Abstract
Background
Antiretroviral therapies have remained the cornerstone to improving the quality of life among people living with HIV. Adherence to these antiretroviral therapies continues to be crucial to the clinical outcomes for people living with HIV and their overall well-being. Thus, this study was conducted to evaluate the relationship between adherence to antiretroviral therapy and health-related quality of life for people living with HIV.
Methods
This was a cross-sectional analytical study involving people living with HIV accessing care in three tertiary hospitals in Nigeria. The study involved 877 respondents, who were selected using a multi-staged systematic sampling and administered a sociodemographic questionnaire, the Simplified Medication Adherence Questionnaire, and the 15D QoL Questionnaire. Descriptive and analytical statistical analyses were conducted using SPSS version 21.
Result
Eight hundred and seventy-seven people living with HIV were enrolled in the study, with the majority being females (64.5%). Of these, 66% were between the ages of 31–50 years, and 63.5% were married. More than half of the participants (63.8%) had secondary-level education and earned less than 30 USD per month. Non-adherence was reported in 456 participants (52.5%), with a mean QoL score of 0.97 ± 0.42. The mean quality of life score was significantly lower (p < 0.001) for non-adherent participants (0.96, S.D. ± 0.33), compared to adherent participants (0.98, S.D. ± 0.04). A multiple linear regression model showed being over 60 years old (β = -0.020, p = 0.032), being divorced (β =-0.021, p = 0.04), and having a comorbid condition (β = -0.013, p = 0.002) was associated with lower quality of life, while medication adherence (β = 0.09, p = 0.017) was a positive predictor of quality of life.
Conclusion
Adherence to ART was suboptimal in this study. Elderly People Living With HIV/AIDS (PLWHA), especially those with comorbid conditions or any of the negative predictors of QoL, are at increased risk of poor QoL and, thus, should be prioritized for QoL optimization strategies in HIV clinics. This calls for the need to review and optimize current strategies to enhance adherence to HIV care.
Keywords: Adherence, Antiretroviral Therapy, People Living With HIV/AIDS, Quality of Life, Northern Nigeria
Background
Human Immunodeficiency Virus (HIV) remains a significant public health issue worldwide, impacting various social, economic, and environmental factors [1]. Nigeria is among the countries with the highest number of people living with HIV/AIDS (PLWHA) in the world, with an estimated 1.9 million individuals affected by the virus [2, 3]. Recent estimates indicate a decline in HIV prevalence in Nigeria, now at 2.1%, compared to 2.8% in 2019 [2, 4]. This improvement is attributed to the enhanced effectiveness of antiretroviral therapy (ART), expanded access to HIV care services, and improved surveillance systems [5]. Over 85% of PLWHA in Nigeria are now receiving ART, reflecting progress in the nation’s response to the epidemic [3]. However, ART’s success largely depends on strict adherence to the prescribed regimen [4]. Adherence to ART requires individuals to take their medication consistently and correctly over time. Despite the proven efficacy of ART, non-adherence remains a pervasive issue, with various barriers contributing to suboptimal adherence [5]. These barriers include forgetfulness, fear of stigma, adverse drug reactions, and psychosocial factors such as depression and lack of social support [6]. Addressing these barriers is critical to improving health outcomes and reducing the public health burden of HIV.
Adherence to ART in African countries shows significant variability, with reported rates ranging from approximately 49% in southern Africa, 50% in Nigeria, and 90% in South Africa and Uganda, depending on the socio-economic, physical, and physiological factors [7–10]. Factors like stigma, side effects of drugs, long queues at the hospitals, work-related problems, and irregular doctor visits were some of the common reasons for non-adherence [11, 12]. Poor adherence increases the risk of morbidity, drug resistance, early onset of opportunistic infections, treatment failure, and ultimately higher mortality rates [13]. The relationship between adherence to ART and quality of life (QoL) is intricate and reciprocal. Individuals with high QoL tend to demonstrate greater adherence to their treatment protocols, as they may encounter fewer physical and psychological health barriers during care [14]. Conversely, adherence to ART contributes positively to clinical results, diminishes the likelihood of opportunistic infections, and enhances overall QoL [15]. This interaction highlights the necessity of understanding the factors that impact both adherence and QoL to guide the development of targeted interventions [16].
However, non-adherence to treatment can significantly diminish an individual’s quality of life, leading to exacerbated health challenges and outcomes [17]. This is particularly relevant for PLWHA on ART. Cultural, social, and economic factors also influence treatment decisions, complicates ART adherence and perpetuating a cycle that harms the quality of life [18]. Understanding the relationships among sociodemographic factors, clinical status, and personal behavior is key to improving ART adherence among PLWHA [7, 19]. This study aims to evaluate the relationship between adherence to antiretroviral therapy and health-related quality of life for people living with HIV in Northwestern Nigeria. The study also explores more insights into the sociodemographic and clinical factors influencing these outcomes. By examining adherence patterns, health-related quality of life (HRQoL) scores, and their predictors, the study seeks to inform strategies for improving health outcomes and addressing the unique needs of PLWHA.
Methodology
Study design and setting
The research constituted a cross-sectional descriptive study focused on individuals living with HIV/AIDS receiving care from three tertiary hospitals located in Northwestern Nigeria. These hospitals include Usmanu Danfodiyo University Teaching Hospital (UDUTH) in Sokoto, Ahmadu Bello University Teaching Hospital (ABUTH) in Zaria, and Aminu Kano Teaching Hospital (AKTH) in Kano between 1st July 2021 and 31st August 2022. All the hospitals are tertiary health facilities in Northwestern Nigeria, that serve as a referral center for more than 20 million people from Sokoto, Zamfara, Niger, Kebbi, Katsina, Kaduna, Kano, Jigawa, and the neighboring Niger and Benin Republics in the West African sub-region [20]. These hospitals were purposively selected as the foremost teaching hospitals providing specialized medical services and comprehensive HIV treatment and care in the zone, thus providing care to over 20,000 PLWHA each year [21, 22].
Study population
The research comprised all eligible adult individuals (aged 18 years and above) living with HIV/AIDS who were receiving care at the HIV clinics of UDUTH, ABUTH, and AKTH, provided they met the eligibility criteria: PLWHA aged 18 years or older, participants who were on Highly Active Antiretroviral Therapy (HAART), participants who consented to take part in the research and may decide to not participate at any time, and participants possessing the capability to comprehend either the Hausa or English language, whether verbally or in written form. Adolescents below 18 years were excluded due to ethical consideration surrounding age of consent and the adult-oriented design of the study tools.
Sampling and data collection
Participants were chosen through a multi-staged systematic sampling method of recruitment for a total of 877 PLWHA from three tertiary hospitals: UDUTH, ABUTH, and AKTH. Participants were enrolled proportionally using the following stages. In the first stage, the three hospitals were purposively selected based on their high volume of PLWHA and geographical representation. In the second stage, we used a proportional allocation to determine the number of participants to be recruited from each hospital based on their average monthly HIV clinic attendance. In the last and third stage, systematic sampling was used at each site to select participants. During the data collection period, PLWHA’s daily attendance at the HIV clinic was recorded and divided by the predetermined number of participants to be interviewed each day (k = 10) to calculate the sample interval. Subsequently, every Kth individual from the population was selected for an interview, approached for consent, and enrolled until the site-specific sample size was achieved. At the end of this process, we had 307 from UDUTH, 300 from ABUTH, and 270 from AKTH.
The data were collected through an interviewer-administered approach after fulfilling the selection criteria. Data collection occurred biweekly over 12 weeks to guarantee a balanced representation of PLWHA receiving care in the HIV clinics. The data instrument was administered primarily in the English language, and the validity approach is explained below in the study instrument section. The interviewers translated the instrument into Hausa for participants who could not understand English. Data collection was done by the principal researcher and two properly trained research assistants. On average, data was collected from approximately 10 participants per day, with each interview typically lasting around 30 min. However, the duration varied slightly depending on individual participant responses and the need for clarification during questionnaire administration. We ensured that no participant was assessed twice or more during the data collection and the possibility of the client visiting the clinic again by implementing a unique identifier at the first point of contact to track participation without compromising confidentiality, cross-checking clinic records, including participant name and clinic ID number, and also maintained same logbook/electronic register at each new clinic day to prevent duplication. Further, before data collection, we had a session with the staff of the department on the need to confirm whether the client had already participated in the study using the identifiers before administering the questionnaire.
Study instruments
The attributes of the respondents, encompassing factors such as sex, age, marital status, employment status, viral load, and comorbid conditions were assessed using a sociodemographic and clinical characteristics questionnaire adapted from a study [22]. Participants’ adherence levels with varying disease states were analyzed using the Simplified Medication Adherence Questionnaire (SMAQ) as adapted from the study [23]. This instrument comprises six items inquiring about instances when PLWHA may have forgotten to take their medication and the frequency of such occurrences. A result derived from the SMAQ is deemed positive if the PLWHA is identified as non-adherent. Non-adherence is operationalized by a positive response to any qualitative questions, missing more than two doses in the preceding week, and/or having over two days of total non-adherence in the past month [24]. The 15D questionnaire is a generic instrument that encompasses 15 dimensions for measuring health-related quality of life (HRQoL). It serves both as a comprehensive profile and as a singular index score assessment [25]. The 15 dimensions include mobility, vision, hearing, breathing, sleeping, eating, speech, excretion, customary activities, mental function, discomfort and symptoms, depression, distress, vitality, and sexual activity. Each dimension is evaluated on a scale ranging from 1 to 5, respectively, where 1 indicates the optimal health state and 5 signifies the most detrimental health state. The utility score is quantified between 0 and 1, with 0 representing death and 1 denoting perfect health, respectively [25].
Data analysis
Data was coded and keyed into the Statistical Package for the Social Sciences (SPSS) version 21 for analysis. Sociodemographic and clinical characteristics were analyzed using descriptive statistics. Non-adherence to HAART was classified using a self-reported adherence tool, with participants considered non-adherent following standard definitions in the HIV Care proforma. The chi-square test was used to measure the association between categorical variables. Independent t-test and one-way ANOVA were used to determine the mean difference in adherence and QoL across sociodemographic categories. A multiple linear regression was used to assess and determine the relationship between the individual sociodemographic and interacting predictors of QoL. This allowed for adjustments of potential confounders and a better understanding of the independent contribution of each predictor. In the regression model, adherence to ART was treated as a binary categorical variable (1 = adherent, 0-non-adherent), and other categorical predictors with multiple regression were evaluated: independence of residuals was assessed using the Durbin-Watson statistic, and multicollinearity was tested using Variance Inflation Factors (VIF), all of which were within acceptable thresholds. Residual plots were examined to confirm linearity, homoscedasticity, and normality of residuals. For all the statistics, a p-value of < 0.05 was used as the significance level.
Results
Table 1 describes the sociodemographic characteristics of our study cohort, which included 877 participants, the majority of whom were females (n = 566, 64.5%). About two-thirds (66%, n = 517) were aged between 31 and 50 years, and most were married (n = 554, 63.5%). Over half (63.8%) had completed secondary education or higher, with a significant portion of the participants being employed (n = 623, 71.5%), while 2.6% (n = 23) were retired. About 65% of the participants had a monthly income of less than N30,000 per month (less than 78 USD per month). Additionally, more than half of the participants (63.9%, n = 552) in this study report that they are not aware of any family member living with HIV.
Table 1.
Sociodemographic characteristics of PLWHA
| Variable | Frequency (Percentage) N = 877 |
|---|---|
| Gender | |
| Female | 566 (64.5) |
| Male | 311 (35.5) |
| Total | 877 (100) |
| Age (Years) | |
| 18–30 | 139 (16.1) |
| 31–40 | 317 (36.6) |
| 41–50 | 260 (30.1) |
| 51–60 | 114 (13.2) |
| 60 and above | 34 (3.9) |
| Total | 864 (100) |
| Religion | |
| Islam | 700 (80.0) |
| Christianity | 175 (20.0) |
| Total | 875 (100) |
| Highest Educational Level | |
| None | 7 (0.8) |
| Non-formal | 215 (24.9) |
| Primary | 90 (10.4) |
| Secondary | 285 (33.1) |
| Tertiary | 265 (30.7) |
| Total | 862 (100) |
| Marital Status | |
| Single | 94 (10.8) |
| Married | 554 (63.5) |
| Widowed | 184 (21.1) |
| Divorced | 40 (4.6) |
| Total | 872 (100) |
| Employment Status | |
| Employed | 623 (71.5) |
| Unemployed | 208 (23.9) |
| Retired | 23 (2.6) |
| Student | 17 (2.0) |
| Total | 871 (100) |
| Monthly Income (Naira)* | |
| No income | 181 (20.8) |
| Less than 30,000 (< 78 USD) | 384 (44.2) |
| 30,000–50,000 (78–130 USD) | 188 (21.6) |
| More than 50,000 (> 130 USD) | 116 (13.3) |
| Total | 869 (100) |
| Number of Family Members Living With HIV/AIDS | |
| None | 552 (62.9) |
| 1 | 255 (29.0) |
| 2 | 63 (7.2) |
| 3 | 7 (0.8) |
| Total | 877 (100) |
| Having a Family Member Living With HIV/AIDS | |
| No | 552 (62.9) |
| Yes | 325 (62.9) |
| Total | 877 (100) |
https://www.oanda.com/currency-converter/en/?from=NGN&to=USD&amount=1
*Naira – USD Conversion Rate in July 2021: 1 Naira = 0.0026 USD
Table 2 presents the adherence levels of PLWHA to their ART as assessed by the SMAQ. A majority of respondents (65.10%) reported that they had never forgotten to take their medications since the initiation of their ART regimen; conversely, 34 individuals (3.1%) acknowledged that they discontinued their medications when experiencing illness. Approximately 778 participants (89.50%) indicated that they had not missed any doses within the past week, while 795 respondents (91.5%) stated that they did not miss taking their medications for more than two consecutive days during the three months before the interview.
Table 2.
Adherence of PLWHA to antiretroviral therapy using SMAQ
| Variable | Response | Frequency (Percentage) |
|---|---|---|
| 1. Did you ever forget to take your medicine? | Yes | 303 (34.90) |
| No | 566 (65.10) | |
| Total | 869 (100) | |
| 2. Are you careless at times about taking your medicine? | Yes | 216 (24.90) |
| No | 652 (74.10) | |
| Total | 868 (100) | |
| 3. Sometimes, if you feel worse, do you stop taking your medicines? | Yes | 34 (3.1) |
| No | 835 (96.1) | |
| Total | 869 (100) | |
| 4. Thinking about last week. How often have you not taken your medicine? | Never | 778 (89.50) |
| 1–2 times | 71 (8.20) | |
| 3–5 times | 12 (1.40) | |
| 6–10 times | 3 (0.30) | |
| > 10 times | 5 (0.60) | |
| Total | 869 (100) | |
| 5. Did you not take any of your medicine over the past weekend? | Yes | 41 (4.70) |
| No | 827 (95.30) | |
| Total | 868 (100) | |
| 6. Over the past 3 months, how many days have you not taken any medicine at all? | ≤ 2 days | 794 (91.50) |
| > 2 days | 74 (8.50) | |
| Total | 866 (100) | |
| 7. Overall Adherence | Adherent | 413 (47.50) |
| Non-adherent | 456 (52.50) | |
| Total | 869 (100) |
According to the SMAQ scoring system, 52.5% of respondents demonstrated non-adherence to their ART regimen. The relationship between adherence and sociodemographic factors is illustrated in Table 3. The findings did not reveal any significant associations between sociodemographic characteristics and adherence.
Table 3.
Adherence of PLWHA to antiretroviral therapy across sociodemographic characteristics
| Variable | Non-adherent N (%) | Adherent N (%) | Total N (%) | p-Value |
|---|---|---|---|---|
| Gender | ||||
| Female | 293 (64.3) | 265 (64.2) | 558 (64.2) | |
| Male | 163 (35.7) | 148 (36.1) | 311 (35.7) | 0.978 |
| Total | 456 (100) | 413 (100) | 869 (100) | |
| Age (Years) | ||||
| 18–30 | 71 (15.7) | 67 (16.6) | 138 (16.1) | |
| 31–40 | 169 (37.5) | 145 (35.7) | 314 (36.6) | |
| 41–50 | 140 (31.0) | 117 (28.8) | 257 (30.0) | 0.144 |
| 51–60 | 49 (10.9) | 65 (16.0) | 114 (13.3) | |
| 60 and above | 22 (4.9) | 12 (3.0) | 34 (4.0) | |
| Total | 451 (52.2) | 406 (47.4) | 857 (100) | |
| Highest Educational Level | ||||
| None | 5 (1.1) | 2 (05) | 7 (0.8) | |
| Non-formal | 103 (22.8) | 112 (27.7) | 215 (25.1) | |
| Primary | 53 (11.8) | 37 (9.1) | 90 (10.5) | |
| Secondary | 146 (32.4) | 138 (34.1) | 284 (33.2) | 0.259 |
| Tertiary | 144 (31.9) | 116 (28.6) | 260 (30.4) | |
| Total | 451 (100) | 405 (100) | 856 (100) | |
| Marital Status | ||||
| Single | 59 (13.1) | 35 (8.5) | 94 (10.9) | |
| Married | 277 (61.0) | 271 (66.1) | 548 (63.4) | |
| Widowed | 92 (20.3) | 90 (22.0) | 182 (21.1) | 0.055 |
| Divorced | 26 (5.7) | 14 (3.4) | 40 (4.6) | |
| Total | 454 (100) | 410 (100) | 864 (100) | |
| Employment | ||||
| Employed | 325 (71.6) | 294 (71.1) | 616 (71.4) | |
| Unemployed | 109 (24.0) | 98 (24.0) | 207 (24.0) | |
| Retired | 9 (2.0) | 14 (3.4) | 23 (2.7) | 0.444 |
| Student | 11 (2.4) | 6 (1.5) | 17 (2.0) | |
| Total | 454 (100) | 409 (100) | 862 (100) | |
| Monthly Income (Naira) | ||||
| No income | 101 (22.6) | 80 (19.5) | 81 (21.0) | |
| Less than 30,000 | 202 (44.8) | 176 (42.9) | 378 (43.9) | |
| 30,000–50,000 | 83 (18.4) | 104 (25.4) | 187 (21.7) | 0.086 |
| More than 50,000 | 65 (14.4) | 50 (12.2) | 1145 (13.4) | |
| Total | 451 (100) | 410 (100) | 861 (100) |
Chi-square test, *Significant at P <0.05
In contrast, significant associations were identified between specific clinical characteristics and adherence, as detailed in Table 4. Adherence among PLWHA was notably related to the type of antiretroviral therapy administered (p = 0.012). Additionally, a significant relationship was established between the status of comorbid conditions and adherence (p = 0.009), as well as the use of medications for comorbid conditions and adherence to ART (p = 0.004).
Table 4.
Adherence of PLWHA to antiretroviral therapy across clinical characteristics
| Variables | Non-adherent N (%) | Adherent (%) | Total N (%) | p-Value | |||||
|---|---|---|---|---|---|---|---|---|---|
| Duration of Diagnosis (Years) | |||||||||
| < 1 | 13 (2.9) | 20 (4.8) | 33 (3.8) | ||||||
| 1–5 | 94 (20.7) | 91 (22.4) | 185 (21.3) | ||||||
| 6–10 | 148 (32.5) | 136 (32.9) | 284 (32.7) | ||||||
| 11–15 | 142 (31.2) | 128 (31.0) | 270 (31.1) | 0.125 | |||||
| 16–20 | 38 (8.4) | 30 (7.3) | 69 (7.9) | ||||||
| > 20 | 6 (1.3) | 6 (1.5) | 12 (1.4) | ||||||
| Don’t Know | 13 (2.9) | 2 (0.5) | 15 (1.7) | ||||||
| Total | 455 (100) | 413 (100) | 868 (100) | ||||||
| Duration of Antiretroviral Therapy (Years) | |||||||||
| < 1 | 11 (2.4) | 22 (5.3) | 33 (3.8) | ||||||
| 1–5 | 97 (21.3) | 91 (22.0) | 188 (21.7) | ||||||
| 6–10 | 152 (33.4) | 140 (33.9) | 292 (33.7) | ||||||
| 11–15 | 139 (30.5) | 124 (30.0) | 263 (30.3) | 0.078 | |||||
| 16–20 | 39 (8.6) | 28 (6.8) | 67 (7.7) | ||||||
| > 20 | 4 (0.9) | 5 (1.2) | 9 (1.0) | ||||||
| Don’t Know | 13 (2.9) | 3 (0.7) | 16 (1.8) | ||||||
| Total | 455 (100) | 413 (100) | 868 (100) | ||||||
| Type of Antiretroviral Therapy | |||||||||
| TDF+3TC + DTG | 326 (71.5) | 326 (78.6) | 652 (75.0) | ||||||
| TDF+3TC + LPV/r | 25 (5.5) | 12 (2.9) | 37 (4.3) | ||||||
| TDF+3TC + ATV/r | 63 (13.8) | 37 (9.0) | 100 (11.5) | 0.012* | |||||
| Others | 42 (9.2) | 38 (9.5) | 80 (9.2) | ||||||
| Total | 456 (100) | 413 (100) | 869 (100) | ||||||
| Most Recent Viral Load (copies/ ml) | |||||||||
| < 20 | 273 (67.4) | 257 (68.7) | 530 (68.0) | ||||||
| 21–999 | 98 (24.2) | 95 (25.4) | 193 (24.8) | 0.393 | |||||
| > 999 | 34 (8.4) | 22 (5.9) | 56 (7.2) | ||||||
| Total | 405 (100) | 374 (100) | 779 (100) | ||||||
| Having a Comorbid Condition | |||||||||
| No | 373 (81.8) | 364 (88.1) | 737 (84.8) | ||||||
| Yes | 83 (18.2) | 49 (11.9) | 132 (15.2) | 0.009* | |||||
| Total | 456 (100) | 413 (100) | 868 (100) | ||||||
| Taking Medication for Comorbid Conditions | |||||||||
| No | 16 (19.3) | 1 (2.0) | 17 (12.9) | ||||||
| Yes | 67 (80.7) | 48 (98.0) | 115 (87.1) | 0.004* | |||||
| Total | 81 (100) | 51 (100) | 132 (100) | ||||||
*Significant at P < 0.05
The various domains and the composite mean scores of the 15D QoL assessment for the respondents are detailed in Table 5. The domain of speech exhibited the highest mean value (0.99, S.D. ±0.04), followed closely by breathing (0.98, S.D. ±0.08), eating (0.98, S.D. ±0.08), usual activities (0.98, S.D. ±0.08), depression (0.98, S.D. ±0.10), distress (0.98, S.D. ±0.08), vitality (0.98, S.D. ±0.08), and sexual activities (0.98, S.D. ±0.09). The domains with the lowest mean scores included discomfort and symptoms (0.92, S.D. ±0.14), mental function (0.92, S.D. ±0.15), and vision (0.93, S.D. ±0.12).
Table 5.
Mean quality of life of PLWHA
| Variable | Mean (
|
±SD | |
|---|---|---|---|
| The overall quality of life | 0.97 | 0.42 | |
| Quality of life domains | |||
| Mobility | 0.94 | 0.15 | |
| Vision | 0.93 | 0.12 | |
| Hearing | 0.99 | 0.05 | |
| Breathing | 0.98 | 0.08 | |
| Sleeping | 0.97 | 0.11 | |
| Eating | 0.98 | 0.08 | |
| Speech | 0.99 | 0.04 | |
| Excretion | 0.97 | 0.10 | |
| Usual Activities | 0.98 | 0.08 | |
| Mental Function | 0.92 | 0.15 | |
| Discomfort and Symptoms | 0.92 | 0.14 | |
| Depression | 0.98 | 0.10 | |
| Distress | 0.98 | 0.08 | |
| Vitality | 0.98 | 0.08 | |
| Sexual activity | 0.98 | 0.09 | |
The overall mean QoL score among the studied PLWHA was 0.97 (S.D. ±0.04). The mean differences in QoL concerning depressive symptoms and adherence categories are presented in Table 6. Notably, the mean QoL score was significantly lower (p < 0.001) among PLWHA who were non-adherent to their medications (0.96, S.D. ±0.33).
Table 6.
Mean comparison of quality of life between adherent and non-adherent PLWHA
| Adherence to ART | Quality of life
|
p-Value |
|---|---|---|
| Adherent | 0.98 (0.04) |
0.025 <0.001 |
| Non-adherent | 0.96 (0.33) |
Independent Sample T-test *Significant at P < 0.05
A linear regression analysis aimed at identifying predictors of QoL is outlined in Table 7. Factors such as being over 60 years old ( β= -0.020, p = 0.032), being divorced ( β= -0.021, p = 0.04), having a comorbid condition (β=-0.013, p = 0.002), and adherence to a regimen of ABC+3TC + DTG ( β = -0.052, p = 0.019) emerged as significant predictors of QoL. When controlling for other variables, being older than 60 years was linked to a 0.020-unit decrease in QoL, while being divorced corresponded to a 0.021-unit decrease. The presence of comorbid conditions was associated with a 0.013-unit reduction in QoL. Conversely, adherence to antiretroviral therapy indicated an increase of 0.014 units in QoL. Collectively, the regression model accounted for an estimated 6.8% of the variance in QoL.
Table 7.
Predictors of QoL among PLWHA
| Variable | B | S.E | Standardized coefficient (B) | P-Value |
|---|---|---|---|---|
| (Constant) | 0.947 | 0.022 | 0.000 | |
| Gender | ||||
| Male | 0.001 | 0.004 | 0.013 | 0.769 |
| Age | ||||
| Reference: 18–30 years | ||||
| Age: 31–40 | 0.005 | 0.005 | 0.057 | 0.304 |
| Age: 41–50 | 0.002 | 0.005 | 0.020 | 0.724 |
| Age: 51–60 | -0.009 | 0.006 | -0.072 | 0.159 |
| Age: above 60 | -0.020 | 0.009 | -0.098 | 0.032 |
|
Highest Educational Level Reference: Not educated |
||||
| Non-formal Education | 0.021 | 0.018 | 0.218 | 0.235 |
| Primary | 0.028 | 0.018 | 0.211 | 0.119 |
| Secondary | 0.017 | 0.018 | 0.187 | 0.346 |
| Tertiary | 0.020 | 0.018 | 0.217 | 0.267 |
|
Marital Status Reference: Single |
||||
| Married | 0.006 | 0.005 | 0.064 | 0.298 |
| Widowed | 0.003 | 0.006 | 0.032 | 0.609 |
| Divorced | -0.020 | 0.009 | -0.099 | 0.020 |
|
Employment Status Reference: Unemployed |
||||
| Employed | 0.000 | 0.004 | -0.004 | 0.926 |
| Retired | 0.000 | 0.012 | -0.001 | 0.985 |
| Student | 0.018 | 0.012 | 0.059 | 0.118 |
| Monthly Income | ||||
| Reference: Less than 30,000 | ||||
| N30, 000–50,000 | 0.002 | 0.004 | 0.021 | 0.570 |
| More than 50, 000 | -3.411E-05 | 0.006 | 0.000 | 0.996 |
| Having a Comorbid Condition | -0.013 | 0.004 | -0.113 | 0.002 |
| Most Recent Viral Load | 5.512E-09 | 0.000 | 0.016 | 0.672 |
| Type of Antiretroviral Regiment | ||||
| Reference: TDF+ 3TC + EFV | ||||
| TDF+3TC + DTG | -0.008 | 0.013 | -0.078 | 0.549 |
| ABC+3TC + DTG | -0.052 | 0.022 | -0.101 | 0.019 |
| ABC+3TC + EFV | 0.023 | 0.027 | 0.035 | 0.399 |
| AZT+3TC + NVP | -0.018 | 0.022 | -0.036 | 0.406 |
| TDF+3TC+LPVr | -0.006 | 0.014 | -0.030 | 0.669 |
| TDF+3TC+ATVr | -0.015 | 0.013 | -0.114 | 0.261 |
| ABC+3TC+LPVr | 0.014 | 0.032 | 0.017 | 0.659 |
| ABC+3TC+ATVr | -0.002 | 0.018 | -0.005 | 0.924 |
| AZT+3TC+LPVr | -0.012 | 0.015 | -0.050 | 0.428 |
| AZT+3TC+ATVr | -0.010 | 0.019 | -0.025 | 0.608 |
| Adherence to ART | 0.014 | 0.003 | 0.174 | < 0.001 |
| Adjusted R Square | 6.8% | |||
| Model P-value | < 0.001 | |||
*Significant at P < 0.05
Discussion
This study was carried out to explore the adherence level of PLWHA in northwestern Nigeria and how that relates to their quality of life. The present study consists of predominantly females, individuals aged 31–50, and those who were employed and married. Despite a relatively high level of employment and education, a significant number of participants lived less than N30,000 (< 78 USD) monthly, highlighting underlying economic vulnerabilities. Meanwhile, most participants reported non-adherence to ART based on the SMAQ, with nearly half classified as adherent. Notably, there was no statistically significant association between adherence and sociodemographic variables. However, the clinical factors such as the presence of comorbidities, specific ART regimen, and use of medication showed a significant association with adherence levels. The study also revealed high self-reported QoL among PLWHA, with the highest domain scores observed in areas such as breathing, speech, and eating. However, domains such as vision, mental functioning, and discomfort scored relatively lower. Importantly, non-adherence to ART was significantly associated with lower QoL. While this study identified age over 60, being divorced, and having comorbid conditions as significant negative predictors of QoL, while ART adherence positively influenced QoL, the regression model explained a modest portion of QoL variance, further showing the need to integrate clinical and psychological support interventions to enhance adherence and improve QoL among PLWHA.
In our study, we used the SMAQ adherence questionnaire to assess PLWHA’s adherence to their ART regimen and found non-adherence to be reported in slightly more than half of the assessed PLWHA. Our finding contradicts that of several other studies conducted among PLWHA. Similar studies conducted in Nigeria showed that the majority of PLWHA adhere to their medications [26, 27]. These studies, however, utilized self-reported adherence, which is susceptible to recall and social desirability bias. Similar studies conducted in other countries also revealed a higher proportion of PLWHA being adherent to their medications, although some studies still revealed suboptimal adherence levels [28, 29]. A possible explanation for this variation in findings may partly be explained by differences in measurement tools and the definition of adherence by different tools. The SMAQ adherence questionnaire is a validated tool, it is like another self-report instrument subject to recall and social desirability bias, which affects the accuracy of response. Unlike some tools that assess adherence over a shorter time frame, SMAQ includes items that classify individuals as non-adherent based on past behavior and considers adherence as an absolute variable, not a factor that changes over time. For example, the first question assessed whether a person had ever forgotten to take their medication. A positive response to this question indicates non-adherence. This implies that adherence status is fixed and does not change over time. The implication of this is that PLWHA, with initial poor adherence levels who improve over time, will still be considered not adherent to ART. As a result, SMAQ may overclassify individuals as non-adherent, particularly those who have experienced occasional lapses but have since maintained consistent adherence. This is more profound when we look at the question that asks about the number of days that a PLWHA missed taking medication in the last 3 months. A total of 91.5% of the PLWHA reported not missing their medications within the last three months. This is a 42.8% difference in the overall adherence with adherence in the last three months. PLWHA tend to be less adherent to their medication during the early days of their diagnosis with HIV, and their adherence improves with time [30–32]. This could be attributed to the initial side effects that PLWHA experience with the ARTs and the immune reconstitution syndrome that sometimes occurs. Adherence usually improves as the side effects fade away and PLWHA have internalized the regular use of ARTs [33]. It is expected, therefore, to have a lower level of adherence if the initial adherence of PLWHA is factored in when assessing overall adherence.
Certain clinical characteristics, including the type of antiretroviral therapy, were found to be significantly associated with adherence to ART among PLWHA. This is corroborated by findings of other studies on adherence to ART across Africa, including those with similar demographics in Nigeria [26, 34], Ghana [35], Ethiopia [36], Egypt [37], and across the world including the Caribbeans [38], and the Americans [39]. These antiretroviral therapies differ in their dosage regimen, pill burden, and adverse effects, thereby influencing adherence [20]. Adherence has been directly linked to the number of pills and dosing frequency, with medications with fewer dosing frequencies and less pill burden being easier to adhere [31]. Some antiretroviral regimens have also been associated with some side effects which have been associated with a lower level of adherence [40].
We also found a significant association between having comorbid conditions and adherence to ART. The PLWHA that reported having a comorbid condition had a significantly lower level of adherence than those without comorbid conditions. The presence of a comorbid condition means that PLWHA have to deal with the burden of other disease conditions and may likely take multiple conditions causing possible pill fatigue [30, 31]. Some of these comorbid conditions such as depression have been independently associated with lowered adherence to ART [41]. It is anticipated that the impact of the comorbid condition will be alleviated if it is managed effectively and if the PLWHA is adhering to the prescribed medication for the comorbid condition. This relationship is evident in the significant association between the intake of medication for comorbid conditions and adherence to Antiretroviral Therapy (ART). PLWHA who are on medication for their comorbid conditions exhibit a greater rate of adherence in comparison to those who are not, suggesting that the appropriate management of the comorbid condition may reduce its influence on adherence to ART regimens [42].
We also evaluated the relationship between medication adherence to PLWHA and the resultant QoL. We found that there was a significant mean difference between PLWHA that were adherent to ART and those who were not. The mean QoL was significantly higher among PLWHA who ere adherent to ART. This finding agrees with that of several others who found an association between adherence to QoL [43, 44]. The HRQoL of PLWHA encompasses both the physical and mental components of life. However, HIV/AIDS is associated with symptoms that impair the different domains of quality of life. The negative symptoms of HIV are manifest in a PLWHA with poor adherence, hence the lower quality of life. A study that also demonstrated this relationship between adherence and QoL was conducted [45]. where the predictive effect of adherence on QoL was modeled. It was found that adherence significantly predicts the physical and psychological domains of WHOQOL [45].
Further, we determined the predictors of QoL in PLWHA using a linear regression model. The model consisted of participants’ sociodemographic, clinical characteristics, and adherence to ART. The model predicted a 6.8% variation in QoL. Age was the only sociodemographic characteristic that was a significant predictor of quality of life. This is consistent with earlier findings that showed age to predict lower QoL [46–50]. A study has also reported that older predicts poorer QoL [51]. This is likely due to the decrease in physical functioning that occurs with the aging process [52]. Other studies, however, found contradictory results. A study among PLWHA in Georgia showed that people who are 40 years and younger were more likely to have a poor QoL than older PLWHA [53]. Having a comorbid condition was also a significant predictor of quality of life. These further stress the impact that comorbid conditions have on QoL and the need to adequately manage the comorbidities of PLWHA. Other previous studies documented a similar negative predictive value of comorbid conditions on QoL [45]. A study has found a significant association between comorbid conditions and poor QoL, especially the physical components, within the elderly [54]. Other studies among PLWHA also showed that the number of comorbid conditions significantly predicts poor QoL [31, 55]. The presence of the comorbid condition, particularly in elderly PLWHA, thus, should be accorded with prioritized attention to ensure optimal QoL. Our findings showed that adherence to prescribed medications is a significant predictor of substantial improvement in the overall quality of life (QoL) for PLWHA. This assertion is corroborated by a multitude of studies that examined the substantial effects of adherence on QoL outcomes [44, 56]. An optimal quality of life can only be attained when a PLWHA exhibits few, if any, symptoms related to HIV/AIDS. Such a desired state can be realized through the consistent and effective suppression of viral load, which is directly associated with strict compliance with the designated treatment regimen. Therefore, it is imperative to implement comprehensive and innovative strategies that foster and enhance adherence to antiretroviral therapy (ART) to significantly improve the quality of life for PLWHA.
Conclusion and recommendations
Adherence to ART was found to be suboptimal in this study. This finding calls for the need to review the existing strategies for improving adherence in HIV clinics. Approaches that improve adherence should be devised, especially among those with comorbid conditions. At the societal level, targeted education for PLHWA will be useful in enhancing understanding of the benefits of ART, thereby increasing uptake and adherence to the therapy. Future studies should also identify the linkage between the type of ART and the risk of non-adherence to aid in a targeted approach in PLWHA using ARTs with a higher propensity for non-adherence. Adherence to ART remains essential for suppressing HIV viral replication, reducing the incidence of resistance, and ensuring improved quality of life among PLWHA. As such, there is a need for healthcare providers to continuously engage their PLWHA in discussions of the potential consequences of non-adherence and to support them in finding ways to minimize it. The assessment of the relationship between adherence to antiretroviral therapy and health-related quality of life showed high QoL among PLWHA, except for mental functions, discomforts and symptoms, and vision profiles. This implies the need for further research to explore the factors that are responsible for poor QoL in these domains. This study found an association between ART adherence and the quality of life of the clients. Some variables have been identified as predictors of QoL in PLWHA‒ age, comorbid conditions, and adherence were significant predictors of QoL. Adherence is a dynamic state that may require continuous interactions with healthcare providers over the life of ART. However, one-time educational programs aimed at improving the health of the PLWHA have the potential to improve health and provide cost savings to the country. Elderly PLWHA, especially those with comorbid conditions or any of the negative predictors of QoL, are at increased risk of poor QoL and, thus, should be prioritized for QoL optimization strategies in HIV clinics. Ultimately, the findings will contribute to the broader understanding of HIV care and support efforts to achieve the global goal of ending the HIV/AIDS epidemic by 2030.
Strengths and limitations
The strengths of this study reside in its provision of empirical evidence on how adherence is associated with quality of life among people living with HIV/AIDS receiving antiretroviral therapy. It also highlights some of the less well-known aspects of this relationship in the study area. The results of the study will provide a unique focus on the mediating effects of the major factors related to adherence in improving the clinical status of living with HIV, particularly in developing regions like Nigeria. As the knowledge of the quality of life as a result of adherence to the treatment and care of people living with HIV/AIDS is less informed in the study area, the results of this study can be informative and guide necessary interventions to improve adherence-associated quality of life for people in the area. Our research is not without limitations. The methodology used for data collection involved interviewer-administered approaches with PLWHA, potentially introducing interviewer bias. The use of a cross-sectional design, which has limitations for the generalizability of findings and a lack of causality, is another limitation of this study. Replicating this study with a longitudinal design will increase our understanding of the temporal sequence of factors associated with ART non-adherence and identify unique factors within different socio-cultural communities in Nigeria and other similar contexts. Finally, the SMAQ questionnaires inquired about individuals’ previous experiences, which elevated the likelihood of recall bias. The SMAQ’s approach treats adherence as a somewhat static variable, which does not capture its dynamic nature, where adherence can fluctuate over time due to personal, clinical, or contextual factors. Given these considerations of our usage of the SMAQ tool, our findings highlight the need for complementary adherence monitoring approaches in clinical settings. While self-report tools like SMAQ are practical and easy to administer, they should be supplemented with objective measures such as pharmacy refill records, pill counts, or viral load monitoring, where feasible, to provide a more accurate picture of adherence for PLWHA. Additionally, adherence support interventions should recognize that non-adherence may not be persistent and can be improved with timely counseling, treatment literacy, peer support, and people-centered care strategies. From a policy perspective, these results underscore the importance of designing adherence assessment protocols that reflect the fluid nature of adherence behavior and encourage routine, longitudinal monitoring. Tailoring adherence interventions to individual histories, rather than using fixed definitions, could enhance responsiveness to PLWHA’s evolving needs and ultimately improve treatment outcomes among people living with HIV/AIDS.
Despite these limitations, the main findings of this study add insights into the interplay of determinants of ART adherence and quality of life among PLWHA.
Recommendations for future research
The findings of this study necessitate some recommendations for future research. First, prospective studies with established designs, such as cohort studies, will be useful in avoiding selection bias and determining causality and direction of association between risk factors and medication adherence. Second, longitudinal research on the effect of adherence and follow-up of PLWHA over time is needed to assess how changes in medication adherence influence quality of life in a larger population may help clinical practitioners design effective policies to improve the quality of life for PLWHA. These will also help to better understand the temporal relationship between clinical, behavioral, and sociodemographic factors and allow for more robust conclusions about causality and the direction of observed associations. Third, given the limitations of the self-reported SMAQ tool, future research should incorporate objective adherence measures such as pharmacy refill data, electronic pill monitoring, or viral load trends. This will help validate self-reported data and minimize recall bias. Further, future research should explore structural and contextual factors influencing adherence, including institutional practices, community support systems, and policy-level enablers or barriers, which are necessary to create a supportive environment for PLWHA or at-risk groups to adhere to medication regimens, to better inform care and policies. These multilevel insights would better inform the design of targeted interventions to support ART adherence and improve the overall well-being of PLWHA.
Acknowledgements
Acknowledgements: The authors would like to thank and appreciate the participants in the research study and the staff of the Ahmadu Bello University Teaching Hospital, Usmanu Danfodiyo University Teaching Hospital, and Aminu Kano Teaching Hospital for providing insight into the study method and data collection.
Authors’ contributions
AA, MOA, IA, DOA and BGA conceived the study and collected data; AA, YHW, MOA, IA, DOA, MKM, and AYF wrote the main manuscript; AA, MOA, IA, KAG, AS, IAO, JA, OI, and YHW reviewed the draft copy of the manuscript, and all authors reviewed the final version of the manuscript.
Funding
No Funding.
Data availability
Data and other materials that were analyzed in this study are available upon request from the corresponding author at [hwada@sfhnigeria.org](mailto: hwada@sfhnigeria.org).
Declarations
Ethics approval and consent to participate
Ethical approval for the present study was secured from the Health Research Ethics Committee of Usmanu Danfodiyo University Teaching Hospital (UDUTH) (NHREC/30/012/2019), Ahmadu Bello University Teaching Hospital (ABUTH) (NREC/10/2015), and Aminu Kano Teaching Hospital (AKTH) (NHREC/28/01/2020/AKTH/2846). Informed consent, both verbal and written, was acquired from every participant involved in the study. The nature and objectives of the study were explained to each participant, and assurance of confidentiality and anonymity was given with an option to opt out at any time, and written consent for participation in the study by way of signing the consent form was obtained. Participants were made to understand that participation in the study was completely voluntary ab initio, and individuals who did not consent to participate in the study were exempted. The research was also conducted per the Helsinki Ethical Principles for Medical Research involving human participants and the local guidelines as outlined in the ethical approval guidelines.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data and other materials that were analyzed in this study are available upon request from the corresponding author at [hwada@sfhnigeria.org](mailto: hwada@sfhnigeria.org).