The burden of mental health problems among elderly persons living with HIV in countries across sub-Saharan Africa: systematic review and meta-analysis protocol

Abstract

Background

The burden of HIV (human immunodeficiency virus) infection among the elderly has seen an increasing trend over the years. With improved treatment outcomes for HIV, it is expected that persons with the infection will experience longer life expectancy. The elderly are a very vulnerable group and prone to numerous health complications including cognitive decline associated with ageing. HIV infection among this group presents increased complications to their health, particularly their mental health. It is, therefore, imperative to investigate the burden of mental health problems among these vulnerable elderly persons living with HIV.

Methods

All relevant databases, grey literature, and non-database sources will be searched. The databases to be searched include PubMed, LILACS, CINAHL, SCOPUS, and PsycINFO, from inception to March 31, 2025, with no language restrictions. We will also search African Index Medicus, HINARI, African Journals Online, and IMSEAR. Reference lists of articles will be reviewed, and experts will be contacted for additional studies missed by our searches. Study selection, data extraction, and risk-of-bias assessment will be conducted independently by at least two reviewers after a calibration exercise. Any discrepancies will be resolved through discussion. Binary outcomes, such as the prevalence and incidence of mental health problems, will be assessed using pooled proportions, odds ratio (OR), or risk ratio (RR), and continuous outcomes will be measured as mean differences (MD) with standard deviation; all estimates will be presented with their 95% confidence intervals (CIs). Heterogeneity will be assessed graphically by checking for overlapping CIs and statistically using the I² statistic. Subgroup analyses will be performed to address heterogeneity. Random-effects model meta-analysis will be conducted to obtain pooled estimates. The overall level of evidence will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework.

Discussion

This systematic review aims to investigate the burden of mental health problems among elderly people living with HIV (EPLHIV). This is crucial due to the unique challenges posed by both ageing and HIV. Mental health issues in this population, such as depression and anxiety, can lead to poor adherence to antiretroviral therapy (ART), negatively impacting health outcomes and increasing the risk of AIDS progression. Despite existing research, significant gaps remain, particularly regarding less commonly studied mental health conditions like schizophrenia and bipolar disorder in these vulnerable groups. In sub-Saharan Africa (SSA), the burden and determinants of these conditions among EPLHIV are largely unknown. Addressing these gaps through targeted research can inform the development of integrated care models that improve the quality of life and overall well-being of this vulnerable group, guiding public health policies and enhancing mental health services.

Systematic review registration

PROSPERO CRD42024574793.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13643-025-02830-2.

Background

The number of older persons living with HIV/AIDS has grown considerably over the years [1]. Globally, the proportion of persons over 50 years living with HIV (PLHIV50 +) increased substantially, doubling from 8% in 2000 to 16% in 2016, mainly as a result of the availability of antiretroviral therapy (ART) and improvement in the quality and coverage of treatment [2]. Over 38.4 million people were living with HIV in 2021, of which countries across sub-Saharan Africa (SSA) accounted for 25.4 million (66.1%), with the number of PLHIV50 + projected to increase by 45% by 2030 [3, 4]. Improvements in coverage and uptake of ART have led to reductions in HIV-related morbidities and deaths, resulting in higher life expectancy [5]. The gain in life expectancy, on the other hand, has resulted in increased incidence of age-related comorbidities such as coronary artery disease [6–8]; cardiovascular diseases [5, 6]; diabetes [4, 5, 7]; hypertension [5, 7]; lung, liver, and kidney disorders [4, 5]; Alzheimer’s disease [4] and dementia [8, 10]; and polypharmacy [8–10], particularly among PLHIV50 + [6–9].

Living with HIV does not only lead to physical ailments and disorders, but it can precipitate neurocognitive dysfunction earlier than persons without HIV [11–13]. In addition to the diminished self-esteem, stigma, loneliness, and reduced social support, elderly persons living with HIV (EPLHIV) have an increased risk of depression [14], anxiety [14], suicidal ideation [15], and other mental health problems [16–18]. There is evidence that cognitive function decline is higher among EPLHIV than their HIV-negative counterparts [6–9, 16–20]. In fact, it is suggested that various psychiatric disorders may contribute to the progression of HIV through interactions that further lead to immunosuppression [18]. For example, mitochondrial damage leads to post-traumatic stress disorders and chronic fatigue syndrome that in turn contribute to further cognitive and neurological disorders among EPLHIV [19]. Apart from the clinical medical ailments, the ageing HIV-positive population may also experience pronounced social problems including financial constraints due to increased healthcare costs [20], reduced workforce participation [21], and discrimination in employment [22], which further exacerbate their already compromised well-being [23].

Elderly people in general have marked reduction in hepatic and renal function, reduced body mass, and plasma volume which impact on the pharmacokinetics of drug administration [24]. There is a negative feedback mechanism where reduced hepatic function reduces the metabolism of drugs and/or toxins which in turn reduces renal function and excretion leading to drug overload and, sometimes, toxicity [25]. Therefore, polypharmacy, drug-drug interaction, and other pharmacotherapy-related health outcomes are a big challenge among EPLHIV who are comorbid with mental health problems and depend on many medications (polypharmacy). The pharmacokinetics and pharmacodynamics of antiretroviral agents are greatly dependent on the proper functioning of the liver and kidney, considering their narrow therapeutic window [25]. Where there is polypharmacy for the management of different conditions in the same person, there is an increased risk of drug toxicity, hepatotoxicity, and renal malfunction, as well as complications associated with the considerable drug-drug interaction between the antipsychotics and antiretrovirals [26, 27], which further exacerbate treatment compliance and outcomes [28].

Among the elderly, quality of life, especially physical functioning, is negatively impacted [29, 30]. Likewise, in HIV or mental health patients, several studies have found an association with poor quality of life [31–34]. Therefore, an intersection of these two conditions in an elderly person may severely exacerbate their poor quality of life [14, 35]. The challenges posed by multimorbidity on quality of health of the individual are enormous. For instance, HIV or mental health patients independently suffer from stigmatization, and this is pronounced when HIV is comorbid with mental health disorders [36]. Stigmatization leads to withdrawal from social interaction which in turn results in poor emotional and psychosocial ill-health [36]. Additionally, the increased risk associated with poor adherence to medication as a result of polypharmacy may lead to the deterioration of each of the comorbid conditions further posing psychological, physical, and cognitive challenges to these individuals [37]. Improving quality of life of HIV-infected patients has been shown to increase survival and better treatment outcomes, as factors that influence survival and quality of life of EPLHIV are intertwined [40–42].

Only one systematic review has been identified that investigated mental health among PLHIV50 + [17] but of a narrow focus (as it investigated only three common mental health problems — depression, anxiety, and stress), and the evidence was inconclusive. Undoubtedly, significant research gaps remain with regard to other important mental health conditions such as schizophrenia, suicidal ideation, bipolar disorder, and alcohol and substance abuse in this vulnerable group. Anecdotal evidence suggests 5% schizophrenia, 10% bipolar disorder, and up to 50% alcohol and substance abuse occur in PLHIV [41, 42]. Worryingly, in SSA, there is lack of robust evidence on the burden and determinants of these mental health conditions in EPLHIV. There is lack of psychological health research on EPLHIV, as with evidence on the long-term mental health issues of HIV infection in elderly people. Collating rigorous evidence through a systematic review and meta-analysis will be the first step towards understanding the magnitude of mental health needs of EPLHIV and the development of comprehensive and context-sensitive care models that address both physical and psychological health of EPLHIV.

This review seeks to collate existing studies and distill evidence at the highest level on mental health challenges faced by EPLHIV and provide a clearer picture of the magnitude (incidence, prevalence, and severity) of mental health problems in this vulnerable group. Additionally, the current systematic review and meta-analysis will help in identifying critical issues and knowledge gaps in polypharmacy such as possible treatment challenges, drug-drug interaction, medication adherence, and adverse effects experienced by EPLHIV. Among others, this study will assess quality of life of this vulnerable population and utilize the findings to inform the development of targeted interventions and optimization of care strategies that are sensitive to the complex interplay between ageing, HIV, and mental health. Undoubtedly, this will lead to a more holistic approach to healthcare that not only focuses on the physical aspects of HIV but also addresses the mental well-being of elderly HIV patients.

Methods

This protocol for a systematic review has been prepared following guidelines specified in the Cochrane Handbook [43] and the reporting format of earlier published works [44–51]. The protocol has been reported in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Protocols (PRISMA-P) guideline [52] (Additional file 1). The full systematic review will be reported using the PRISMA guidelines [53]. The study retrieval process will involve comprehensive database and non-database searches, and the flow of studies through the selection process will be reported using the PRISMA flow diagram [54] (Additional file 2).

Criteria for considering studies for inclusion in this review

Types of studies

Informed by earlier published works [44, 48, 50, 51], this systematic review will include observational studies (cohort, case–control, or cross-sectional studies) conducted in SSA that evaluated the burden of mental health problems among EPLHIV. This systematic review is not about intervention effectiveness; hence, randomized controlled trials (RCTs) will not be our focus. However, if an RCT reports baseline case numbers and uses a well-defined sample size that enables the computations of proportion, prevalence, or incidence of a mental health problem among EPLHIV, it will be considered for inclusion. Review articles themselves will not be eligible for inclusion; rather, we will go through them to identify any potentially relevant studies missed during our searches. If a global review includes subsets from SSA or subregional data, we will extract and include those studies specific to SSA. Studies that provide country or regional estimates without a well-defined sample, or representative subsample of the source population, will be excluded. Results from multicountry studies that are aggregated and not possible to be separated by country will be excluded. Case studies and case series (they are atypical and not representative of the source population), commentaries, and opinion pieces will not be considered for inclusion.

Participants

Older adults aged 50 years and above living with HIV in any country in SSA who have been diagnosed with any mental health disorder will be eligible for inclusion. We have used the Centre for Disease Control (CDC) and Blanco et al. (2012) classification of elderly persons living with HIV, as those aged 50 + years, and not the 65 + years for the general population [55–57]. The lower age threshold reflects certain physiological aspects of ageing in individuals living with HIV who age faster than the non-HIV population [55–57]. The HIV infection status of participants should be determined using an antigen/antibody test or nucleic acid test [58]. The mental health disorders should be diagnosed using a validated tool or criteria, such as the Research Diagnostic Criteria (RDC) [59], the 11^th edition of the International Classification of Diseases (ICD-11) [60], or the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) [61]. Any applied cut-offs or thresholds of the diagnostic tools should be reported. Mental health problems to be considered include but are not limited to depression, anxiety, bipolar disorders, substance misuse disorders, suicidal ideation, dysthymia, obsessive–compulsive disorder (OCD), post-traumatic stress disorder (PTSD), schizophrenia, suicidal ideation, paranoia, psychopathy, neurosis/neurotic disorders, self-harm, anorexia nervosa, and bulimia.

Intervention

This is not a review of interventions effectiveness; rather, it is a review assessing the impact of HIV (as an exposure) on the mental health of EPLHIV across countries in the sub-Saharan African context.

Comparator

This is not a comparative systematic review, but where data are available, we will conduct head-to-head or subgroup comparisons.

Outcomes

Primary outcomes

1. Burden of mental health problems and their determinants among EPLHIV

Secondary outcomes

1. Polypharmacy and drug interactions among EPLHIV on treatment

2. Adherence to medication or treatment

3. Quality of life assessed with any standard or validated measurement scale including the Quality of Life Scale (QoLS) by Flanagan 1978 [62]; the McGill Quality of Life Questionnaire, developed by Cohen et al. (1996) and expanded in 2019 [63]; the Health-Related Quality of Life Questionnaire, developed by the CDC in 2000 [64]; the World Health Organization Quality of Life Instrument [65]; and the Global Quality of Life Scale, developed in 1996 [66].

Search strategy

We will conduct searches in the following electronic databases: PubMed, PsycINFO, LILACS, and CINAHL, from inception to March 31, 2025. There will be no language restrictions, and we will use the terms/concepts listed in Table 1 for the searches. Additional searches will be conducted in African Index Medicus, HINARI, African Journals Online, IMSEAR, and relevant preprint repositories (MedRxiv, ResearchGate, and AfricArXiv). Grey literature sources, including dissertation databases (ProQuest, EBSCO Open Dissertations, and Database of African Thesis and Dissertations), conference proceedings, and NGO and government reports, will be searched for potentially eligible studies for inclusion. The reference lists of relevant articles will be examined, and experts in the field of mental health will be contacted by emails, WhatsApp, etc. for any potentially eligible study missed by our searches. The search strategy developed for PubMed (Table 2) will be adapted for use in the other databases including grey literature sources. The searches will be updated when necessary and before the final analyses to allow the inclusion of newly completed or published eligible studies.

Table 1.

Search terms/concepts

Concept 1	Concept 2	Concept 3
• Acquired immune deficiency syndrome • Acquired immunodeficiency syndrome • AIDS • Immunocompromised • Human immune virus • Human immunodeficiency virus • HIV • HIV/AIDS • HIV-1 • HIV-2	• Elderly over 50 • Adult persons over 50 • Adults 50 +  • Older adults 50 and above • Persons over 50 years • Aged • Above 50 years • Over 50 years • Older persons	• Mental health problems • Obsessive–compulsive disorder • Posttraumatic stress disorder • Schizophrenia • Substance abuse • Suicidal ideation • Psychopathy • Bulimia nervosa • Disruptive behaviour • Dissocial disorder • Cognitive disorder • Alzheimer disease • Personality disorder attention deficit	• Hyperplasia Disorder • Dysmorphic • Mania • Anxiety • Psychosis • Dysthymia • Paranoia • Depression • Self-harm • Neurosis • Bipolar • Stress • Phobia • Dementia • Autism • Amnesia • Sociopathy

Table 2.

Search strategy developed for PubMed

Search	Query	Results
#1	Search: ((((((((((((((((((((((((((‘mental health’(Title/Abstract)) OR (‘mental disorder’(Title/Abstract))) OR (‘mental illness’(Title/Abstract))) OR (‘mental problem’(Title/Abstract))) OR (‘chronic mental illness’ (Title/Abstract))) OR (‘psychiatric illness’(Title/Abstract))) OR (‘chronic psychiatric illness’(Title/Abstract))) OR (‘chronic insanity’(Title/Abstract))) OR (insanity(Title/Abstract))) OR (‘chronic mental disorder’(Title/Abstract))) OR (‘dementia praecox’(Title/Abstract))) OR (schizophrenia(Title/Abstract))) OR (psychoses(Title/Abstract))) OR psychosis(Title/Abstract))) OR (‘schizophrenic psychosis’(Title/Abstract))) OR (depression(Title/Abstract))) OR (‘mental sickness’(Title/Abstract))) OR (‘mental disease’(Title/Abstract))) OR (maladjustment(Title/Abstract))) OR (‘emotional disorder’(Title/Abstract))) OR (‘nervous disorder’(Title/Abstract))) OR (‘nervous breakdown’(Title/Abstract))) OR (neurosis(Title/Abstract))) OR (‘neurotic disorder’(Title/Abstract))) OR (psychopathy(Title/Abstract))) OR (mania(Title/Abstract)) OR (autism(Title/Abstract)) OR (phobia(Title/Abstract)) OR (neurosis(Title/Abstract))
#2	Search: (((((‘HIV(Title/Abstract)) OR (Human Immune Virus (Title/Abstract))) OR (AIDS(Title/Abstract))) OR (Acquire Immune Deficiency Syndrome (Title/Abstract))) OR (HIV/AIDS(Title/Abstract))) OR (Immunocompromised (Title/Abstract))) OR (Acquired Immunodeficiency Syndrome (Title/Abstract))) OR (Human immunodeficiency virus (Title/Abstract))) OR (HIV-1 (Title/Abstract))) OR (HIV-2 (Title/Abstract))
#3	Search: (#1) AND (#2)
#4	Search: ((((((Elderly persons over 50 (Title/Abstract)) OR (Elderly over 50))) OR (Adult persons over 50 (Title/Abstract))) OR (Adults 50 + (Title/Abstract))) OR (Older adults above 50 (Title/Abstract))) OR (Older adults (Title/Abstract))) OR (Older persons (Title/Abstract))) OR (Persons over 50 years (Title/Abstract))) OR (Above 50 years (Title/Abstract))) OR))) OR (Over 50 years (Title/Abstract))
#5	Search: (#3) AND (#4)

Managing the search results and study selection

The search results will be managed, collated and deduplicated using EndNote version 21 [67], and the deduplicated articles will be exported to Rayyan [68] for screening and selection. We will calibrate the study selection process where a set of randomly picked studies (10 studies) will be assessed by all the reviewers using a piloted study selection flow chart developed from the pre-specified eligibility criteria (Fig. 1). Where there is agreement between the reviewers, we will proceed to allocate the remaining studies to start with the actual study selection. However, if there are inconsistencies or disagreements between reviewers, the calibration process will be repeated until a high level of agreement is attained. Two reviewers will independently screen the titles and abstracts of retrieved studies using the piloted study selection flow chart. The full texts of potentially relevant studies will be obtained and independently reviewed for inclusion. The PRISMA flow diagram will be used to document the flow of studies through the study selection process, and the reasons for excluding potentially eligible full text studies will be provided. Any discrepancies will be resolved through discussion between the reviewers.

Fig. 1.

Study selection flow chart

Data extraction and management

A pretested Microsoft 365 Excel Version 2408 data extraction sheet adapted from Cochrane will be used to independently extract data. The data extraction process will be calibrated by an initial assessment of 2–3 randomly selected studies for extraction by all the data extractors using the pretested data extraction sheet. Where there is agreement between data extractors, we will proceed to allocate the remaining studies for extraction. Where there are disagreements, we will hold discussions to resolve them and repeat the calibration process until a high level of consistency is achieved between data extractors. Data to be extracted include study characteristics (such as the year study was conducted, year study was published, country study was conducted, study design, and sample size), sociodemographic characteristics of participants (including age, setting, socioeconomic status, level of education level, and occupation), HIV status (with what — and how — it was diagnosed), mental health conditions (including depression, anxiety, dysthymia/persistent depressive disorder, OCD, PTSD, intrusive thoughts, mania, schizophrenia, infanticide, substance use disorder, anorexia nervosa, bulimia, suicidal ideation, bipolar affective disorder, paranoia, psychopathy, neurotic disorders, and self-harm), and quality domains of the risk-of-bias tool (ROBINS-E). Data on the burden of disease (such as prevalence, incidence, and duration of the mental health problem) will also be extracted. Where necessary, primary study authors will be contacted for missing, insufficient, or unclear data. If the additional data or information cannot be obtained, we will not input the data; instead, the extent and reasons for missing data will be provided. Data will be coded and recoded as necessary before analysis. The extracted data will be independently verified, and any disagreements will be resolved through discussion.

Assessment of risk of bias in the included studies

The reviewers involved in the risk-of-bias assessment will be trained using a randomly selected set of studies. Where there is consistency between assessors, the actual risk-of-bias assessment process will commence. However, where there are disagreements, we will hold discussions to resolve them and repeat the training process until consistency is attained. At least two reviewers will independently assess quality of the included observational studies (cohort, case–control, cross-sectional studies) for risk of bias using Cochrane Risk Of Bias In Non-randomized Studies-of Exposure (ROBINS-E) (Version 20 June 2023) [69] (Additional file 3). This provides a structured approach to assessing the risk of bias in observational epidemiological studies which thoroughly examines the strength of evidence about the presence of, and/or nature of, a potential effect of an exposure on an outcome. ROBINS-E is based on a series of signaling questions across seven risk-of-bias domains: (1) confounding, (2) selection of study participants, (3) measurement of exposure, (4) postexposure intervention, (5) missing data, (6) measurement of outcome, and (7) selection of reported results. Responses to each of the signaling questions are ‘yes’, ‘probably yes’, ‘probably no’, ‘no’, and ‘no information’. The risk of bias will be judged as ‘low’ for a domain with little or no concern about bias, ‘some concerns’ where there are some concerns about bias in a specific domain but with no certainty of an important risk of bias, ‘high risk’ for domains with some important bias concerns, and ‘very high risk of bias’ for studies with suspected serious bias. The results from the risk-of-bias assessment will be presented in a table with supporting statements from the primary studies. Where necessary, we will employ the risk-of-bias tool developed by Hoy and colleagues [70] for prevalence studies (Additional file 4). This tool assesses the following: selection bias, non-response bias, measurement bias, and bias related to data analysis. Each domain will be judged as ‘low risk’, ‘high risk’, or ‘unclear’ risk of bias. Any disagreements in risk-of-bias assessment will be resolved through discussion between the reviewers.

Data analysis

Data will be analysed using Review Manager version 5.4 [71]. Binary outcomes will be assessed using odds ratio (OR) or risk ratio (RR), while continuous data will be analysed using mean difference (MD) with their standard deviation (for means that were measured using the same scale) or standardized mean differences (SMD) for means that utilized different scales. The DerSimonian and Laird meta-analysis will be used to combine the outcomes of similar studies. The pooled OR, RR, and MD will be presented with their 95% confidence intervals (CI) [72]. Random-effects model will be used in the meta-analysis. Non-comparative studies will be combined to generate an overall (pooled) effect estimate which will be presented with their CIs.

Heterogeneity assessment

Heterogeneity, which arises due to variations in study design, participant characteristics, or outcomes between or within studies, will be investigated both graphically and statistically. The I² statistic, which describes the percentage of variability due to heterogeneity rather than chance [43], will be estimated. The I² statistic will be classified by four levels: 0–40% as unimportant heterogeneity, 30–60% moderate, 50–90% substantial, and 75–100% considerable heterogeneity. An I² > 50% will indicate significant heterogeneity [43]. Cochran’s Q test and Tau-squared (τ²) will be presented, and p ≤ 0.05 will be used to represent statistically significant heterogeneity.

Subgroup analysis

Subgroup analysis will be performed to assess the impact of heterogeneity across key variables. The burden of mental health problems will be estimated separately for urban and rural areas and different age groups. Where there is sufficient number of studies, subgroup analysis will be conducted on type of mental health disorder, diagnostic criteria, study design, and region where the studies were conducted.

Sensitivity analysis

Sensitivity analysis will be conducted to test the robustness of the pooled estimates around the methodological and quality domains if the number of studies will allow. We will exclude outlier studies and studies with poor methodological quality (i.e. ‘high risk’ studies) from the primary meta-analysis and rerun the analysis to assess their influence on the pooled estimate of the meta-analysis.

Publication bias

Egger’s test [73] will be conducted to assess evidence of publication bias, and where bias is identified, the trim and fill approach [74] will be used to assess the impact of the bias on the estimated effect.

Grading the evidence

The overall certainty of evidence (quality of evidence or the confidence in the effect estimates) produced from the systematic review will be graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system [75] (http://www.gradeworkinggroup.org/). The GRADE system assesses the following domains: risk of bias (risk of systematic errors), imprecision (risk of random errors), inconsistency (unexplained heterogeneity of results), indirectness (differences in population, exposure, or outcome), and publication bias (systematic underestimation or overestimation of effect estimate due to selective publication of studies). Under each domain, the quality of evidence may be rated down by one or two levels where there are serious or very serious concerns [75, 76]. Additionally, the quality of evidence may be rated higher for observational studies, although this is rarely done [76, 77]. The overall certainty of the evidence will be classified as high, moderate, low, or very low. High-quality evidence implies that further research is very unlikely to change confidence in the estimate of effect, while very low-quality evidence indicates that the estimate of effect is very uncertain. The overall grading of evidence for each outcome will be presented in a summary of findings tables together with the study types, the number of studies and participants, and relative and absolute effects for each outcome [77].

Discussion

Investigating mental health problems among elderly persons infected with HIV is of paramount importance for several reasons. First, the intersection of ageing and HIV presents unique challenges that can significantly impact mental health [78, 79]. Second, mental health issues in EPLHIV can negatively affect their overall health outcomes, particularly mental well-being, and is likely to increase their risk of developing depression and anxiety, which in turn can lead to poor adherence to antiretroviral therapy (ART), crucial for managing HIV [80]. Non-adherence to ART can result in higher viral loads, increased risk of transmission, and faster progression to AIDS [80, 81]. Understanding the mental health needs of EPLHIV can inform the development of comprehensive and context-sensitive models of care that address both physical and psychological health. Integrated care models that provide holistic support and include mental health services component can improve the quality of life of this vulnerable population [82]. Addressing mental health in this demographic can also alleviate the broader healthcare burden by reducing the need for emergency services, interventions, and hospitalizations [83]. Finally, there is a significant gap in research concerning the mental health of EPLHIV as most studies have focused on other vulnerable populations such as pregnant and postnatal mothers or the physical health aspects of HIV. By investigating mental health in EPLHIV, researchers can uncover specific risk factors and their correlates, protective factors, and effective interventions that can be tailored to their needs.

Although a systematic review has been conducted to assess mental health issues and well-being among the elderly in SSA [14], this review only focused on the three common mental health issues, i.e. depression, anxiety, and stress. Other important mental health problems such as schizophrenia, bipolar, mania, and obsessive–compulsive disorder have largely been overlooked among the elderly. However, the burden of these conditions has been estimated to be high among the HIV infected population in general. For instance schizophrenia have been diagnosed in about 5% of PLHIV, bipolar disorder was 10%, and alcohol and substance abuse was about 9 to 50% [41, 42]. The lack of research reflects an important yet neglected public health concern.

Therefore, knowledge is needed on the burden, types and determinants of mental health conditions, polypharmacy and drug interactions, and compliance to treatment and how these could be integrated to provide evidence-based care for this population. This knowledge can be used to guide public health policies, improve mental health services, and ultimately enhance the overall well-being of elderly individuals living with HIV. Understanding and addressing their mental health issues are not only a matter of improving individuals’ lives but also a crucial step towards a more inclusive and effective healthcare system [84]. Considering multimorbidity of mental health and HIV infection in geriatrics who are considered a vulnerable group, there is an increased risk of polypharmacy. One challenge associated with polypharmacy is noncompliance. Among HIV patients, polypharmacy has been established to lead to ART nonadherence and worsening health outcomes [85]. Aggregating evidence under this review can assist in the classification of the types of drugs combination and the identification of potential interactions. Knowledge of potential interactions could help avert serious adverse events. This can subsequently improve treatment outcomes.

This review will contribute to two of the sustainable development goals (SDGs) — SDG 3 and SDG 10, and highlight the burden of multimorbidity and polypharmacy. The SDG 3 seeks to ensure healthy lives and well-being for all, including EPLHIV or patients with mental health disorders [86]. SDG 10 aims to reduce inequalities [87], of which EPLHIV with comorbid mental health problems (a very marginalized group) often experience significant health disparities including limited access to health, higher cost of treatment, and several challenges associated with multimorbidity. This systematic review will shed light on inequalities by identifying specific barriers and challenges this vulnerable population faces.

Abbreviations

AIDS

Acquired-immunodeficiency syndrome

ART

Antiretroviral therapy

CDC

Centre for Disease Control

CI

Confidence interval

DSM

Diagnostic and Statistical Manual

EPLHIV

Elderly persons living with HIV

GRADE

Grading of Recommendations Assessment, Development and Evaluation

HIV

Human immunodeficiency virus

ICD

International Classification of Diseases

MD

Mean difference

OCD

Obsessive-compulsive disorder

OR

Odds ratio

PLHIV

People living with HIV

PROSPERO

Prospective Register for Systematic Reviews

PTSD

Post-traumatic stress disorder

QoL

Quality of life

QoLS

Quality of Life Scale

RCTs

Randomized controlled trials

ROB

Risk of bias

RR

Risk ratio

SMD

Standardized mean difference

SDGs

Sustainable Development Goals

Authors’ contributions

This review was conceptualized by ADA, SMPK, KN, and MA. Draft of the manuscript, reviewing, and editing are by ADA, SMPK, KN, and MA. Project validation and administration were done by ADA. All authors read and approved the final document.

Authors’ information

This systematic review was prepared as part of capacity-building initiative of the Centre for Evidence Synthesis and Policy (CESP), University of Ghana, and the Africa Communities of Evidence Synthesis and Translation (ACEST), Accra, Ghana, which train health professionals and scientists in Evidence Synthesis and Research Translation across low- and middle-income countries (LMICs). Dr Sheba Mary Pognaa Kunfah, Kenneth Nartey, and Morrison Asiamah are PhD students at the School of Public Health, University of Ghana, who are specializing in evidence synthesis and translation; they are mentored by Prof. Anthony Danso-Appiah (Director, Centre for Evidence Synthesis and Policy, University of Ghana, Legon, Accra).

Funding

The authors received no specific funding for this work.

Data availability

Data sets have not been generated or analysed.

Declarations

Ethics approval and consent to participate

Ethical clearance and consent to participate are not required for a systematic review as it is based on freely available empirical data. However, if any of the studies has serious ethical issues, it will be excluded and the reason for exclusion provided.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.