Introduction

Human Immunodeficiency Virus (HIV) infection is a chronic, incurable disease that can lead to acquired immunodeficiency syndrome (AIDS) if untreated with antiretroviral therapy1. HIV remains a key public health burden, and globally 38.4 million people were living with HIV, and 650,000 deaths were reported by the World Health Organization (WHO) in 2021. More than two-thirds of people live with HIV worldwide, with nearly 25.6 million people living in Africa2. The increase in life expectancy and reduction in deaths are attributed to the success of highly active antiretroviral therapy (HAART) among HIV patients (PLHIV); however, the emergence of several cardiometabolic perturbations overshadows the decline in morbidity and mortality in HIV patients3,4,5. "cardio-metabolic perturbations” include a collection of concurrent metabolic risk factors, for instance, dyslipidemia, abdominal obesity, arterial hypertension and impaired glucose metabolism6.

Numerous complex mechanisms are yet to be clarified in the pathophysiology of MetS. MetS results from environmental, lifestyle, genetic, and epigenetic factors7. Most activated pathways of MetS are triggered by visceral adiposity, which is caused by high-calorie intake8,9. Insulin resistance, chronic inflammation, and neurohormonal activation are the proposed mechanisms for the progression of MetS10.

Metabolic syndrome (MetS) has long been used as an indicator of metabolic illness11. Metabolic syndrome (MetS) has become a growing concern in HIV-infected individuals over the last two decades12. Metabolic disorders in patients with HIV are caused by insulin resistance, aging, lifestyle changes, ART, and the virus itself. Lipid imbalances can occur during the natural course of an HIV infection.

People with MetS have sign and symptoms such as high blood pressure, high triglyceride, central obesity, and dyslipidemia and insulin resistance. People with insulin resistance may have acanthosis nigericans, which is darkened skin area on the back of neck, armpits and under the breast13.

MetS prevalence among PLHIV estimates ranging from 11.2 to 45.4%14,15. In SSA, HIV has been a pandemic for several years and remains a primary concern at the expense of similar dangerous diseases. While attention has been focused on the HIV pandemic, the emergence and spread of other equally dangerous health problems have remained unabated in several SSA nations. MetS exacerbates disease burden through clinical and biochemical links in HIV-positive patients. Several studies have reported a link between anti-retroviruses5,16. Studies from SSA have shown that the prevalence of MetS can reach up to 21.5%17. This difference may be due to differences in sample size, demographic characteristics, and criteria for the measurement of MetS15.

Many studies conducted in sub-Saharan African (SSA) countries have reported a prevalence of metabolic syndrome (MetS) of 21.5%17 however, there is a need to update this estimate, as numerous studies have been published since 2019 that provide new estimates on the prevalence of MetS among people living with HIV (PLHIV) in SSA countries. It is important to note that previous work did not exclusively focus on PLHIV and used various study designs (RCT, cohort, case–control, and cross-sectional) to report the pooled prevalence of MetS, which is a methodological limitation of their work. Therefore, this systematic review and meta-analysis aimed to determine the pooled estimates of MetS among PLHIV in SSA, using primary studies in the region.

This study offers evidence on the prevalence of MetS that can be crucial for policy makers for decision-making in healthcare regarding MetS prevention and patient management among PLHIV. It might be used by program directors to develop effective interventions to integrate care plans for PLHIV in the region and focus on risk reduction among PLHIV before the onset of MetS. Furthermore, pooling the prevalence of MetS among PLHIV will allow for a reduction in existing disparities and aid in the development of preventive and management strategies for healthcare services. As a result, this systematic review and meta-analysis was conducted to estimate the pooled prevalence of MetS among PLHIV in sub-Saharan Africa.

Methods

Reporting and protocol registration

This systematic review and meta-analysis were based on the recommended methodology and followed the Preferred Reporting Items for Systematic Review and Meta-Analysis for Protocols (PRISMA-P) 202018 (Supplementary Table S1). The results were reported based on the PRISMA statement, and the article screening and selection process were demonstrated using a PRISMA-P flow diagram. The study was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (registration number: CRD: 42023445294).

Search strategy

We used different electronic biomedical databases and indexing services such as Google Scholar, Science Direct, Scopus, Web of Sciences, EMBASE, and PubMed/MEDLINE to search for relevant articles. Potentially applicable studies were manually searched for using a list of references from the retrieved studies. The search was limited to articles published in English. The search terms used for this systematic review and meta-analysis were 'prevalence,’ ‘Epidemiology,’ ‘magnitude,’ ‘burden,’ ‘metabolic syndrome,’ ‘metabolic disease,’ ‘metabolic disorder,’ ‘HIV/AIDS,’ ‘Africa’ and ‘Sub-Saharan Africa.’ Studies relevant to MetS prevalence were considered. The search strategy involved using keywords with “Medical Subjects Headings (MeSH)” and “All fields” by connecting “AND” and “OR” as necessary. The search was conducted between February 15th and March 12, 2023, by three authors (YSA, GAK, and MMK) who thoroughly examined various sources and databases following a rigorous methodology. The search strategy details are provided in a separate file (Supplementary Table S2).

Eligibility criteria (inclusion and exclusion criteria)

The following criteria were used to include studies: (1) study type, both observational and experimental; (2) study period, studies published from database inception until December 2022; (3) study area, studies conducted in sub-Saharan Africa; (4) population, people living with HIV aged 18 years; and (5) Published in the English Language. Case reports, case series, review articles, and letters to editors, articles reported other than NCEP-ATP III and IDF criteria were excluded.

Data extraction

Endnote citation manager for Windows Version X8 (Thomson Reuters, Philadelphia, PA, USA) was used to import the retrieved studies, and duplicates were removed. Four independent reviewers screened all the articles for the eligibility criteria. Reviewers began by screening the abstracts and titles, followed by full-text screening. Disagreements were resolved by inviting a fifth investigator to participate. Microsoft Excel with a standardized extraction format was used by two investigators for the data extraction. The Excel spreadsheet included the first author’s name, sample size, publication year, country, study design, impaired fasting glucose, elevated blood pressure, high triglyceride (TG), low level of high-density lipoprotein (low HDL), and prevalence of MetS according to the criteria of (National Cholesterol Education Program and Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in adults (Adults Treatment Panel III)) and IDF (International Diabetes Federation). According to the PICO statement: Population: People living with HIV in SSA; Intervention: Exploring MetS; Comparison: Studies reporting MetS among people living with HIV outside SSA; Outcome: Proportion of MetS.

Statistical analysis

STATA version 14.2 Statistical software (StataCorp, College Station, Texas, USA) was used for the analysis, and heterogeneity was checked across studies by computing the I2 statistical test. We assumed no, low, medium, and high heterogeneity across the studies if the I2 values were 0%, 25%, 50%, and 75%, respectively. A random effects model was used to analyze the pooled estimated prevalence with 95% confidence intervals (CI) using the “metaprop” command, since significant heterogeneity was detected between studies. Funnel plots for visual inspection and Egger’s and Begg’s rank tests were used to assess the evidence of publication bias. A forest plot was used to report the estimated pooled prevalence of MetS and its subcomponents.

Outcome measurement

This study aimed to gather and analyze data from various studies conducted across sub-Saharan Africa to determine the pooled prevalence of MetS among people living with HIV in SSA, according to the NCEP ATP III and IDF criteria. The researchers used a systematic approach to identify relevant studies and extract relevant data. They then employed statistical methods to combine data from different studies and estimate the overall prevalence of MetS among people living with HIV in SSA.

These criteria are considered a subset of the following medical conditions or disorders:

  1. 1.

    Hypertension: systolic blood pressure > 130 mmHg or Diastolic blood pressure > 85 mmHg or pharmacologic Hypertension treatment

  2. 2.

    Abdominal obesity: Waist circumference of > 102 cm for men and > 88 cm for women

  3. 3.

    Dyslipidemia: Triglyceride (TG) 150 mg/dl or pharmacologic treatment

  4. 4.

    Hyperglycaemia: Fasting glucose > 100 mg/dl or pharmacologic treatment Dyslipidemia (Low HDL)

  5. 5.

    High-density lipoprotein cholesterol (HDL): < 40 mg/dl for men and < 50 mg/dl for women or pharmacologic treatment

In the case of NCEP-ATP III, three of the aforementioned criteria are utilized as diagnostic variables Similarly, in the IDF criteria, abdominal obesity (defined as waist circumferences of 94 cm for men and 80 cm for women) in combination with two of the aforementioned criteria listed above are considered19,20.

Results

Search results

A total of 1112 articles were initially identified using different biomedical databases, and 969 duplicates were excluded. Of the remaining 143 studies, 114 were excluded after reviewing their abstracts and titles. The full texts of the remaining 29 studies were downloaded and assessed to fulfil the required criteria. We again excluded seven studies (N = 4, different outcomes of Interest and N = 3, inconsistent results). Using citation search, we found three articles that met all inclusion criteria. Finally, 25 studies that met the inclusion criteria were included in this review using the search strategy, and duplicates were excluded using the endnote citation manager. Figure 1 illustrates the process of literature review, screening, and eligibility assessment of the study articles, and Supplementary Table S3 illustrates the details of the exclusion criteria.

Figure 1
figure 1

PRISMA flow diagram of the selection process of studies on MetS prevalence among PLHIV in sub-Saharan Africa in 2023.

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Characteristics of included studies

Among the 25 included studies, eight were from Ethiopia21,22,23,24,25,26,27,28, six were from South Africa29,30,31,32,33,34, three were from Nigeria35,36,37, two were from Kenya38,39, two were from Zambia40,41, and one each was from Cameroon42, Uganda43, Botswana44, and Zimbabwe40. The included study sample sizes ranged from 7945 to 110841, with a total of 8602 people living with HIV/AIDS. Observational and experimental studies were conducted before July 2023, were conducted. The estimated pooled prevalence of MetS was assessed according to NCEP/ATP III and IDF criteria. Table 1 summarizes the baseline characteristics of the included studies. All the articles had a cross-sectional design and were facility-based. More than ten studies have been published since 2018. Nineteen studies defined MetS according to the NCEP/ATP III criteria, and 18 studies used the IDF criteria.

Table 1 Baseline characteristics of the included studies for the prevalence metabolic syndrome among people living with HIV in sub-Saharan Africa 2023.
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Overall pooled prevalence estimates of MetS using ATP III and IDF criteria

The estimated pooled prevalence of MetS among people living with HIV in SSA was 21.01% [(95% CI: 16.50, 25.51); I2 = 85.3%, P < 0.001] using NCEP/ATP III criteria (Fig. 2) and 23.42% [(95% CI: 19.16, 27.08); I2 = 80.8%, P < 0.001]) using IDF criteria (Fig. 3).

Figure 2
figure 2

Forest plot depicting the overall pooled prevalence estimate of MetS among PLHIV in sub-Saharan Africa using NCEP/ATP III criteria.

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Figure 3
figure 3

Forest plot depicting the overall pooled prevalence estimate of MetS among PLHIV in sub-Saharan Africa using the IDF criteria.

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Sub-components of metabolic syndrome

Twenty-two studies reported impaired fasting glucose and Low HDL levels22,24,26,28,29,30,31,32,34,35,36,37,38,39,40,41,42,43,44,46,47,48, 24 studies reported high triglyceride levels, and 20 studies reported hypertension/raised BP and increased waist circumference/abdominal obesity21,22,24,25,26,27,28,29,31,32,34,35,37,38,39,40,41,42,44,45,48 prevalence among PLHIV. The sub-components of MetS prevalence differed significantly among studies conducted in sub-Saharan Africa for PLHIV. The estimated prevalence of subcomponents was 21.17% [(95% CI: 15.74, 26.50), I2 = 88.3%, P < 0.001] for impaired fasting glucose, 30.55% [(95% CI: 21.72, 39.38), I2 = 91.0%, P < 0.001] for raised blood pressure, 24.55% [(95% CI: 18.04, 30.85), I2 = 92.0%, P < 0.001] for high triglyceride levels, 47.25% [(95% CI: 34.17, 60.33), I2 = 89.7%, P < 0.001] for low HDL, and 38.44% [(95% CI: 28.81, 48.88), I2 = 93.0%, P < 0.001] for abdominal obesity/increased waist circumference (Figs. 4, 5, 6, 7, 8).

Figure 4
figure 4

Forest plot depicting the overall pooled prevalence estimate of hyperglycemia among PLHIV in sub-Saharan Africa in 2023.

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Figure 5
figure 5

Forest plot depicting the overall pooled prevalence estimate of raised blood pressure among PLHIV in sub-Saharan Africa in 2023.

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Figure 6
figure 6

Forest plot depicting the overall pooled prevalence estimate of elevated triglyceride among PLHIV in sub-Saharan Africa in 2023.

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Figure 7
figure 7

Forest plot depicting the overall pooled prevalence estimate of LDL-C among PLHIV in sub-Saharan Africa 2023.

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Figure 8
figure 8

Forest plot depicting the overall pooled prevalence estimate of abdominal obesity among PLHIV in sub-Saharan Africa in 2023.

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Publication bias

Funnel plots and Egger and Begg rank statistical tests at a 5% significance level were used to evaluate the presence of publication bias. The funnel plot showed symmetry (Supplementary Fig. S4) for pooled estimates using the NCEP-ATP III, and the Egger and Begg rank tests were not statistically significant (P-value = 0.258 and P-value = 0.225, respectively). Additionally, the funnel plot was almost symmetric (Supplementary Fig. S5) for IDF pooled estimates, and the Egger and Begg rank tests did not provide statistical evidence for the presence of publication bias (P-value = 0.863 and P-value = 0.158, respectively).

Sensitivity analysis

By excluding each study individually, a leave-out-one sensitivity analysis was used to determine the effect of a single study on the pooled prevalence of MetS among people living with HIV in sub-Saharan Africa. According to our findings, no single study had a significant impact on the pooled prevalence of MetS among people living with HIV in sub-Saharan Africa using the NCEP-ATP III and IDF (Figs. 9 and 10).

Figure 9
figure 9

Sensitivity analysis for single study effect of estimated pooled prevalence based on NCEP/ATP III 2023.

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Figure 10
figure 10

Sensitivity analysis for single study effect of estimated pooled prevalence based on IDF 2023.

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Discussion

The review found that among people living with HIV in sub-Saharan Africa, the prevalence of metabolic syndrome (MetS) was 21.01% according to NCEP/ATPIII criteria and 23.42% based on IDF criteria. Common components of MetS in this population included low HDL levels, increased waist circumference, and elevated blood pressure. This review is consistent with a similar review that found a high estimated pooled prevalence of MetS according to IDF criteria17. The use of a similar case definition for MetS might be attributed to the similarity of the studies. Likewise, the pooled prevalence in this study based on the NCEP/ATP III was comparable with reports from a global systematic review (20.6%)49 and sub-Saharan Africa (19.9%)17. This suggests that the findings of this study are consistent with those of previous research on MetS in PLHIV. These findings highlight the need for routine screening and management of MetS in PLHIV in SSA to reduce the risk of cardiovascular disease and other related complications. Further research is needed to understand the underlying mechanisms and risk factors associated with MetS and to inform targeted interventions to prevent and manage MetS in this vulnerable population.

In the present review, Low HDL (47%) was a common subcomponent of MetS, which is comparable to reports from Brazil50 and Italy51. Low HDL-C reflects an atherogenic dyslipidemia phenotype. Atherogenic dyslipidemia is a central lipoprotein associated with the development of MetS52. Atherogenic dyslipidemia can inhibit insulin metabolism through apoptosis and dysfunction of pancreatic beta cells53,54,55. Although the relationship between HDL function and MetS is not well established, it is likely that the relationship between HDL and insulin resistance also affects the development of MetS. Low HDL is mainly a result of apoA-I dysfunction (low levels of HDL in the blood) and systematic low-grade inflammation56. The second highest individual component of MetS was increased blood pressure/hypertension (30%). This finding was supported by studies from a systematic review and meta-analysis57. Antiretroviral therapy for PLHIV is commonly associated with hypertension (30%). The other MetS sub-component observed to be prevalent in this study was increased waist circumference (38%). This finding is consistent with that of a previous review58. The justification for the high prevalence of low HDL raised blood pressure/hypertension and increased waist circumference as individual components of MetS among PLHIV in sub-Saharan Africa might be due to the use of HAART. HAART has been shown to increase lipid levels and may not return to normal levels, leading to a high prevalence of low HDL levels. Additionally, the use of HAART in PLHIV is commonly associated with hypertension, resulting in a high prevalence of elevated blood hypertension. Finally, increased waist circumference and adiposity are also prevalent among HIV/AIDS patients and contribute to the high prevalence of MetS in this population. Therefore, appropriate interventions are necessary to prevent and manage MetS in PLHIV, including routine screening, lifestyle modifications, and pharmacological interventions, when necessary. Moreover, other MetS sub-components, such as high triglycerides (24%) and impaired fasting glucose (21%), are major among PLHIV in sub-Saharan, which is consistent with a previous review58. To mitigate the risk of metabolic syndromes, the latest HIV guidelines emphasize the importance of lifestyle modifications, including weight loss, increased physical activity, avoidance of substance abuse, and the implementation of medical interventions such as lipid-lowering therapy and antihypertensive drugs59.

Our review has clinical practice and public health implications; the clinical practice implications are healthcare providers should regularly evaluate HIV patients for metabolic syndrome components, including abdominal obesity, hypertension, elevated blood sugar levels, and abnormal lipid profiles. Early identification enables timely interventions and management. Individualized treatment plans tailored to the patients' specific risk factors and comorbidities are essential. These plans may include lifestyle modifications, medication adjustments, and regular follow-up visits. Collaborative care from professionals across different specialties, such as infectious disease specialists, endocrinologists, dieticians, and mental health professionals, is crucial for the comprehensive management of metabolic syndrome in HIV patients. Public health campaigns should raise awareness about the increased risk of metabolic syndrome in people living with HIV and promote healthy lifestyle behaviors to prevent and manage metabolic disturbances. Improving access to healthcare services for HIV patients, including the screening, diagnosis, and treatment of metabolic syndrome, is essential. This may involve reducing barriers to care, increasing healthcare provider training, and expanding the healthcare infrastructure. Continued research on the prevalence, risk factors, and outcomes of MetS in HIV populations is necessary to inform public health policies and interventions. Surveillance systems can help track trends and monitor the impact of interventions over time are the public health implications.

Strength and limitation of the study

This review adhered to the PRISMA guidelines and conducted a thorough literature search across multiple databases to identify relevant studies. Although the meta-analytical methods applied in this study were robust, the findings must be interpreted with caution because of the limitations of the study. Heterogeneity was observed among the studies included in the meta-analysis. In addition, the study only included data from ten countries, which restricts the representativeness of the findings.

Conclusion

The prevalence of MetS among PLHIV in sub-Saharan Africa is relatively high. Our review revealed that one in five study participants had MetS. Low high-density lipoprotein (HDL) levels, increased waist circumference, and increased BP pressure were more common in this review. We recommend early screening and appropriate interventions, including lifestyle modifications and pharmacological treatment, may be essential to prevent and manage MetS in PLHIV. Routine follow-up clinical and biochemical monitoring is also recommended. Additionally, creating awareness among PLHIV about MetS prevention, diagnosis, and treatment to prevent further complications is crucial. Promoting regular physical exercise, developing legislation for health promotion, and fighting obesity must be developed as a policy to address the modifiable risk factors of MetS among PLHIV. Furthermore, implementing novel interventions, such as integrated care plans for PLHIV in the region that can help strengthen the overburdened health system that also deals with other communicable diseases, can be an essential action.