Prevalence and predictors of cardiovascular disease risk among people living with human immunodeficiency virus in Nigeria

Abstract

Introduction

Advances in HIV/AIDS treatment have transformed HIV into a manageable chronic condition. However, cardiovascular disease (CVD) and other non-communicable diseases are increasingly emerging among people living with HIV (PLHIV), especially in developing countries. This study assessed the prevalence and determinants of CVD risk among PLHIV in Nigeria.

Methods

A cross-sectional study was conducted from February to May 2024 across ten Nigerian health facilities, involving 1,000 PLHIV on antiretroviral therapy (ART). Data on socio-demographic characteristics, lifestyle behaviors, family history of CVD, and HIV-related clinical factors were collected through structured questionnaires and medical records. Chi-square tests and logistic regression analyses were conducted using SPSS v24, with significance set at p < 0.05.

Results

Participants had a median age of 48 years (IQR: 41–56), and 60.7% were female. Hypertension (26.2%), overweight (27.9%), high-risk waist-hip ratio (39.6%), and obesity (19.6%) were common. Overall, 61.1% were at risk for CVD. Significant predictors of higher CVD risk included urban residence (aOR: 1.48; 95% CI: 1.13–1.94), smoking (aOR: 2.16; 95% CI: 1.26–3.68), family history of hypertension (aOR: 1.7; 95% CI: 1.2–2.4), being on ART for ≥ 10 years (aOR: 1.5; 95% CI: 1.1–2.01), and infrequent consumption of high-fat, sugar, and salt (HFSS) foods (aOR: 1.4; 95% CI: 1.1–1.9). Conversely, being retired or a student was associated with lower risk.

Conclusion

CVD risk is prevalent among PLHIV in Nigeria and is linked to demographic, clinical, and lifestyle factors. Targeted, integrated interventions, and client-centered care strategies are required to reduce CVD burden among PLHIV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12981-025-00786-w.

Introduction

Globally, Human Immunodeficiency Virus (HIV)/Acquired Immunodeficiency Syndrome (AIDS) remains a public health concern, with Sub-Saharan African (SSA) countries accounting for two-thirds of the global burden [1]. Nigeria has the fourth highest number of people living with HIV (PLHIV) globally, with a national prevalence of 1.4% and an estimated 1.9 million PLHIV in 2018 [2]. The strides made in the fight against HIV/AIDS have transmuted the HIV infection from a progressive, fatal disease to a chronic medical condition that does not stand in the way of normal life. However, global mortality rates remain higher in PLHIV in comparison to the general population [3]. This coincides with current trend of the disproportionate burden of non-HIV-related co-morbidities, particularly Non-Communicable Diseases (NCDs), within the PLHIV demographic [4].

CVDs are a group of disorders of the heart and blood vessels and include coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions [5]. According to World Health Organization (WHO), CVD is the leading cause of mortality and morbidity globally, claiming 17.3 million lives per year [5]. PLHIV have a 61% increased relative risk for CVD development compared with the general population, which has been linked to interplay of traditional cardiovascular risk, HIV-related risk, and antiretroviral therapy (ART)-associated risk factors [6]. Traditional risk factors like hypertension, dyslipidemia, diabetes mellitus, smoking, obesity, sedentary lifestyles, and unhealthy diets are prevalent in this population and contribute significantly to CVD risk.

Studies have reported that HIV-related factors, including chronic inflammation, immune dysregulation and elevated viral load further exacerbate cardiovascular risk by promoting endothelial dysfunction and atherosclerosis [7]. Antiretroviral therapy (ART), while essential for managing HIV, have been proven to influence CVD risk through metabolic side effects such as dyslipidemia, insulin resistance, and weight gain, particularly with some drug classes like the older protease inhibitors and some integrase inhibitors [7].

With improved survival among the PLHIV population; it is estimated that by the year 2030, 73% of PLHIV will be ≥ 50 years of age, and 78% of these individuals will be diagnosed with CVD [8]. Addressing these multifaceted risk factors through tailored interventions, including lifestyle modifications, optimal ART selection, and proactive management of comorbidities, is critical for reducing the burden of CVD in this vulnerable population.

The burden and impact of CVD risk factors among PLHIV in low middle income countries (LMIC) with robust antiretroviral therapy (ART) programs are still not well elucidated, however, a recent cohort study in four African countries including Nigeria found a prevalence of 27.9% and 8.4% respectively for Hypertension and Diabetes Mellitus amongst PLHIVs aged 50 years and above [9].

In Nigeria, the estimated prevalence of hypertension among adults aged 18 years and above in the general population is 32.5% while the national prevalence of Diabetes Mellitus is 5.8% [10]. Amongst the estimated population with hypertension, only 30% are aware of their HIV status, with only less than 20% on treatment and 12% with controlled hypertension [10]. Previous studies have also reported prevalence of hypertension of 20.9% and 26% among PLHIV as well as high prevalence of other CVD risk factors, such as obesity and dyslipidemia among PLHIV [11, 12].

Prevention, early detection, and prompt treatment of Non-communicable Diseases (NCD) can reduce progression to CVD which would ultimately improve the quality of life among PLHIVin care [13]. The WHO recommended integrating NCD interventions into primary health care packages with referral systems to all levels of care as a cost-effective way to improve NCD prevention and control services [13]. Despite the adoption of the recommendation by the Nigerian government, following the launch of the National Multi-sectorial Action Plan for the prevention and control of NCDs, access to essential NCD interventions at ART facilities remains sub-optimal. Integrated care for HIV-NCD comorbidity is still at the conceptual stage in the country [14]. This puts the burden of NCD treatment on the PLHIV to bear, mostly through out-of-pocket expenditure, which may prevent many patients from seeking care. An implication of this is preventable and premature morbidity and mortality of the otherwise virally suppressed older aged PLHIV in care.

As HIV programmes worldwide near epidemic control, it is crucial that they are sustained and consolidated. This requires prioritizing PLHIV integrated comprehensive care. This study aims to determine the prevalence and predictorsof CVD risks among PLHIV, with the hope that our findings translate to developing sustainable strategies of ensuring a long productive life for the PLHIV in Nigeria.

Methodology

Study design and setting

We conducted a multi-centre cross-sectional study of adult PLHIV receiving treatment at selected comprehensive ART sitesin North-Central and South-West regions in Nigeria.This multiregional study spanned five Nigerian states (Benue, Plateau, Ogun, Oyo, and Ondo) across two geopolitical zones. These regions were strategically selected due to their diverse healthcare systems, varying HIV prevalence rates (1.2% in southwest and 2.1% in north-central) [2]and growing burden of CVD risk factors, such as hypertension and diabetes.

The southwestern states (Ogun, Oyo, and Ondo) are relatively more urbanized and industrialized, with healthcare resource and infrastructurebetter positioned to deliver integrated HIV care and NCD management. In contrast, north-central states (Benue and Plateau) present a complex healthcare landscape, with rural and urban populations. Benue, with one of Nigeria’s highest HIV prevalence rates (4.8%) [2], faces significant healthcare access challenges due to terrain and under-resourced infrastructure.

Sampling technique and study participants recruitment

The study population consisted of PLHIV aged 18 years and above who received care at the selected ART sites. The sample size was determined using Cochran’s sample size formula for a single proportion, incorporating a normal standard deviation of 1.96 for a 95% confidence interval, a margin of error of 0.05, and the prevalence of NCDs among PLHIV from a previous study in Nigeria [7, 15]. The overall estimated sample size was 735. A multistage sampling technique was employed to select study participants in five states. First, facilities implementing the HIV/NCD integration program were purposively selected. Out of the seven sites per state that were part of the program, two facilities with the highest client attendance were selected based on high client attendance, resulting in a total of ten facilities across five states. These selected facilities account for 70–80% of active PLHIV on ART in project states. Thereafter, the sample sizes were equally allocated to each facility. A systematic sampling technique was then used to select kth study participants from serially listed clients in the facility: where k is determined by dividing the total PLHIV by the required sample size. K.

Data collection

Between February 2024 and May 2024, data was collected by trained research assistants through questionnaire. Data collected for the estimation of CVD risk included: socio-demographic characteristics (gender, age, level of education, employment status, and ethnicity), lifestyle (alcohol intake, smoking status, etc.), and anthropometric measurements (height, weight, hip circumference, and waist circumference). CVD risk (among > 40years) was assessed using the WHO non-laboratory risk assessment tool. Data on age, gender, smoking status, blood pressure, and presence of diabetes were collected from participants. All participants received random blood glucose screening and those who were found to be “prediabetic” were requested to return for a fasting blood glucose test. Fasting blood samples were collected from each participant after a 12 h overnight fast for the fasting blood glucose test.

Outcomes definition

The primary outcome ‘’CVD risk’’ was defined as the presence of any abnormal Body Mass Index (BMI), Waist to Hip Ratio (WHR), Elevated Blood pressure (BP), Fasting Blood Glucose (FBG) and Random Blood Glucose(RBG)values in the study participants. The aforementioned variables are documented risk factors for CVD [6, 16]. Hypertension was defined as an average systolic blood pressure (SBP) ≥ 140 mm Hg and/or an average diastolic blood pressure (DBP) ≥ 90 mm Hg of the two readings [13]. Diabetes was defined as having a fasting blood sugar ≥ 126 mg/dl. Body Mass Index (BMI) of less than 18.5 kg/m² was defined underweight, 18.5 to 24.9 kg/m² was defined normal body weight, 25 to 29.9 kg/m² was defined overweight, and ≥ 30 kg/m² was defined obesity [17]. Waist to Hip Ratio (WHR) measurements are categorized to assess health risks. For men, a WHR of ≤ 0.90 indicates low risk, 0.91–0.99 indicates moderate risk, and ≥ 1.00 indicates high risk. For women, a WHR of ≤ 0.80 indicates low risk, 0.81–0.85 indicates moderate risk, and ≥ 0.86 indicates high risk. Waist to Height Ratio (WHtR) measurements were defined by health risk: a WHtR of ≤ 0.49 indicates low risk, 0.50–0.59 indicates moderate risk, and ≥ 0.60 indicates high risk.

The independent variables include sociodemographic (e.g. age, sex), clinical (e.g. viral load, CD4, family history of hypertension), and lifestyle variables (e.g. cigarette smoking, alcohol ingestion).The CD4 and Viral load results were obtained from the patients’ electronic medical record conducted at initiation and within year of the study respectively.

Data analysis

Analyses were conducted using the Statistical Package for the Social Sciences (SPSS) version 24, IBM, Armonk, New York, USA). The study participants characteristics was described using medians and interquartile ranges for numerical variables while frequency and proportions for categorical variables. The dependent variable is CVD risk (dichotomized into those at risk of CVD and not at risk of CVD). Study participants with at least one or more abnormal BMI, WHR, BP, RBG, and FBG were categorized into the CVD risk group. The prevalence of CVD risk factors was calculated using frequency and percentages. We used chi square to test relationship between categorical variables. We employed a univariate and multivariate logistic regression to assess factors associated with CVD risk. Significant factors with p ≤ 0.05 in bivariate analyses were included in the multivariable model. Through backwards elimination, we simplified the saturated multivariable model (including all significant variables in the univariate analysis) until only the variables significantly associated with CVD risk remained. The alpha level of statistical significance was set at < 0.05.

Ethics statement

The study was approved by the Institutional Research Board of APIN Public Health Initiatives (NHREC/APIN/2/12/2022 C). Written informed consent was obtained from all participants in the study. All information gathered was kept confidential, with anonymized data while ensuring participant privacy. Participation was voluntary, with the option to withdraw at any time. All Participants identified with CVD risks received comprehensive counseling and emotional support, and they were linked or referred for appropriate management.

Results

Between February and May 2024, 1,000 adult PLHIV met the study inclusion criteria and were screened for CVD risk factors. The characteristics of the study participants are shown in Table 1. The median age of study participants was 48.0 years (IQR: 41.0–56.0) andmajority (60.7%, n = 607) were female. Predominantly, 45.1% (451) had attained secondary education while 29.0% (n = 29) had tertiary education.

Table 1.

Characteristics of adult plhivscreened for CVD risk in HIV clinics in northcentral and Southwestern Nigeria, 2024

	Total (n)	Cardiovascular risk		p-value
		Yes	No
		n (%)	n (%)
Age				0.11
20–39	196	83 (42.3)	113 (57.7)
40–49	374	187 (50)	187 (50)
50–59	265	121 (45.7)	144 (54.3)
60–69	133	52 (39.1)	81 (60.9)
=/>70	32	11 (34.4)	21 (65.6)
Sex				0.64
Female	607	272 (44.8)	335 (55.2)
Male	393	182 (46.3)	211 (53.7)
Education				0.53
None	82	34 (7.5)	48 (8.8)
Primary	177	77 (17)	100 (18.3)
Secondary	451	216 (47.6)	235 (43)
Tertiary	290	127 (28)	163 (29.9)
Occupation				0.01
Unemployed	169	79 (46.7)	90 (53.3)
Retired	120	39 (32.5)	81 (67.5)
Employed	687	331 (48.2)	356 (51.8)
Student	24	5 (20.8)	19 (79.2)
Residence				0.01
Rural	409	160 (39.1)	249 (60.9)
Urban	591	294 (49.7)	297 (50.3)
Duration on ART (years)				0.04
1–5	283	112 (39.6)	171 (60.4)
6–10	319	145 (45.5)	174 (54.5)
Older than 10	398	197 (49.5)	201 (50.5)
ART regimen				0.25
DTG-based therapy	956	432 (45.2)	524 (54.8)
Efavirenz-based therapy	17	11 (64.7)	6 (35.3)
Nevirapine-based therapy	27	11 (40.7)	16 (59.3)
Family history of hypertension				< 0.01
No	823	351 (42.6)	472 (57.4)
Yes	177	103 (58.2)	74 (41.8)
Family history of DM				0.03
No	919	408 (44.4)	511 (55.6)
Yes	81	46 (56.8	35 (43.2
VL suppression				0.2
<=1000	974	439 (45.1)	535 (54.9)
> 1000	26	15 (57.7)	11 (42.3)

ART antiretroviral therapy, DM diabetes mellitus, VL viral load, DTG Dolutegravir

Prevalence of CVD risk factors

Table 2 shows the prevalence of CVD risk factors among PLHIV.About60.1% (n = 601) of the study participants had at least one or more CVD risk factors. CVD risk factors are indicated by abnormal BMI, WHR, FBG and RBG, and an elevated BP. Using the BMI to assess the risk of CVD, 27.9% (n = 279) of participants were overweight and 19.6% (n = 196) fell into obesity categories. In terms of Waist Hip Ratio, 39.6% (n = 396) were at high risk. The Waist Height Ratio showed that 10.4% (n = 104) of patients were at high risk. Random blood glucose levels indicated 90.7% (n = 907) were normoglycemic, while among those who were dysglycaemic, 89.2% (n = 83) had diabetes.

Table 2.

Prevalence of cardiovascular disease risk factors among adult PLHIV enrolled in HIV care in northcentral and Southwestern nigeria, 2024

Variables	Frequency - n (%)
Body mass index
Underweight	73 (7.3)
Normal weight	452 (45.2)
Overweight	279 (27.9)
Obesity class 1	128 (12.8)
Obesity class 2	38 (3.8)
Obesity class 3	30 (3)
Waist hip ratio
Low risk	344 (34.4)
Moderate risk	260 (26)
High risk	396 (39.6)
Waist height ratio
Low risk	744 (74.4)
Moderate risk	152 (15.2)
High risk	104 (10.4)
Blood pressure
Normal	278 (27.8)
Prehypertension	460 (46)
Hypertension	262 (26.2)
Random blood glucose
Normoglycemia	907 (90.7)
Dysglycemia	93 (9.3)
Fasting blood glucose (n = 93)
Normal	2 (2.2)
Prediabetes	8 (8.6)
Diabetes	83 (89.2)

An estimated 22.7% (n = 103) and 10.1% (n = 46) of PLHIV at risk of CVD had a family history of hypertension and diabetes respectively (Table 1). A higher proportion (57.7%, n = 11) of study participants at risk of CVD were not virally suppressed (Viral load ≥ 1000 copies/ml) compared to patients who were not at risk (42.3%). Majority (54.8%, n = 524) of the patients on Dolutegravir-based regimen were not at CVD risk compared to those on Efavirenz-based regimen, with about 65% (n = 11) of them at risk.

Lifestyle characteristics of study participants

Participants lived sedentary lifestyles with limited engagement in vigorous (17.9%) and moderate (16.1%) occupational activities. Supplementary Table 1 shows the lifestyle characteristics of PLHIV screened for CVD risk. Their dietary habits included infrequent HFSS (foods high in fat, sugar, and salt) food consumption (less than once a week − 51.7%), fruits (3–6 times a week − 41.0%), and vegetables (1–2 servings daily − 58.4%). Cigarette smoking was rare (6.5%) and 14.7% of study participants currently consumed alcohol (supplementary table Table 1).

Factors associated with CVD risk among PLHIV

In the, univariate analysis (Table 3), having retired (OR = 0.55; 95% CI: 0.34–0.89), being a student (OR = 0.30; 95% CI: 0.11–0.84), urban residence (OR = 1.54; 95% CI: 1.19–1.99), family history of hypertension (OR = 1.87; 95% CI: 1.35–2.60), and family history of DM (OR = 0.61; 95% CI: 0.38–0.96), zero consumption of vegetable(OR = 2.16; 95% CI: 1.26–3.72), cigarette smoking (OR = 1.76; 95% CI: 1.05–2.92), and alcohol consumption (OR = 1.49; 95% CI: 1.05–2.12) were significantly associated with CVD risk.

Table 3.

Factors associated with cardiovascular disease risk among adult PLHIV receiving HIV care in HIV clinics in northcentral and Southwestern nigeria, 2024

	cOR	95% C.I.	aOR	95% C.I.
Age
20–39	Ref
40–49	1.36	0.96–1.93
50–59	1.14	0.79–1.66
60–69	0.87	0.56–1.37
=/>70	0.71	0.33–1.56
Sex
Female	Ref
Male	1.06	0.82–1.37
Occupation
Unemployed	Ref
Retired	0.55*	0.34–0.89	0.56*	0.34–0.93
Employed	1.06	0.76–1.48	1.04	0.73–1.48
Student	0.3*	0.11–0.84	0.29*	0.1–0.85
Residence
Rural	Ref
Urban	1.54**	1.19–1.99	1.48**	1.13–1.94
Duration on ART (years)		–
1–5	Ref
6–10	1.27	0.92–1.76	1.25	0.89–1.76
> 10	1.5**	1.1–2.04	1.46*	1.06–2.01
Family history of hypertension
No	Ref
Yes	1.87**	1.35–2.6	1.7**	1.2–2.4
Family history of DM
No	Ref
Yes	0.61*	0.38–0.96
Vegetable
1–2 serves daily	Ref
3–4 serves daily	1.09	0.82–1.44	1.01	0.75–1.36
5 or more serves daily	1.23	0.73–2.07	1.17	0.68–2.01
Usually none	2.16**	1.26–3.72	2.11**	1.21–3.69
Cigarette smoking
No	Ref
Yes	1.76*	1.05–2.92	2.16**	1.26–3.68
HFSS		–
1–2 times a week	Ref
3–6 times a week	1.54	0.98–2.42	1.51	0.95–2.41
Every day	2.26	0.9–5.65	2.38	0.93–6.06
Less than once a week	1.38*	1.05–1.8	1.43**	1.08–1.89

Ref Reference category, ART antiretroviral therapy, DM diabetes mellitus, VL viral load, HFSS food which are high in fat, sugar or salt, cOR crude odd ratio, aOR adjusted odd ratio

*p < 0.05, ** p < 0.01

In the adjusted model (Table 3), living in urban residence (aOR 1.48; 95%CI: 1.13–1.94) vs. rural; smoking cigarette (aOR 2.16; 95%CI: 1.26–3.68) vs. non-cigarette smoking; family history of hypertension (aOR 1.7; 95%CI: 1.2–2.4) vs. no family history of hypertension; and 10 years or more on ART (aOR 1.5; 95%CI: 1.1–2.01) vs. less than 5 years of ART, eating HFSS less than once a week (aOR 1.4; 95%CI: 1.1–1.9) vs. 1–2 times a week, were factors significantly associated with increased CVD risk. Having retired (adjusted odds ratio (aOR) 0.56; 95%CI: 0.34–0.93), and being a student (aOR 0.29; 95%CI: 0.10–0.85) vs. unemployed were associated with lower CVD risk among study participants.

Discussion

This study described the occurrence and factors associated with CVD risks in adult PLHIV receiving ART. Our findings show that about two-thirds (60.1%) of adult PLHIV are at risk of developing CVD. An estimated 26% and 8.3% of PLHIV were hypertensive and diabetic respectively. About 28% and 19% of PLHIV were overweight and obese respectively. Predictors of CVD risk include occupation, living in urban areas, cigarette smoking, long duration on ART, and family history of hypertension.

Our study’s finding of 60.1% CVD risk prevalence matches previous studies on CVD risk factors that show PLHIV on ART are at higher risk [18–20].  A systematic review and meta-analysis by Islam et al. that assessed the relative risk of CVD among PLHIV revealed that HIV infection conferred a 61% increased risk of cardiovascular disease endpoints [6]. This similarity may be attributed to the homogeneous social determinants of health characteristic of the Sub Saharan African region. Furthermore, the ongoing epidemiological transition in sub-Saharan Africa supports this hypothesis.

This study presents composite CVD risk data for PLHIV in Nigeria for the first time. Previous local studies have focused on individual disease entities. Our study found a significantly higher prevalence of pre-hypertension 46.1% among participants, compared to the 30.9% reported in the general population according to a meta-analysis by Adeloye et al. [16]. This difference highlights the urgent need for an even earlier intervention in the PLHIV population, as untreated pre-hypertension raises the risk of hypertension, cardiovascular complications, and target organ damage by at least 30% [16]. Similar to a study that reported a hypertension prevalence rate of 26% among PLHIV in Jos, Nigeria [11]. We also found the prevalence of hypertension among PLHIV to be high at 26%. This high prevalence also corroborates the previously reported hypertension prevalence rate of 20.9% among PLHIV in Ogun State, Nigeria by Aridegbe et al. [12]

Our study findings are supported by studies that have shown that individuals with family history of hypertension and diabetes mellitus are at higher risk of developing CVD [21] thus emphasizing the impact of epigenetics in the emergence of CVD. This study, therefore, necessitates the integration of CVD awareness and related lifestyle modification counselling with HIV service delivery, particularly prioritizing PLHIV with a positive family history of hypertension and diabetes mellitus.

The observed diabetes prevalence of 8% in our study contrasts with the higher rate (20.5%) reported in a single-center Abuja study [22]. Variations in study design and population characteristics may contribute to this difference. A review of existing literature yields mixed findings in the PLHIV and non-PLHIV population, underscoring the complex interplay between modifiable risk factors and HIV status in NCD development [23, 24].

The relative contribution of traditional risk factors, viral factors, and treatment-related factors to the development of CVD risk among people living with HIV (PLHIV) remains poorly understood [25]. This study seeks to gain new insight into this complex relationship. One of the key findings from our study reveal a significant association between the duration of antiretroviral therapy (ART) and the risk of developing CVD. Specifically, participants who had been on ART for 10 years or longer were found to be more likely to manifest CVD risk factors compared to those with shorter durations of treatment. This observation aligns with existing literature, which suggests that PLHIV on long-term ART face a greater risk of developing cardiovascular risk factors [18, 26]. Studies have suggested that ART-related changes in certain risk factors, such as higher BMI, older age and higher lipid as well as other ART-related metabolic changes can mediate ART’s effects on blood pressure, leading to hypertension in PLHIV on longer duration of ART [26, 27].

Our study also highlights the role of environmental and lifestyle factors in shaping CVD risk among PLHIV. We found that PLHIV residing in urban areas were more likely to develop CVD compared to their counterparts in rural settings. This disparity may be attributed to the distinct lifestyle patterns associated with urban living, such as increased sedentary behavior, poorer dietary habits, and higher levels of stress. Urban environments often lack access to fresh, nutritious foods and may promote physical inactivity due to limited recreational spaces or reliance on motorized transportation. These factors, combined with the physiological impacts of long-term HIV infection and ART, may exacerbate the risk of cardiovascular diseases in urban-dwelling PLHIV [28].

Our study revealed that 6.5% of clients were current cigarette smokers, consistent with global trends among PLHIV [29]. Meta-analysis findings indicate smoking prevalence among PLHIV increases with national income, ranging from 10.1% in low-income to 45.2% in high-income countries [29]. This report found West and Central Africa to have the lowest prevalence (4.4%). Aggressive anti-tobacco campaigns in many African countries likely contribute to this trend. Notably, our study identified a significant association between cigarette smoking and cardiovascular disease (CVD).

Therefore, interventions targeting health facilities and PLHIV should include counselling on healthy living and lifestyle modification. Integrating NCD programmes into HIV care will increase access to early detection of CVD and management through effective screening for risk factors in PLHIV at primary healthcare centres or ART clinics. However, for effective integration, there is need for policy guidance and capacity building of Human Resource for Health to provide NCD care.

Study limitations and strengths

The strength of this study is the study design and real-time data collection from study participants, which reduced the possibility of missing data. Our study was more representative due to the purposive selection of high-volume ART centres and random sampling of participants. However, allocating the same sample sizes to all states may have resulted in over or underestimation of study effects. Also, excluding pregnant women and Advanced HIV disease (AHD) clients may have resulted in selection bias. Measurement bias may result from inadequate standardization of lifestyle variables like sugar intake, HFSS, vegetables, etc. Future studies should standardize lifestyle variable collection and assessment using a reliable and valid tool.

Conclusion

This study found that PLHIV in Nigeria are at increased risk of developing CVD. Occupation, living in urban areas, cigarette smoking, long duration on ART, and family history of hypertension predict CVD risk in PLHIV. Therefore, we recommend patient-centered care, integrated and comprehensive care approaches to address CVD-related risk factors at the individual, family, and health systems level.

While the Nigeria National Policy on HIV & AIDS (2020) focuses on reducing new infections and ensuring sustainable care, it does not explicitly address strategies for preventing cardiovascular disease (CVD) among people living with HIV (PLHIV).

Key strategies should include early ART initiation to reduce CVD risk, routine CVD risk screening integrated into HIV care, and targeted education for healthcare providers and PLHIV to enhance risk management and self-care. Integrating HIV and NCD services into a single framework will streamline care and improve adherence. Strengthening healthcare systems by addressing health insurance coverage, workforce and infrastructural gaps is also critical for sustaining this proposed model.

These models can help Nigeria address the growing CVD burden among PLHIV and provide a scalable framework for other countries facing similar challenges, ensuring a more comprehensive approach to HIV care that prioritizes long-term quality of life.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

AI conceptualized the study. OI, AI, OO, and TO carried out the data analysis, interpreted the findings, and contributed to the writing and revision of the manuscript. PJ, IO, JS, and PO provided supervision for the study and reviewed the manuscript. All authors have read and approved the final version for publication.

Funding

The authors did not receive any funding for this study.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Competing interests

The authors declare no competing interests.