Long-term Antiretroviral Therapy and Prevalent Hypertension among Adults Living with HIV in Yaounde, Cameroon: A Cross-Sectional Study

Long-term Antiretroviral Therapy and Prevalent Hypertension among Adults Living with HIV in Yaounde, Cameroon: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Long-term Antiretroviral Therapy and Prevalent Hypertension among Adults Living with HIV in Yaounde, Cameroon: A Cross-Sectional Study Francis Duhamel NANG NANG, Liliane KUATE MFEUKEU, Paul Junior CHEUBO, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9349092/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Hypertension is an increasingly common comorbidity among adults living with HIV in sub-Saharan Africa, yet data from routine HIV clinics in Cameroon remain limited. We examined factors associated with prevalent hypertension among adults receiving antiretroviral therapy (ART) at Yaoundé Central Hospital. In this cross-sectional study of 460 participants, hypertension (blood pressure ≥ 140/90 mmHg and/or current antihypertensive treatment) was present in 43.3%. Using robust Poisson regression, older age and obesity were independently associated with higher hypertension prevalence, and family history showed the strongest association (adjusted prevalence ratio 2.83). Cumulative ART duration was not independently associated after adjustment. Weekly fruit and vegetable intake was associated with lower hypertension prevalence, whereas salt/seasoning cube intake and most behavioural factors were not associated after adjustment. Restricted cubic spline analyses did not suggest non-linearity in the relationship between ART duration and hypertension. In this urban HIV care setting, hypertension clustered primarily with conventional cardiometabolic factors rather than time on ART. Integrating systematic blood pressure screening and standardised hypertension management within HIV services, alongside weight management and lifestyle counselling, may help reduce cardiovascular burden among people living with HIV. Antiretroviral Therapy Highly Active Hypertension HIV Infections Cross-Sectional Studies Cameroon Figures Figure 1 I. Introduction With the scale-up of antiretroviral therapy (ART), HIV infection has increasingly become a chronic condition, and morbidity among people living with HIV (PLHIV) is progressively shifting toward non-communicable diseases, foremost among them arterial hypertension. Globally, hypertension is a major driver of cardiovascular morbidity and mortality; among PLHIV, it contributes to a “double burden” in which cardiometabolic comorbidities are becoming a priority for health systems. This epidemiologic transition supports the routine integration of hypertension screening and management within HIV services, particularly in resource-limited settings[1]. In sub-Saharan Africa, where a substantial share of the global HIV burden is concentrated, recent syntheses suggest that a sizeable proportion of PLHIV live with hypertension, highlighting the magnitude of the problem and its implications for continuity of care and cardiovascular prevention[2–5]. However, major contextual differences (access to care, cardiometabolic profiles, urban vs rural environments, and availability of antihypertensive medicines) strongly shape hypertension detection, treatment, and control within HIV clinics. In Cameroon, data from HIV care platforms (including the Central Africa IeDEA network) and reports from the Yaounde Central Hospital indicate that hypertension affects a substantial proportion of PLHIV in follow-up, with gaps across the care cascade (screening, treatment initiation, adherence, and blood pressure control)[5, 6]. Additional studies conducted in Cameroonian settings also report a high burden of hypertension among PLHIV and underscore the need for integrated HIV–hypertension approaches tailored to local realities[7–9]. Several plausible pathways may link HIV infection, ART exposure, and hypertension, without allowing causal inference from cross-sectional designs alone. On one hand, ART reduces immune activation and may improve certain vascular markers; on the other, residual inflammation, endothelial dysfunction, and metabolic changes (weight gain, dyslipidaemia, insulin resistance) reported with some therapeutic classes may be associated with higher blood pressure levels[10]. In this context, cumulative duration of ART exposure is a key variable to consider when studying associations with hypertension among PLHIV. In addition, urban environments may shape cardiometabolic risk. In Yaounde, exposure to lifestyle-related factors (salt-rich diets, physical inactivity, psychosocial stress, and pollution) may influence the distribution of hypertension among PLHIV, beyond virologic status[11]. Since the adoption of “Treat All” and the widespread use of integrase inhibitor, based regimens, particularly dolutegravir, several observational analyses in Africa have reported weight gain and, in some contexts, higher hypertension prevalence, whereas other studies do not show a uniform short-term rise in blood pressure[12–14]. These mixed findings suggest that hypertension among PLHIV reflects a complex set of determinants (age, adiposity, health behaviours, and care context) in which ART exposure and its cumulative duration may play variable roles. Despite this background, recent analytical data remain limited in Cameroon, particularly in urban HIV clinics, regarding factors associated with prevalent hypertension among PLHIV and the independent contribution of cumulative ART duration after accounting for major co-determinants (age, adiposity, behavioural and clinical factors). Addressing this gap is important to guide cardiovascular prevention and to standardize hypertension care within HIV services, in line with integrated care approaches[15]. This cross-sectional study aimed to identify factors associated with hypertension among adults living with HIV in Yaoundé, Cameroon, with cumulative duration of antiretroviral therapy as the primary explanatory variable. We hypothesised that prolonged ART exposure would be associated with a higher prevalence of hypertension after accounting for age, adiposity, and behavioural factors. II. Materials and Methods 1. Study design and setting We conducted a cross-sectional study at the Day Hospital of Yaoundé Central Hospital, Cameroon, between January and March 2024. The facility is an urban HIV care center serving approximately 12,000 people living with HIV. All measurements (blood pressure, anthropometry, ART history, and laboratory data) were obtained or abstracted at a single point in time for each participant. The study followed the STROBE guidelines for cross-sectional studies. 2. Participants and eligibility Inclusion criteria were adults ≥21 years living with HIV, followed at the clinic for ≥6 months, with available data on blood pressure and ART history at the index visit. Non-inclusion criteria (pre-enrolment) were pregnancy, hypertensive emergency at presentation, chronic renal dialysis, age <21 years, or follow-up <6 months. Exclusion criteria (post-eligibility) applied to participants meeting inclusion criteria but removed from the final analysis due to non-imputable missing data on essential variables or major unresolved inconsistencies identified during data quality checks. 3. Sampling Method Participants were recruited through consecutive convenience sampling. All adults living with HIV who attended routine follow-up visits at the Day Hospital of Yaoundé Central Hospital between January and March 2024 and met the eligibility criteria were invited to participate until the required sample size was reached. This approach was chosen for operational feasibility within the study period but may limit the representativeness of the broader clinic population. 4. Outcome Definition and Variable Classification The dependent variable was hypertension status at the time of data collection. Hypertension was defined by meeting at least one of the following: (i) mean of the last two of three seated blood pressure measurements ≥140/90 mmHg at the index visit; (ii) current use of antihypertensive medication; or (iii) prior clinician-documented diagnosis of hypertension in the medical record. Participants with no prior hypertension diagnosis, not receiving antihypertensive therapy, and with mean seated BP <140/90 mmHg were classified as non-hypertensive. The index date was the calendar date of the qualifying blood pressure assessment. Exposure variables and time-updated covariates (when applicable) were computed up to the index date. 5. Exposure and covariates The primary exposure was cumulative duration of antiretroviral therapy (ART) (years), analyzed primarily as a continuous variable. ART regimen category/therapeutic line (e.g., first-line vs second line) was defined from routine clinic records. Exposure to major antiretroviral drug classes and treatment lines was examined in preliminary analyses; however, no consistent independent associations with hypertension were observed, and these variables were therefore not retained in the final multivariable models. Priori covariates were selected for epidemiological relevance and to minimize overfitting. These included: age, sex, education level, smoking status (never/former/current), alcohol use (AUDIT-C cut-offs), physical activity (IPAQ-short categories), adiposity indicators (BMI and/or waist circumference using standard sex-specific thresholds), diabetes status, dyslipidaemia, chronic kidney disease (eGFR <60 mL/min/1.73 m² using the 2021 CKD-EPI equation), HIV-related markers (e.g., viral suppression status, CD4 count as available), and concomitant medications known to influence blood pressure when reliably documented. 6. Data Sources and Measurement Procedures Clinical data abstraction. Sociodemographic, clinical, HIV treatment history, and pharmacy information were abstracted from routine clinical records (electronic medical records and pharmacy databases) using a standardized case report form. Blood pressure. Blood pressure was measured using a validated automated Oscillo metric device. Three seated readings were taken 1–2 minutes apart after a rest period; the mean of the last two readings was used for classification. Anthropometry. Weight and height were measured using standard procedures to compute BMI. Waist circumference was measured using standardized techniques to assess central obesity. Laboratory variables. Fasting glucose, lipid profile, creatinine, CD4 count, and HIV viral load were obtained from routine laboratory records performed within 90 days of the index date. eGFR was estimated to use the 2021 CKD-EPI (race-free) equation. 7. Sample size and precision considerations Sample size was first determined to estimate the prevalence of hypertension among adults living with HIV with adequate precision. Assuming a 95% confidence level, expected prevalence of 50% (conservative), and absolute precision of 5%, the minimum required sample size was 384 participants using the single-proportion formula. To support multivariable modelling with ART duration as the main exposure and adjustment for key confounders, recruitment aimed at least 400 participants. The final analytic sample is reported in the Results. 8. Statistical analysis Analyses were conducted using IBM SPSS Statistics (version 29) (and R when needed for specific modelling/graphics). Participant characteristics were summarised using median (IQR) for continuous variables and n (%) for categorical variables. Hypertension prevalence was estimated with 95% confidence intervals. Associations between explanatory variables and hypertension were assessed using Poisson regression with robust variance to estimate prevalence ratios (PRs), reporting adjusted PRs with 95% confidence intervals. ART duration was modelled primarily as a continuous exposure. Linearity assumptions were assessed; when indicated, restricted cubic splines were used and displayed using predicted marginal effects. Restricted cubic spline analyses were conducted using multivariable logistic regression models with four knots placed at recommended percentiles of the ART duration distribution. Logistic models were used for spline analysis because robust poisson models are not directly supported within the rms framework we used in R. Multicollinearity and influential observations were checked using standard diagnostics. All tests were two-sided, with p<0.05 considered statistically significant. Missing data were described and handled using complete-case analysis for variables included in the final model. Ethics and confidentiality This study was approved by the Ethics Committee of the Regional Ethics Committee for Human Health Research in the Central Region (CRERSHC) N 0 :CEN000633/CRERSHC/2023 on August 8, 2023. All participants provided written informed consent prior to enrolment in the study. Administrative authorization was granted by the Director of the Central Hospital of Yaounde (N02023/265/AR/MINSANTE/SG/DHCY/UAF) on May 8, 2023, prior to the commencement of data collection. III. Results Characteristics of Study Participants Among 460 adults living with HIV receiving ART, 199 had prevalent hypertension (43.3%). The mean age was 50.5 ± 10.9 years and 73.5% were women. Participants with hypertension were older (53.1 ± 10.1 vs 48.5 ± 11.0 years) and had a longer ART duration (12.1 ± 5.5 vs 10.1 ± 6.1 years). Family history of hypertension and obesity were more frequent among participants with hypertension (Table 1). Overall, participants were predominantly middle-aged adults with long-term exposure to ART, reflecting a relatively stable cohort in routine HIV care. Table 1. Sociodemographic, clinical, and treatment characteristics of the study population, overall and stratified by hypertension status. Variable Category Overall Hypertensive Non-hypertensive Age (years) Mean ± SD 50.5 ± 10.9 53.1 ± 10.1 48.5 ± 11.0 Sex Female 338 (73.5%) 142 (71.4%) 196 (75.1%) Male 122 (26.5%) 57 (28.6%) 65 (24.9%) Marital status Married 180 (39.1%) 86 (43.2%) 94 (36.0%) Single 122 (26.5%) 46 (23.1%) 76 (29.1%) Cohabiting 58 (12.6%) 20 (10.1%) 38 (14.6%) Divorced 13 (2.8%) 4 (2.0%) 9 (3.4%) Widowed 87 (18.9%) 43 (21.6%) 44 (16.9%) Education level Secondary 255 (55.4%) 102 (51.3%) 153 (58.6%) None 23 (5.0%) 14 (7.0%) 9 (3.4%) Primary 133 (28.9%) 64 (32.2%) 69 (26.4%) Higher 49 (10.7%) 19 (9.5%) 30 (11.5%) Employment status Employed 97 (21.1%) 32 (16.1%) 65 (24.9%) Self-employed 137 (29.8%) 55 (27.6%) 82 (31.4%) Unemployed 154 (33.5%) 75 (37.7%) 79 (30.3%) Retired 72 (15.7%) 37 (18.6%) 35 (13.4%) Family history of hypertension No 289 (62.8%) 72 (36.2%) 217 (83.1%) Yes 171 (37.2%) 127 (63.8%) 44 (16.9%) HIV stage at initiation Stage I 235 (51.1%) 93 (46.7%) 142 (54.4%) Stage II 159 (34.6%) 81 (40.7%) 78 (29.9%) Stage III/IV 66 (14.3%) 25 (12.6%) 41 (15.7%) BMI category Normal weight 188 (40.9%) 68 (34.2%) 120 (46.0%) Obesity 106 (23.0%) 55 (27.6%) 51 (19.5%) Overweight 166 (36.1%) 76 (38.2%) 90 (34.5%) ART treatment line First-line 376 (81.7%) 157 (78.9%) 219 (83.9%) Second/third-line 84 (18.3%) 42 (21.1%) 42 (16.1%) Viral load category Undetectable 357 (77.6%) 150 (75.4%) 207 (79.3%) High 50 (10.9%) 20 (10.1%) 30 (11.5%) Suppressed 53 (11.5%) 29 (14.6%) 24 (9.2%) ART duration (years) Mean ± SD 10.9 ± 5.9 12.1 ± 5.5 10.1 ± 6.1 Salt/seasoning cube intake No 186 (40.4%) 91 (45.7%) 95 (36.4%) Yes 274 (59.6%) 108 (54.3%) 166 (63.6%) Fruit & vegetable intake Bi-weekly 79 (17.2%) 45 (22.6%) 34 (13.0%) Weekly 242 (52.6%) 101 (50.8%) 141 (54.0%) Rarely 90 (19.6%) 35 (17.6%) 55 (21.1%) Three times per week 49 (10.7%) 18 (9.0%) 31 (11.9%) Bivariable associations In bivariable robust Poisson models, older age was associated with prevalent hypertension (PR per 1-year increase 1.02, 95% CI 1.01-1.03; p<0.001). Longer ART duration was also associated with hypertension (PR per 1-year increase 1.03, 95% CI 1.01-1.05; p<0.001). Hypertension was more prevalent among participants reporting a family history of hypertension (PR 2.98, 95% CI 2.40-3.71; p<0.001) and among those with obesity (PR 1.43, 95% CI 1.10-1.87; p=0.007) (Table 2). Table 2. Bivariable analysis of factors associated with prevalent hypertension among adults receiving antiretroviral therapy. Variable Category PR 95% CI p-value Age (years) Per 1-year increase 1.02 1.01-1.03 <0.001 Sex Female (ref) 1.00 Ref Male 1.11 0.89-1.40 0.359 Marital status Married (ref) 1.00 Ref Single 0.79 0.60-1.04 0.091 Cohabiting 0.72 0.49-1.06 0.098 Divorced 0.64 0.28-1.48 0.298 Widowed 1.03 0.80-1.34 0.800 Education level Secondary (ref) 1.00 Ref None 1.52 1.06-2.18 0.022 Primary 1.20 0.95-1.52 0.118 Higher 0.97 0.66-1.42 0.873 Employment status Employed (ref) 1.00 Ref Self-employed 1.22 0.86-1.73 0.271 Unemployed 1.48 1.06-2.05 0.019 Retired 1.56 1.08-2.24 0.016 Family history of hypertension No (ref) 1.00 Ref Yes 2.98 2.40-3.71 <0.001 HIV stage at initiation I (ref) 1.00 Ref II 1.29 1.03-1.60 0.024 III/IV 0.96 0.68-1.35 0.805 BMI category Normal weight (ref) 1.00 Ref Obesity 1.43 1.10-1.87 0.007 Overweight 1.27 0.98-1.63 0.067 ART treatment line First-line (ref) 1.00 Ref Second/third line 1.20 0.94-1.53 0.149 Viral load category Undetectable (ref) 1.00 Ref High 0.95 0.66-1.37 0.789 Suppressed 1.30 0.99-1.71 0.058 ART duration (years) Per 1-year increase 1.03 1.01-1.05 <0.001 Salt/seasoning cube intake No (ref) 1.00 Ref Yes 0.81 0.65-0.99 0.041 Fruit & vegetable intake Twice weekly (ref) 1.00 Ref Once weekly 0.73 0.57-0.93 0.012 Rarely 0.68 0.49-0.94 0.020 Three times weekly 0.64 0.43-0.98 0.038 Physical activity Adequate (WHO-compliant) (ref) 1.00 Ref High/optimal 1.00 0.61-1.64 0.997 Low 1.14 0.73-1.78 0.559 Monthly frequency (once/month) 1.46 0.86-2.49 0.160 Inactive 1.11 0.74-1.67 0.607 Tobacco use No (ref) 1.00 Ref Yes 0.80 0.57-1.13 0.208 Alcohol use Weekly/daily (ref) 1.00 Ref Monthly 1.03 0.72-1.49 0.856 None 1.01 0.76-1.34 0.935 Occasional 1.00 0.76-1.32 0.984 Multivariable model and independent correlates In the multivariable robust Poisson model (Table 3), age remained independently associated with prevalent hypertension (aPR per 1-year increase 1.02, 95% CI 1.01-1.03; p=0.002). Family history of hypertension showed the strongest independent association (aPR 2.83, 95% CI 2.25-3.57; p<0.001). Obesity was independently associated with hypertension (aPR 1.29, 95% CI 1.01-1.65; p=0.045), whereas overweight showed borderline evidence (aPR 1.23, 95% CI 0.99-1.53; p=0.066). After multivariate adjustment, the crude association between ART duration and hypertension was fully attenuated(aPR per 1-year increase 1.00, 95% CI 0.99-1.02; p=0.619) suggesting substancial confounding by age. Family history showed the strongest independent association, with nearly a threefold higher prevalence of hypertension. Weekly fruit and vegetable intake was associated with lower hypertension prevalence (aPR 0.67, 95% CI 0.53-0.85; p=0.001), while salt/seasoning cube intake was not associated after adjustment. Table 3. Adjusted prevalence ratios for independent factors associated with prevalent hypertension in multivariable Poisson regression. Variable Category aPR 95% CI p-value Age (years) Per 1-year increase 1.02 1.01-1.03 0.002 ART duration (years) Per 1-year increase 1.00 0.99-1.02 0.619 Marital status Married (ref) 1.00 Ref – Single 1.04 0.79-1.37 0.776 Cohabiting 0.98 0.70-1.38 0.929 Divorced 1.08 0.50-2.34 0.842 Widowed 1.00 0.79-1.27 0.980 Education level Secondary (ref) 1.00 Ref – None 1.15 0.84-1.57 0.378 Primary 1.06 0.85-1.33 0.594 Higher 1.01 0.70-1.46 0.962 Employment status Employed (ref) 1.00 Ref – Self-employed 1.18 0.82-1.70 0.367 Unemployed 1.07 0.76-1.50 0.707 Retired 0.88 0.58-1.34 0.554 Family history of hypertension No (ref) 1.00 Ref – Yes 2.83 2.25-3.57 <0.001 BMI category Normal weight (ref) 1.00 Ref – Obesity 1.29 1.01-1.65 0.045 Overweight 1.23 0.99-1.53 0.066 Salt/seasoning cube intake No (ref) 1.00 Ref – Yes 0.98 0.81-1.20 0.863 Fruit & vegetable intake Bi-weekly (ref) 1.00 Ref – Weekly 0.67 0.53-0.85 0.001 Rarely 0.76 0.56-1.04 0.083 Three times per week 0.68 0.44-1.04 0.077 Assessment of non-linearity for ART duration Restricted cubic spline analyses did not provide evidence of a sighificant non-linear association between ART duration and prevalent hypertension; both overall and non- linear components were non-significant andthe adjusted curve remained approximately flat across the observed ART duration range, with confidence intervals crossing the null (Figure 1). IV. Discussion Overview of main findings In this cross-sectional analysis of 460 adults living with HIV receiving ART at the Central Hospital of Yaounde, hypertension was common (43.3%). In adjusted analyses, prevalent hypertension clustered with older age, obesity, and a family history of hypertension, while cumulative ART duration was not independently associated when modelled continuously. Restricted cubic spline modelling similarly provided no evidence of a meaningful non-linear association between ART duration and hypertension (Figure 1). These findings support the integration of standardized hypertension prevention and control within routine HIV services.[16–20] Comparison with previous studies The strong associations observed for age and adiposity are consistent with reports from sub-Saharan Africa and other settings, where hypertension prevalence increases with ageing and cardiometabolic risk factors among treated people living with HIV.[2,21–24] The lack of an independent association between ART duration and hypertension after adjustment, despite a positive crude association, suggests confounding by age and adiposity, because longer ART exposure is inherently correlated with ageing and cumulative weight trajectories. This pattern aligns with mixed evidence in the literature, where associations between ART exposure and hypertension often attenuate after accounting for age and body mass index, and may vary by regimen composition and switching histories.[2,9,23,25,26] Our results therefore argue against using "time on ART" alone as a clinical proxy for hypertension risk in this setting. Biological and pathophysiological interpretation The age gradient likely reflects cumulative vascular ageing and endothelial dysfunction, processes that may be accentuated by chronic immune activation and low-grade inflammation in treated HIV. The independent association of obesity with hypertension is biologically plausible through insulin resistance, adipokine imbalance, oxidative stress, and neurohormonal activation pathways, which have been described in people living with HIV as survival improves and metabolic phenotypes evolve.[24,27] The strong association with family history further supports the contribution of genetic susceptibility and shared household environments, and highlights the relevance of simple clinical history for risk stratification in HIV clinics. Dietary variables and behavioural factors Weekly fruit and vegetable intake was associated with lower hypertension prevalence after adjustment, whereas other intake categories did not show a clear monotonic pattern. Given the reliance on self-report, potential residual confounding, and the possibility of dietary changes after hypertension diagnosis, these findings should be interpreted cautiously. Similarly, the crude inverse association observed for salt/seasoning cube intake did not persist after adjustment, suggesting that this proxy measure may not adequately capture true sodium exposure in this context. Most behavioural variables assessed (physical activity, tobacco, alcohol) were not strongly associated, which may reflect limited measurement precision or exposure variability. Implications for clinical practice and public health These data support prioritising systematic blood pressure screening and management embedded in HIV care, particularly for older adults and those with obesity or a family history of hypertension. Simplified treatment protocols, reliable antihypertensive supply, task sharing, and routine monitoring within HIV clinics can increase detection and control, consistent with standardized primary-care approaches such as HEARTS.[16,28] Given the absence of an independent association between cumulative ART duration and hypertension, integrated care models should focus on conventional cardiometabolic risk factors, while programme monitoring should track blood pressure control and weight trajectories over time. Strengths and limitations Strengths include the relatively large sample size, standardized blood pressure measurement within an HIV care setting, and use of prevalence ratios with robust Poisson regression appropriate for common outcomes. We also explicitly assessed non-linearity using restricted cubic splines. Limitations include the cross-sectional design, which precludes causal inference and is susceptible to reverse causation particularly for behavioural and dietary variables, potential residual confounding (notably for diet and socioeconomic factors), and limited ability of ART duration alone to capture cumulative exposure to specific drug classes and switching histories. The single-centre context may constrain generalisability. Although ART duration was examined as the main exposure, it may not fully capture cumulative cardiometabolic risk related to specific drug classes, treatment switches, and long-term metabolic trajectories. Research and programmatic perspectives Future research should prioritise prospective cohorts to delineate temporal relationships among ART exposure, weight trajectories, and incident hypertension; incorporate mechanistic biomarkers (endothelial, inflammatory, metabolic); and evaluate HEARTS-aligned implementation strategies within HIV clinics while tracking blood pressure control and treatment intensification.[18,28,33] Studies that characterise regimen-specific exposures and switching patterns will be particularly important to clarify whether specific drug classes contribute to cardiometabolic risk beyond the effects of ageing and adiposity. V. Conclusion Among PLHIV in routine care in Yaoundé, age and obesity were the dominant correlations of HTN; prolonged ART exposure showed only a borderline independent association after adjustment. Diagnostics support internal validity, and discrimination was moderate. These findings reinforce the imperative to embed HTN prevention and control within HIV services, leveraging WHO HEARTS components to streamline screening, treatment, and follow‑up. Declarations Competing interests We declare that none of the authors have any competing interests that have influenced the conduct of the study and the write-up of this manuscript. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution Francis Duhamel Nang Nang, André Pascal Kengne, Jean Pierre Junior Tchitetchoun, Charles Kouanfack, Simeon Pierre Choukem, and Anastase Dzudie conceived and designed the study. Francis Duhamel Nang Nang, Jean Pierre Junior Tchitetchoun, Paul Junior Chebo, Rita Marie Ifoue, François Anicet Onana Akoa, Lawson Ngwagwe Mbolueh, and Liliane Mfeukeu Kuate contributed to study implementation and data collection. Francis Duhamel Nang Nang, François Anicet Onana Akoa, and Luc Baudoin Fankoua TchapTcha performed the analyses and prepared the tables and figures. Francis Duhamel Nang Nang drafted the first version of the manuscript. Charles Kouanfack, Simeon Pierre Choukem, André Pascal Kengne, and Anastase Dzudie critically revised the manuscript for important intellectual content. All authors had access to the data, approved the final version, and agree to be accountable for all aspects of the work. Acknowledgements We extend our sincere gratitude to all individuals who contributed, directly or indirectly, to the completion of this work. We are particularly grateful to the healthcare staff of the Day Hospital, where our study was conducted, for their guidance and encouragement. We also wish to acknowledge the people living with HIV who participated in the study without any financial compensation, as this research was conducted as a student project without external funding. Our appreciation goes to the teaching staff of the Faculty of Medicine and Pharmaceutical Sciences at the University of Douala for the knowledge and expertise they imparted, as well as to the non-teaching staff of the faculty for their unwavering support. Data Availability The individual participant data underlying the findings of this article (including text, tables, figures, and supplementary materials), accompanied by a detailed data dictionary, are the intellectual property of the research team. This data will be made available at reasonable requests to researchers whose proposals have been approved by the study’s principal investigators. The findings will be formally presented during the PhD thesis defense in Epidemiology at the University of Dschang. In addition, results have been communicated to the authorities of the Yaoundé Central Hospital, and key messages have been displayed in the Day Hospital unit as part of a preventive health initiative. Proposals should be directed to [ [email protected] ](mailto: [email protected] ) . Access to the data will require the signing of a data use agreement. References Chen A, Chan YK, Mocumbi AO, et al. Hypertension among people living with human immunodeficiency virus in sub-Saharan Africa: a systematic review and meta-analysis. Sci Rep. 2024;14:16858. https://doi.org/10.1038/s41598-024-67703-5 . Dzudie A, Hoover D, Kim HY, Ajeh R, Adedimeji A, Shi Q, et al. Hypertension among people living with HIV/AIDS in Cameroon: A cross-sectional analysis from Central Africa International Epidemiology Databases to Evaluate AIDS. PLoS ONE. 2021;16(7):e0253742. Kouanfack C, Nang Nang FD, IFOUE NGUIMFACK RM, et al. Hypertension Burden and Care Cascade Gaps Among People Living With HIV in an Urban HIV Clinic in Cameroon 2024. J Int Association Providers AIDS Care (JIAPAC). 2025;24. 10.1177/23259582251378538 . Mohamed SF, Mutua MK, Wamai R, Wekesah F, Haregu T, Juma P, et al. 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Dimala CA, Atashili J, Mbuagbaw JC, Wilfred A, Monekosso GL. Prevalence of Hypertension in HIV/AIDS Patients on Highly Active Antiretroviral Therapy (HAART) Compared with HAART-Naïve Patients at the Limbe Regional Hospital, Cameroon. PLoS ONE. 2016;11(2):e0148100. 10.1371/journal.pone.0148100 . PMID: 26862763; PMCID: PMC4749660. Brennan AT, Nattey C, Kileel EM, Rosen S, Maskew M, Stokes AC et al. Change in body weight and risk of hypertension after switching from efavirenz to dolutegravir in adults living with HIV: evidence from routine care in Johannesburg, South Africa. eClinicalMedicine [Internet]. 2023 Mar [cited 2025 Sep 20];57:. Available from: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(23)00013-5/fulltext Calmy AC. A Dolutegravir-based and low-dose efavirenz-based regimen for the initial treatment of HIV-1 infection (NAMSAL): week 96 results from a two-group, multicentre, randomised, open label, phase 3 non-inferiority trial in Cameroon. 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Integrated management of HIV, diabetes, and hypertension in sub-Saharan Africa (INTE-AFRICA): a pragmatic cluster-randomised, controlled trial. Lancet. 2023;402(10409):1241–50. 10.1016/S0140-6736(23)01573-8 . STROBE Initiative. Checklists. STROBE [Internet]. [cited 2025 Sep 17]. Available from: https://www.strobe-statement.org/checklists/ World Health Organization. Global report on hypertension: the race against a silent killer. Geneva, WHO. : 2023 [Internet]. [cited 2025 Oct 9]. Available from: https://www.who.int/publications/i/item/9789240081062 Xu Y, Chen X, Wang K. Global prevalence of hypertension among people living with HIV: a systematic review and meta-analysis. J Am Soc Hypertens. 2017;11(8):530–40. Bigna JJ, Ndoadoumgue AL, Nansseu JR, Tochie JN, Nyaga UF, Nkeck JR, et al. Global burden of hypertension among people living with HIV in the era of increased life expectancy: a systematic review and meta-analysis. J Hypertens. 2020;38(9):1659–68. Baral S, Sifakis F, Cleghorn F, Beyrer C. Elevated risk for HIV infection among men who have sex with men in low- and middle-income countries 2000–2006: a systematic review. PLoS Med. 2007;4(12):e339. Davis K, Perez-Guzman P, Hoyer A, Brinks R, Gregg E, Althoff KN, et al. Association between HIV infection and hypertension: a global systematic review and meta-analysis of cross-sectional studies. BMC Med. 2021;19(1):105. Carey RM, Muntner P, Bosworth HB, Whelton PK. Prevention and control of hypertension: JACC Health Promotion Series. J Am Coll Cardiol. 2018;72(11):1278–93. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6:42. Muddu M, Ssinabulya I, Kigozi SP, Ssennyonjo R, Ayebare F, Katwesigye R, et al. Hypertension care cascade at a large urban HIV clinic in Uganda: a mixed methods study using the Capability, Opportunity, Motivation for Behavior change (COM-B) model. Implement Sci Commun. 2021;2(1):121. Feinstein MJ, Hsue PY, Benjamin LA, Bloomfield GS, Currier JS, Freiberg MS, et al. Characteristics, prevention, and management of cardiovascular disease in people living with HIV: A scientific statement from the American Heart Association. Circulation. 2019;140(2):e98–124. Willem DF, Venter M, Moorhouse S, Sokhela MB. Ch.B. and al. Dolutegravir plus two different prodrugs of tenofovir to treat HIV. N Engl J Med [Internet]. 2019 [cited 2025 Oct 9]. Available from: https://www.nejm.org/doi/full/ 10.1056/NEJMoa1902824 Eckard AR, McComsey GA. Weight gain and integrase inhibitors. Curr Opin Infect Dis. 2020;33(1):10–9. Triant VA. Cardiovascular disease and HIV infection. Curr HIV/AIDS Rep. 2013;10(3):199–206. World Health Organization. HEARTS: Technical package for cardiovascular disease management in primary health care: Risk-based CVD management. Geneva: WHO; 2020 [Internet]. [cited 2025 Aug 12]. Available from: https://www.who.int/publications/i/item/9789240001367 Fox J, Monette G. Generalized collinearity diagnostics. J Am Stat Assoc [Internet]. 1992 [cited 2025 Oct 9];87(417):178 – 83. Available from: https://www.tandfonline.com/doi/abs/ 10.1080/01621459.1992.10475190 Hosmer DW, Lemeshow S, Sturdivant RX. Application of logistic regression with different sampling models. In: Applied Logistic Regression [Internet]. 3rd ed. Hoboken: John Wiley & Sons; 2013 [cited 2025 Oct 9]. pp. 227 – 42. Available from: https://onlinelibrary.wiley.com/doi/abs/ 10.1002/9781118548387.ch6 Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010;5(9):1315–6. Hajian-Tilaki K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Casp J Intern Med. 2013;4(2):627–35. Additional Declarations No competing interests reported. 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Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Charles","middleName":"","lastName":"KOUANFACK","suffix":""},{"id":624654792,"identity":"353dad69-0076-4e3d-b4f2-bf7f936d43a7","order_by":11,"name":"Simeon Pierre CHOUKEM","email":"","orcid":"","institution":"Faculty of Medicine and Pharmaceutical Sciences, University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Simeon","middleName":"Pierre","lastName":"CHOUKEM","suffix":""}],"badges":[],"createdAt":"2026-04-07 20:09:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9349092/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9349092/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107257764,"identity":"e67e7a72-8624-4d18-80df-972cd92c2e77","added_by":"auto","created_at":"2026-04-19 12:33:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75337,"visible":true,"origin":"","legend":"\u003cp\u003eAdjusted non-linear association between ART duration and prevalent hypertension using restricted cubic splines.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9349092/v1/6fb518a0411bec6bcb3a9b75.png"},{"id":109067539,"identity":"1892b1cb-d269-4507-bfcb-43a4bc89fc60","added_by":"auto","created_at":"2026-05-12 09:55:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":562278,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9349092/v1/69b1047b-a89f-4c26-b6ad-294e6fda2770.pdf"},{"id":107257763,"identity":"39d68c0b-b5aa-47bf-8120-c7ce87a7dfd1","added_by":"auto","created_at":"2026-04-19 12:33:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":149677,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistv4casecontrol2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9349092/v1/a3bdcdf355cc33287a065bf9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Long-term Antiretroviral Therapy and Prevalent Hypertension among Adults Living with HIV in Yaounde, Cameroon: A Cross-Sectional Study","fulltext":[{"header":"I. Introduction ","content":"\u003cp\u003eWith the scale-up of antiretroviral therapy (ART), HIV infection has increasingly become a chronic condition, and morbidity among people living with HIV (PLHIV) is progressively shifting toward non-communicable diseases, foremost among them arterial hypertension. Globally, hypertension is a major driver of cardiovascular morbidity and mortality; among PLHIV, it contributes to a \u0026ldquo;double burden\u0026rdquo; in which cardiometabolic comorbidities are becoming a priority for health systems. This epidemiologic transition supports the routine integration of hypertension screening and management within HIV services, particularly in resource-limited settings[1].\u003c/p\u003e\n\u003cp\u003eIn sub-Saharan Africa, where a substantial share of the global HIV burden is concentrated, recent syntheses suggest that a sizeable proportion of PLHIV live with hypertension, highlighting the magnitude of the problem and its implications for continuity of care and cardiovascular prevention[2\u0026ndash;5]. However, major contextual differences (access to care, cardiometabolic profiles, urban vs rural environments, and availability of antihypertensive medicines) strongly shape hypertension detection, treatment, and control within HIV clinics.\u003c/p\u003e\n\u003cp\u003eIn Cameroon, data from HIV care platforms (including the Central Africa IeDEA network) and reports from the Yaounde Central Hospital indicate that hypertension affects a substantial proportion of PLHIV in follow-up, with gaps across the care cascade (screening, treatment initiation, adherence, and blood pressure control)[5, 6]. \u0026nbsp;Additional studies conducted in Cameroonian settings also report a high burden of hypertension among PLHIV and underscore the need for integrated HIV\u0026ndash;hypertension approaches tailored to local realities[7\u0026ndash;9].\u003c/p\u003e\n\u003cp\u003eSeveral plausible pathways may link HIV infection, ART exposure, and hypertension, without allowing causal inference from cross-sectional designs alone. On one hand, ART reduces immune activation and may improve certain vascular markers; on the other, residual inflammation, endothelial dysfunction, and metabolic changes (weight gain, dyslipidaemia, insulin resistance) reported with some therapeutic classes may be associated with higher blood pressure levels[10]. In this context, cumulative duration of ART exposure is a key variable to consider when studying associations with hypertension among PLHIV.\u003c/p\u003e\n\u003cp\u003eIn addition, urban environments may shape cardiometabolic risk. In Yaounde, exposure to lifestyle-related factors (salt-rich diets, physical inactivity, psychosocial stress, and pollution) may influence the distribution of hypertension among PLHIV, beyond virologic status[11]. Since the adoption of \u0026ldquo;Treat All\u0026rdquo; and the widespread use of integrase inhibitor, based regimens, particularly dolutegravir, several observational analyses in Africa have reported weight gain and, in some contexts, higher hypertension prevalence, whereas other studies do not show a uniform short-term rise in blood pressure[12\u0026ndash;14]. These mixed findings suggest that hypertension among PLHIV reflects a complex set of determinants (age, adiposity, health behaviours, and care context) in which ART exposure and its cumulative duration may play variable roles.\u003c/p\u003e\n\u003cp\u003eDespite this background, recent analytical data remain limited in Cameroon, particularly in urban HIV clinics, regarding factors associated with prevalent hypertension among PLHIV and the independent contribution of cumulative ART duration after accounting for major co-determinants (age, adiposity, behavioural and clinical factors). Addressing this gap is important to guide cardiovascular prevention and to standardize hypertension care within HIV services, in line with integrated care approaches[15].\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study aimed to identify factors associated with hypertension among adults living with HIV in Yaound\u0026eacute;, Cameroon, with cumulative duration of antiretroviral therapy as the primary explanatory variable. We hypothesised that prolonged ART exposure would be associated with a higher prevalence of hypertension after accounting for age, adiposity, and behavioural factors.\u003c/p\u003e"},{"header":"II. Materials and Methods ","content":"\u003cp\u003e\u003cstrong\u003e1.\u0026nbsp; \u0026nbsp;\u0026nbsp;Study design and setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional study at the Day Hospital of Yaound\u0026eacute; Central Hospital, Cameroon, between January and March 2024. The facility is an urban HIV care center serving approximately 12,000 people living with HIV. All measurements (blood pressure, anthropometry, ART history, and laboratory data) were obtained or abstracted at a single point in time for each participant. The study followed the STROBE guidelines for cross-sectional studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.\u0026nbsp; \u0026nbsp;\u0026nbsp;Participants and eligibility\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion criteria were adults \u0026ge;21 years living with HIV, followed at the clinic for \u0026ge;6 months, with available data on blood pressure and ART history at the index visit. Non-inclusion criteria (pre-enrolment) were pregnancy, hypertensive emergency at presentation, chronic renal dialysis, age \u0026lt;21 years, or follow-up \u0026lt;6 months. Exclusion criteria (post-eligibility) applied to participants meeting inclusion criteria but removed from the final analysis due to non-imputable missing data on essential variables or major unresolved inconsistencies identified during data quality checks.\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eSampling Method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were recruited through consecutive convenience sampling. All adults living with HIV who attended routine follow-up visits at the Day Hospital of Yaound\u0026eacute; Central Hospital between January and March 2024 and met the eligibility criteria were invited to participate until the required sample size was reached. This approach was chosen for operational feasibility within the study period but may limit the representativeness of the broader clinic population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.\u0026nbsp; \u0026nbsp;\u0026nbsp;Outcome Definition and Variable Classification\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dependent variable was hypertension status at the time of data collection. Hypertension was defined by meeting at least one of the following: (i) mean of the last two of three seated blood pressure measurements \u0026ge;140/90 mmHg at the index visit; (ii) current use of antihypertensive medication; or (iii) prior clinician-documented diagnosis of hypertension in the medical record. Participants with no prior hypertension diagnosis, not receiving antihypertensive therapy, and with mean seated BP \u0026lt;140/90 mmHg were classified as non-hypertensive. The index date was the calendar date of the qualifying blood pressure assessment. Exposure variables and time-updated covariates (when applicable) were computed up to the index date.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.\u0026nbsp; \u0026nbsp;\u0026nbsp;Exposure and covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary exposure was cumulative duration of antiretroviral therapy (ART) (years), analyzed primarily as a continuous variable. ART regimen category/therapeutic line (e.g., first-line vs second line) was defined from routine clinic records. Exposure to major antiretroviral drug classes and treatment lines was examined in preliminary analyses; however, no consistent independent associations with hypertension were observed, and these variables were therefore not retained in the final multivariable models. \u0026nbsp;Priori covariates were selected for epidemiological relevance and to minimize overfitting. These included: age, sex, education level, smoking status (never/former/current), alcohol use (AUDIT-C cut-offs), physical activity (IPAQ-short categories), adiposity indicators (BMI and/or waist circumference using standard sex-specific thresholds), diabetes status, dyslipidaemia, chronic kidney disease (eGFR \u0026lt;60 mL/min/1.73 m\u0026sup2; using the 2021 CKD-EPI equation), HIV-related markers (e.g., viral suppression status, CD4 count as available), and concomitant medications known to influence blood pressure when reliably documented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6.\u0026nbsp; \u0026nbsp;Data Sources and Measurement Procedures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical data abstraction. Sociodemographic, clinical, HIV treatment history, and pharmacy information were abstracted from routine clinical records (electronic medical records and pharmacy databases) using a standardized case report form. Blood pressure. Blood pressure was measured using a validated automated Oscillo metric device. Three seated readings were taken 1\u0026ndash;2 minutes apart after a rest period; the mean of the last two readings was used for classification. \u0026nbsp;Anthropometry. Weight and height were measured using standard procedures to compute BMI. Waist circumference was measured using standardized techniques to assess central obesity. Laboratory variables. Fasting glucose, lipid profile, creatinine, CD4 count, and HIV viral load were obtained from routine laboratory records performed within 90 days of the index date. eGFR was estimated to use the 2021 CKD-EPI (race-free) equation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7.\u0026nbsp; \u0026nbsp;\u0026nbsp;Sample size and precision considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSample size was first determined to estimate the prevalence of hypertension among adults living with HIV with adequate precision. Assuming a 95% confidence level, expected prevalence of 50% (conservative), and absolute precision of 5%, the minimum required sample size was 384 participants using the single-proportion formula. To support multivariable modelling with ART duration as the main exposure and adjustment for key confounders, recruitment aimed at least 400 participants. The final analytic sample is reported in the Results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8.\u0026nbsp; \u0026nbsp;Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalyses were conducted using IBM SPSS Statistics (version 29) (and R when needed for specific modelling/graphics). Participant characteristics were summarised using median (IQR) for continuous variables and n (%) for categorical variables. Hypertension prevalence was estimated with 95% confidence intervals. Associations between explanatory variables and hypertension were assessed using Poisson regression with robust variance to estimate prevalence ratios (PRs), reporting adjusted PRs with 95% confidence intervals. ART duration was modelled primarily as a continuous exposure. Linearity assumptions were assessed; when indicated, restricted cubic splines were used and displayed using predicted marginal effects.\u0026nbsp;Restricted cubic spline analyses were conducted using multivariable logistic regression models with four knots placed at recommended percentiles of the ART duration distribution. Logistic models were used for spline analysis because robust poisson models are not directly supported within the rms framework we used in R.\u0026nbsp;Multicollinearity and influential observations were checked using standard diagnostics. All tests were two-sided, with p\u0026lt;0.05 considered statistically significant. Missing data were described and handled using complete-case analysis for variables included in the final model.\u003c/p\u003e\n\u003ch3\u003eEthics and confidentiality\u003c/h3\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Regional Ethics Committee for Human Health Research in the Central Region (CRERSHC)\u0026nbsp;N\u003csup\u003e0\u003c/sup\u003e:CEN000633/CRERSHC/2023 on August 8, 2023. All participants provided written informed consent prior to enrolment in the study. \u0026nbsp;Administrative authorization was granted by the Director of the Central Hospital of Yaounde (N02023/265/AR/MINSANTE/SG/DHCY/UAF) on May 8, 2023, prior to the commencement of data collection.\u003c/p\u003e"},{"header":"III.\tResults ","content":"\u003ch2\u003eCharacteristics of Study Participants\u003c/h2\u003e\n\u003cp\u003eAmong 460 adults living with HIV receiving ART, 199 had prevalent hypertension (43.3%). The mean age was 50.5 \u0026plusmn; 10.9 years and 73.5% were women. Participants with hypertension were older (53.1 \u0026plusmn; 10.1 vs 48.5 \u0026plusmn; 11.0 years) and had a longer ART duration (12.1 \u0026plusmn; 5.5 vs 10.1 \u0026plusmn; 6.1 years). Family history of hypertension and obesity were more frequent among participants with hypertension (Table 1). Overall, participants were predominantly middle-aged adults with long-term exposure to ART, reflecting a relatively stable cohort in routine HIV care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Sociodemographic, clinical, and treatment characteristics of the study population, overall and stratified by hypertension status.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertensive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-hypertensive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e50.5 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e53.1 \u0026plusmn; 10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e48.5 \u0026plusmn; 11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e338 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e142 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e196 (75.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e122 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e57 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e65 (24.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 11px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e180 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e86 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e94 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e122 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e46 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e76 (29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eCohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e58 (12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e20 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e38 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e13 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e4 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e9 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e87 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e43 (21.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e44 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 11px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e255 (55.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e102 (51.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e153 (58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e23 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e14 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e9 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e133 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e64 (32.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e69 (26.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e49 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e19 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e30 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 11px;\"\u003e\n \u003cp\u003eEmployment status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e97 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e32 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e65 (24.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSelf-employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e137 (29.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e55 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e82 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e154 (33.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e75 (37.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e79 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e72 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e37 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e35 (13.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eFamily history of hypertension\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e289 (62.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e72 (36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e217 (83.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e171 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e127 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e44 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 11px;\"\u003e\n \u003cp\u003eHIV stage at initiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e235 (51.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e93 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e142 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e159 (34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e81 (40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e78 (29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eStage III/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e66 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e25 (12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e41 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 11px;\"\u003e\n \u003cp\u003eBMI category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eNormal weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e188 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e68 (34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e120 (46.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e106 (23.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e55 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e51 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e166 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e76 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e90 (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eART treatment line\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eFirst-line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e376 (81.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e157 (78.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e219 (83.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSecond/third-line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e84 (18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e42 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e42 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 11px;\"\u003e\n \u003cp\u003eViral load category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eUndetectable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e357 (77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e150 (75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e207 (79.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e50 (10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e20 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e30 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSuppressed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e53 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e29 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e24 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eART duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e10.9 \u0026plusmn; 5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e12.1 \u0026plusmn; 5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e10.1 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eSalt/seasoning cube intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e186 (40.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e91 (45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e95 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e274 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e108 (54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e166 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 11px;\"\u003e\n \u003cp\u003eFruit \u0026amp; vegetable intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eBi-weekly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e79 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e45 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e34 (13.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eWeekly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e242 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e101 (50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e141 (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e90 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e35 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e55 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eThree times per week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e49 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e18 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e31 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eBivariable associations\u003c/h2\u003e\n\u003cp\u003eIn bivariable robust Poisson models, older age was associated with prevalent hypertension (PR per 1-year increase 1.02, 95% CI 1.01-1.03; p\u0026lt;0.001). Longer ART duration was also associated with hypertension (PR per 1-year increase 1.03, 95% CI 1.01-1.05; p\u0026lt;0.001). Hypertension was more prevalent among participants reporting a family history of hypertension (PR 2.98, 95% CI 2.40-3.71; p\u0026lt;0.001) and among those with obesity (PR 1.43, 95% CI 1.10-1.87; p=0.007) (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Bivariable analysis of factors associated with prevalent hypertension among adults receiving antiretroviral therapy.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePer 1-year increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.01-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eFemale (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.89-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 173px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eMarried (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.60-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eCohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.49-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.28-1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.80-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSecondary (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.06-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.95-1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.66-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eEmployment status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eEmployed (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSelf-employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.86-1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.06-2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.08-2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eFamily history of hypertension\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNo (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e2.40-3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 173px;\"\u003e\n \u003cp\u003eHIV stage at initiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eI (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.03-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eIII/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.68-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 173px;\"\u003e\n \u003cp\u003eBMI category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNormal weight (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.10-1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.98-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eART treatment line\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eFirst-line (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSecond/third line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.94-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 173px;\"\u003e\n \u003cp\u003eViral load category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eUndetectable (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.66-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSuppressed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.99-1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eART duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePer 1-year increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.01-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eSalt/seasoning cube intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNo (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.65-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eFruit \u0026amp; vegetable intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eTwice weekly (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eOnce weekly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.57-0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.49-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eThree times weekly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.43-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 173px;\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eAdequate (WHO-compliant) (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eHigh/optimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.61-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.73-1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eMonthly frequency (once/month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.86-2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eInactive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.74-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eTobacco use\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNo (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.57-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eAlcohol use\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eWeekly/daily (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eMonthly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.72-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.76-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.935\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eOccasional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.76-1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eMultivariable model and independent correlates\u003c/h2\u003e\n\u003cp\u003eIn the multivariable robust Poisson model (Table 3), age remained independently associated with prevalent hypertension (aPR per 1-year increase 1.02, 95% CI 1.01-1.03; p=0.002). Family history of hypertension showed the strongest independent association (aPR 2.83, 95% CI 2.25-3.57; p\u0026lt;0.001). Obesity was independently associated with hypertension (aPR 1.29, 95% CI 1.01-1.65; p=0.045), whereas overweight showed borderline evidence (aPR 1.23, 95% CI 0.99-1.53; p=0.066). After multivariate adjustment, \u0026nbsp;the crude association between ART duration and hypertension was fully attenuated(aPR per 1-year increase 1.00, 95% CI 0.99-1.02; p=0.619) suggesting substancial confounding by age. Family history showed the strongest independent association, with nearly a threefold higher prevalence of hypertension. Weekly fruit and vegetable intake was associated with lower hypertension prevalence (aPR 0.67, 95% CI 0.53-0.85; p=0.001), while salt/seasoning cube intake was not associated after adjustment.\u003c/p\u003e\n\u003cp\u003eTable 3. Adjusted prevalence ratios for independent factors associated with prevalent hypertension in multivariable Poisson regression.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaPR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePer 1-year increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.01-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eART duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePer 1-year increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.99-1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 173px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eMarried (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.79-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eCohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.70-1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.50-2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.79-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.980\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSecondary (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.84-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.85-1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.70-1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eEmployment status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eEmployed (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eSelf-employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.82-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.76-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.707\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.58-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eFamily history of hypertension\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNo (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e2.25-3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 173px;\"\u003e\n \u003cp\u003eBMI category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNormal weight (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e1.01-1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.99-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 173px;\"\u003e\n \u003cp\u003eSalt/seasoning cube intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eNo (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.81-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 173px;\"\u003e\n \u003cp\u003eFruit \u0026amp; vegetable intake\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eBi-weekly (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eWeekly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.53-0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.56-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 211px;\"\u003e\n \u003cp\u003eThree times per week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.44-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eAssessment of non-linearity for ART duration\u003c/h2\u003e\n\u003cp\u003eRestricted cubic spline analyses did not provide evidence of a sighificant non-linear association between ART duration and prevalent hypertension; both overall and non- linear components were non-significant andthe adjusted curve remained approximately flat across the observed ART duration range, with confidence intervals crossing the null (Figure 1).\u003c/p\u003e"},{"header":"IV.\tDiscussion","content":"\u003ch2\u003eOverview of main findings\u003c/h2\u003e\n\u003cp\u003eIn this cross-sectional analysis of 460 adults living with HIV receiving ART at the Central Hospital of Yaounde, hypertension was common (43.3%). In adjusted analyses, prevalent hypertension clustered with older age, obesity, and a family history of hypertension, while cumulative ART duration was not independently associated when modelled continuously. Restricted cubic spline modelling similarly provided no evidence of a meaningful non-linear association between ART duration and hypertension (Figure 1). These findings support the integration of standardized hypertension prevention and control within routine HIV services.[16\u0026ndash;20]\u003c/p\u003e\n\u003ch2\u003eComparison with previous studies\u003c/h2\u003e\n\u003cp\u003eThe strong associations observed for age and adiposity are consistent with reports from sub-Saharan Africa and other settings, where hypertension prevalence increases with ageing and cardiometabolic risk factors among treated people living with HIV.[2,21\u0026ndash;24] The lack of an independent association between ART duration and hypertension after adjustment, despite a positive crude association, suggests confounding by age and adiposity, because longer ART exposure is inherently correlated with ageing and cumulative weight trajectories. This pattern aligns with mixed evidence in the literature, where associations between ART exposure and hypertension often attenuate after accounting for age and body mass index, and may vary by regimen composition and switching histories.[2,9,23,25,26] Our results therefore argue against using \u0026quot;time on ART\u0026quot; alone as a clinical proxy for hypertension risk in this setting.\u003c/p\u003e\n\u003ch2\u003eBiological and pathophysiological interpretation\u003c/h2\u003e\n\u003cp\u003eThe age gradient likely reflects cumulative vascular ageing and endothelial dysfunction, processes that may be accentuated by chronic immune activation and low-grade inflammation in treated HIV. The independent association of obesity with hypertension is biologically plausible through insulin resistance, adipokine imbalance, oxidative stress, and neurohormonal activation pathways, which have been described in people living with HIV as survival improves and metabolic phenotypes evolve.[24,27] The strong association with family history further supports the contribution of genetic susceptibility and shared household environments, and highlights the relevance of simple clinical history for risk stratification in HIV clinics.\u003c/p\u003e\n\u003ch2\u003eDietary variables and behavioural factors\u003c/h2\u003e\n\u003cp\u003eWeekly fruit and vegetable intake was associated with lower hypertension prevalence after adjustment, whereas other intake categories did not show a clear monotonic pattern. Given the reliance on self-report, potential residual confounding, and the possibility of dietary changes after hypertension diagnosis, these findings should be interpreted cautiously. Similarly, the crude inverse association observed for salt/seasoning cube intake did not persist after adjustment, suggesting that this proxy measure may not adequately capture true sodium exposure in this context. Most behavioural variables assessed (physical activity, tobacco, alcohol) were not strongly associated, which may reflect limited measurement precision or exposure variability.\u003c/p\u003e\n\u003ch2\u003eImplications for clinical practice and public health\u003c/h2\u003e\n\u003cp\u003eThese data support prioritising systematic blood pressure screening and management embedded in HIV care, particularly for older adults and those with obesity or a family history of hypertension. Simplified treatment protocols, reliable antihypertensive supply, task sharing, and routine monitoring within HIV clinics can increase detection and control, consistent with standardized primary-care approaches such as HEARTS.[16,28] Given the absence of an independent association between cumulative ART duration and hypertension, integrated care models should focus on conventional cardiometabolic risk factors, while programme monitoring should track blood pressure control and weight trajectories over time.\u003c/p\u003e\n\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\n\u003cp\u003eStrengths include the relatively large sample size, standardized blood pressure measurement within an HIV care setting, and use of prevalence ratios with robust Poisson regression appropriate for common outcomes. We also explicitly assessed non-linearity using restricted cubic splines. Limitations include the cross-sectional design, which precludes causal inference and is susceptible to reverse causation particularly for behavioural and dietary variables, potential residual confounding (notably for diet and socioeconomic factors), and limited ability of ART duration alone to capture cumulative exposure to specific drug classes and switching histories. The single-centre context may constrain generalisability. Although ART duration was examined as the main exposure, it may not fully capture cumulative cardiometabolic risk related to specific drug classes, treatment switches, and long-term metabolic trajectories.\u003c/p\u003e\n\u003ch2\u003eResearch and programmatic perspectives\u003c/h2\u003e\n\u003cp\u003eFuture research should prioritise prospective cohorts to delineate temporal relationships among ART exposure, weight trajectories, and incident hypertension; incorporate mechanistic biomarkers (endothelial, inflammatory, metabolic); and evaluate HEARTS-aligned implementation strategies within HIV clinics while tracking blood pressure control and treatment intensification.[18,28,33] Studies that characterise regimen-specific exposures and switching patterns will be particularly important to clarify whether specific drug classes contribute to cardiometabolic risk beyond the effects of ageing and adiposity.\u003c/p\u003e"},{"header":"V.\tConclusion","content":"\u003cp\u003eAmong PLHIV in routine care in Yaoundé, age and obesity were the dominant correlations of HTN; prolonged ART exposure showed only a borderline independent association after adjustment. Diagnostics support internal validity, and discrimination was moderate. These findings reinforce the imperative to embed HTN prevention and control within HIV services, leveraging WHO HEARTS components to streamline screening, treatment, and follow‑up.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eWe declare that none of the authors have any competing interests that have influenced the conduct of the study and the write-up of this manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFrancis Duhamel Nang Nang, Andr\u0026eacute; Pascal Kengne, Jean Pierre Junior Tchitetchoun, Charles Kouanfack, Simeon Pierre Choukem, and Anastase Dzudie conceived and designed the study. Francis Duhamel Nang Nang, Jean Pierre Junior Tchitetchoun, Paul Junior Chebo, Rita Marie Ifoue, Fran\u0026ccedil;ois Anicet Onana Akoa, Lawson Ngwagwe Mbolueh, and Liliane Mfeukeu Kuate contributed to study implementation and data collection. Francis Duhamel Nang Nang, Fran\u0026ccedil;ois Anicet Onana Akoa, and Luc Baudoin Fankoua TchapTcha performed the analyses and prepared the tables and figures. Francis Duhamel Nang Nang drafted the first version of the manuscript. Charles Kouanfack, Simeon Pierre Choukem, Andr\u0026eacute; Pascal Kengne, and Anastase Dzudie critically revised the manuscript for important intellectual content. All authors had access to the data, approved the final version, and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe extend our sincere gratitude to all individuals who contributed, directly or indirectly, to the completion of this work. We are particularly grateful to the healthcare staff of the Day Hospital, where our study was conducted, for their guidance and encouragement. We also wish to acknowledge the people living with HIV who participated in the study without any financial compensation, as this research was conducted as a student project without external funding. Our appreciation goes to the teaching staff of the Faculty of Medicine and Pharmaceutical Sciences at the University of Douala for the knowledge and expertise they imparted, as well as to the non-teaching staff of the faculty for their unwavering support.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe individual participant data underlying the findings of this article (including text, tables, figures, and supplementary materials), accompanied by a detailed data dictionary, are the intellectual property of the research team. This data will be made available at reasonable requests to researchers whose proposals have been approved by the study\u0026rsquo;s principal investigators. The findings will be formally presented during the PhD thesis defense in Epidemiology at the University of Dschang. In addition, results have been communicated to the authorities of the Yaound\u0026eacute; Central Hospital, and key messages have been displayed in the Day Hospital unit as part of a preventive health initiative. Proposals should be directed to [[email protected]](mailto:[email protected]) . Access to the data will require the signing of a data use agreement.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen A, Chan YK, Mocumbi AO, et al. Hypertension among people living with human immunodeficiency virus in sub-Saharan Africa: a systematic review and meta-analysis. Sci Rep. 2024;14:16858. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-024-67703-5\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-67703-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDzudie A, Hoover D, Kim HY, Ajeh R, Adedimeji A, Shi Q, et al. Hypertension among people living with HIV/AIDS in Cameroon: A cross-sectional analysis from Central Africa International Epidemiology Databases to Evaluate AIDS. PLoS ONE. 2021;16(7):e0253742.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKouanfack C, Nang Nang FD, IFOUE NGUIMFACK RM, et al. Hypertension Burden and Care Cascade Gaps Among People Living With HIV in an Urban HIV Clinic in Cameroon 2024. 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Casp J Intern Med. 2013;4(2):627\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aids-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arty","sideBox":"Learn more about [AIDS Research and Therapy](http://aidsrestherapy.biomedcentral.com/)","snPcode":"12981","submissionUrl":"https://submission.nature.com/new-submission/12981/3","title":"AIDS Research and Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Antiretroviral Therapy, Highly Active, Hypertension, HIV Infections, Cross-Sectional Studies, Cameroon","lastPublishedDoi":"10.21203/rs.3.rs-9349092/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9349092/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHypertension is an increasingly common comorbidity among adults living with HIV in sub-Saharan Africa, yet data from routine HIV clinics in Cameroon remain limited. We examined factors associated with prevalent hypertension among adults receiving antiretroviral therapy (ART) at Yaound\u0026eacute; Central Hospital. In this cross-sectional study of 460 participants, hypertension (blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg and/or current antihypertensive treatment) was present in 43.3%. Using robust Poisson regression, older age and obesity were independently associated with higher hypertension prevalence, and family history showed the strongest association (adjusted prevalence ratio 2.83). Cumulative ART duration was not independently associated after adjustment. Weekly fruit and vegetable intake was associated with lower hypertension prevalence, whereas salt/seasoning cube intake and most behavioural factors were not associated after adjustment. Restricted cubic spline analyses did not suggest non-linearity in the relationship between ART duration and hypertension. In this urban HIV care setting, hypertension clustered primarily with conventional cardiometabolic factors rather than time on ART. Integrating systematic blood pressure screening and standardised hypertension management within HIV services, alongside weight management and lifestyle counselling, may help reduce cardiovascular burden among people living with HIV.\u003c/p\u003e","manuscriptTitle":"Long-term Antiretroviral Therapy and Prevalent Hypertension among Adults Living with HIV in Yaounde, Cameroon: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:33:33","doi":"10.21203/rs.3.rs-9349092/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-22T19:28:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T23:28:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107836971206509518719770193711524990641","date":"2026-04-20T23:03:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T19:30:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195799652938917524225762470989943712594","date":"2026-04-18T15:06:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49186090293169224005247609747571986987","date":"2026-04-17T04:02:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139252129524367548933425832918057739100","date":"2026-04-16T09:30:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217063731299199090513541702989065708406","date":"2026-04-11T02:52:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-10T05:08:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-10T05:06:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-09T11:52:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"AIDS Research and Therapy","date":"2026-04-07T19:58:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aids-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arty","sideBox":"Learn more about [AIDS Research and Therapy](http://aidsrestherapy.biomedcentral.com/)","snPcode":"12981","submissionUrl":"https://submission.nature.com/new-submission/12981/3","title":"AIDS Research and Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c79671d3-57d5-4cbe-b337-a2a576821964","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T19:39:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:33:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9349092","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9349092","identity":"rs-9349092","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}