Abstract
Background
This study was aimed to evaluates the quality of life using WHOQOL-BREF in VL patients co-infected with HIV in Bihar, India.
Methods
This cross-sectional study enrolled 240 participants: 60 HIV-VL co-infected, 60 HIV, 60 VL and 60 healthy individuals. Socio-demographic data and QOL assessments used the Hindi WHOQOL-BREF questionnaire. The data were compared using the chi-square test, One-Way ANOVA followed by Tukey's post-hoc Test. Generalised linear regression was performed for analyses of predictors of QOL, as well as the socio-economic status was determined by using the Modified Kuppuswamy socio-economic Scale 2022.
Results
HIV-VL co-infected patients reported significantly lower QOL scores across all domains (physical, psychological, social relationships, and environmental) compared to healthy individuals (p < 0.05). Notably, psychological (12.17 ± 1.17), social relationship (5.90 ± 1.16), and environmental (14.10 ± 1.68) domains were severely impacted in HIV-VL coinfection in contrast to HIV (p < 0.05) and VL (p < 0.05).
Conclusion
HIV-VL co-infection profoundly affects quality of life, emphasizing the need for targeted interventions addressing psychological, social and environmental well-being. Future research should prioritize strategies improving QOL and assessing long-term treatment effects in HIV-VL co-infection.
Supplementary Information
The online version contains supplementary material available at 10.1186/s41043-025-00821-6.
Keywords: Quality of life, HIV coinfection, Visceral leishmaniasis (VL), WHOQOL-BREF
Introduction
Visceral leishmaniasis (VL) is a severe systemic manifestation of leishmaniasis, classified as a neglected tropical disease and transmitted by female phlebotomine sandflies. The global incidence of VL is estimated to be between 50,000 and 90,000 cases annually [1]. In 2020, Brazil, Ethiopia, Eritrea, India, Iraq, Kenya, Nepal, Somalia, South Sudan and Sudan. These high-burden countries are among the more than 70 countries in which VL is considered endemic over 90% of WHO-reported VL cases [2, 3], presenting a significant public health challenge, particularly in endemic regions like Bihar, India, which alone represents approximately 40% of worldwide cases [3].
HIV-infected patients face a heightened risk of developing VL, either from a latent infection or as a clinical manifestation of initial leishmania infection in HIV-endemic areas. [2, 4] The interplay between HIV and VL is particularly detrimental; the presence of VL can accelerate HIV replication and hasten the progression toward AIDS [2, 5]. This co-infection can reactivate dormant leishmania infections, making HIV-positive individuals more susceptible to symptomatic VL. Consequently, VL is often viewed as an opportunistic infection in HIV patients, frequently presenting with atypical clinical features. Co-infected patients are at greater risk of mortality and relapses, with common symptoms including fever, splenomegaly or hepatomegaly, loss of appetite, and weight loss. In cases of severe immunosuppression, VL may affect atypical sites such as the gastrointestinal tract, oral mucosa, and skin [5]
The treatment of HIV-VL patients follows the World Health Organisation (WHO) guidelines, which recommend either Liposomal Amphotericin B (L-AMB) monotherapy or a combination therapy of L-AMB and miltefosine. Specific dosages include 100 mg/day of miltefosine for 14 days combined with L-AMB at 5 mg/kg [2, 3]. The treatment of HIV positive patients was given as per the NACO guideline 2018, the recommended choice of first line regimen comprises of a NRTI backbone [1], preferably Non-Thymidine (Tenofovir plus Lamivudine) and one NNRTI, preferably EFV. Based on the evidence supporting better efficacy and fewer side effects, it is now recommended that all PLHIV with HIV-1 infection be initiated on a regimen consisting of Tenofovir (TDF 300 mg) + Lamivudine (3TC 300 mg) + Efavirenz (EFV 600 mg) (TLE) as fixed dose combination (FDC) in a single pill once a day [4, 6].
Previous studies showed that VL patients face numerous physical, psychological, and environmental challenges, exacerbated by the side effects of antileishmanial therapies [7]. The co-infection with HIV complicates VL outcomes, resulting in higher rates of disease relapse, treatment failure, and increased mortality [5]. Additionally, the psychological effects of HIV-VL co-infection can lead to stigma, social isolation, and deplorable quality of life. [8, 9]. Despite these implications, the impact of HIV-VL co-infection on quality of life remains inadequately explored, and there is a need for the study to assess the effect of HIV-VL co-infection on quality of life (QOL). QOL, as defined by the WHO is “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns” [10]. Given that HIV-VL is a chronic condition, a thorough assessment of QOL is essential for understanding its physical, social, and psychological impacts [11].
The present study hypothesizes that, there are no differences in QOL between the HIV-VL coinfection, VL only, HIV only, and healthy individuals. To test this hypothesis, this study focuses on evaluating the quality of life in VL patients co-infected with HIV in the endemic region of Bihar, India.
Methods
Study design and setting
This cross-sectional study was conducted at the Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Indian Council of Medical Research (ICMR) in Patna, Bihar, India, from February 2023 to June 2024. The RMRIMS is the WHO collaboration centre for the diagnosis and treatment of VL in the state of Bihar, India.
Inclusion and exclusion criteria
The participants for the study were selected based on specific inclusion and exclusion criteria. Patients had to meet the following criteria: age group 18–70 years, a confirmed diagnosis of HIV-VL co-infection, admission to the inpatient department of the study site, and willingness to participate in the study. Conversely, patients were excluded from the study if they were having age less than 18 year and more than 70 years or any chronic condition or comorbidities like diabetes mellites, hypertension, and their medical records were incomplete. This ensured the accuracy and reliability of the collected data.
Study participants
The patients diagnosed with HIV-VL co-infection and VL only were recruited from the inpatient ward of RMRIMS, while HIV patients on antiretroviral therapy (ART) were enrolled from the ART centre, and Healthy Individuals, without HIV and VL positive and not taking any medication were recruited from the outpatient department of the RMRIMS. This study included 240 participants; were divided into four different groups to assess the underling effect of disease or treatment associated with disease on QOL, compare to healthy individuals: HIV-VL (n = 60); VL (n = 60); HIV only (n = 60) and Healthy individuals (HI; n = 60).
Sample size calculation
The sample size calculation was based on a study by Devi Priya et al. (2019). Assuming a 25% difference in Quality of Life (QOL) scores between groups, the following parameters were used:
Population size (N): 1,000,000
Hypothesized percentage frequency of outcome factor in the population (p): 30% (25% + 5%)
Confidence limits (d): 5% (absolute)
Using these parameters, the expected sample size was calculated to be n = 203 (90% Confidence Interval). However, to enhance the generalizability of the results, a total of 240 samples were collected.
Data collection
The demographic data including age, sex, marital status, area of stay, education, occupation and monthly income of patients were collected by using semi structured questionnaire. Furthermore, data were collected using the validated Hindi version of the WHO Quality of Life Instrument (WHOQOL-BREF-Hindi) [12, 13] to assess the QOL of VL patients co-infected with HIV. This standardized self-report questionnaire assesses an individual's QOL across four domains: physical health, psychological health, social relationships, and environment. The questionnaire was administered to the patients on bedside in inpatient department by the principal investigator. Literate patients completed it independently, while for those who were illiterate, a face-to-face interview was conducted in a quiet and private area to ensure Patient’s comfort and confidentiality. The WHOQOL-BREF Hindi version has been previously validated and tested for its reliability and validity in the Indian population [11].
Scoring and computation
The WHOQOL-BREF Hindi version consists of 26 items, of which 24 are categorized into four domains: physical health, psychological health, social relationships, and environment. The remaining two items assess self-perceived quality of life and satisfaction with health. Responses are scored using a 5-point Likert scale, assessing various aspects such as intensity (nothing-extreme), capacity (nothing-complete), frequency (never-always), and assessment scales (very dissatisfied-very satisfied; very bad-very good). Each item is rated on a scale from one to five. The raw scores are then manually transformed according to the WHOQOL-BREF guidelines, transforming them to a 0–100 scale to facilitate comparisons between domains with different numbers of items [14].
The physical domain consisted of questions e.g.1. To what extent do you feel that physical pain prevents you from doing what you need? 2. How much do you need any medical treatment to function in your daily life? (Not at all-1, A little-2, A moderate amount-3, Very much-4, An extreme amount-5). The questions in psychological domain e.g. 1. How much do you enjoy life? 2.To what extent do you feel your life to be meaningful? (Not at all-1, A little-2, A moderate amount-3, Very much-4, An extreme amount-5). The social relationship domain includes the questions like, e.g.1.How satisfied are you with your personal relationships? 2.how satisfied are you with your sex life? 3.How satisfied are you with the support you get from your friends? (The given scores were, very dissatisfied-1, Dissatisfied-2, Neither satisfied nor dissatisfied-3, Satisfied-4, Very satisfied-5). The environment domain of QOL comprises the questions like, 1. How safe do you feel in your daily life?2. How healthy is your Physical environment? (Not at all-1, A little-2, A moderate amount-3, Very much-4, Extremely-5) [15].
Potential sources of biases
This study was susceptible to biases, including selection bias due to consecutive sampling, social desirability bias in patient-reported QOL data, information bias from recall errors, and confounding bias from unmeasured variables. Confidentiality and anonymity of patient responses and use of a validated QOL instrument were employed to minimise bias.
Ethical statement
This study received approval from the Institutional Ethics Committee of ICMR-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna (RMRI/EC/48/2023). The questionnaire was administered only after the study's purpose had been clearly explained to the participants, and written informed consent was obtained in Hindi. Participants were assured of the anonymity and confidentiality of their data.
Data analysis
The independent variables across the four group were compared using the Chi-square test; where, continuous variables were represented as the mean and standard deviation (SD), while categorical variables were summarized using frequencies and percentages. The comparison of QOL between HIV-VL and control groups (HIV only, VL, and Healthy Individuals) with WHOQOL-BREF domains was evaluated using the One-Way ANOVA followed by Tukey's post-hoc Test. Generalised linear regression was done for predictor analyses and the Socio-Economic Status (SES) was determined by using the Modified Kuppuswamy Socio-Economic Scale 2022. All statistical tests were two-tailed, with a p-value ≤ 0.05 considered statistically significant. Data analysis was performed using the Statistical Package for Social Sciences (SPSS), version 27.0.
Results
Participant characteristics
A total of 240 participants were enrolled in the study, comprising four different groups: HIV-VL (n = 60), HIV (n = 60), VL (n = 60), and healthy individuals (n = 60). The demographic characteristics of the participants are presented in Table 1.
Table 1.
Demographic characteristics of participants
| Category | Variables | HIV-VL | HIV | VL | HI | P-value |
|---|---|---|---|---|---|---|
| N (%) | N (%) | N (%) | N (%) | |||
| Gender | Male | 37 (61.7) | 42 (70.0) | 39 (65.0) | 35 (58.3) | 0.60 |
| Female | 23 (38.3) | 18 (30.0) | 21 (35.0) | 25 (41.7) | ||
| Age | 18–35 | 21 (35.0) | 22 (36.7) | 27 (45.0) | 35 (58.3) | 0.06 |
| 36–53 | 9 (15.0) | 14 (23.3) | 19 (31.7) | 17 (28.3) | ||
| > 53 | 30 (50.0) | 24 (40.0) | 14 (23.3) | 8 (13.3) | ||
| Marital status | Married | 47 (78.3) | 44 (73.3) | 43 (71.7) | 41 (68.3) | 0.66 |
| Unmarried | 13 (5.0) | 16 (11.7) | 17 (18.7) | 19 (10.0) | ||
| Area of residence | Urban | 20 (33.3) | 17 (28.3) | 10 (16.7) | 23 (38.3) | 0.05 |
| Rural | 40 (66.0) | 43 (71.7) | 50 (83.3) | 37 (61.7) | ||
| Education | Illiterate | 32(53.33) | 22 (36.66) | 28 (46.66) | 13 (21.66) | 0.05 |
| Primary school | 10 (16.66) | 13 (21.66) | 5 (8.33) | 2 (3.33) | ||
| Middle school | 8 (13.33) | 9 (15) | 14 (23.33) | 20 (33.33) | ||
| Intermediate/Diploma | 8 (13.33) | 13 (21.66) | 11 (18.33) | 6 (10) | ||
| Graduate | 2 (3.33) | 3 (5) | 2 (3.33) | 19 (31.66) | ||
| Occupation | Unskilled workers | 14 (23.33) | 6 (10.00) | 12 (20) | 5 (8.33) | 0.05 |
| Clerical/shop/farmer | 24 (40.00) | 5 (8.33) | 18 (30) | 12 (20.00) | ||
| Unemployed | 19 (31.66) | 1 (1.66) | 24 (40) | 13 (21.66) | ||
| Semi Professional | 3 (5) | 15 (25.00) | 5 (8.33) | 25 (41.66) | ||
| Semi-skilled workers | 0 | 33 (55) | 1 (1.66) | 5 (8.33) | ||
| Monthly income (INR) | < 9307 | 31 (51.66) | 35 (58.33) | 38(63.33) | 23 (38.33) | 0.05 |
| 9308–27882 | 29 (48.33) | 19 (31.66) | 21(35) | 27 (45) | ||
| 27883–46474 | 0 | 0 | 0 | 4 (6.66) | ||
| 46475–69534 | 0 | 6 (10.00) | 1 (1.66) | 6 (10.00) | ||
| SEC | Lower (V) | 21 (35.0) | 9(15.0) | 14 (23.3) | 14 (23.3) | |
| Upper Lower (IV) | 14 (23.3) | 20 (33.3) | 19 (31.7) | 16 (26.7) | 0.36 | |
| Lower Middle (III) | 16 (26.7) | 16 (26.7) | 18 (30.0) | 21 (35.0) | ||
| Upper Middle (II) | 9 (15.0) | 15 (25.0) | ||||
| 9 (15.0) | 9(15.00) |
The values are represented in numbers and percentages, The proportions were compared using Chi-square test, p- value < 0.05 indicating statistically significant difference
SEC: Socioeconomic class
The mean age of the HIV-VL group was 38.12 years, with 50.0% (n = 30) of the participants above 53 years old. The majority were male (61.7 % n = 37 p = 0.60), married (78.3%, n = 47, p = 0.66), and belonged to rural areas (66.0%, n = 40, p = 0.05).The level of education varied and statistically significant (p = 0.05) among the participants, with (53.33%, n = 32) being illiterate, followed by primary school (16.66%, n = 10), middle school (13.33%, n = 8), intermediate/diploma (13.33%, n = 8), and graduate (3.33%, n = 2). In terms of occupation, there was a statistical significant difference (p = 0.05), the majority of participants in the HIV-VL group were engaged in clerical/shop/farmer occupations (40.0%, n = 24), followed by unemployed (31.66%, n = 19).The monthly income of the participants also varied and found statistically significant (p = 0.05), with 51.66% (n = 31) having a monthly income of INR < 9307 (51.6% n = 31), followed by INR 9308–27882 (48.33%, n = 29).The SES of the participants was diverse, with the largest proportion (35.0%, n = 21, p = 0.36) belonging to the lower SEC.
Quality of life outcomes
Comparison of QOL outcomes across groups revealed significant differences (p < 0.05) in all the domains of the WHOQOL-BREF scale presented in Table 2.
Table 2.
Comparison on QOL domains among different groups
| QOL Domains | HIV-VL | HIV | VL | HI | HIV-VL v/s HIV | HIV-VL v/s VL | HIV-VL v/s HI |
|---|---|---|---|---|---|---|---|
| Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | ||||
| Physical | 18.78 ± 2.40 | 18.78 ± 2.94 | 18.35 ± 3.12 | 21.90 ± 3.46 | 1 | 0.86 | < 0.05 |
| Psychological | 12.17 ± 1.17 | 14.15 ± 2.31 | 15.70 ± 1.90 | 19.53 ± 3.20 | < 0.05 | < 0.05 | < 0.05 |
| Social Relationship | 5.90 ± 1.16 | 5.23 ± 0.91 | 6.62 ± 1.56 | 10.00 ± 2.12 | 0.077 | 0.05 | < 0.05 |
| Environment | 14.10 ± 1.68 | 17.80 ± 2.44 | 17.30 ± 3.28 | 23.12 ± 2.73 | < 0.05 | < 0.05 | < 0.05 |
The values are represented in mean and standard deviation (SD), One-Way ANOVA and Tukey’s post-hoc were used for comparison, p-value ≤ 0.05 indicating a statistically significant difference
The physical domain showed no significant differences between HIV-VL (18.78 ± 2.40) and HIV (18.78 ± 2.94) (p = 1.00) or VL (18.35 ± 3.12) (p = 0.86) groups, but was significantly lower compared to healthy individuals (21.90 ± 3.46) (p < 0.05). In the psychological domain, HIV-VL participants (12.17 ± 1.17) reported significantly poorer QOL compared to HIV (14.15 ± 2.31, p < 0.05), VL (15.70 ± 1.90, p < 0.05), and healthy individuals (19.53 ± 3.20, p < 0.001).The social relationship domain was significantly impaired in HIV-VL (5.90 ± 1.16) compared to healthy individuals (10.00 ± 2.12, p < 0.05) and marginally significant compared to VL (6.62 ± 1.56, P = 0.05). Furthermore, the environmental domain demonstrated significant differences, with HIV-VL participants (14.10 ± 1.68) reporting poorer QOL compared to HIV (17.80 ± 2.44, p < 0.05), VL (17.30 ± 3.28, P < 0.05), and healthy individuals (23.12 ± 2.73, p < 0.05).
QOL comparison among all the groups
There were significant differences (P < 0.05) in all domains of QOL between the HIV-VL and control groups (HIV, VL, and Healthy Individuals). The only domains in which the HIV-VL group did not differ from the HIV group were the physical and social relationship domains. Furthermore, we observed significant differences between the HIV-VL group, the VL group, and healthy individuals (P < 0.05) (Fig. 1).
Fig. 1.
Comparisons of QOL outcomes in HIV-VL patients with HIV only, VL only, Healthy Individuals. A represents Physical Domain; B represents, psychological domain; C represents social relationship; D represents, Environmental domain of QOL
Comparison of QOL domains with different demographic variables
This study examined the association between QOL domains and various demographic variables. The results are summarized in Table 3.
Table 3.
Comparison of different demographic variables with QOL domains
| Category | Demographic variable | Physical | Psychological | Social relationship | Environment |
|---|---|---|---|---|---|
| Age (Years) | 18–35 | 19.87 ± 3.62 | 15.92 ± 3.70 | 7.25 ± 2.63 | 18.56 ± 4.48 |
| 36–53 | 19.09 ± 2.82 | 14.68 ± 3.35 | 6.46 ± 1.99 | 17.22 ± 3.69 | |
| > 53 | 18.96 ± 3.44 | 15.72 ± 2.90 | 7.26 ± 2.27 | 19.11 ± 3.66 | |
| p-value | .167 | < 0.05 | < 0.05 | < 0.05 | |
| Gender | Male | 19.31 ± 3.46 | 14.89 ± 3.54 | 6.74 ± 2.29 | 17.65 ± 4.11 |
| Female | 19.67 ± 3.25 | 16.17 ± 3.37 | 7.23 ± 2.47 | 18.74 ± 4.12 | |
| p-value | .418 | < 0.05 | .121 | < 0.05 | |
| Area of Stay | Rural | 19.42 ± 3.24 | 15.35 ± 3.45 | 6.87 ± 2.25 | 18.08 ± 4.08 |
| Urban | 19.51 ± 3.48 | 15.48 ± 3.52 | 7.10 ± 2.64 | 18.07 ± 4.31 | |
| p-value | 0.85 | 0.79 | 0.49 | 0.98 | |
| Level of Education | Illiterate | 19.08 ± 3.08 | 14.48 ± 3.05 | 6.52 ± 1.99 | 17.01 ± 3.58 |
| Primary School | 18.56 ± 3.33 | 14.06 ± 2.80 | 5.96 ± 1.97 | 17.10 ± 2.68 | |
| Middle School | 19.86 ± 3.65 | 16.41 ± 3.67 | 7.60 ± 2.68 | 19.13 ± 4.51 | |
| Intermediate/Diploma | 18.89 ± 3.06 | 14.86 ± 3.00 | 6.28 ± 1.90 | 17.42 ± 4.27 | |
| Graduated | 21.84 ± 2.67 | 18.96 ± 3.62 | 9.19 ± 2.44 | 22.00 ± 3.90 | |
| p-value | < 0.05 | < 0.05 | < 0.05 | < 0.05 | |
| Marital status | Married | 16.92 ± 1.83 | 11.88 ± 1.57 | 5.29 ± 1.43 | 16.48 ± 2.24 |
| Unmarried | 17.30 ± 1.53 | 11.60 ± 1.69 | 5.42 ± 1.14 | 16.91 ± 2.6 | |
| p-value | 0.24 | 0.41 | 0.60 | 0.44 | |
| SEC | Lower (V) | 19.15 ± 3.33 | 14.68 ± 3.19 | 6.73 ± 2.20 | 17.13 ± 3.65 |
| Upper Lower (IV) | 19.26 ± 3.28 | 15.21 ± 3.38 | 6.69 ± 2.34 | 18.16 ± 3.97 | |
| Lower Middle (III) | 19.91 ± 3.06 | 16.70 ± 3.89 | 7.59 ± 2.56 | 19.23 ± 4.85 | |
| Upper Middle (II) | 22.71 ± 3.54 | 18.00 ± 3.87 | 8.57 ± 2.50 | 21.14 ± 4.56 | |
| p-value | < 0.05 | < 0.05 | < 0.05 | < 0.05 |
The values are represented in mean and standard deviation (SD), One-Way ANOVA and Tukey’s post-hoc were used for comparison, p-value ≤ 0.05 indicating a statistically significant difference
SEC: Socioeconomic class
The analysis revealed significant associations between age categories and three QOL domains: psychological (V social relationships (p < 0.05), and environment (p < 0.05). However, no significant association was found with the physical domain. We observed gender differences in two QOL domains. Males had poorer QOL scores than females in the psychological domain (14.89 ± 3.54 vs. 16.17 ± 3.37, p < 0.05) and environment domain (17.65 ± 4.11 vs. 18.74 ± 4.12, p < 0.05). The level of education was also found to be associated with QOL domains. Participants with a primary school education had poorer physical domain scores (18.56 ± 3.33) compared to those with a graduate-level education (21.84 ± 2.67). Similarly, participants with primary school or no formal education (illiterate) had poorer psychological domain scores (14.06 ± 2.80) than graduates.
In the social relationships domain, all education levels had poorer QOL scores than graduates (p < 0.05). In the environment domain, illiterate participants had the poorest QOL scores (17.01 ± 3.58), which were significantly different from all other education levels (p < 0.05). The socioeconomic status was also found to be associated with the poor QOL score in all the domains. In physical domain lower SEC had a poor QOL score (19.15 ± 3.33) compare to Upper middle (II), lower middle (III) and upper lower (IV) class of SES. Similarly in psychological domain lower SEC had a poor QOL score (14.68 ± 3.19, p < 0.05). Furthermore, the environment domain of WHOQOL-BREF had a significantly poor QOL score (17.13 ± 3.65, p < 0.05) in comparison with other class of SES.
Generalised linear regression analyses
The results of the generalized linear regression analyses, presented in Table 4, identified significant predictors of health-related quality of life (HRQoL) across different domains.
Table 4.
Generalized Linear regression analyses between sociodemographic variables and QOL
| Category | Predictor variables | Beta | 95% CI Lower | 95% CI Upper | df | p-value |
|---|---|---|---|---|---|---|
| Physical | ||||||
| Occupation | Unskilled workers | 0.72 | 0.32 | 1.41 | 1 | < 0.05 |
| Clerical/Shop/Farmer | 1.33 | 0.65 | 2.02 | 1 | < 0.05 | |
| Unemployed | 1.65 | 0.90 | 2.40 | 1 | < 0.05 | |
| Semi-Professional | 0.53 | − 0.38 | 1.45 | 1 | 0.25 | |
| Semi-skilled workers | Ref | – | – | – | – | |
| Education Level | Illiterate | − 1.61 | − 2.75 | − 0.47 | 1 | < 0.05 |
| Primary school | − 1.65 | − 2.81 | − 0.57 | 1 | < 0.05 | |
| Middle school | − 1.75 | − 2.85 | − 0.65 | 1 | < 0.05 | |
| Intermediate/Diploma | − 1.30 | − 2.22 | − 0.37 | 1 | < 0.05 | |
| Graduate | Ref | – | – | – | – | |
| Psychological | ||||||
| Occupation | Clerical/Shop/Farmer | − 0.90 | − 1.66 | − 0.13 | 1 | < 0.05 |
| Semi-Professional | − 1.66 | − 2.68 | − 0.63 | 1 | < 0.05 | |
| Semi-skilled workers | Ref | – | – | – | – | |
| Education level | Illiterate | 1.88 | 0.61 | 3.14 | 1 | < 0.05 |
| Primary School | − 1.42 | 0.13 | 2.70 | 1 | < 0.05 | |
| Middle School | 1.17 | − 0.04 | 2.40 | 1 | 0.05 | |
| Intermediate/Diploma | 1.31 | 0.29 | 2.34 | 1 | < 0.05 | |
| Graduate | Ref | – | – | – | – | |
| SEC | lower | − 3.04 | − 5.75 | − 0.34 | 1 | < 0.05 |
| Social relationship | ||||||
| Gender | Male | − 0.43 | − 0.11 | 7.00 | 1 | < 0.05 |
| Female | Ref | – | – | – | – | |
| Area of Stay | Rural | − 0.35 | − 0.02 | 4.40 | 1 | < 0.05 |
| Urban | 0a | |||||
| Occupation | Clerical/Shop/Farmer | 1.53 | 0.98 | 2.09 | 1 | < 0.05 |
| Semi-Professional | 1.14 | 0.39 | 1.89 | 1 | < 0.05 | |
| Semi-skilled workers | Ref | – | – | – | – | |
| Monthly Income (INR) | 27883–46474 | 2.81 | 1.25 | 4.36 | 1 | < 0.05 |
| 46475–69534 | Ref | – | – | – | – | |
| Education Level | Illiterate | − 2.12 | − 3.05 | − 1.19 | 1 | < 0.05 |
| Primary School | − 2.45 | − 3.39 | − 1.51 | 1 | < 0.05 | |
| Middle School | − 1.66 | − 2.55 | − 0.76 | 1 | < 0.05 | |
| Intermediate/Diploma | − 0.94 | − 1.69 | − 0.18 | 1 | < 0.05 | |
| Graduate | Ref | – | – | – | – | |
| SEC | Lower middle | − 1.38 | − 2.80 | < 0.05 | 1 | 0.05 |
| Upper middle | Ref | – | – | – | – | |
| Environment | ||||||
| Gender | Male | − 1.30 | − 1.96 | − 0.64 | 1 | < 0.05 |
| Female | Ref | – | – | – | – | |
| Area of Stay | Rural | − 0.06 | − 1.37 | − 0.10 | 1 | < 0.05 |
| Urban | Ref | – | – | – | – | |
| Occupation | Unemployed | − 1.56 | − 2.82 | − 0.31 | 1 | < 0.05 |
| Education level | Illiterate | − 4.09 | − 6.00 | − 2.19 | 1 | < 0.05 |
| Primary School | − 3.96 | − 5.88 | − 2.03 | 1 | < 0.05 | |
| Middle School | − 2.63 | − 4.47 | − 0.79 | 1 | 0.05 | |
| Intermediate/Diploma | − 4.27 | − 5.82 | − 0.72 | 1 | < 0.05 | |
| Graduate | Ref | – | – | – | – | |
| SEC | Lower | 4.04 | − 0.01 | 8.09 | 1 | 0.05 |
Ref: Reference (constant); df: degrees of freedom; p-value ≤ 0.05 indicating a statistically significant difference
In the physical domain, unskilled workers reported significantly lower scores (β = 0.72, p < 0.05). Individuals with occupations such as clerical, shopkeeping, or farming (β = 1.33, p < 0.05), as well as those categorized as unemployed (β = 1.65, p < 0.05), exhibited significantly poor QOL scores compared to semi-skilled workers. Additionally, educational attainment was significantly associated with QOL. Participants who were illiterate (β = − 1.61, p < 0.05), had completed primary school (β = − 1.65, p < 0.05), middle school (β = − 1.75, p < 0.05), or intermediate/diploma education (β = − 1.30, p < 0.05) demonstrated lower QOL scores when compared to graduates.
In the psychological domain, individuals in the occupational category of clerical, shopkeeping, or farming (β = − 0.90, p < 0.05) and those classified as semi-professionals (β = − 1.66, p < 0.05) exhibited significantly lower scores. Furthermore, educational levels were consistently associated with poorer QOL across all domains. Specifically, individuals who were illiterate (β = 1.88, p < 0.05), had completed primary school (β = − 1.42, p < 0.05), middle school (β = 1.17, p < 0.05), or intermediate/diploma education (β = 1.31, p < 0.05) exhibited significantly lower QOL scores compared to graduates. Additionally, participants having lower SEC showed the significant difference in QOL (β = − 3.04, p < 0.05).
The social relationship domain was significantly influenced by monthly income, with individuals earning INR 27,883–46,474 reporting higher scores (β = 2.81, p = 0.05). Furthermore Male had a strongly associated with poor QOL compare to female (β = − 0.43, p < 0.05), Participants living in rural area (β = − 0.35, p < 0.05), as well as individuals who worked as clerical/shop/farmer (β = 1.53, p < 0.05) and semi-professional (β = 1.14, p < 0.05) were found to be associated with poor QOL scores in the social relationship domain .Additionally those with an illiterate (β = − 2.12, p = < 0.05), primary school (β = − 2.45, p = < 0.05), middle school (β = − 1.66, p < 0.05) and intermediate/diploma level of education reported lower social relationship domain scores (β = − 0.94, (β = 2.81, p = 0.05) compared with graduate. Additionally, participants having lower middle SEC showed the significant difference in QOL (β = − 1.38, p < 0.05).
In the environmental domain, males reported significantly lower scores (β = − 1.30, p < 0.05). Participants living in rural area (β = − 0.06, p < 0.05), as well as unemployed individuals (β = − 1.56, p < 0.05). Additionally, level of education was significantly associated with QOL. Participants who were illiterate (β = − 4.09, p < 0.05), had completed primary school (β = − 3.96, p < 0.05), middle school (β = − 2.63, p < 0.05), or intermediate/diploma education (β = − 4.27, p < 0.05) demonstrated lower QOL scores when compared to graduates. Those demographic variables were not significantly associated with the QOL have been included in the supplementary file.
Discussion
The co-infection of visceral leishmaniasis (VL) and human immunodeficiency virus (HIV) presents significant challenges to healthcare systems, especially in endemic regions [2]. Previous studies reported that coinfected patients had poor quality of life in WHOQOL- HIV instrument as compared to people living with HIV alone. The simultaneous presence of both diseases in a single person has significant impact on QOL affecting the physical, social and mental wellbeing. The reason for this is chronic immune stimulation and boost of HIV replication and disease progression by the VL [9]. Our study examined the impact of HIV-VL co-infection on health-related quality of life (HRQOL) using the WHOQOL-BREF questionnaire. The findings emphasize the substantial burden of HIV-VL co-infection on QOL, highlighting the need for comprehensive care and support.
Consistent with previous studies [9, 16, 17], demographic factors, including monthly income, educational level, and occupation, are important determinants of low QOL scores [16, 18]. Our study found that having less education (illiterate, primary school, middle school, and intermediate/diploma) and employment in specific (especially unskilled ones, like clerical/shop/farmers), as well as being unemployed, were strong indicators of poor QOL in the physical domain. These findings could potentially stem from the fact that unskilled workers frequently engage in daily wage and labour-intensive tasks, such as construction. They also earn lower wages, constraining their ability to afford nutritious food, access to a good healthcare system, and a healthy living environment. Similarly, clerical, shop, and farming individuals may experience physical stress due to longer working hours, monotonous work, and lack of ergonomic work facilities. Furthermore, individuals with a higher education level are more concerned about their health and might have more knowledge about the disease. All these factors are responsible for poor physical health.
In the psychological domain, individuals employed in clerical, shops, farming, and semi-professional occupations exhibited poorer quality of life scores. Moreover, lesser educational level (illiteracy, primary education, middle school, and intermediate/diploma) and impaired socioeconomic status (SES) were significant predictors of psychological well-being. These findings highlight the potential impact of employment assurance, financial stability, and level of education on psychological well-being, given that people with lower educational qualifications might experience more anxiety due to limited career opportunities and financial limitations.
Male participants, those living in rural areas, and those working in semi-professional, semi-skilled, and clerical/shop/farming occupations reported lower QOL scores for the social relationship domain. Additionally, a monthly income ranging from INR 27,883 to ₹46,474, coupled with lower levels of educational attainment (illiterate, primary school, middle school, and intermediate/diploma), were key indicators of social well-being.
In the environmental domain, significant factors contributing to poorer quality of life scores included male gender, rural residency, unemployment, and lower educational levels (illiteracy to intermediate/diploma) in comparison to graduates.
Socio-Economic Status (SES) by using an updated modified Kuppuswamy SES, 2022. Among the various instruments available for assessing socioeconomic status, the "updated modified Kuppuswamy SES" stands out as one of the most commonly employed and recognized scales in India [19]. This scale evaluates three main factors: overall income, level of education, and employment status [20]. The Kuppuswamy scale categorizes families into five distinct groups on the basis of total scores of three key factors: Education (1 = Illiterate to 7 for professional degree), Occupation (Unemployed = 1 to Professional = 7) and family income (< 9307 = 1 to > ≥ 185,895 = 12): upper class (score = 26–29), upper middle class (score = 16–25), lower middle class (score = 11–15), upper lower class (score = 5–10), and lower class (score = < 5). The result of this study revealed that, the lower SEC was associated with poorer QOL score compared to the upper middle (II). It is particularly noteworthy that individuals from lower socio-economic backgrounds demonstrated poor QOL.
Align with previous study, all the domains (including physical, psychological, social relationship, and environment) patients who were coinfected with HIV and VL had a lower mean score compare to HIV patient, which indicated that their quality of life was poor [9].
In the present study, comparative analysis revealed significant differences in QOL scores between all the participants. HIV-VL patients had lower QOL scores across psychological and environmental domains compared to HIV-only patients, while scores in the physical and social relationship domains did not show significant differences. HIV-VL patients demonstrated lower scores across all QOL domains compared to VL patients and healthy individuals. The study findings highlight the profound impact of HIV-VL co-infection on QOL and highlight the need for targeted interventions addressing demographic disparities. The hypothesis of present study was, there are no differences in QOL between the HIV-VL coinfection, VL only, HIV only, and healthy individuals but we found significant difference in QOL of score in all the domains of WHOQOL-BREF in HIV-VL patients compared to healthy individuals, therefore the null hypothesis is rejected.
Limitations include the small sample size, baseline assessment, and reliance on the WHOQOL-BREF. Future longitudinal studies with larger sample sizes and specialized tools are necessary to comprehensively address the QOL of HIV-VL patients. Healthcare policy and practice implications include addressing socio-economic determinants of health, improving access to education and healthcare, and providing comprehensive care and support. Tailored interventions targeting vulnerable populations, such as older adults and those with lower educational attainment, may also be necessary.
Conclusion
In conclusion, this study highlights the significant impact of co-infection of HIV-VL on quality of life. The study found significantly lower scores across all domains when compared to individuals with only HIV, only VL, and healthy individuals. Future research should prioritize improving all aspects of quality of life and evaluating the long-term effects of treatment in HIV-VL patients. It is crucial to implement targeted interventions that address socioeconomic disparities, educational vulnerabilities, and age-related factors. This study provides valuable insights for healthcare policy and practice, emphasizing the need for integrated, patient-centred care for HIV-VL patients.
Supplementary Information
Acknowledgements
The authors would like to acknowledge the support of medical and nursing staff, Integrated Counselling and Testing Centre (ICTC), ART Center and Central Diagnostic Laboratory (CDL) staff and participants attending the clinic of the ICMR-RMRIMS hospital, Patna. Special thanks to Dr Akshay Shelke, Mr V. Uday Kumar and Ms Ruchi Pandey, as well as the Department of Pharmaceuticals, Ministry of Chemicals and Fertilisers, Government of India.
Abbreviations
- SES
Socioeconomic status
- SEC
Socioeconomic class
- WHOQOL-BREF
World Health organisation Quality of Life- Brief Version
- VL
Visceral leishmaniasis
- L-AMB
Liposomal amphotericin B
- NACO
National AIDS Control Organization
Author contributions
RP, SD, KP, and GV participated in the design and conceptualization of the study. RP was involved in data collection. GV and RP performed the statistical analysis. RP, SD, and MM are involved in manuscript writing and editing. All the authors were involved in finalizing the manuscript; they read and approved the final version.
Funding
Not applicable.
Availability of data and materials
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
This study received approval from the Institutional Ethics Committee of ICMR-Rajendra Memorial Research Institute of Medical Sciences (RMRIMS), Patna (RMRI/EC/48/2023). The questionnaire was administered only after the study's purpose had been clearly explained to the participants, and written informed consent was obtained in Hindi. Participants were assured of the anonymity and confidentiality of their data.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
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Contributor Information
Krishna Pandey, Email: drkrishnapandey@yahoo.com, Email: pandey.krishna@icmr.gov.in.
Sameer Dhingra, Email: sameerdhingra78@gmail.com, Email: sameer.dhingra@niperhajipur.ac.in.
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Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.