24	18.38	55.81	20.81	46.07	13.86
Married	55.11	13.69	50.00	14.11	50.11	20.53	42.25	13.03
Separated	55.56	16.03	46.05	11.06	48.72	14.25	42.79	13.26
Divorced	54.37	12.25	48.81	16.09	48.02	23.26	42.86	14.15
Widowed	50.42	23.18	51.46	15.43	46.25	21.88	39.69	16.88
p-value	0.412		0.028		0.132		0.256
Employment status
Employed	58.28	16.62	50.69	16.90	53.06	20.10	46.33	13.10
Unemployed	52.13	18.49	52.26	14.23	48.94	20.38	39.16	13.94
p-value	0.008		0.456		0.123		0.000

There were no statistically significant differences in physical health, psychological and social domain scores across age and gender groups implying that age and gender were not significant factors influencing participants’ perceptions of their QoL on all the four domains. Higher levels of education (secondary or tertiary) were significantly linked to more positive perceptions of physical health (p < 0.001), psychological well-being (p = 0.007), and social domains (p = 0.001) compared to individuals with lower educational attainment (none or primary level) Participants with tertiary education scored significantly higher with regards to their perception on the environmental domain compared to those with none, primary and secondary education. There were no statistically significant differences in QoL domain scores across various marital status groups except for the psychosocial domain, where single participants reported a better perception and scored higher compared to those who were separated (p = 0.028). With regards to employment status, employed participants scored higher on physical health and environment domains compared with the unemployed (p = 0.008 and 0.001. respectively), whereas there was no significant difference in the scores for psychological and social domains based on employment status.

As shown in Table 5, participants’ income was strongly associated with their perception of their QoL, with higher income associated with better perceptions of their physical health, psychological, social, and environmental domains (p = 0.000, respectively). There was no significant variation in mean QoL domain scores based on participants’ geographic location. However, regarding religion, only the psychological domain scores showed a significant difference, with African Traditional religion participants scoring higher than Muslims or those of other religions ( Table 5).

Table 5. Mean scores and standard deviations for WHOQOL-BREF Domains (Physical, Psychological, Social, and Environmental) by socio-demographic variables.

Variables	Physical domain		Phycological domain		Social domain Mean		Environmental domain
Variables	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Locality type
Rural	55.09	19.93	52.54	16.81	53.02	20.14	41.65	14.11
Urban	57.15	16.45	51.56	15.41	50.51	21.36	45.33	13.67
Informal settlement	54.95	11.17	46.09	13.38	48.96	17.16	44.92	12.94
p-value	0.659		0.126		0.504		0.130
Income
Low income	52.40	16.24	48.34	13.63	46.93	18.72	40.15	12.99
Moderate income	61.00	17.23	55.27	17.54	58.57	19.73	49.31	12.57
High income	78.70	18.69	73.15	18.53	76.85	18.06	59.72	13.30
p-value	0.000		0.000		0.000		0.000

Religion
Christian	124	50.8	44.5–57.1
Muslim	74	30.3	24.6–36.0
African Religion	38	15.6	11.1–20.1
Other	8	3.3	1.1–5.5

Discussion

The study revealed a moderate overall quality of life, with an average score of 50.2% across the four domains, which was consistent with participants’ moderate self-rated health. This overall picture, however, was strongly influenced by socioeconomic factors. Specifically, individuals with higher levels of education, those who were employed, and those with higher incomes reported significantly better outcomes in each of the four QoL domains: physical health, psychological well-being, social relationships, and environmental functioning.

Accompanied by a moderate self-rated health status, participants reported a moderate quality of life across all domains, as measured by their perceptions. Although significant variations were noted between domains, the domain scores for physical health, psychological, social, and environmental domains remained moderate. It was also found that level of education, employment status, and income were significant factors influencing the perception of quality of life for most of the QoL domains. The observed study findings are similar to the results of other studies that have shown that education, employment and income are key determinants of quality of life, as well as principal enabling factors for affording lifestyle choices such as health seeking, use of tobacco products, alcohol intake, physical activity and diet.^7,15–17

Higher level of education is known to improve personal health risk perception and knowledge about disease causation and healthier treatment options, hence greater control over health.^18,19 Better education can also increase competitive advantage in securing higher income employment opportunities, consequently, higher disposable income for funding lifestyle choices.^17–20 This may, in part, explain the findings from this study where higher levels of education, employed status and higher income were linked to higher self-rated quality of life domains together with reduced alcohol-and tobacco-use behaviours. With more disposable outcome, people with high income can afford lifestyle behaviours such as a better diet and harmful use of alcohol and tobacco as observed in this study.^5,17

Participants’ dual engagement in both healthier behaviours (such as better diet and physical activity) and counterproductive health behaviours could have a neutralising effect, possibly explaining the observed moderate QoL and SRH scores. In other similar studies where good and very good QoL and SRH scores were observed, higher levels of healthy behaviours and none or very low levels of counterproductive health behaviours were also reported among the participants, in contrast to the present study findings.^5,7,15,16,18 This study further highlights that socioeconomic status significantly influences all domains of QoL. The socioeconomic hardships not only lead to physical illnesses but also negatively impact mental health and put a strain on social connections.²¹ This gives a broader perspective on how inequality harms human well-being. This study was conducted over a brief period; thus, longitudinal studies could aid in monitoring the disconnect between behaviour, socioeconomic status, and quality of life.

Strengths and limitations

In this study, the participant pool consisted of individuals from a uniform cultural and socioeconomic background, which streamlined the data collection process. However, this lack of diversity, combined with the specific concentration on individuals living with HIV who are virally suppressed, restricts the ability to apply the results to a wider audience. Additionally, it makes it challenging to directly compare these findings with research that includes a more diverse range of HIV-positive individuals. In this study, the participant pool consisted of individuals from a uniform cultural and socioeconomic background, which streamlined the data collection process. However, this lack of diversity, combined with the specific concentration on PLWH who are virally suppressed, restricts the ability to apply the results to a wider audience. Additionally, it makes it challenging to directly compare these findings with research that includes a more diverse range of HIV-positive individuals.

Conclusions

This study addresses a critical issue in HIV care, emphasizing that while antiretroviral therapy (ART) effectively reduces viral levels, it does not guarantee a good quality of life for people living with HIV in the Eastern Cape Province. Despite improved physical health scores, mental health, social relationships, and environmental conditions remain significant challenges, particularly due to psychological and structural issues. The lowest scores were linked to environmental factors like financial resources and access to services. Additionally, socioeconomic factors such as education, employment, and income are strongly associated with quality of life, indicating that financial stability is vital for the well-being of individuals even after achieving viral suppression.

To optimise viral suppression benefits, public health policies must address the social determinants of health impacting quality of life and lifestyle behaviours. This requires a shift from a biomedical to a socio-ecological model. Key strategies include implementing economic empowerment programs to combat poverty and food insecurity, ensuring housing security for stable care engagement, and integrating mental health into HIV care. By supporting these social factors, policies can help people living with HIV not only survive but thrive, enhancing both individual and public health outcomes.

Ethics

The study’s ethical principles were guided by the Helsinki Declaration. Ethical approval (Ref. no. 093/2022) was issued on 20 October 2022 by the Walter Sisulu University Faculty of Medicine and Health Sciences Human Research Ethics Committee.

Informed consent

All participants signed a written informed consent prior to all data collection.

Data availability

Due to ethical and legal restrictions imposed by the Walter Sisulu University Faculty of Medicine and Health Sciences Human Research Ethics Committee (WSU-FMHS-HREC), the full dataset cannot be made publicly available. The ethics approval (Ref. no. 093/2022) specifically states that participant data, even when coded, must be protected under the South African Protection of Personal Information Act (POPIA) and may only be released with explicit permission from the committee and only for purposes consistent with the original informed consent. To request access to the coded, de-identified dataset, researchers should submit a formal application to the WSU-FMHS-HREC at [email protected] with a copy to the corresponding author, Zanele Bennedict Nomatshila, at [email protected]. The application must include: (1) a detailed research proposal specifying the intended purpose, (2) the applicant’s qualifications and institutional affiliation, (3) a data management and security plan outlining storage, access controls, and disposal after analysis, and (4) proof of ethical approval from the applicant’s own institution. Access will only be granted for purposes that align with the original study consent and will be subject to a signed data transfer agreement.

Extended Data

The following materials have been deposited on a public repository

• WHOQOL-BREF questionnaire (full 26-item instrument as administered)
• study information sheet
• Written informed consent form (template)

These materials are available under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence under the name, Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa. Zenodo. https://doi.org/10.5281/zenodo.18415016.²²

Acknowledgements

Participants of the study, health facility personnel, and Ms Sesethu Sehole.

References

1. Organization WH: The role of HIV viral suppression in improving individual health and reducing transmission: policy brief. World Health Organization; 2023.
2. Okere NE, Censi V, Machibya C, et al.: Beyond viral suppression: Quality of life among stable ART clients in a differentiated service delivery intervention in Tanzania. Quality of Life Research. 2022; 31: 159–170. Publisher Full Text
3. Lesko CR, Chander G, Moore RD, et al.: Variation in estimated viral suppression associated with the definition of viral suppression used. Aids. 2020; 34(10): 1519–1526. PubMed Abstract | Publisher Full Text | Free Full Text
4. Djiyou AB, Penda CI, Madec Y, et al.: Viral load suppression in HIV-infected adolescents in cameroon: towards achieving the UNAIDS 95% viral suppression target. BMC pediatrics. 2023; 23(1): 119. PubMed Abstract | Publisher Full Text | Free Full Text
5. Puciato D, Rozpara M, Bugdol M, et al.: Quality of life of low-income adults. Work. 2023; 74(2): 631–648. PubMed Abstract | Publisher Full Text
6. Group W: Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological medicine. 1998; 28(3): 551–558. Publisher Full Text
7. Weber R-M, Anand C, Koeder C, et al.: Healthy lifestyle changes can improve quality of life: the Healthy Lifestyle Community Program (cohort 2; HLCP-2). Journal of Public Health. 2025; 1-15. Publisher Full Text
8. UNAIDS: Global HIV & AIDS statistics — Fact sheet 2025 [Fact Sheet].Reference Source
9. WHO: HIV statistics, globally and by WHO region, 2024: World Health Organization 2024.Reference Source
10. HSRC: Fact Sheet - The Sixth South African National HIV Prevalence, Incidence, Behaviour and Communication Survey (SABSSM VI). Human Sciences Research Council; 2023 [cited 2025. Reference Source
11. UNGA UNGA: Resolution No A/RES/70/266, Political Declaration on HIV and AIDS: On the Fast-Track to Accelerate the Fight against HIV and to End the AIDS Epidemic by 2030.2016. Contract No.: Resolution No A/RES/70/266.
12. Lazarus JV, Safreed-Harmon K, Barton SE, et al.: Beyond viral suppression of HIV - the new quality of life frontier. BMC Medicine. 2016; 14: 14. Publisher Full Text
13. StatsSA: Improving Lives Through Data Ecosystem. Republic of South Africa: Statistics South Africa; 2022.
14. WHO: WHOQOL-BREF: introduction, administration, scoring and generic version of the assessment: field trial version, December 1996. WHO; 1996 [cited 2024 16/05/2024]. Reference Source
15. Raphael D: Social Structure, Living Conditions, and. Social Determinants of Health: Canadian Perspectives.2025; 37.
16. Sussman S: Impact of behavioral addictions on quality of life: Universal and behavior-specific consequences. Handbook of Addiction, Recovery and Quality of Life: Cross-cutting Perspectives from Around the Globe. Springer; 2025; p. 119–36.
17. Zaid FA, Liamputtong P: Determinants of Health, Health Promotion, and Illness Prevention. Handbook of Concepts in Health, Health Behavior and Environmental Health. Springer; 2025; p. 1–19. Publisher Full Text
18. Ferrara P: Health Risk Factors, Prevention, and Inequalities. MDPI; 2025; 127.
19. Rangan V: Influence of Social Factors on Health Behavior. Behavioral Economics and Neuroeconomics of Health and Healthcare. IGI Global; 2025; p. 153–80.
20. Liao W, Liu X, Kang N, et al.: Associations between healthy lifestyle score and health-related quality of life among Chinese rural adults: variations in age, sex, education level, and income. Quality of Life Research. 2023; 32(1): 81–92. PubMed Abstract | Publisher Full Text
21. Salem M, Robenson J: The Impact of Socioeconomic Factors on Mental Health: A Conceptual Framework. Cureus. 2025; 17(7): e88244. Publisher Full Text
22. Nomatshila ZB: Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa. Dataset. Zenodo. 2026. Publisher Full Text

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 09 Jun 2026

Author details Author details

¹ School of Public Health, Walter Sisulu University, Mthathja, Eastern Cape, 5117, South Africa
² Department of Social Work, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa
³ University of Stirling Faculty of Health Sciences and Sport, Stirling, Scotland, UK
⁴ WSU Society and Health Research Institute, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa
⁵ School of Pathology, Walter Sisulu University, Mthatha, Eastern Cape, 5117, South Africa

Zanele Benedict Nomatshila
Roles: Conceptualization, Investigation, Methodology, Visualization, Writing – Original Draft Preparation

Laston Gonah
Roles: Data Curation, Formal Analysis, Software, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Guillermo Alfredo Pulido-Estrada
Roles: Data Curation, Formal Analysis, Software, Validation

Monwabisi Faleni
Roles: Investigation, Project Administration

Sibusiso Cyprian Nomatshila
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Teke Ruffin Apalata
Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Supervision, Visualization

Competing interests

No competing interests were disclosed.

Grant information

The work reported herein was made possible through funding by the South African Medical Research Council through its Division of Research Capacity Development under the SAMRC Research Capacity Development Initiative (MRC-RFACC 01-2014), from funding received from the South African National Treasury. The content hereof is the sole responsibility of the authors and does not necessarily represent the official views of the SAMRC or the funders.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (1)

version 1

Published: 09 Jun 2026, 15:898

https://doi.org/10.12688/f1000research.174519.1

Copyright

© 2026 Nomatshila ZB et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

0

SEE MORE DETAILS

CITE

how to cite this article

Nomatshila ZB, Gonah L, Pulido-Estrada GA et al. Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa  [version 1; peer review: awaiting peer review]. F1000Research 2026, 15:898 (https://doi.org/10.12688/f1000research.174519.1)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 09 Jun 2026

Open Peer Review

Reviewer Status

AWAITING PEER REVIEW

Comments on this article

All Comments(0)

Add a comment

Sign up for content alerts

Browse by related subjects

[1] 1. Organization WH: The role of HIV viral suppression in improving individual health and reducing transmission: policy brief. World Health Organization; 2023.

[2] 2. Okere NE, Censi V, Machibya C, et al.: Beyond viral suppression: Quality of life among stable ART clients in a differentiated service delivery intervention in Tanzania. Quality of Life Research. 2022; 31: 159–170. Publisher Full Text

[3] 3. Lesko CR, Chander G, Moore RD, et al.: Variation in estimated viral suppression associated with the definition of viral suppression used. Aids. 2020; 34(10): 1519–1526. PubMed Abstract | Publisher Full Text | Free Full Text

[4] 4. Djiyou AB, Penda CI, Madec Y, et al.: Viral load suppression in HIV-infected adolescents in cameroon: towards achieving the UNAIDS 95% viral suppression target. BMC pediatrics. 2023; 23(1): 119. PubMed Abstract | Publisher Full Text | Free Full Text

[5] 5. Puciato D, Rozpara M, Bugdol M, et al.: Quality of life of low-income adults. Work. 2023; 74(2): 631–648. PubMed Abstract | Publisher Full Text

[6] 6. Group W: Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological medicine. 1998; 28(3): 551–558. Publisher Full Text

[7] 7. Weber R-M, Anand C, Koeder C, et al.: Healthy lifestyle changes can improve quality of life: the Healthy Lifestyle Community Program (cohort 2; HLCP-2). Journal of Public Health. 2025; 1-15. Publisher Full Text

[8] 8. UNAIDS: Global HIV & AIDS statistics — Fact sheet 2025 [Fact Sheet].Reference Source

[9] 9. WHO: HIV statistics, globally and by WHO region, 2024: World Health Organization 2024.Reference Source

[10] 10. HSRC: Fact Sheet - The Sixth South African National HIV Prevalence, Incidence, Behaviour and Communication Survey (SABSSM VI). Human Sciences Research Council; 2023 [cited 2025. Reference Source

[11] 11. UNGA UNGA: Resolution No A/RES/70/266, Political Declaration on HIV and AIDS: On the Fast-Track to Accelerate the Fight against HIV and to End the AIDS Epidemic by 2030.2016. Contract No.: Resolution No A/RES/70/266.

[12] 12. Lazarus JV, Safreed-Harmon K, Barton SE, et al.: Beyond viral suppression of HIV - the new quality of life frontier. BMC Medicine. 2016; 14: 14. Publisher Full Text

[13] 13. StatsSA: Improving Lives Through Data Ecosystem. Republic of South Africa: Statistics South Africa; 2022.

[14] 14. WHO: WHOQOL-BREF: introduction, administration, scoring and generic version of the assessment: field trial version, December 1996. WHO; 1996 [cited 2024 16/05/2024]. Reference Source

[15] 15. Raphael D: Social Structure, Living Conditions, and. Social Determinants of Health: Canadian Perspectives.2025; 37.

[16] 16. Sussman S: Impact of behavioral addictions on quality of life: Universal and behavior-specific consequences. Handbook of Addiction, Recovery and Quality of Life: Cross-cutting Perspectives from Around the Globe. Springer; 2025; p. 119–36.

[17] 17. Zaid FA, Liamputtong P: Determinants of Health, Health Promotion, and Illness Prevention. Handbook of Concepts in Health, Health Behavior and Environmental Health. Springer; 2025; p. 1–19. Publisher Full Text

[18] 18. Ferrara P: Health Risk Factors, Prevention, and Inequalities. MDPI; 2025; 127.

[19] 19. Rangan V: Influence of Social Factors on Health Behavior. Behavioral Economics and Neuroeconomics of Health and Healthcare. IGI Global; 2025; p. 153–80.

[20] 20. Liao W, Liu X, Kang N, et al.: Associations between healthy lifestyle score and health-related quality of life among Chinese rural adults: variations in age, sex, education level, and income. Quality of Life Research. 2023; 32(1): 81–92. PubMed Abstract | Publisher Full Text

[21] 21. Salem M, Robenson J: The Impact of Socioeconomic Factors on Mental Health: A Conceptual Framework. Cureus. 2025; 17(7): e88244. Publisher Full Text

[22] 22. Nomatshila ZB: Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa. Dataset. Zenodo. 2026. Publisher Full Text

Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa

Abstract

Background

Objectives

Methods

Results

Keywords

Introduction

Methods

Research design

Study setting

Participants and sampling

Data collection

Data analysis

Results

Participants characteristics

Table 1. Socio-demographic information of study participants.

Self-rated health status

Figure 1. Self-rated health status distribution among respondents.

Quality of life scores according to domains

Table 2. QoL Scores according to QoL domains for study participants.

Repeated measures ANOVA and pairwise comparisons of mean score differences between WHOQOL-BREF domains

Table 3. Bonferroni post-hoc test results of pairwise comparison of mean score differences between the four QoL domains.

Mean scores for the WHOQOL-BREF Domains by socio-demographic variables

Table 4. Mean scores for the WHOQOL-BREF Domains by socio-demographic variables.

Table 5. Mean scores and standard deviations for WHOQOL-BREF Domains (Physical, Psychological, Social, and Environmental) by socio-demographic variables.

Discussion

Strengths and limitations

Conclusions

Ethics

Informed consent

Data availability

Extended Data

Acknowledgements

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated

Quality of Life of People Living with Virally Suppressed HIV in the Eastern Cape Province of South Africa 