Gender disparities in health-related quality of life and its predictors among adults on HAART at public health facilities of southern Ethiopia, 2022: A comparative cross-sectional study

doi:10.21203/rs.3.rs-3942226/v1

Background

Health-Related Quality of Life (HRQoL) has been widely used in the era of Highly Active Antiretroviral Therapy (HAART) to assess the impacts and success, as well as the physical, psychological, and social implications of treatment on people living with HIV/AIDS. Identifying and addressing gender disparities in HRQoL is a critical tool in combatting the AIDS epidemic by 2030. Hence, this study aimed at assessing gender disparities in HRQoL among clients on HAART in southern Ethiopia, in 2022.

Methods

A facility-based comparative cross-sectional study was carried out from July 1 – October 30, 2022. A total of 1179 clients (590 males and 589 females) were selected randomly. Pre-tested interviewer-administered questionnaires and a data abstraction checklist were used to collect the data. The data were entered into EpiData3.1 and exported to SPPS version 23 for analysis. HRQoL was measured using the World Health Organization's Quality of Life HIV short-form (WHOQOL-HIV BREF) tool. χ2 test was computed to see a significant difference in overall HRQoL across males and females. A multivariable regression model was fitted to identify determinants of HRQoL. The adjusted odds ratios (AOR) with the corresponding 95% confidence intervals (95% CI) were used to report determinants of HRQoL. Statistically significant variables in the final model were declared at p-value < 0.05.

Results

The overall mean (±SD) score of HRQoL was 11.14(±1.87) in which more than half (55.8%) of the clients had a good HRQoL. There was a significant difference in good HRQoL between males (60.5%) and females (51.1%) (χ2=21.57, p <0.001). Being urban residents (AOR= 1.86, 95% CI; 1.36, 2.54), higher educational level education (AOR=5.31, 95% CI; 2.92, 9.66), and having a current CD4 count of ≥500 cells/mm3 (AOR= 2.26, 95% CI; 1.43, 3.58) were positive predictors of a good HRQoL. On the other hand, the presence of opportunistic infection (AOR=0.67, 95% CI; 0.45, 0.89), and being a hazardous alcohol consumer (AOR = 0.73, 95% CI = 0.53, 0.92) were negative predictors.

Conclusion

Overall HRQoL was found to be low in the study area, with females having significantly lower scores in the majority of domains and overall HRQoL. Due emphasis should be given to those clients with no formal education and who came from rural areas. HAART service providers, addiction counsellors, and psychiatrists should collaborate in offering education on healthy living behaviours, coping mechanisms, and peer support for hazardous alcohol users.

Infectious Diseases

Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome(HIV/AIDS) is one of the major global public health challenges because of its high morbidity and mortality rates, as well as its detrimental effects on human well-being and quality of life[1][1][1]. As reported by the United Nations Programme on HIV/AIDS (UNAIDS), an estimated 37.6 million people globally were living with HIV in 2020, with 35.9 million of them being adults[2][2][2]. In 2020, more than 690,000 people died from HIV-related causes, despite a 39% decrease since 2010[3][3][3]. The disease is most prominent (95%) in low and middle-income countries, with Sub-Saharan Africa (SSA) accounting for an estimated 70% of People living with HIV/AIDS (PLWHA) [2, 4] [2, 4] [2, 4]. When compared to men, women in the SSA region are disproportionately affected by HIV/AIDS, accounting for 59% of all infections in the region [5][5][5]. Ethiopia is one of the countries severely struck by HIV/AIDS, which is endangering the country's overall progress. In 2016, it was estimated that 740, 251 Ethiopians were infected with the virus, with 442,895 (59.8%) of them being females[6][6][6]. More than two-thirds (67%) were receiving antiretroviral therapy at the end of 2019, a rate that has more than tripled since 2010[2, 7][2, 7][2, 7].

HIV/AIDS has a wide range of repercussions, comprising personal sufferings and discomforts related to the disease's progression, social, emotional, and psychological consequences, and related stigma[8, 9]. On the other hand, the treatment has an unfavourable effect on patients' quality of life, with up to 50% of people on Highly Active Antiretroviral Therapy (HAART) may experience drug side effects, making it difficult to adhere to the regimen[10]. Generally, the quality of life deteriorates as the HIV disease advances[11].

Quality of life (QoL) is defined by the World Health Organisation(WHO) as "individuals' views of their place in life in the context of the values and culture in which they live, and regarding their goals, desires, standards, and concerns." [12, 13] [12, 13] [12, 13]. Health-related Quality of Life (HRQoL) refers to how people's health impacts their capacity to operate in daily life as well as their feeling of well-being in all of their physical, mental, environmental and social domains[14]. In the era of HAART, HRQoL has been widely employed for assessing the impacts and the success of treatment on various populations, rather than the conventional results like death, the number of survivors, the frequency of opportunistic infections, Clusters CD4 count, and viral load[15]. Furthermore, it has become an increasingly important tool for measuring the physical, psychological, and social consequences of HAART [16, 17].

Gender disparities have been shown to have an impact on HRQoL in PLWHA [9]. The United Nations General Assembly agreed, focusing on gender inequalities and addressing them as a crucial tool in combating the AIDS pandemic by 2030[2, 18][2, 18][2, 18]. Women's economic reliance on men, as well as the significant stigma and discrimination faced by HIV-infected women, could hinder their access to care, treatment, and supportive services[19][19][19]. If those inequities are left unaddressed, they may interfere with day-to-day functioning and result in difficulties in personal relationships and financial hardship among PLWHA, especially for women[20].

Even though HAART and its broad availability in many settings have lowered mortality among PLWHA, there are still challenges associated with poor HRQoL [21][21][21]. According to studies, PLWHA in Asian countries has a good QoL, ranging from 26–67% [22]. According to findings from Nigeria and Zambia, a large percentage of patients had a good or very good QoL[23, 24]. The findings from Ghana and Burkina Faso, PLWHA have a good QoL, with 79.75% and 82.4%, respectively[24, 25]. The magnitude of poor HRQoL ranges between 43% and 55%, according to studies conducted in Ethiopia [26–29]. Studies in northern and western Ethiopia looked at gender variations in the QoL and found that women had a lower QoL than men [30, 31].

As per studies, disease-related factors such as CD4 count, viral loads, HIV disease stage, and infections, and psychosocial factors such as social support, coping, and disclosure have been identified as predictors of QoL among HIV/AIDS clients [8, 32]. Depression has also been linked to alterations in general health perceptions, emotional well-being, and reduced overall HRQoL domains[33, 34][33, 34][33, 34].

Despite studies looking into HRQoL among clients on HAART in Ethiopia, the majority of them failed to quantify all over and each dimension across both genders concurrently[27, 29]. Comparative studies are well known for their importance in establishing gender disparities in HRQoL along with identifying areas where interventions could improve their QoL. In addition, most studies in the country failed to evaluate HRQoL by strictly following World Health Organization's Quality of life HIV short-form tool(WHOQoL-HIV-BREF) tool, implying that a genuine technique for measuring facet domains and major domains is necessary. Hence, the current study aimed at assessing gender disparities in HRQoL among clients on HAART in public health facilities in southern Ethiopia by using the WHOQoL-HIV-BREF tool.

Study design, area, and period

A comparative cross-sectional study was carried out at public health facilities of Hadiya Zone from July 1 – October 30, 2022. The zone is located 230 kilometres from Addis Ababa, the capital city of Ethiopia, and 194 kilometres from Hawassa, the capital of the Southern Nations, Nationalities, and People Region (SNNPR). There are one comprehensive and specialized hospital, four first-level hospitals, 59 government health centers, two non-governmental health centers, and 311 health posts in the zone. The total number of PLWHA in the zone was 2267, with 1201 and 1066 males and females, respectively.

The population of the study

The source population comprised all adult PLWHA enrolled in HAART centers of public health facilities in the Hadiya zone. Whereas the study population was made up of all randomly selected clients from the selected public health facilities. The study included all adults over the age of 15, and who had been on therapy for at least three months. Those clients who were severely ill at the time of data collection and those with inadequate or incomplete clinical records were excluded.

Sample size determination

The sample size for the two groups was estimated using Open Epi software version 2.3, taking into account the following parameters: power of 80%, confidence interval of 95%, a 1: 1 ratio of male to female on HAART, and mean(SD) of HRQoL( which was taken from related studies). After accounting for a 10% non-response rate, the maximum sample size for the study was 1,192(596 males and 596 females) (Table 1).

Table 1. Sample size determination for the study by using OpenEepi Version 2.3, 2022

Mean		SD		Difference	Power	95%CI	Ratio	NR	n1	n2	Total	Ref
Male	Female	Male	Female	Difference	Power	95%CI	Ratio	NR	n1	n2	Total	Ref
81.2	77	14.9	17.4	4.2	80	1.96	1:1	10	234	234	515	[35]
4.11	3.96	0.85	0.91	0.15	80	1.96	1:1	10	541	541	1192	[31][31][31]
3.5	3.0	1.1	1.0	0.5	80	1.96	1:1	10	70	70	154	[30]

Where, SD: standard deviation, n1, and n2: estimated sample size for males and females respectively before adding NR (non-response rate)

Sampling procedure

From a total of five hospitals and twenty HAART centers in the Hadiya zone, two public hospitals and ten HAART centers were selected by simple random sampling (Lottery method). A sampling frame was formed from a list of PLHIV who had an appointment during the two-the study period. Based on the number of patients on follow-up, the sample size was distributed proportionally throughout the health facilities. Study participants were selected based on their unique ART numbers using computer-generated random numbers (Figure 1).

Fig 1. Schematic presentation of sampling procedures followed to get clients on HAART in Southern Ethiopia, 2022

Data collection tools, methods, and personnel

A pretested interviewer-administered structured questionnaire and data abstraction checklist were used to collect data. A face-to-face interview was carried out to collect data on Socio-demographic (age, educational level, marital status, ethnicity, religion, occupation, and residence), behavioural (HIV serostatus disclosure, physical activity, smoking, and alcohol intake) and family-related (family support, current living status and serostatus of the family members) characteristics. Clinical information such as WHO clinical stages, CD4 count(recent and baseline), haemoglobin level, adherence to HAART, TB/HIV co-infection, current illness reported side effects, duration of stay on HAART, and the type of HAART regimen were collected by reviewing records of the HAART registration book and individual follow-up form.

HRQoL was assessed using the WHOQOL-HIV BREF[36]. For each item, a five-point Likert scale was used, with 1 and 5 representing the lowest (negative) and the highest (positive) perceptions respectively. For example, an item in the positive feeling facet asks “How much do you enjoy life?” and the available responses are 1 (not at all), 2 (a little) 3 (a moderate amount), 4 (very much), and 5 (an extreme amount). The six domains used to assess overall HRQoL were: physical health, psychological well-being, social relationships, environmental health, level of independence, and spiritual health. Two items focus on an individual's overall perception of quality of life, and overall perception of health were used to examine the general QoL (Table 2). The proposed reference period for each experience in each QOL category was two weeks[37](S1File).

Table 2. HRQoL domains with their respective facets and number of items, 2022

Domains	No. of items	List of Items	Number of questions
Domain I= Physical	4	1. Pain and discomfort	4
		2. Energy and fatigue	4
		3. Sleep and rest	4
		50. Symptoms of PLWHA*	4
Domain II=Psychological	5	4. Positive feelings	4
		5. Thinking, learning, memory, and concentration	4
		6. Self-esteem	4
		7. Bodily image and appearance	4
		8. Negative feelings	4
Domain III Level of Independence	4	9. Mobility	4
		10. Activities of daily living	4
		11. Dependence on medication or treatments	4
		12. Work capacity	4
Domain IV Social Relationships	4	13 Personal relationships	4
		14 Social support	4
		15 Sexual activity	4
		51 Social Inclusion	4
Domain V Environment	8	16. Physical safety and security	4
		17. Home environment	4
		18. Financial resources	4
		19. Health and social care: accessibility and quality	4
		20. Opportunities for acquiring new information and skills	4
		21. Participation in and opportunities for recreation/ leisure activities	4
		22. Physical environment	4
		23. Transport	4
Domain VI Spirituality/Religion/ Personal Beliefs	5	24. SRPB	4
		52. Forgiveness and Blame	4
		53. Concerns about the Future	4
		54. Death and Dying	4
		The overall quality of life and general health perceptions	4

* Facets highlighted in bold were specific to the PLWHA, and as such have been added to the original WHOQOL Instrument.

To assess the level of depression and stigma, the Beck Depression Inventory, Second Edition (BDI-II) [38] and Berger's HIV stigma scale (BHSS) [39] were used, which have been well-validated in most African countries. Alcohol consumption was assessed using the FAST alcohol screening test measurement scale[40][41][41]. WHO criteria for controlling and monitoring the tobacco epidemic tool was used to assess the status of smoking[41][42][42]. Anthropometric data (weight and height) were used to assess clients' nutritional status. Weight was measured using a standard beam balance, in light clothing and bare feet. The beam balance was reset to zero scale before each measurement and the readings were recorded to the nearest 0.1 kg. A standard scale was used to measure height. Participants were told to remove their shoes, stand tall, and position themselves on the Frankfurt plane with their feet together and knees straight. The readings were recorded to the nearest 0.1 cm by touching the heels, buttocks, shoulder blades, and back of the head (occiput) against the stadiometer vertical stand.

Data quality management

Properly designed data collection instruments were provided after translation into the local language, Hadiyissa. The data collectors and supervisors were provided with intensive training that lasts two days on the objective of the study, the way of data collection, and how to deal with difficulties that may arise at the time of the data collection. A pre-test was done on 5% of the sample size (30 males and 30 females) at Worabe Comprehensive and specialized hospital one week before the actual data collection. Necessary corrections were made based on the result to avoid any confusion and for better completion of the questionnaires. The internal consistency of the WHOQOL-HIV-BREF instrument was measured and determined by using a Cronbach’s alpha. As a result, the Cronbach's alpha coefficients for physical, spiritual, independence, environmental, and social domains were 0.81, 0.83, 0.86, 0.88, and 0.84, respectively, and were all good enough. In addition the internal consistency for Bergen's scale, and the Beck Depression Inventory-Second Edition (BDI-II) were assessed and their Cronbach’s alpha value was 0.79 and 0.82 respectively. Throughout the data collection period, the principal investigator and supervisors gave on-site supervision. Every day, each questionnaire was checked for completeness, and the appropriate feedback was given to the data collectors. To minimize social desirability bias, study participants were interviewed privately.

Measurement of variables of the study

Outcome variable measurement

The outcome variable for the study was HRQoL which was measured by using (WHOQOL-HIV BREF)[36]. The domain scores were scaled upward, with a higher score representing a higher QoL. The mean score of items within each domain was used to compute each domain score.First, facet scores were developed by using summative scaling by taking the average of each item (Table 3).

Table 3: Calculation of the facet score for each item in all the six domains of HRQoL among PLWHA, 2022

Items	Calculating the facet score
1. Pain and discomfort	Pain = (f1.1 + f1.2 + f1.3 + f1.4)/4
2. Energy and fatigue	Energy = (f2.1 + f2.2 + f2.3 + f2.4)/4
3. Sleep and rest	Sleep = (f3.1 + f3.2 + f3.3 + f3.4)/4
50. Symptoms of PLWHA*	Symptom = (f50.1 + f50.2+ f50.3 + f50.4)/4
4. Positive feelings	Pfeel= (f4.1 + f4.2 + f4.3 + f4.4)/4
5. Thinking, learning, memory, and concentration	Cog = (f5.1 + f5.2 + f5.3 + f5.4)/4
6. Self-esteem	Esteem = (f6.1 + f6.2 + f6.3 + f6.4)/4
7. Bodily image and appearance	Body = (f7.1 + f7.2 + f7.3 + f7.4)/4 .
8. Negative feelings	Nfeel = (f8.1 + f8.2 + f8.3 + f8.4)/4 .
9. Mobility	Mobil = (f9.1 + f9.2 + f9.3 + f9.4)/4 .
10. Activities of daily living	Adl = (f10.1 + f10.2 + f10.3 + f10.4)/4 .
11. Dependence on medication or treatments	Depend = (f11.1 + f11.2 + f11.3 + f11.4)/4
12. Work capacity	Work = (f12.1 + f12.2 + f12.3 + f12.4)/4
13 Personal relationships	relation = (f13.1 + f13.2 + f13.3 + f13.4)/4
14 Social support	Support = (f14.1 + f14.2 + f14.3 + f14.4)/4
15 Sexual activity	sex = (f15.1 + f15.2 + f15.3 + f15.4)/4
51 Social Inclusion	Inclusi= (f51.1 + f51.2 + f51.3 + f51.4)/4
16. Physical safety and security	Safe = (f16.1 + f16.2 + f16.3 + f16.4)/4
17. Home environment	Home = (f17.1 + f17.2 + f17.3 + f17.4)/4
18. Financial resources	Finance = (f18.1 + f18.2 + f18.3 + f18.4)/4
19. Health and social care: accessibility and quality	Care = (f19.1 + f19.2 + f19.3 + f19.4)/4
20. Opportunities for acquiring new information and skills	Info = (f20.1 + f20.2 + f20.3 + f20.4)/4
21. Participation in and opportunities for recreation/ leisure activities	Leisure = (f21.1 + f21.2 + f21.3 + f21.4)/4
22. Physical environment	Enviro = (f22.1 + f22.2 + f22.3 + f22.4)/4
23. Transport	Trans = (f23.1 + f23.2 + f23.3 + f23.4)/4
24. Spirituality, Religion, and Personal Beliefs	Srpb = (f24.1 + f24.2 + f24.3 + f24.4)/4
52. Forgiveness and Blame	Forgive = (f52.1 + f52.2 + f52.3 + f52.4)/4
53. Concerns about the Future	Future = (f53.1 + f53.2 + f53.3 + f53.4)/4
54. Death and Dying	Death = (f54.1 + f54.2 + f54.3 + f54.4)/4
The overall QoL and general health perceptions	General = (g.1 + g.2 + g.3 + g.4)/4

The next step was to construct domain scores by taking the mean of the facet scores estimated in the previous stage.The mean scores were then multiplied by four to create a domain score comparable to the WHOQOL-100 scores and resulting in a range of four to twenty. HRQoL was dichotomized as poor or good by using the mean of each domain as a cut-off point. Individuals who scored below the mean in each of the six domains will be labeled as having a poor QoL.

Domain1 = (pain + energy + sleep + symptom) / 4 * 4

Domain2 = (pfeel + cog + esteem + body + nfeel)/5 * 4

Domain3 = (mobil + adl + depend + work)/4 * 4

Domain4 = (relatio + support + sex + inclusi)/4 * 4

Domain5 = (safe + home + finance + care + info + leisure + enviro + rans)/8*4

Domain6 = (forgive + future + death + srpb)/4 *4

Explanatory variables

Psychosocial Support from Family Members: It is family or friend support for the PLHIV in terms of psychological, financial, or adherence aid[31][31][31].

Perceived stigma: Berger’s HIV stigma scale(HSS-40) was used to assess how PLWHA feel about four dimensions of stigma: (a) personalized stigma (or acted stigma), (b) concerns about disclosing one's own HIV serostatus, (c) negative self-image (self-stigma), and (d) concerns about public attitudes towards PLWHA. There were 40 items on the scale, each having a 4-point Likert-type response as strongly disagree (=1), disagree (=2), agree (=3), and strongly agree (=4). The scores were scaled in a positive direction, suggesting that the higher the score, the more stigma there is. The composite index of the total stigma score varies from 40 to 160. Low, middle, and high-level stigma were defined as values between the 25^th and 50^th (40-80), 50^th and 75^th (81-120), and greater than the 75^th percentiles (121-160), respectively [77, 78].

Level of depression: The BDI-II was used to determine the severity of depression. It had 21 questions with a scale of 0 to 3, meaning the lowest possible total score is 0 and the greatest possible total for the entire test is 63. BDI-II: a score of 0–10 indicates no depression/normal, whereas a score of more than 11 indicates depression [38].

Nutritional status: Was assessed by computing Body Mass Index (BMI) using weight and height measurements, and typical cut-off points of <18.5 kg/m2 considered underweight, 18.5–24.9 kg/m2 considered normal, and greater than or equal to 25 kg/m2 considered overweight.

Psychosocial support outside family members. It is support for the PLHIV outside family members like governmental or non-governmental organizations, religious-based organizations, and community-based organizations in terms of psychological, financial, material, or spiritual support.

Current smoking status: Smokers and non-smokers were classified based on WHO criteria for controlling and monitoring the tobacco epidemic [41][42][42]. A smoker is someone who uses tobacco products on a daily or occasional basis, whereas a non-smoker is someone who does not use tobacco products at all. Non-smokers include ex-smokers, never-smokers, and ex-occasional smokers.

Alcohol consumption: Alcohol consumption was assessed using the FAST alcohol screening test measurement scale which has 4 questions and a 5-point Likert scale. For the 1^st, 2^nd, and 3^rd questions, 0 to 4 Likert scales were used as (0 = never, 1 = Less than monthly, 2 = monthly, 3 = weekly, 4 = daily or almost daily). However, for the 4^th question, we used 0 for No, 2 for Yes (on one occasion), and 3 for Yes (on more than one occasion) and categorized it into two categories. The [40][41][41]. A composite index was formed with a minimum and a maximum score of 0 and 16 respectively. Finally, it was dichotomized as non-hazardous drinkers (<3), and hazardous drinkers(≥ 3) [40][41][41].

Data analysis

The data were entered into EpiData version 3.1 and then exported to SPSS version 23 for analysis. The WHO-HRQoL-HIV-BREF instrument was rigorously followed to compute the facet and domain scores[36, 37]. The original 40-item Berger HIV-stigma scale will be conducted via exploratory factor analysis (EFA) utilizing the original 4-component structure (Personalized Stigma, Disclosure Concerns, Negative Self-Image, and Public Attitudes) [39]. The factor loading (lambda) was fixed at 0.6 in the EFA to guide item retention and shorten the scale. We then removed items with factor loadings <0.6 and items deemed redundant by our expert panel to produce the abridged scale. Descriptive statistics namely frequency, percentage, mean and standard deviation were computed. Chi-square testing was done to see if there was any significant difference in the outcome of interest and covariates across males and females. Accordingly, a statistically significant difference in HRQoL was observed between the two groups (χ2=21.57, p <0.001), and therefore, three models were fitted separately for the whole study participants, males, and females. To identify predictors of good HRQoL, bivariable logistic regression analysis was carried out at first, and factors that showed association at p-value<0.25 were entered into a multivariable logistic regression model. The reason we chose logistic regression over linear regression was that our data did not meet the fundamental assumptions of linear regression, like normality and constant variance of residuals[42]. In such instances, logistic regression is a reliable choice for modeling by transforming the continuous variable to binary outcomes. The adjusted odds ratio with the corresponding 95% confidence interval was reported and significant predictors were declared at p-value<0.05. A Variance Inflation Factor (VIF) was used to test for multicollinearity across the covariates and found none (i.e. the VIF ranged from 1.02 to 2.27 with a mean of 1.19). Finally, the goodness of fit of the final model was checked using Hosmer and Lemeshow statistics.

Ethical consideration and consent to participate

Ethical clearance was obtained from the institutional review board (IRB) of Wachamo University, through the Office of Research, and Community Service Vice President with a reference number WCU /321/22. Permission was also obtained from each district Health office and respective health facilities with HAART centers. Respondents were well informed about the objective and purpose of the study and written informed consent was obtained from each respondent of age 18 years. Those under the age of 18 gave their consent through their parents or guardians. A unique ID number was assigned to keep the information confidential. Furthermore, respondents were told that the information they gave would be utilized solely for research purposes and would not be given to anybody outside of the study team. Personal protective equipment was provided for data collectors because the study is taking place in the midst of a global pandemic, COVID-19.

Sociodemographic characteristics of the respondents

A total of 1179 clients (590 males and 589 females) took part in the study which yielded a response rate of 98.9%. The majority of the respondents, 792 (67.2%), were attending their follow-up at the Hospitals followed by 387 (32.8%) at Health Center. The mean (± SD) age of the respondents was 31.36(SD ± 4.71), with 32.58(± 4.31) for males and 30.13(± 4.78) for females. In terms of educational status, 183 (15.5%) of respondents had no formal education, with males and females accounting for 12.9% and 18.1% respectively. The majority, 674(57.2%) of the respondents were protestant religion followers, 380(64.5%) for males and 294(49.9%) for females (Table 4).

Table 4

Sociodemographic characteristics of clients on HAART, in public health facilities of Hadiya Zone, Southern Ethiopia, 2022.
Variable categories	Male (n = 590)	Female (n = 589)	Total = 1179	Test statistics
Variable categories	n(%)	n(%)	n(%)	Test statistics
Age (n = 1075)				χ2 = 0.056 P = 0.432
15–24	31(5.2)	75(12.7)	105(9.0)
25–34	401(68.0)	432(73.3)	814(69.0)
>=35	158(26.8)	82(13.9)	260(22.0)
Mean(± SD) age	32.58(4.31)	30.13(± 4.78)	31.36(± 4.71)
Marital status
Single	85(14.4)	95(16.1)	180(15.4)	χ2 = 0.952 P = 0.202
Married	301(51.0)	288(48.9)	589(49.9)
Divorced	148(25.1)	159(27.0)	307(26.0)
Widowed	56(9.5)	47(8.0)	103(8.7)
Ethnicity
Hadiya	416(70.5)	373(63.3)	789(66.9)	χ2 = 2.02 P = 0.568
Kembata	126(21.3)	144(24.4)	270(22.9)
Silte	31(5.2)	57(9.7)	88(7.5)
Amhara	17(2.9)	15(2.5)	32(2.7)
Educational status
No formal education	76(12.9)	107(18.1)	183(15.5)	χ2 = 10.95 P < 0.012
Primary education	338(57.3)	290(49.2)	628(53.3)
Secondary education	121(20.5)	121(20.5)	242(20.5)
College and above	55(9.3)	71(12.0)	126(10.7)
Religion				χ2 = 27.38 P < 0.001
Protestant	380(64.5)	294(49.9)	674(57.2)
Orthodox	169(28.6)	252(42.8)	421(35.7)
Muslim	41(6.9)	43(7.3)	84(7.1)
Occupation
Unemployed	108(18.3)	106(18.0)	214(18.2)	χ2 = 5.75 P = 0.451
Farmer	148(25.0)	133(22.6)	281(23.8)
Merchant	121(20.5)	139(23.6)	260(22.0)
Govt employee	65(11.0)	76(12.9)	141(12.0)
Daily laborer	93(15.8)	73(12.4)	166(14.1)
Student	44(7.5)	50(8.5)	94(8.0)
Driver	11(1.9)	12(2.0)	23(1.9)
Residence
Urban	382(64.7)	377(64.0)	759(64.3)	χ2 = 15.62 P = 0.032
Rural	208(35.2)	212(36.0)	420(35.6)	χ2 = 15.62 P = 0.032
Wealth index				χ2 = 11.62 P < 0.001
Richest	119(20.2)	121(205)	240(20.3)
Richer	116(19.7)	116(19.7)	232(19.7)
Middle	107(18.1)	127(21.6)	234(19.8)
Poorer	130(22.0)	114(19.3)	244(20.6)
Poorest	118(20.0)	111(18.8)	229(19.4)

Clinical and behavioural characteristics of the respondents

Nearly two-thirds, 756(64.1%) of clients were symptomatic. Nearly nine out of 10 respondents (86.3%) had a baseline CD4 + cell count of 200 cells/mm3, and 89.5% had a recent CD4 + cell count of 500 cells/mm3 or above. Lypodystrophy was recorded for 86 clients 265(22.5%). More than one-third (35.4%) of clients had a history of regimen change, with males and females accounting for 34.7% and 36.2%, respectively (χ2 = 17.38, p < 0.021). A total of 507 (42.9%) participants, 278 (47.1%) males and 229 (33.9%) females, reported a history of opportunistic infection (χ2 = 42.02, p = 0.008. More than one-fifth (22.0%) of clients were hazardous alcohol consumers (Table 5).

Table 5

Clinical and behavioural characteristics of clients on HAART, in public health facilities of Hadiya Zone, Southern Ethiopia, 2022.
Clinical characteristics of respondents	Male (n = 590)	Female (n = 589)	Total = 1179	Test statistics
Clinical characteristics of respondents	n(%)	n(%)	n(%)	Test statistics
Serostatus
Asymptomatic	44(7.5)	128(21.8)	172(14.6)	χ2 = 71.183 p < 0.032
Symptomatic	377(63.9)	379(64.3)	756(64.1)
AIDS converted	169(28.6)	82(13.9)	251(21.3)
Baseline CD₄⁺ cell count				χ2 = 3.76 p = .032
≥ 200 cells/ mm³	92(15.6)	69(11.7)	161(13.7)
< 200 cells/ mm³	498(84.4)	520(88.3)	1018(86.3)
Current CD₄⁺ Cell Count				χ2 = 15.237 p = 0.014
< 500 cells/ mm³	50(8.5)	74(12.6)	124(10.5)
≥ 500 cells/ mm³	540(91.5)	515(87.4)	1055(89.5)
Duration of HAART
≥ 36 months	328(55.6)	298(50.6)	626(53.1)	χ2 = 12.02 p = 0.038
< 36 months	262(44.4)	291(49.4)	553(45.2)	χ2 = 12.02 p = 0.038
History of Opportunistic Infection
No	312(52.9)	360(61.1)	672(57.0)	χ2 = 42.02 p = 0.008
Yes	278(47.1)	229(33.9)	507(43.0)	χ2 = 42.02 p = 0.008
Types of opportunistic infection
Skin infection	245(88.1)	201(87.8)	446(87.9)	χ2 = 0.838 P < 0.416
TB	11(3.9)	21(9.2)	32(6.3)
Others	24(8.6)	13(5.7)	37(7.3)
Regimen Change
Yes	205(34.7)	213(36.2)	418(35.4)	χ2 = 17.38 p < 0.021
No	385(65.3)	376(63.8)	761(64.6)	χ2 = 17.38 p < 0.021
History of smoking
Yes	61(10.3)	39(6.8)	99(8.4)
No	529(89.7)	549(93.2)	1078(91.4)
Alcohol consumption
Hazardous	134(22.7)	125(21.2)	259(22.0)	χ2 = 7.534 p = 0.042
Non-hazardous	456(77.3)	464(78.8)	920(78.0)	χ2 = 7.534 p = 0.042

Disparity in the mean facets scores across males and females

Summative scaling was used to obtain facet scores. Each item had an equal impact on the facet score. Accordingly, there was a significant difference in the mean (± SD) score of sleep and rest between males and females, 3.01(± 0.33) and 2.72(± 0.48), respectively. Facets with the highest and the lowest mean scores were sexual activity, and personal relationship at 3.03(± 0.85), and 2.60(± 0.48) respectively (Table 6).

Table 6

The facet score for each item in all the six domains of HRQoL among PLWHA in public health facilities of Hadiya zone, southern Ethiopia, 2022
Domains	Facets	Male (n = 590)	Female (n = 589)	Total = 1179
		Mean(± SD)	Mean(± SD)	Mean(± SD)
Domain 1	Pain and discomfort	2.60(0.48)	2.24(0.55)	2.42(0.54)
	Energy and fatigue	2.85(0.51)	2.46(0.54)	2.66(0.56)
	Sleep and rest	3.01(0.33)	2.72(0.48)	2.89(0.43)
	Symptoms of PLWHA	2.76(0.39)	2.52(0.50)	2.64(0.47)
Domain 2	Positive feelings	3.12(0.43)	2.80(0.62)	2.96(0.56)
	Thinking, learning, memory, and concentration (cognitive)	2.85(0.41)	2.71(0.38)	2.79(0.39)
	Self-esteem	2.85(0.65)	2.71(0.45)	2.78(0.56)
	Bodily image and appearance	2.96(0.36)	2.78(0.49)	2.87(0.44)
	Negative feelings	2.85(0.50)	2.74(0.53)	2.80(0.52)
Domain 3	Mobility	2.83(0.52)	2.73(0.48)	2.78(0.50)
	Activities of daily living	2.84(0.57)	2.48(0.58)	2.66(0.60)
	Dependence on medication or treatments	2.66(0.49)	2.54(0.46)	2.60(0.43)
	Work capacity	2.93(0.70)	2.89(0.48)	2.91(0.60)
Domain 4	Personal relationships	2.73(0.52)	2.48(0.39)	2.60(0.48)
	Social support	2.78(0.37)	2.57(0.43)	2.67(0.42)
	Sexual activity	3.14(0.83)	2.92(0.87)	3.03(0.85)
	Social Inclusion	2.82(0.78)	2.67(0.68)	2.74(0.74)
Domain5	Physical safety and security	2.85(0.86)	2.64(0.39)	2.75(0.68)
	Home environment	3.18(0.81)	2.74(0.51)	2.96(0.71)
	Financial resources	3.05(0.85)	2.66(0.44)	2.85(0.70)
	Health and social care	2.85(0.53)	2.64(0.32)	2.74(0.45)
	Opportunities for acquiring new information and skills	2.72(0.69)	2.59(0.53)	2.66(0.62)
	Leisure activities	3.17(0.59)	2.72(0.48)	2.99(0.57)
	Physical environment	2.76(0.60)	2.44(0.54)	2.60(0.59)
	Transport	3.20(0.65)	2.89(0.64)	3.05(0.66)
Domain6	Spirituality, Religion and Personal Beliefs	2.90(0.71)	2.76(0.53)	2.84(0.63)
	Forgiveness and Blame	2.97(0.56)	2.77(0.63)	2.87(0.60)
	Concerns about the Future	2.99(0.53)	2.71(0.59)	2.85(0.58)
	Death and Dying	3.12(0.57)	2.76(0.66)	2.94(0.64)
	The overall QoL and general health perceptions	3.06(0.56)	2.67(0.58)	2.87(0.60)

Differences in the mean scores of HRQoL domains across males and females

The result showed that the average scores of females for all six domains and two general questions were lower than the males’ scores on the 4–20 scales. Males had a greater QoL scores across all domains, except for social relationship and spiritual/personal belief domains. The overall mean (± SD) score of HRQoL was 11.14(± 1.87), with 11.16(± 1.86) for males and 10.85(± 1.69) for females. Relatively a huge difference was observed in the mean (± SD) score of physical domain between males and females at 11.84(± 1.48) and 10.01(± 1.82) respectively (Table 7).

Table 7

The difference in the mean score of HRQOL domains across males and females on HAART in public health facilities of Hadiya Zone, southern Ethiopia, 2022
Domain	Male (n = 590)	Female (n = 589)	Total = 1179
Domain	Mean(± SD)	Mean(± SD)	Mean(± SD)
Physical domain	11.84(1.48)	10.01(1.82)	10.91(1.77)
Psychological	11.72(1.55)	11.02(1.64)	11.36(1.64)
Level of Independence	11.26(2.09)	10.66(1.88)	10.96(2.01)
Social Relationships	11.48(2.25)	10.65(2.27)	11.06(2.29)
Environmental	11.48(2.25)	10.72(1.68)	10.63(1.87)
Spirituality/Religion/ Personal Beliefs	11.90(2.57)	11.01(2.22)	11.50(2.24)
Overall HRQoL	11.16(1.86)	10.85(1.69)	11.14(1.87)

The overall HRQoL among Clients on HAART

HRQoL was measured by using the WHOQOL-HIV BIEF tool that contains 31 questions distributed into 6 domains. Accordingly, more than half, 658(55.8%) of the study participants had a good overall HRQoL. The magnitude was higher among men (60.5%) as compared to women (51.1%) (χ2 = 21.57, p < 0.001) (Fig. 2).

Figure 2: The magnitude of HRQoL among clients on HAART in public health facilities of Hadiya Zone, southern Ethiopia, 2022

Determinants of HRQoL

Three different models (multivariable logistic regression) were fitted to look at determinants of HRQoL. The first model was used to identify the factors associated with the client's overall HRQoL. As a result, marital status, sex, residence, educational status, current CD4 count, opportunistic infection, and adherence were found as significant predictors of good HRQoL. The odds of having a good HRQoL were 2.12 times higher among male clients than female ones (AOR = 2.12, 95% CI; 1.60, 2.80). Clients with a recent CD4 count of 500 cells/mm3 or higher were 2.26 times more likely to have good HRQoL than those with a recent CD4 level of < 500 cells/mm3 (AOR = 2.26, 95% CI; 1.43, 3.58). Clients with any opportunistic infection were 33% less likely to have good HRQoL than those without any OIs (AOR = 0.67, 95% CI; 0.45, 0.89). Participants who attend college and above were 5.31 times more likely to have good HRQoL than those who had no formal education (AOR = 5.31, 95% CI; 2.92, 9.66). Respondents in a marital relationship had 1.45 higher odds of having a good HRQOL as compared to their counterparts (AOR = 1.45, 95% CI; 1.10, 1.89). When compared to non-hazardous alcohol drinkers, hazardous alcohol consumers were 27% less likely to exhibit a good HRQoL (AOR = 0.73, 95% CI = 0.53, 0.92) (Table 8).

Table 8

Results of bivariable and multivariable logistic regression analysis to identify determinants of good HRQoL among clients on HAART in public health facilities of Hadiya Zone, Southern Ethiopia, 2022
Variable categories	HRQOL		COR(95%CI)	AOR(95%CI)	P-value
Variable categories	Good (%)	Poor (%)	COR(95%CI)	AOR(95%CI)	P-value
Age (n = 1075)
15–24	80(76.2)	25(23.8)	1.32(0.78, 2.22)	1.59(0.87, 2.90)	.132
25–34	394(48.4)	420(51.6)	0.39(0.29, 0.52)	0.69(0.47, 1.00)	.050
>=35	184(70.8)	76(29.2)	1	1
Sex
Male	377(63.9)	213(36.1)	1.94(1.54, 2.45)*	2.12(1.60, 2.80)^**	< 0.001
Female	281(47.7)	308(52.3)	1	1
Marital status
In marital relationship	351(59.6)	238(40.4)	1.36(1.08, 1.71)*	1.45(1.10, 1.89) ^**	0.007
Not in a marital relationship	307(52.0)	283(48.0)	1
Educational status
College and above	101(80.1)	25(19.9)	3.99(2.36, 6.75)*	5.31(2.92, 9.66) ^**	< 0.001
Secondary education	183(75.6)	59(24.4)	3.07(2.03, 4.63)*	4.95(2.79, 8.78) ^**	< 0.001
Primary education	282(44.9)	346(55.1)	0.81(0.58, 1.12)*	2.03(1.31, 3.13) ^**	< 0.001
No formal education	92(50.3)	91(49.7)	1	1
Residence
Urban	457(60.2)	302(39.8)	1.65(1.29, 2.09)*	1.86(1.36, 2.54)	0.013
Rural	201(47.9)	219(52.1)	1	1
Wealth index
Richest	122(50.8)	118(49.2)	0.79(0.54, 1.13)
Richer	128(55.2)	104(44.8)	0.94(0.65, 1.35)
Middle	139(59.4)	95(40.6)	1.11(0.77, 1.61)
Poorer	139(57.0)	105(43.0)	1.01(0.70, 1.45)
Poorest	130(56.8)	99(43.2)	1
Baseline CD₄⁺ cell count
≥ 200 cells/ mm³	89(55.3)	72(44.7)	0.87(0.69, 1.06)	0.89(0.59, 1.33)	0.574
< 200 cells/ mm³	569(55.9)	449(44.1)	1	1
Current CD₄⁺ cell Count
≥ 500 cells/ mm³	623(59.0)	432(41.0)	3.67(2.43, 5.52)*	2.26(1.43, 3.58)^**	0.012
< 500 cells/ mm³	35(28.2)	89(71.8)	1	1
Duration of HAART
≥ 36 months	349(55.7)	277(44.2)	0.99(0.79, 1.25)*	0.94(0.72, 1.22)	0.631
< 36 months	309(55.9)	244(44.1)	1	1
History of Opportunistic Infection
Yes	246()	261()	0.59(0.47, 0.76)*	0.67(0.45, 0.89)^**	0.002
No	412()	260()	1
Regimen Change
Yes	238(56.9)	180(43.1)	1.07(0.84, 1.37)
No	420()	341()	1
History of smoking
No	478(44.3)	600(55.7)	0.92(0.61, 1.40)
Yes	57(57.6)	42(42.4)	1
Alcohol consumption
Hazardous	128(49.4)	131(50.6)	0.72(0.54, 0.95)*	0.73(0.53, 0.92)^**	0.028
Non-hazardous	530(57.6)	390(42.4)	1	1
Key: 1: reference category, AOR: adjusted odds ratio, COR: Crude odds ratio, ^* significant at p-value < 0.25, ^**significant at p-value < 0.05

The second model was fitted only for males, and five variables namely, educational status, residence, adherence to HAART, and alcohol consumption were identified as significant predictors of overall HRQoL. When compared to males with no formal education, the odds of having high HRQoL were 5.01 (AOR = 5.01, 95% CI; 1.97, 12.76) and 2.69 (AOR = 2.69, 95% CI; 1.15, 4.33) times higher among those who attended college and above and secondary education, respectively. Male clients from urban were 3.13 times more likely than their rural counterparts to have a good HRQoL (AOR = 3.13, 95% CI; 1.43, 3.58). When compared to non-hazardous alcohol drinkers, hazardous alcohol consumers were 41% less likely to exhibit a good HRQoL (AOR = 0.59, 95% CI = 0.37, 0.93) (Table 9)

Table 9

Results of bivariable and multivariable logistic regression analysis to identify determinants of good HRQoL among male clients on HAART, Southern Ethiopia, 2022
Variable categories (n = 590)	HRQOL		COR(95%CI)	AOR(95%CI)	P-value
Variable categories (n = 590)	Good (%)	Poor (%)	COR(95%CI)	AOR(95%CI)	P-value
Age
15–24	12	38	0.84(0.39, 1.78)	0.74(0.32, 1.71)	.493
25–34	198	189	0.28(0.18, 0.43)	0.49(0.29, 1.03)	.081
>=35	121	32	1	1
Sex
Marital status
In marital relationship	187	114	1.15(0.82, 1.59)	1.17(0.79, 1.72)	0.434
Not in marital relationship	170	119	1	1
Educational status
College and above	53	6	7.64(2.90, 20.11)	5.01(1.97, 12.76)^**	< 0.001
Secondary education	120	19	5.46(2.78, 10.75)	2.69(1.15, 4.33)^**	0.023
Primary education	147	176	0.72(0.43, 1.22)	1.37(0.87, 2.62)	0.398
No formal education	37	32	1	1
Residence
Urban	278	104	4.36(3.05, 6.25)	3.13(1.83, 6.81)^**	< 0.001
Rural	79	129	1	1
Wealth index
Richest	71	48	0.88(0.52, 1.48)	1.08(0.59, 1.98)	0.333
Richer	67	49	0.81(0.48. 1.37)	0.85(0.46, 1.56)	0.214
Middle	64	43	0.88(0.52, 1.51)	0.95(0.51, 1.78)	0.139
Poorer	81	49	0.98(0.58, 1.64)	1.09(0.59, 1.99)	0.236
Poorest	74	44	1
Baseline CD₄⁺ cell count
≥ 200 cells/ mm³	55	37	0.96(0.61, 1.52)
< 200 cells/ mm³	302	196	1	1
Current CD₄⁺ cell Count
≥ 500 cells/ mm³	340	209	2.29(1.20, 4.37)	1.35(0.64, 2.82)	0.427
< 500 cells/ mm³	17	24	1	1
Duration of HAART
≥ 36 months	206	122	1.24(0.89, 1.73)*	1.13(0.76, 1.67)	0.538
< 36 months	151	111	1	1
History of Opportunistic Infection
No	186	134	0.80(0.57, 1.12)*	0.90(0.61, 1.33)	0.604
Yes	171	99	1
Regimen Change
Yes	130	75	1.20(0.85, 1.71)	1.28(0.85, 1.94)	0.235
No	227	158	1	1
History of smoking
No	317	212	0.75(0.42, 1.31)
Yes	40	20	1
Alcohol consumption
Hazardous	64	70	0.51(0.34, 0.75)*	0.59(0.37, 0.93)**	0.025
Non-hazardous	293	163	1	1
Key: 1: reference category, AOR: adjusted odds ratio, COR: Crude odds ratio, ^* significant at p-value < 0.25, ^**significant at p-value < 0.05

The third and final model was fitted to identify determinants of HRQoL among females. Accordingly, residence, marital status, education level, current CD4 level, history of opportunistic infections, and adherence to HAART were associated with HRQoL. The odds of having a good HRQoL were 2.31 times higher among married females as compared to their unmarried counterparts (AOR = 2.31, 95% CI = 1.48, 3.63). Women with a college education or above were 3.79 times more likely to have good HRQoL than women with no formal education (AOR = 3.79, 95% CI; 2.67, 9.79). Females with a current CD4 count of ≥ 500 cells/mm3 were 4.06 times more likely to have a good HRQoL than women with a CD4 count of < 500 cells/mm3 (AOR = 4.06, 95% CI; 2.04, 8.08). When comparing female clients who were diagnosed with any OIs to their counterparts who were not diagnosed, the odds of having a good HRQoL decreased by 75% (AOR = 0.35, 95% CI; 0.22, 0.57) (Table 10).

Table 10

Results of bivariable and multivariable logistic regression analysis to identify determinants of good HRQoL among female clients on HAART, Southern Ethiopia, 2022
Variable categories	HRQOL		COR(95%CI)	AOR(95%CI)	P-value
Variable categories	Good (%)	Poor (%)	COR(95%CI)	AOR(95%CI)	P-value
Age (n = 590)
15–24	40	16	1.58(0.78, 3.17)^*	1.74(0.96, 4.09)	0.061
25–34	196	231	0.63(0.44, 1.27)	0.67(0.35, 1.28)	0.131
>=35	65	41	1	1
Marital status
In marital relationship	164	124	1.58(1.14, 2.19)^*	2.31(1.48, 3.63)^**	0.434
Not in marital relationship	137	164	1	1
Educational status
College and above	53	13	5.30(2.60, 10.78) ^*	3.79(2.67, 9.79)^**	< 0.001
Secondary education	63	40	2.05(1.19, 3.52) ^*	2.92(1.88, 6.63) ^**	0.013
Primary education	137	70	1.03(0.67, 1.59)	1.55(1.29, 3.01)^**	0.028
No formal education	50	65	1	1
Residence
Urban	204	176	1.34(0.95, 1.87)^*	1.71(1.04, 2.83)	< 0.001
Rural	97	112	1	1
Wealth index
Richest	51	70	0.71(0.42, 1.20)
Richer	61	55	1.09(0.64, 1.83)
Middle	75	52	1.41(0.84, 2.37)
Poorer	58	56	1.02(0.60, 1.72)
Poorest	56	55	1
Baseline CD₄⁺ cell count
≥ 200 cells/ mm³	34	35	0.92(0.55, 1.52)^*	1.04(0.50, 2.15)	0.614
< 200 cells/ mm³	267	253	1	1
Current CD₄⁺ cell Count
≥ 500 cells/ mm³	283	223	4.58(2.64, 7.95) ^*	4.06(2.04, 8.08)^**	< 0.001
< 500 cells/ mm³	18	65	1	1
Duration of HAART
≥ 36 months	145	155	0.78(0.56, 1.27)
< 36 months	158	133	1
History of Opportunistic Infection
Yes	93	144	0.44(0.32, 0.63)*	0.36(0.22, 0.57)^**	0.006
No	208	144	1
Regimen Change
Yes	128	85	1.77(1.25, 2.48)*	1.36(0.87, 2.12)	0.169
No	173	203	1	1
History of smoking
No	283	266	1.38(0.71, 2.65)	1.66(0.68, 4.09)	0.266
Yes	17	22	1
Alcohol consumption
Hazardous	54	73	0.64(0.43, 0.96)*	0.69(0.41, 1.15)	0.150
Non-hazardous	247	215	1	1
Key: 1: reference category, AOR: adjusted odds ratio, COR: Crude odds ratio, ^* significant at p-value < 0.25, ^**significant at p-value < 0.05

The current study assessed the level of HRQoL and its determinants among clients on HAART in Southern Ethiopia. The study showed that 55.8% of clients had a good HRQoL. The finding was slightly higher than the findings from studies conducted in southwest Ethiopia (46.5%)[27] and northern Ethiopia (43.6%)[26, 31], and comparable to the finding of a study conducted in southern Ethiopia (52.9%)[29]. On the other hand, the finding was lower than the findings of studies conducted in Ghana(79.75%)[43], Burkina Faso(82.4%)[25], and Central India71.3%)[44]. This difference could be attributed to socioeconomic differences in the study populations as well as the method by which the outcome variables were measured, as the current study was conducted with a relatively large sample size and the outcome variables were measured in accordance with the WHO recommendation.

These results also revealed that there was a significant gender disparity in having a good HRQoL among male and female clients, in which females had a lower HRQoL than males. This was supported by a study conducted in LMICs[45], United States of America[46], and other primary studies conducted in northern Ethiopia[31][31][31], southwest Ethiopia[27], and western Ethiopia[30]. Studies conducted oversea like Vietnam [47], and Nepal[48] also supported this finding in that females had lower HRQoL than their male counterparts. This could be due to a variety of reasons. Firstly, it might be due to biological differences, such as hormonal fluctuations and reproductive health issues, which can interact with HIV and its treatment, potentially leading to more complicated health outcomes and lower HRQoL[49]. Secondly, females living with HIV may encounter more stigma and discrimination than men, which can have a detrimental impact on their emotional well-being and social support systems, which exposed them to loneliness, mental health issues, and a low feeling of self-worth, all of which can reduced their HRQoL[50]. Furthermore, HIV-positive women may have additional concerns about pregnancy, childbirth, and the possibility of transferring the virus to their children, and these additional stresses can have a detrimental effect on HRQoL, particularly if they're experiencing difficulty receiving proper medical care and support[51]. Women experience greater economic and social disadvantages than men in general, and this can be worsened in conjunction with HIV by limiting access to medical care, educational opportunities, and career prospects, all of which could have a detrimental impact on HRQoL[52]. Finally, in many countries, women frequently take on caregiving tasks for the household, which can increase their burden and stress levels, and balancing HAART with those responsibilities can further affect their HRQoL [53].

The current study identified educational level, marital status, residence, adherence to HAART, duration on HAART, alcohol consumption, recent CD4 count, and opportunistic infection as significant predictors of HRQoL.

Having a recent CD4 count of ≥ 500 cells/mm3 was positively associated with a good HRQoL. This finding is consistent with the results of similar studies conducted in South Africa[54], Rwanda[55] and Ireland[56], and Ethiopia[26, 29]. CD4 cells are white blood cells that play an important function in the immune system. When a person's CD4 count is high, their immune system is boosted, and as a result, they are more equipped to combat systemic and opportunistic infections and maintain overall well-being, which leads to an increased HRQoL[57]. As a result, clients have fewer crippling symptoms such as exhaustion, fever, weight loss, and other signs of HIV infection, which brings in improved HRQoL. Furthermore, clients who have an increasing CD4 count have better health outcomes and are more likely to stick to their treatment regimen. Adherence to HAART in turn is critical for patients to continue taking their medications as prescribed, which contributes to their improved HRQoL[58]. A greater CD4 count can improve an individual's physical and mental well-being, and knowing that their immune system is improving may lower stress, anxiety, and depression, resulting in improved HRQoL.

Adherence to HAART was also associated with a good HRQoL. This was supported by studies conducted in South Africa, Brazil, and Ethiopia [20, 59, 60]. This might be because clients who comply with their treatment regimen are less likely to progress to the late stages of HIV/AIDS and associated risks of OIs by suppressing the replication of HIV in the body[61]. This reduces the frequency and severity of illnesses which resulted in a good HRQoL. In addition, good adherence to HAART is known to improve social functioning and lessen the psychological burden, resulting in positive social interactions and support, lower anxiety, despair, and stress, and a greater sense of well-being and HRQoL. Good adherence also contributes to positive long-term health outcomes and the prevention of drug-resistant strains, which is essential to the prevention of drug-resistant strains and the effectiveness of therapy. Overall, good HAART adherence is critical for attaining viral suppression, lowering opportunistic infections, minimizing side effects, and preserving psychological well-being.

Educational status was also identified as a determinant of a good HRQoL. This was supported by a multi-country study among patients with HIV[62], and studies conducted in Togo[63], South Africa[54], Uganda[64], and Ethiopia[27, 31, 65]. Education was found to have a strong association with the independence, environment, and spiritual domains of HRQoL in studies done in Brazil, Iran, Togo, and Ethiopia [30, 63, 66, 67]. This could be attributed to a multitude of reasons. To begin with, higher education is frequently associated with improved health literacy, which is the ability to comprehend and use health-related information to make enlightened health decisions[68]. Thus, clients with higher education levels are more likely to comprehend medical information, stick to treatment schedules, and engage in preventive health behaviours, resulting in improved health outcomes and HRQoL. Furthermore, those with higher levels of education might be more likely to acquire appropriate coping strategies, allowing them to overcome the hardships of living with HIV and cope with potential emotional and physical burdens, thereby enhancing their HRQoL. Moreover, more educated people may face less discrimination, which might enhance their psychological health and HRQoL. It also could be due to literate individuals could have better financial resources, work capacity and access to quality health and social care. Thus health care providers in the service delivery points need to give a due emphasis to those women who are illiterate.

Residence was one of the significant predictors for having a good QoL. This finding was supported by studies conducted in Thailand[69],Indonesia[70], and Northern Ethiopia[19, 31][19, 31][19, 31]. This could be because PLWHA who resided in urban areas typically have better infrastructures such as transportation, sanitation, and better access to healthcare facilities, specialized HIV treatment centers, and well experienced healthcare providers all of them can influence their well-being by providing a more comfortable living environment. This means that they can access timely medical care, HAART, and other necessary services, resulting in improved health outcomes and overall well-being, which leads to a good HRQoL[70]. In addition, governments and non-governmental organisations in Ethiopia frequently focus on urban areas with various initiatives that offer emotional support, education, counselling, treatment, care, and support for those living with HIV. All of these aids and services might enhance HRQoL by reducing feelings of isolation and boosting psychological well-being. In urban areas, there may be a broader range of job prospects, which can be especially important for PLWHA who want to maintain employment and economic independence, and stable earnings might contribute to a good QoL.

The current study revealed that being a hazardous alcohol drunker was negatively affect HRQoL of people on HAART. This was supported by studies conducted in USA[71], Vietnam[72], Uganda[64], and Ethiopia[73]. This could be because alcohol impairs the immune system, leaving PLWHA more vulnerable to opportunistic infections and disease progression, which can lead to a reduction in physical health and well-being, negatively impacting HRQoL. Similarly, alcohol can interact negatively with HAART by reducing their effectiveness or causing harmful side effects[74]. Furthermore, alcohol can cause increased liver damage, mental illnesses such as depression and anxiety. These conditions can have a negative impact on physical and psychological well-being, as well as overall HRQoL. Hazardous alcohol intake can impair cognitive function, resulting in memory, attention, and decision-making difficulties, social isolation, troubled relationships, and increased stigma for PLWHA. These can exacerbate the inability to cope with the hardships of living with HIV and lower HRQoL. Finally, hazardous alcohol consumption can lead to poor medication adherence and reduced nutritional absorption, making treatment and maintaining a balanced diet tough both of which lead to poor health outcomes and HRQoL[75].

The study also showed that developing any OIs was found to have a negative influence on having a good HRQoL. This was supported by studies conducted in India[76], Brazil[77], Uganda[64], and Ethiopia[27, 29, 78]. This could be because OIs can cause a variety of physical and psychological symptoms, including fever, exhaustion, pain, gastrointestinal problems, depression, anxiety, and stress. These symptoms can be distressing and limit a person's ability to carry out everyday tasks and lower their overall QoL[79]. In addition, managing both HIV and opportunistic infections requires extensive treatment regimens that include many medications and frequent physician visits. This treatment burden can be demanding and jeopardize regular routines, resulting in a decrease in HRQoL. Overall, the link between HIV and OIs may establish a vicious cycle in which the presence of OIs lowers HRQoL, which impairs the immune system, rendering patients more susceptible to other infections and problems. In order to address this, a comprehensive strategy that includes early diagnosis, prompt and suitable treatment, psychological support, and adherence to ART is necessary.

There were limitations to the study that needed to be mentioned. First, as the respondents were actively seeking routine medical care from health facilities, the study was prone to selection bias. They may not represent patients who do not come to the healthcare facility from the surrounding communities; thus, generalizability is limited to those on ART follow-up. Because interviewer-administered questionnaires for HRQoL are assessing experiences that took place within the recent two weeks, recall bias may be introduced into the study despite being pretested. Due to the cross-sectional nature of the study difficult to establish temporal and cause-effect temporal relationships. As various social factors can affect HRQoL in individuals on HAART and potentially compromise the findings of this study, it has significance to carry out subsequent longitudinal studies triangulated with qualitative approaches.

Overall HRQoL was found to be low in the study area, with females having significantly lower scores in the majority of domains and overall HRQoL. Being urban residents, higher educational level, and having a current CD4 count of ≥ 500 cells/mm3 were positively associated with a good HRQoL in both genders. On the other hand, the presence of opportunistic infection, and hazardous alcohol consumption were identified as negative predictors of a good HRQoL. As a result, due emphasis should be given to those clients with no formal education and who came from rural areas. HAART service providers, addiction counsellors, and psychiatrists should collaborate in offering education on healthy living behaviours, coping mechanisms, and peer support for hazardous alcohol users.

AOR

Adjusted Odds Ratio

BDI-II

Beck Depression Inventory-Second Edition

BHSS

Berger's HIV stigma

CD4

Clusters of differentiation 4

COR

Crude Odds Ratio

HAART

Highly Active Antiretroviral Therapy

HRQoL

Health-related Quality of Life

MMAPS-8

Morisky Medication Adherence Predictor Scale

OIs

Opportunistic Infections

QoL

Quality of Life

SSA

Sub Saharan Africa, PLWHA:People living with HIV/AIDS

UNAIDS

United Nations Programme on HIV/AIDS

WHO

World of Health Organizations

WHOQOL-HIV BREF

World Health Organization's Quality of life HIV short-form tool

Acknowledgments

We would like to acknowledge the Demographic Health Survey program office for allowing us to access all the relevant DHS data for this study.

Funding:

There is no funding to report

Data Availability

All the data used to strengthen the results of this study are fully available without restriction.

Disclosure

We would like to assure you that, with full responsibility and communication, the document has been submitted. We indicated that there is no conflict of interest with other individuals or organizations that could influence or bias the content of the paper inappropriately.

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The authors declare no competing interests.

S1File.docx
Data collection tool to assess the magnitude and determinants of HRQoL Supporting files S1File-Data collection tool to assess the magnitude and determinants of HRQoL S1-Data: The raw data supporting the findings

Gender disparities in health-related quality of life and its predictors among adults on HAART at public health facilities of southern Ethiopia, 2022: A comparative cross-sectional study

Status:

Version 1

Abstract

Figures

Introduction

Methods

Study design, area, and period

The population of the study

Sample size determination

Sampling procedure

Data collection tools, methods, and personnel

Data quality management

Measurement of variables of the study

Outcome variable measurement

Data analysis

Ethical consideration and consent to participate

Results

Sociodemographic characteristics of the respondents

Clinical and behavioural characteristics of the respondents

Disparity in the mean facets scores across males and females

Differences in the mean scores of HRQoL domains across males and females

The overall HRQoL among Clients on HAART

Determinants of HRQoL

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1