|Year : 2020 | Volume
| Issue : 2 | Page : 148-153
Quality of life and its determinants among people living with HIV attending an antiretroviral treatment center in Delhi, India
S Anuradha1, Ayush Mohan Makkar2, Pijush Kanti Nandi2, K Rajeshwari3
1 Director Professor of Medicine, Nodal Officer, ART Center, Maulana Azad Medical College and Associated Lok Nayak Hospital, New Delhi, India
2 Senior Resident, Department of Medicine, Maulana Azad Medical College and Associated Lok Nayak Hospital, New Delhi, India
3 Director Professor, Department of Pediatrics, Maulana Azad Medical College and Associated Lok Nayak Hospital, New Delhi, India
|Date of Submission||15-Aug-2019|
|Date of Decision||02-Nov-2019|
|Date of Acceptance||14-May-2020|
|Date of Web Publication||16-Jun-2020|
117 B L Taneja Building, Maulana Azad Medical College, Bahadur Shah Zafar Marg, New Delhi - 110 002
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: With universal access to antiretroviral treatment (ART), the management of people living with human immunodeficiency virus (PLHIV) encompasses holistic, comprehensive care. Despite being a vital goal of care, quality of life (QOL) assessment of PLHIV in India is neglected. Objectives: This study assessed the QOL and its determinants among PLHIV accessing services through ART centers. Methods: The cross-sectional study was conducted from November 2015 to February 2017 among 109 PLHIV attending an ART center in New Delhi. Sociodemographic and clinical profile characteristics were ascertained. QoL was evaluated using the medical outcomes study HIV health survey questionnaire; physical health summary (PHS), and mental health summary (MHS) scores were calculated. Depression was evaluated with the becks depression inventory and social support using the multidimensional scale of perceived social support. Chi-square test, Student's t-test, and analysis of variance were used as test of significance. Results: The overall QOL was: PHS-48.04 ± 8.27 and MHS 42.43 ± 8.79. PHS scores were significantly higher among PLHIV with older age (P = 0.04), higher formal education (P = 0.022), early HIV disease (P = 0.006), higher CD4 counts (current, peak and nadir: P =0.024, 0.008, and ≤0.001, respectively), receiving ART (P = 0.05), with better social support (P = 0.012) and without depression (P ≤ 0.001). Similarly, MHS scores were better in PLHIV with greater formal education (P = 0.009), early HIV disease (P = 0.046), without depression (P ≤ 0.001). Conclusion: Depression and social support mechanisms emerged as two key determinants of QOL. Older age, higher education, less advanced disease, and ART were predictive of better QOL.
Keywords: Antiretroviral treatment, determinants, India, people living with human immunodeficiency virus, quality of life
|How to cite this article:|
Anuradha S, Makkar AM, Nandi PK, Rajeshwari K. Quality of life and its determinants among people living with HIV attending an antiretroviral treatment center in Delhi, India. Indian J Public Health 2020;64:148-53
|How to cite this URL:|
Anuradha S, Makkar AM, Nandi PK, Rajeshwari K. Quality of life and its determinants among people living with HIV attending an antiretroviral treatment center in Delhi, India. Indian J Public Health [serial online] 2020 [cited 2020 Oct 1];64:148-53. Available from: http://www.ijph.in/text.asp?2020/64/2/148/286815
| Introduction|| |
The access to universal and early antiretroviral treatment (ART) for people living with human immunodeficiency virus (PLHIV) has dramatically transformed the disease outcome in terms of mortality, survival, and morbidity. With increased longevity of PLHIV, the ambit of care is evolving to address complex issues like quality of life (QOL) among them. The concept of QOL in relation to many noncommunicable diseases is not new. However, its evaluation among PLHIV is challenging and the interpretation of the results is intricate and complicated. QOL has not been assessed systematically among PLHIV in India, and its determinants have not been understood well. Although improving the QOL of all PLHIV is a defined goal of India's National Programme, strategies to enhance the QOL of PLHIV have not been adequately identified or implemented.
Studies on QOL of PLHIV from India are scarce due to many reasons. Asocio-demographically very diverse HIV population across India ensues due to the dynamics and patterns of the epidemic not being uniform across the country. The parameters for measuring QOL are also not clearly defined, and many tools with varying sensitivities exist, making the assessment of QOL difficult. Globally, clinical, socio-economic, psychological, and behavioral parameters have been variably and unpredictably observed to impact the health-related QOL in PLHIV. An understanding of the factors impacting the QOL of PLHIV will facilitate the development and incorporation of suitable policies in programs. The present study was conducted to assess the QOL among PLHIV and determine the factors associated with it.
| Materials and Methods|| |
This cross-sectional study was conducted from November 2015 to February 2017among adult PLHIV (≥18 years of age) attending the ART center at a tertiary care hospital in New Delhi, India, under the National AIDS Control Programme of the Government of India.
The study was approved by the Institutional Ethics Committee (IEC) vide approval number F. No. 11/IEC/MAMC/2015/317 dated November 27, 20115. Informed consent was obtained from all study participants.
All 109 patients enrolled were subjected to a detailed history, including sociodemographic evaluation and physical examination to assess the baseline clinical status and the WHO clinical staging. The presence of depression was evaluated using the becks depression inventory-2 (BDI-2). Social support was determined using the multidimensional scale of perceived social support, which is a research tool designed to measure perceptions of support from three sources: Family, Friends, and a Significant Other.
QOL assessment was made using the medical outcomes study HIV health survey (MOS-HIV) questionnaire developed by Wu et al. with prior permission from the developer. MOS-HIV consists of 35 items that include eleven dimensions of QOL, including the perception of general health, physical functional status, bodily pain suffered, perceived role functioning, social functioning, mental health, energy/vitality, cognitive functioning, health-related distress, overall QOL. In addition to these subscales, the physical health summary score (PHS) and mental health summary score (MHS) were calculated by standardizing the score of each domain and the domains were scored as summated rating scales from 0 (worst state of health possible) to 100 (best state of health possible). The PHS score and MHS score were derived from the ten dimensions using the algorithm provided in the manual.
Sociodemographic (age, sex, marital status, number of children, educational background, employment status, income level, sexual orientation, tobacco, alcohol, drug use, social support, and family); Clinical (WHO stage, presence of opportunistic infections, Hepatitis B and C co-infections, CD4 cell count); psychological (presence of depression, self-perception of the level of support received) and ART-related (receiving ART or ART-naive, ART adherence, type of regimen, ART adverse effects) variables were assessed for their association with QOL scores.
A descriptive profile analysis on the sample, the results of which are expressed as mean, standard deviation, frequencies, and percentages was carried out. The association between variables and QOL was studied using the Chi-square test and Student's t-test. An analysis of variance (ANOVA) was used to compare differences between groups when required. All statistical analyses were performed using Statistical Package for the social sciences software version 24.
| Results|| |
Among the 109 patients, 62 (56.9%) were men, 47 (43.1%) were women, mean age was 35 ± 7.5 years (range 18–57 years), 85.3% had WHO stage 1 disease and 80 (73.4%) received ART. The median CD4 count was 373.00 cells/mm3 and 31.2% patientshad CD4 counts >500 cells/mm3. 62.9% of the study participants self-reported >95% adherence to ART. Among the PLHIV, 25.7% were determined to have depressive symptoms using the BDI-2.
The QOL summary scores (PHS and MHS) of the subjects were determined. The mean PHS score of the study population was 48.042 ± 8.27, and the mean MHS score was 52.43 ± 8.79. A significant correlation was seen between the PHS and MHS scores (spearman's correlation = 0.704; P ≤ 0.001). The mean individual QOL domain scores of the study participants are summarized in [Table 1]. Among the domain scores, the general health perception, QOL and Health Transition scores were found to be poorer as compared to other scores.
|Table 1: Mean quality of life domain scores among people living with human immunodeficiency virus (n=109)|
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The sociodemographic, clinical, psycho-social and ART-related variables were assessed as possible determinants of QOL. The mean MHS and PHS scores were evaluated among PLHIV within the individual variable groups to look for differences and significance. The results are summarized in [Table 2] and [Table 3].
|Table 2: Mean physical health summary and mental health summary scores and individual sociodemographic characteristics (n=109)|
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|Table 3: Mean physical health summary and mental health summary scores and individual clinical profile characteristics (n=109)|
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PHS scores were significantly higher amongst PLHIV with older age (P = 0.040), more years of formal education (P = 0.022), earlier HIV stage (P = 0.006), higher CD4 counts (last P = 0.024, peak P = 0.008, nadir P ≤ 0.001), receiving ART (P = 0.05), with better self-reported social support (P = 0.012) and without depression. (P ≤ 0.001).
No statistical association was seen between PHS and gender, relationship status, sexual orientation, occupation, income, ART regimen or duration, ART adherence, tobacco, or alcohol use.
Similarly, MHS scores were better in PLHIV with more years of formal education (P = 0.009), earlier WHO HIV Stage (P = 0.046) and who were not depressed (P ≤ 0.001).
A significant association was seen between the presence of comorbidities and poorer QOL amongst the study participants (PHS P = 0.004; MHS P = 0.009).
| Discussion|| |
The overall QOL was reported to be satisfactory among the study participants. Although there are no suggested cutoff points for good/bad QOL scores, authors have categorized subjects into good and poor scores based on a standardized mean score of 50. In our study participants, the mean PHS and MHS scores were categorized as below average, and a significant correlation was seen between the PHS and MHS scores (spearman's correlation = 0.704; P ≤ 0.001). Another study using the MOS-HIV questionnaire for QOL assessment also found an association between MHS and PHS scores.
A statistically significant association was found between the age of subjects and PHS, with PLHIV >45 years of age having better PHS scores compared to the younger subjects. No statistical association was found between age and MHS scores. The association between age and QOL is inconsistent: In contrast to our study, most studies,,,,, reported a positive association between younger age and QOL. It has been reasoned that older patients have more life experiences and develop better coping mechanisms and stress management skills; and can adjust to their illness better than younger patients. No statistical association was found between gender and QOL though males had better scores across most of the domains.
Education enables people in making informed decisions, provides better employment opportunities, and improves social support. Education is the single factor that influences multiple facets of life and contributes immensely to QOL directly as well as indirectly. In the present study, higher education was found to be significantly associated with better QOL overall and higher scores in most of the domains. Existing literature also supports a positive correlation between education and both physical and mental health.,,, Although the right to education is a fundamental right under the Indian constitution, illiteracy is common in India and has serious individual and social impact. Meaningful employment is a very powerful factor in determining the QOL among PLHIV. Though our study found no statistically significant association between QOL and employment, most of the studies have reported a positive association between employment and QOL. Improving the skills of PLHIV to provide sustainable, gainful employment is a powerful social tool that will improve overall health outcomes among PLHIV.
The stage of HIV infection is an indicator of the severity of the disease, more severe the disease activity, worse off the QOL. This was confirmed in our study with patients in WHO Stage 1 disease, having better QOL scores as compared to those in stage 3 and stage 4. Overall, both the physical health and mental health QOL scores deteriorated from Stage 1 to Stage 3 and 4 with physical functioning, General Health Perception, and Role Functioning scores found to be statistically significantly impaired. This is in tandem with previous studies indicating that better functional status/better WHO staging equates to better QOL from across the globe.,,,, This is a very crucial observation. Maintaining PLHIV in early stage without allowing the disease to progress into more severe grades of infection is a critical clinical endpoint. Thus, this makes a very strong case for the early initiation of ART among PLHIV. Many studies have documented a significant association between the CD4 count and QOL, with most finding a positive association between QOL and CD4 count: Increasing CD4 count equating to better QOL.,,, CD4 count is an indicator of the person's immune status, and immune restitution is one of the chief goals of ART. In this study, the recent CD4 Count, Peak CD4 count, as well as Nadir CD4 count, were all associated with Physical health performance but not mental health. Lower CD4 counts are associated with more advanced disease and opportunistic infections and with poorer physical health scores. A significant association was seen between the presence of co-morbidities and poorer QOL among the study subjects (PHS P = 0.004; MHS P = 0.009). This again highlights the importance of early ART initiation. It is also important to ensure that those on ART attain an optimal CD4 response as an important treatment endpoint. As CD4 counts rise with ART initiation, attaining virological suppression is critical as well. These observations suggest that early HIV diagnosis, early ART initiation, and optimal VL suppression as the 90-90-90 targets of the UNAIDS will result in not only into better survival outcomes but additionally translate into better QOL of PLHIV.
The use of ART has been associated with better outcomes, with most of the studies confirming the same while Harding et al., and Figuero et al. found no association between ART use and QOL. In the present study also, the ART population had statistically significant better PHS scores compared to the ART-naive PLHIV, indicating better Physical Health. At the time the study was conducted, ART initiation was CD4 guided, though now “Treat all strategy” has been implemented under the National Programme. The subjects receiving ART had better scores across Role functioning and social functioning, indicating that ART allows them to lead more productive and meaningful lives. However, the ART-naïve population had better energy scores probably because of the initial side effects of ART. It is possible that ART associated side-effects, the burden of pills, stigma and discrimination associated with daily consumption of medications and simply treatment fatigue may contribute to some worsening of QOL. This is important to consider while deciding the choice of regimen, especially in public health settings and quality counseling services. Adherence to ART has been associated positively with QOL. In our study, though no significant association was found between adherence to ART regimen and QOL, domain scores were higher among those with better ART adherence.
The Social Support system of the PLHIV is one of the most influential parameters determining the QOL. A sound, healthy support system allows the patient to cope well and leading a fulfilling and gratifying life. Most studies have found an overwhelmingly positive correlation between social support and QOL. This was also seen in the studies from Belgium and India studies., This was confirmed in our study, as well. PLHIV with higher self-perceived support had better overall physical health (statistically significant) and better mental health scores. Scores in all domains were higher, indicating better performances with particular significance in physical functioning, social functioning, pain, energy, health distress, and cognitive functioning, indicating better coping strategies in those with better support. These findings stress the need for improving and enriching the social support network of the PLHIV. Involvement of spouse/partner and family into care, identifying a care giver/buddy and the contribution of peer support groups is vital. Extremely critical is the availability of and access to quality counseling services. The significance of quality counseling services cannot be over emphasized. These one to one interactions of counselors and peer support groups help PLHIV face the multifaceted challenges of the disease and have a great positive impact on their QOL.
Depression is multifactorial among PLHIV and can be very subtle in its presentation. Identifying depression early and initiating appropriate consultations and treatment is imperative. In this study, the presence of Depression in PLHIV was very significantly associated with poorer physical and mental health outcomes and overall QOL. All the domain scores of QOL were highly significantly impaired in subjects with depression. This has also been documented in other studies by Figuero et al., Hasanah et al., and Degroote et al. Assessment and management of mental health are one of the most neglected dimensions in the care of PLHIV. Unfortunately, in the busy ART centers in large public hospitals with heavy patient loads, there is often little time to assess for depression. Furthermore, the staff may not be trained enough to recognize early, subtle depression in these subjects. Access to trained counselors/psychologists/psychiatrists also hinders the management of mental health issues among PLHIV. National policies must evolve programs incorporating screening and management of mental health issues into the routine management of PLHIV to improve their QOL.
However, our study also had some limitations. The relatively small sample size, recruited from an outpatient setting at one ART center constrained the extrapolation of results to the wider HIV population. QOL among inpatients could not also be assessed. Clinical parameters like viral load could not be assessed in relation to QOL as the facility was not available at that time as part of the National Program.
This was a single time, cross-sectional study with no subsequent follow-up, and hence, the change on QOL parameters over time and with other interventions like changing of ART regimen could not be assessed.
| Conclusion|| |
With the easy availability of and access to ART, the management of HIV has evolved from merely attaining clinical outcomes and virological endpoints to a holistic approach to care and well-being. Even though the provision of inexpensive, less toxic, and highly effective ART is critical to saving lives, the overall care must include other dimensions such as expanding social support, providing sustainable employment/income, and improving mental health. Improvement of QOL of PLHIV is now a well-recognized goal, although strategies to attain it are still nascent. Many of these strategies are challenging and cannot be met by individual treatment centers alone. However, National Programs must explore and incorporate novel approaches for PLHIV to enhance their overall health and enrich their lives.
The authors would like to acknowledge the developers of the MOS- HIV questionnaire for its free use for this academic study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]