Interactions between long-term Antiretroviral Therapy and Risk of Hypertension among People Living with HIV in an Urban HIV Clinic in Cameroon, 2024: A Case-control Study

Interactions between long-term Antiretroviral Therapy and Risk of Hypertension among People Living with HIV in an Urban HIV Clinic in Cameroon, 2024: A Case-control 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 Article Interactions between long-term Antiretroviral Therapy and Risk of Hypertension among People Living with HIV in an Urban HIV Clinic in Cameroon, 2024: A Case-control Study Francis Duhamel NANG NANG, Liliane MFEUKEU KUATE, Anicet ONANA AKOA, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7821718/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Survival gains under ART have shifted morbidity among PLHIV toward non-communicable diseases, with HTN emerging in sub-Saharan Africa. In Cameroon, evidence from routine HIV care is limited and integration of HTN services is uneven. We aimed to identify factors associated with HTN among PLHIV in Yaounde to inform standardized HTN care within HIV services. Methods We conducted a case-control study at the Central Hospital of Yaoundé (n = 460; 199 HTN cases, 261 controls). Cases were defined as SBP/DBP ≥ 140/90 mmHg or current antihypertensive therapy; controls had BP < 140/90 mmHg without therapy. We collected sociodemographic, clinical, antiretroviral therapy (ART), viral-load, and lifestyle data. Group differences used standard statistical tests. Multivariable logistic regression and adjusted a priori for age, sex, BMI, ART duration, HIV stage at initiation, viral-load class, and lifestyle factors estimated adjusted odds ratios (aOR, 95% CI). Collinearity was assessed via GVIF (cutoff = 5) and model discrimination by ROC/AUC. Two-sided p < 0.05 denoted significance; reporting followed STROBE. Results Among 460 PLHIV, hypertensive cases were older (≥ 40 y: 92.5% vs 78.5%; p < 0.001) and more often obese (27.6% vs 19.5%; p = 0.024). Family history of HTN was more frequent in cases (p < 0.001), and employment differed (unemployed/retired more common among cases; p = 0.037). Sex, marital status, education, HIV stage at initiation, treatment line, and recent viral-load class were not associated (all p > 0.05). In adjusted models, age < 40 y was inversely associated with HTN (aOR 0.37; 95% CI 0.19–0.69; p = 0.002), while obesity increased odds (aOR 1.96; 95% CI 1.18–3.28; p = 0.010). Longer ART exposure (≥ 15 y) showed borderline evidence (aOR 1.50; 95% CI 0.99–2.30; p = 0.059). No dietary variable retained significance; lower odds across some fruit/vegetable frequencies versus the biweekly reference likely reflect measurement or residual confounding. Diagnostics indicated no concerning multicollinearity (all GVIF < 5) and moderate discrimination (AUC 0.689). Conclusions In routine HIV care in Yaoundé, HTN clustered with aging and adiposity, while the apparent effect of long ART exposure attenuated after adjustment. Findings support embedding standardized HTN screening and management and including weight management and lifestyle counseling within HIV services (WHO HEARTS) and encourage prospective studies to test integrated models and clarify causal pathways. Health sciences/Cardiology Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Long-term antiretroviral therapy hypertension HIV case-control study Cameroon Figures Figure 1 Figure 8 I. Introduction HIV has become a chronic disease thanks to antiretroviral therapy (ART). However, this success has shifted morbidity toward cardiometabolic comorbidities, foremost among them hypertension (HTN). In sub-Saharan Africa (SSA), recent syntheses estimate that about one in five people living with HIV (PLWH) have HTN, underscoring the magnitude of the problem in a region that bears most of the global HIV burden. This signal justifies systematically integrating blood pressure screening and control into routine HIV care for PLWH[ 1 ]. In Cameroon, data from the CA-IeDEA network and a recent study conducted at Yaounde Central Hospital show that more than one quarter of PLWH in care sites had HTN, with gaps along the hypertension care cascade [ 2 , 3 ]. Other regional series (Fako, South-West) report a high incidence of HTN among individuals on ART, highlighting that HTN is not only prevalent but also emerges during follow-up despite virologic control. These findings anchor the issue in the Cameroonian reality and call for integrated HIV–HTN models of care[ 4 – 6 ]. The association between HIV, ART, and HTN is ambivalent. On the one hand, ART reduces immune activation and may improve endothelial function; on the other hand, persistent residual inflammation, endothelial dysfunction, and metabolic alterations linked to certain classes (weight gain, dyslipidemia, insulin resistance) promote increases in blood pressure. This tension between virologic benefits and potential cardiometabolic effects places cumulative exposure duration (the “dose–time” dimension) at the heart of HTN etiology in PLWH [ 7 ]. The urban exposome (high-salt diet, sedentary lifestyle, occupational stress, pollution) can amplify these effects. The rapid urbanization of Yaounde thus constitutes an interaction milieu in which weight and blood-pressure trajectories under ART may diverge from those in rural contexts, independent of virologic characteristics. This hypothesis aligns with prior Cameroonian results showing higher BP levels among individuals on ART than among ART-naïve persons, already in the non-INSTI era[ 8 ]. Since adoption of the “Treat All” principle (initiate ART regardless of CD4 count), SSA has shifted massively to integrase inhibitor (INSTI)–based regimens, notably dolutegravir (DTG). Several observational analyses in Africa have reported weight gain and, in some settings, an increased risk of HTN after DTG initiation or switch, whereas other studies do not observe a uniform short-term rise in BP. This paradox (eight gain, blood pressure sometimes elevated, sometimes neutral) suggests that the class effect depends strongly on exposure duration, weight phenotype, and the care environment [ 9 – 13 ]. Against this dual determinism (ART dose–time and urban exposome) arises an operational question: when and in whom does ART duration become a multiplier of hypertension risk? Trials of integrated care (HIV–HTN–diabetes) in SSA show that these conditions can be treated simultaneously without compromising viral suppression and with gains in retention in care, but they do not provide fine-grained answers on the interactions among cumulative ART duration, drug classes, and HTN within urban clinics in Central Africa [ 14 ]. In Cameroon, despite prevalence estimates and some incidence data, no recent analytic study has quantified, within an urban clinical setting, the interaction between prolonged ART exposure (in years) and HTN risk, while distinguishing therapeutic classes and controlling for key co-determinants (age, adiposity, behavioral factors). This gap limits the precision of prevention strategies and targets cardiometabolic monitoring within HIV services in large cities. We aim, using a case–control study conducted in 2024 in an urban HIV clinic in Yaounde, to estimate the association between cumulative ART duration and HTN risk among PLWH, and to test interaction effects with therapeutic line HIV and HTN. We hypothesize that, for equal cumulative exposure, therapeutic line HIV, particularly those associated with weight gain, increase HTN risk, an effect amplified by the urban exposome [ 9 ]. II. Materials and Methods II. 1. Study design and setting We conducted an unmatched case-control study at the Day Hospital (Hôpital de Jour, HJ) of Yaounde Central Hospital (HCY), an urban HIV clinic in Yaounde, Cameroon. Enrollment and data collection occurred from 1 January to 31 Mars 2024, and reporting adheres to STROBE recommendations for case–control studies [ 15 ] ( Supplementary Material 1 ). HCY is the largest secondary-level hospital in Cameroon (650 beds) with a dedicated infectious diseases unit and is accredited by the ANRS (National Agency for Research on AIDS and Viral Hepatitis). The site was selected because of the size and longevity of its cohort of people living with HIV (PLHIV): the Day Hospital follows approximately 12,000 patients, about 3,600 of whom are receiving antiretroviral therapy. We conducted an unmatched case-control study at the Day Hospital of Yaounde Central Hospital an urban HIV clinic in Yaounde, Cameroon. II. 2. Study population Eligibility criteria. Adults (≥ 21 years) living with HIV (PLHIV), followed in the clinic for ≥ 6 months, with complete information on blood pressure (BP), antiretroviral therapy (ART) history, and key covariates. Exclusion criteria. Pregnancy, hypertensive emergency at presentation, chronic dialysis, or non-imputable missing data on essential variables. II. 3. Case and control definitions Cases (hypertension). PLHIV meeting any of: (i) mean of the last two of three seated BP measurements ≥ 140/90 mmHg at the index visit; (ii) current antihypertensive therapy; (iii) prior clinician-documented hypertension in the medical record. Controls (non-hypertensive). PLHIV with no prior hypertension diagnosis, not on antihypertensives, and mean seated BP < 140/90 mmHg at the index visit. Index date. The calendar date of the qualifying BP assessment. All exposures (e.g., cumulative ART duration) and time-varying covariates were computed up to the index date. II. 4. Sampling strategy We enrolled consecutive eligible cases during routine visits. For each case, we randomly selected two controls (1:2 ratio) from eligible PLHIV seen within the same calendar week, using a computer-generated list to limit temporal confounding. We chose an unmatched design to avoid overmatching, preserve statistical power, and allow adjusted estimation for key factors (age, BMI, ART classes, etc.). No participant was enrolled more than once. II. 5. Exposures and covariates 1. Primary exposure: long-term ART - Cumulative ART duration (years, continuous) and categorized as < 15 and ≥ 15 years. - Therapeutic line categorized as First-line treatment (dolutegravir) and Second-line treatment. 2. Priori covariates (potential confounders) Age, sex, education, smoking (never/former/current), alcohol use (AUDIT-C ≥ 3 women/≥4 men), physical activity (IPAQ-short: low/moderate/high), BMI and obesity (BMI ≥ 30 kg/m²), waist circumference (central obesity per WHO/IDF: ≥94 cm men, ≥ 80 cm women), diabetes (fasting plasma glucose ≥ 126 mg/dL, HbA1c ≥ 6.5% or medication), dyslipidemia (abnormal fasting lipids or treatment), chronic kidney disease (eGFR < 60 mL/min/1.73 m² using CKD-EPI 2021, race-free), family history of hypertension, self-reported high salt intake, time since HIV diagnosis, WHO stage at ART initiation, nadir and current CD4 count, viral load suppression (< 200 copies/mL), and concomitant medications affecting BP (systemic corticosteroids, NSAIDs, hormonal contraception). II. 6. Data sources and measurements Data abstraction. Sociodemographic, clinical, HIV and pharmacy data were extracted from electronic medical records and pharmacy databases using a standardized case report form and harmonized SOPs. Abstractors were trained and certified in the SOPs. Blood pressure measurement. Validated automated oscillometric device (ISO 81060-2 compliant); appropriate cuff size; participant seated, arm supported at heart level; 5-minute rest; no caffeine/tobacco/exercise within 30 minutes. Three readings 1–2 minutes apart; the mean of the last two classified BP. Devices were calibrated weekly. Anthropometrics. Weight (calibrated scale), height (stadiometer) to compute BMI; waist circumference measured at the midpoint between the lower rib and iliac crest at end-expiration; two readings averaged. Laboratory assays. Fasting blood draws (glucose, lipid profile, creatinine) and HIV labs (CD4 count, viral load) within ± 90 days of the index date, processed in a certified laboratory with external quality control. eGFR calculated using CKD-EPI 2021. II. 7. Sample size Assuming a 1:2 case: control ratio, two-sided α = 0.05, 80% power, an expected odds ratio (OR) = 1.8 for long-term ART (≥ 10 vs < 10 years), and 30% exposure prevalence among controls, the Fleiss formula for unmatched case–control studies yields ≥ 366 participants (122 cases, 244 controls). Allowing 10% incomplete data, the target sample was ~ 406. All eligible patients during the study period were considered; the final analytic sample is reported in Results. II. 8. Quality assurance and bias minimization To minimize potential biases, several methodological safeguards were implemented. Selection bias was addressed by sampling controls from the same source population and time window as the cases, using a random selection process. Measurement bias was mitigated using standardized blood pressure measurement protocols, comprehensive staff training and supervision, periodic re-audits of 10% of records, and regular calibration of measurement devices. To reduce information bias, key exposures such as antiretroviral therapy (ART) duration and adherence, along with clinical covariates, were extracted from traceable electronic sources, thereby limiting recall bias. Confounding was controlled using a pre-specified strategy based on a directed acyclic graph (DAG), complemented by multivariable adjustment, sensitivity analyses, and propensity score weighting. II. 9. Statistical analysis Data was analyzed using IBM SPSS Statistics version 29 and R version 4.3.2 for advanced analyses. A descriptive approach was first used to characterize the study population (cases vs. controls) using means and standard deviations for normally distributed continuous variables, medians and interquartile ranges (IQR) for skewed variables, and frequencies and percentages for categorical variables. Bivariate comparisons between cases and controls were performed using the student’s t-test or the Mann–Whitney U test for continuous variables, and the chi-square test or Fisher’s exact test for categorical variables. For the main analysis, an unmatched logistic regression model was used to identify factors associated with hypertension (HTN), defined as an average blood pressure ≥ 140/90 mmHg or current antihypertensive treatment. The main exposure variable, duration of antiretroviral therapy (ART), was modeled as a continuous variable using restricted cubic splines (3 to 4 knots) to explore the non-linear dose–response relationship between duration of exposure and HTN risk. Covariates included in the multivariable model were selected based on a predefined causal diagram (DAG) and included: age, sex, body mass index (BMI), abdominal obesity, alcohol and tobacco use, physical activity, salt and cube intake, presence of diabetes, estimated glomerular filtration rate (eGFR < 60 mL/min/1.73 m²), viral suppression, and treatment line according to cumulative exposure duration. Adjusted odds ratios (aORs) and their 95% confidence intervals (95% CI) were calculated for each factor. Prespecified interactions (ART duration × BMI, ART duration × sex, ART duration × treatment line) were tested, and predicted marginal effects were visualized as dose–response curves. Sensitivity analyses included redefining HTN (≥ 130/80 mmHg), restricting the sample to patients with viral suppression, and excluding individuals on corticosteroids or non-steroidal anti-inflammatory drugs. Finally, diagnostics for multicollinearity (Variance Inflation Factor), discrimination (AUC-ROC), and calibration (slope and interception, calibration curve) were performed. Multiple imputation using chained equations (MICE, m = 20) was applied for variables with more than 5% missing data. Results were presented as comparative tables (crude and adjusted ORs) and figures (aOR forest plots, dose–response curves, interaction effects). The robustness of associations was assessed by calculating E-values for the main aORs to estimate potential sensitivity to unmeasured confounding. II. 10. 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. All methods were performed in accordance with the relevant guidelines and regulations, including the principles of the Declaration of Helsinki, Good Clinical Practice (GCP) standards, and the national ethical framework governing human health research in Cameroon. III. Results Characteristics of Study Participants In the study, 460 patients, including 199 (43,3%) cases and 261 (56,7%) controls, met the inclusion criteria as illustrated by the following diagram. ( Table 1 A ) The analysis of sociodemographic and biological characteristics revealed that hypertensive cases were significantly older than controls, with 92.5% aged 40 years or older compared to 78.5% among controls (p < 0.001). Sex distribution was similar between groups, with a predominance of females in both categories (p = 0.428). Neither marital status nor education level was significantly associated with hypertension (p = 0.135 and p = 0.128, respectively). In contrast, employment status showed a significant association (p = 0.037): cases were more frequently unemployed, while controls included a higher proportion of salaried individuals. The family history of hypertension was strongly associated with hypertensive status (p < 0.001), with a markedly higher frequency among cases. HIV stage at initiation did not differ significantly between the two groups (p = 0.091). Finally, body mass index was associated with hypertension (p = 0.024), with a higher proportion of obesity among cases, whereas normal weight was more frequently observed among controls. Table 1 A: Sociodemographic and Biological Characteristics of Participants by Hypertension Status Variable Category Cases n (%) Controls n (%) Total n (%) p-value Age < 40 15 (7.5) 56 (21.5) 71 (15.4) < 0.001 ≥ 40 184 (92.5) 205 (78.5) 389 (84.6) Gender Female 142 (71.4) 196 (75.1) 338 (73.5) 0.428 Male 57 (28.6) 65 (24.9) 122 (26.5) Marital status. Single 46 (23.1) 76 (29.1) 122 (26.5) 0.135 Cohabiting 20 (10.1) 38 (14.6) 58 (12.6) Divorced 4 (2.0) 9 (3.4) 13 (2.8) Married 86 (43.2) 94 (36.0) 180 (39.1) Widowed 43 (21.6) 44 (16.9) 87 (18.9) Education level None 14 (7.0) 9 (3.4) 23 (5.0) 0.128 Primary 64 (32.2) 69 (26.4) 133 (28.9) Secondary 102 (51.3) 153 (58.6) 255 (55.4) Tertiary 19 (9.5) 30 (11.5) 49 (10.7) Employment status Self-employed 55 (27.6) 82 (31.4) 137 (29.8) 0.037 Employed 32 (16.1) 65 (24.9) 97 (21.1) Unemployed 75 (37.7) 79 (30.3) 154 (33.5) Retired 37 (18.6) 35 (13.4) 72 (15.7) HIV stage at initiation Stage I 93 (46.7) 142 (54.4) 235 (51.1) 0.052 Stage II 81 (40.7) 78 (29.9) 159 (34.6) Stage III/IV 25 (12.6) 41 (15.7) 66 (14.3) BMI category (WHO) Obesity 55 (27.6) 51 (19.5) 106 (23.0) 0.024 Normal weight 68 (34.2) 120 (46.0) 188 (40.9) Overweight 76 (38.2) 90 (34.5) 166 (36.1) The (Table 1 B ) below, which presents the distribution of participants according to antiretroviral treatment (ART) characteristics by hypertension status, shows a significant association between ART duration and hypertension (p-value = 0.007). Among cases, 41.2% of individuals were aged 15 years and older, compared to only 28.7% among controls. The comparison of median durations supports this finding: the median duration of ART exposure was longer among cases (12.1 ± 5.5 years) than among controls (10.1 ± 6.1 years), indicating approximately two additional years of exposure among hypertensive patients. In contrast, this study did not identify any significant association between treatment lines and the categories of the most recent viral load results. Table 1 B : Characteristics Related to Antiretroviral Therapy (ART) by Hypertension Status Variable Category Cases n (%) Controls n (%) Total n (%) p-value Current treatment line 1st line 157 (78.9) 219 (83.9) 376 (81.7) 0.209 2nd/3rd line 42 (21.1) 42 (16.1) 84 (18.3) Latest viral load class High 20 (10.1) 30 (11.5) 50 (10.9) 0.194 Undetectable 150 (75.4) 207 (79.3) 357 (77.6) Suppressed 29 (14.6) 24 (9.2) 53 (11.5) Duration on ART < 15 years 117 (58.8) 186 (71.3) 303 (65.9) 0.007 ≥ 15 years 82 (41.2) 75 (28.7) 157 (34.1) Median duration (years, ±SD): Cases = 12.1 ± 5.5; Controls = 10.1 ± 6.1 Table 1 . C below shows that no dietary habit was significantly associated with hypertension. However, two variables showed a trend toward statistical significance. First, salt and seasoning cube intake (p = 0.054) revealed a counterintuitive result: a higher proportion of controls (63.6%) reported consuming salt and cubes in their daily diet compared to cases (54.3%). Second, the variable related to fruit and vegetable consumption also approached significance (p = 0.060). Table 1 C: Dietary Habits, Physical Activity, Tobacco and Alcohol Use by Hypertension Status Variable Category Cases n (%) Controls n (%) Total n (%) p-value Salt and seasoning cubes No 91 (45.7) 95 (36.4) 186 (40.4) 0.054 Yes 108 (54.3) 166 (63.6) 274 (59.6) Fruit and vegetable consumption Rarely 35 (17.6) 52 (20.2) 87 (19.0) 0.06 Weekly 101 (50.8) 141 (54.7) 242 (53.0) Biweekly 45 (22.6) 34 (13.2) 79 (17.3) Three times a week 18 (9.0) 31 (12.0) 49 (10.7) Physical activity Inactive 106 (53.5) 138 (53.3) 244 (53.4) 0.653 Low 41 (20.7) 51 (19.7) 92 (20.1) Monthly 12 (6.1) 9 (3.5) 21 (4.6) Adequate 16 (8.1) 25 (9.7) 41 (9.0) High / Optimal 23 (11.6) 36 (13.9) 59 (12.9) Tobacco use No 175 (87.9) 218 (83.5) 393 (85.4) 0.232 Yes 24 (12.1) 43 (16.5) 67 (14.6) Alcohol consumption None 60 (30.2) 78 (29.9) 138 (30.0) 0.997 Occasional 63 (31.7) 84 (32.2) 147 (32.0) Monthly 24 (12.1) 30 (11.5) 54 (11.7) Weekly / Daily 52 (26.1) 69 (26.4) 121 (26.3) Multivariable Analysis of Factors Associated with Hypertension Among PLHIV The results of the multivariable analysis (Table 2 ) highlight several statistically significant associations between certain clinical and behavioral characteristics and the presence of hypertension (HTN) among people living with HIV (PLHIV). These associations remain generally robust after adjustment for major confounding factors. Age : Participants under 40 years had a significantly lower adjusted odds ratio (aOR) compared to those aged 40 and above (aOR = 0.37; 95% CI: 0.19–0.69; p = 0.002), indicating an approximately 63% lower likelihood of having hypertension, all else being equal. This result is expected given the central role of age in cardiovascular risk and the vascular aging observed over time in PLHIV. Obesity : Compared to individuals with normal weight, obese participants had nearly twice the odds of hypertension (aOR = 1.96; 95% CI: 1.18–3.28; p = 0.010). This association supports the involvement of the metabolic phenotype in the pathophysiology of hypertension among PLHIV, through plausible mechanisms involving insulin resistance, low-grade inflammation, and neurohormonal activation. Fruit and vegetable consumption : Unexpectedly, several frequency categories were associated with lower odds of hypertension compared to the reference category “biweekly (2×/week)”: weekly (aOR = 0.46; 95% CI: 0.26–0.79; p = 0.005), rarely (aOR = 0.42; 95% CI: 0.22–0.81; p = 0.010), and three times a week (aOR = 0.40; 95% CI: 0.18–0.86; p = 0.021). Although statistically significant, these associations appear counterintuitive and may reflect misclassification bias (self-reporting), unmeasured residual confounding, or contextual differences in dietary practices. They warrant further analysis and, if necessary, verification of variable coding and reference category. Attenuated signals after adjustment : Some associations observed in the bivariate analysis did not persist clearly in the multivariable model. HIV stage II (vs. stage I) was associated with an increased crude risk (cOR = 1.59; 95% CI: 1.06–2.38; p = 0.026) but lost statistical significance after adjustment (aOR = 1.48; 95% CI: 0.96–2.28; p = 0.079). Similarly, ART duration ≥ 15 years (vs. <15 years) was associated with increased crude risk (cOR = 1.74; 95% CI: 1.18–2.57; p = 0.005), which attenuated to borderline significance in the adjusted model (aOR = 1.50; 95% CI: 0.99–2.30; p = 0.059). This attenuation suggests that the apparent relationship between prolonged ART exposure and hypertension may be partly explained by correlated factors such as age, BMI, or treatment regimen. In summary, these findings underscore the predominance of metabolic (e.g., obesity) and aging-related determinants in the development of hypertension among PLHIV, while also calling for caution in interpreting unexpected associations related to dietary behaviors. They support the need to systematically integrate hypertension screening and management into HIV care pathways, in line with public health approaches targeting non-communicable diseases (e.g., WHO HEARTS package). Given the case–control study design, the reported associations should not be interpreted as causal, but rather as indicators of intervention and operational research priorities. Table 2 Bivariate and Multivariate Analysis of Factors Associated with Hypertension among PLHIV Variables Categories Bivariate analysis Multivariable analysis cOR 95% CI p-value aOR 95% CI p-value Age category ≥ 40 — — — — < 40 0.30 0.16–0.53 < 0.001 0.37 0.19–0.69 0.002 Marital status Married — — Single 0.66 0.41–1.05 0.084 Cohabiting 0.58 0.31–1.05 0.078 Divorced 0.49 0.13–1.55 0.244 Widowed 1.07 0.64–1.78 0.801 Education level Secondary — — — — None 2.33 0.99–5.79 0.057 2.41 0.97–6.23 0.061 Primary 1.39 0.91–2.12 0.125 1.42 0.91–2.24 0.124 Higher 0.95 0.50–1.77 0.873 1.22 0.61–2.43 0.565 Occupational status Employed — — Self-employed 1.36 0.79–2.36 0.265 Unemployed 1.93 1.14–3.29 0.015 Retired 2.15 1.15–4.05 0.017 Initial HIV stage Stage I — — — — Stage II 1.59 1.06–2.38 0.026 1.48 0.96–2.28 0.079 Stage III/IV 0.93 0.53–1.62 0.803 0.99 0.54–1.78 0.968 BMI category Normal weight — — — — Overweight 1.49 0.97–2.29 0.067 1.45 0.92–2.29 0.107 Obesity 1.90 1.18–3.09 0.009 1.96 1.18–3.28 0.010 Viral load class Undetectable — — — — High 0.92 0.50–1.67 0.787 1.00 0.52–1.87 0.987 Suppressed 1.67 0.93–3.00 0.084 1.77 0.95–3.32 0.074 Duration on ART < 15 years — — — — ≥ 15 years 1.74 1.18–2.57 0.005 1.50 0.99–2.30 0.059 Salt/cube consumption No — — Yes 0.68 0.47–0.99 0.044 Fruit consumption Twice per week (ref) — — — — Once per week 0.54 0.32–0.90 0.019 0.46 0.26–0.79 0.005 Rarely 0.51 0.27–0.94 0.032 0.42 0.22–0.81 0.010 Three times per week 0.44 0.21–0.90 0.027 0.40 0.18–0.86 0.021 Assessment of Collinearity and Model Performance Table 3 presents the Generalized Variance Inflation Factor (GVIF) values for the variables included in the model. Since all values were below the critical threshold of 5, no concerning multicollinearity was detected, confirming the statistical independence of the covariates and the robustness of the model. Table 3 Generalized Variance Inflation Factor (GVIF) for Variables Included in the Model Term GVIF DF Adjusted GVIF Duration on ART category 1.08 1 1.04 Age category 1.07 1 1.03 Education level 1.12 3 1.02 Fruit and vegetable consumption 1.11 3 1.02 Viral load class 1.06 2 1.02 Initial HIV stage (merged) 1.05 2 1.01 BMI category 1.05 2 1.01 The ROC curve (Fig. 1 ) shows an Area Under the Curve (AUC) of 0.689 , indicating a moderate discriminative ability . Thus, the model correctly distinguishes about 69% of hypertension cases among PLHIV followed up at the Central Hospital of Yaoundé, demonstrating acceptable predictive performance for an epidemiological model. IV. Discussion Overview of main findings In this case–control study of 460 adults PLHIV receiving care at the Central Hospital of Yaounde, HTN clustered with older age and obesity, whereas the apparent association with longer ART exposure (≥ 15 years) attenuated after multivariable adjustment. Sociodemographic factors such as education and marital status were not independently associated with HTN. Several frequency categories of fruit and vegetable intake showed lower odds of HTN than the biweekly reference; given reliance on self-report and the pattern across categories, these findings should be interpreted cautiously. Model diagnostics indicated no concerning multicollinearity (all GVIF < 5) and a moderate discriminative performance (AUC‑ROC 0.689). Collectively, these results are consistent with the evolving cardiometabolic profile observed among aging PLHIV in sub‑Saharan Africa and support the integration of NCD prevention and control within HIV services[ 16 – 20 ]. Comparison with previous studies Our findings that age and adiposity are dominant correlates of HTN align with studies from sub‑Saharan Africa and beyond, which report higher HTN prevalence in older PLHIV and strong contributions from metabolic risk factors[ 2 , 21 – 24 ]. The borderline association between longer ART duration and HTN, significant in bivariate analysis but attenuated after adjustment, mirrors mixed evidence: in some cohorts, prolonged ART coincides with HTN via weight gain and metabolic shifts, while in others the effect diminishes after controlling for age and BMI[ 2 , 9 , 23 , 25 , 26 ]. This pattern suggests intertwined pathways (aging, weight trajectories, regimen composition) rather than a uniform pharmacologic effect of ART. Biological and pathophysiological interpretation The age and hypertension gradient likely reflects cumulative vascular aging and endothelial dysfunction, processes accentuated by chronic immune activation and low‑grade inflammation in treated HIV. The strong obesity and HTN association is biologically plausible via insulin resistance, adipokine imbalance, oxidative stress, and neurohormonal activation pathways described in PLHIV as survival improves and weight trajectories change[ 24 , 27 ]. Implications for clinical practice and public health These data argue for systematic HTN screening and management embedded in HIV care, aligned with WHO calls to close the global HTN treatment gap and to scale standardized primary‑care packages (HEARTS). Simplified treatment protocols, reliable antihypertensive supply, task sharing, and routine monitoring within HIV clinics can increase detection and control. Regional implementations show that team‑based care, treatment intensification algorithms, and data feedback loops improve blood‑pressure control at scale, approaches directly portable to HIV settings[ 16 , 28 ]. Model validity and interpretation Collinearity diagnostics revealed no problematic multicollinearity (all GVIF < 5), supporting coefficient stability[ 29 ]. The AUC‑ROC of 0.689 indicates moderate discrimination—better than chance yet improvable. Enhancements could include richer dietary quantification, biochemical markers (e.g., lipids, HbA1c), refined ART exposure metrics (e.g., cumulative class‑specific duration), and interaction testing (age × BMI, ART × BMI). Methodological references generally consider AUC values ≈ 0.60–0.70 as moderate and > 0.80 as strong for clinical decision‑making[ 30 – 32 ]. Strengths and limitations Strengths include a well‑defined case–control design, standardized BP measurement within an HIV care setting, and rigorous multivariable modeling with collinearity diagnostics. The sample reflects real‑world ART exposure patterns and provides locally relevant evidence for Cameroon, where HTN and HIV burdens intersect. Limitations include the observational design (no causal inference), potential recall and classification bias in self‑reported diet and lifestyle, and residual confounding (e.g., sodium quantification, lipid and renal parameters) that were unavailable or imperfectly captured. The single‑center context may constrain generalizability, and the model’s moderate AUC suggests that key predictors remain unmeasured or that the phenotype is inherently multifactorial. Research and programmatic perspectives Future research should prioritize prospective cohorts to delineate temporal relationships among ART exposure, weight trajectories, and HTN incidence; incorporate mechanistic biomarkers (endothelial, inflammatory, metabolic); and evaluate HEARTS‑aligned implementation strategies within HIV clinics, tracking BP control, treatment intensification, and patient‑reported outcomes. Cluster‑randomized or stepped‑wedge designs could quantify the impact of integrated HTN–HIV care on control rates and cardiovascular events, while economic evaluations can inform scaling in resource‑constrained settings[18,28,33]. 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 influ-enced the conduct of the study and write-up of this manuscript Funding This study was entirely self-funded by the family of Mr. Nang Nang Francis Duhamel. No external financial support was received. Author Contribution FDNN, APK, JPJ T, CK, SPC and AD designed the study. FDNN, JPJT, PJC, RMI, FAO and FDN contributed to the overall study conduct and data collection. FDNN, FAO and FTLB performed data analysis and illustration. FDNN, CK, SPC and APK drafted the manuscript. All coauthors had full access to the data, reviewed the final version of the manuscript, and accepted responsibility for submission for publication. Acknowledgement 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. et al. Hypertension among people living with human immunodeficiency virus in sub-Saharan Africa: a systematic review and meta-analysis. Sci. Rep. 14 , 16858. https://doi.org/10.1038/s41598-024-67703-5 (2024). Dzudie, A. et al. 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Opin. Infect. Dis. 33 (1), 10–19 (2020). Triant, V. A. Cardiovascular disease and HIV infection. Curr. HIV/AIDS Rep. 10 (3), 199–206 (2013). World Health Organization. HEARTS: Technical package for cardiovascular disease management in primary health care: Risk-based CVD management. Geneva: WHO. [cited 2025 Aug 12]. (2020). [Internet] Available from: https://www.who.int/publications/i/item/9789240001367 Fox, J. & Monette, G. Generalized collinearity diagnostics. J Am Stat Assoc [Internet]. [cited 2025 Oct 9];87(417):178 – 83. Available from: https://www.tandfonline.com/doi/abs/ (1992). 10.1080/01621459.1992.10475190 Hosmer, D. W., Lemeshow, S. & Sturdivant, R. X. Application of logistic regression with different sampling models. In: Applied Logistic Regression [Internet]. 3rd ed. Hoboken: John Wiley & Sons; [cited 2025 Oct 9]. pp. 227 – 42. Available from: https://onlinelibrary.wiley.com/doi/abs/ (2013). 10.1002/9781118548387.ch6 Mandrekar, J. N. Receiver operating characteristic curve in diagnostic test assessment. J. Thorac. Oncol. 5 (9), 1315–1316 (2010). Hajian-Tilaki, K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Casp. J. Intern. Med. 4 (2), 627–635 (2013). Additional Declarations No competing interests reported. Supplementary Files STROBEchecklistv4casecontrol.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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8","display":"","copyAsset":false,"role":"figure","size":9246,"visible":true,"origin":"","legend":"\u003cp\u003eAUC-ROC curve of the multivariate mode\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7821718/v1/6fcd0d91b75a9f24f8bf2790.png"},{"id":99315642,"identity":"0e2e57ac-8090-435f-951c-75f6f0503b22","added_by":"auto","created_at":"2025-12-31 16:27:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1578553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7821718/v1/af2472cd-a210-4009-8920-4861b61992ff.pdf"},{"id":95190105,"identity":"0b2976a2-ab2b-4678-ae59-eed07a990bf3","added_by":"auto","created_at":"2025-11-05 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Introduction","content":"\u003cp\u003eHIV has become a chronic disease thanks to antiretroviral therapy (ART). However, this success has shifted morbidity toward cardiometabolic comorbidities, foremost among them hypertension (HTN). In sub-Saharan Africa (SSA), recent syntheses estimate that about one in five people living with HIV (PLWH) have HTN, underscoring the magnitude of the problem in a region that bears most of the global HIV burden. This signal justifies systematically integrating blood pressure screening and control into routine HIV care for PLWH[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Cameroon, data from the CA-IeDEA network and a recent study conducted at Yaounde Central Hospital show that more than one quarter of PLWH in care sites had HTN, with gaps along the hypertension care cascade [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Other regional series (Fako, South-West) report a high incidence of HTN among individuals on ART, highlighting that HTN is not only prevalent but also emerges during follow-up despite virologic control. These findings anchor the issue in the Cameroonian reality and call for integrated HIV\u0026ndash;HTN models of care[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe association between HIV, ART, and HTN is ambivalent. On the one hand, ART reduces immune activation and may improve endothelial function; on the other hand, persistent residual inflammation, endothelial dysfunction, and metabolic alterations linked to certain classes (weight gain, dyslipidemia, insulin resistance) promote increases in blood pressure. This tension between virologic benefits and potential cardiometabolic effects places cumulative exposure duration (the \u0026ldquo;dose\u0026ndash;time\u0026rdquo; dimension) at the heart of HTN etiology in PLWH [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe urban exposome (high-salt diet, sedentary lifestyle, occupational stress, pollution) can amplify these effects. The rapid urbanization of Yaounde thus constitutes an interaction milieu in which weight and blood-pressure trajectories under ART may diverge from those in rural contexts, independent of virologic characteristics. This hypothesis aligns with prior Cameroonian results showing higher BP levels among individuals on ART than among ART-na\u0026iuml;ve persons, already in the non-INSTI era[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSince adoption of the \u0026ldquo;Treat All\u0026rdquo; principle (initiate ART regardless of CD4 count), SSA has shifted massively to integrase inhibitor (INSTI)\u0026ndash;based regimens, notably dolutegravir (DTG). Several observational analyses in Africa have reported weight gain and, in some settings, an increased risk of HTN after DTG initiation or switch, whereas other studies do not observe a uniform short-term rise in BP. This paradox (eight gain, blood pressure sometimes elevated, sometimes neutral) suggests that the class effect depends strongly on exposure duration, weight phenotype, and the care environment [\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAgainst this dual determinism (ART dose\u0026ndash;time and urban exposome) arises an operational question: when and in whom does ART duration become a multiplier of hypertension risk? Trials of integrated care (HIV\u0026ndash;HTN\u0026ndash;diabetes) in SSA show that these conditions can be treated simultaneously without compromising viral suppression and with gains in retention in care, but they do not provide fine-grained answers on the interactions among cumulative ART duration, drug classes, and HTN within urban clinics in Central Africa [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Cameroon, despite prevalence estimates and some incidence data, no recent analytic study has quantified, within an urban clinical setting, the interaction between prolonged ART exposure (in years) and HTN risk, while distinguishing therapeutic classes and controlling for key co-determinants (age, adiposity, behavioral factors). This gap limits the precision of prevention strategies and targets cardiometabolic monitoring within HIV services in large cities.\u003c/p\u003e\u003cp\u003eWe aim, using a case\u0026ndash;control study conducted in 2024 in an urban HIV clinic in Yaounde, to estimate the association between cumulative ART duration and HTN risk among PLWH, and to test interaction effects with therapeutic line HIV and HTN. We hypothesize that, for equal cumulative exposure, therapeutic line HIV, particularly those associated with weight gain, increase HTN risk, an effect amplified by the urban exposome [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e"},{"header":"II. Materials and Methods","content":"\u003cp\u003eII. 1. \u003cem\u003eStudy design and setting\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe conducted an unmatched case-control study at the Day Hospital (H\u0026ocirc;pital de Jour, HJ) of Yaounde Central Hospital (HCY), an urban HIV clinic in Yaounde, Cameroon. Enrollment and data collection occurred from 1 January to 31 Mars 2024, and reporting adheres to STROBE recommendations for case\u0026ndash;control studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] (\u003cb\u003eSupplementary Material 1\u003c/b\u003e). HCY is the largest secondary-level hospital in Cameroon (650 beds) with a dedicated infectious diseases unit and is accredited by the ANRS (National Agency for Research on AIDS and Viral Hepatitis). The site was selected because of the size and longevity of its cohort of people living with HIV (PLHIV): the Day Hospital follows approximately 12,000 patients, about 3,600 of whom are receiving antiretroviral therapy. We conducted an unmatched case-control study at the Day Hospital of Yaounde Central Hospital an urban HIV clinic in Yaounde, Cameroon.\u003c/p\u003e\n\u003ch3\u003eII. 2. Study population\u003c/h3\u003e\n\u003cp\u003eEligibility criteria. Adults (\u0026ge;\u0026thinsp;21 years) living with HIV (PLHIV), followed in the clinic for \u0026ge;\u0026thinsp;6 months, with complete information on blood pressure (BP), antiretroviral therapy (ART) history, and key covariates. Exclusion criteria. Pregnancy, hypertensive emergency at presentation, chronic dialysis, or non-imputable missing data on essential variables.\u003c/p\u003e\n\u003ch3\u003eII. 3. Case and control definitions\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eCases\u003c/b\u003e (hypertension). PLHIV meeting any of: (i) mean of the last two of three seated BP measurements\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg at the index visit; (ii) current antihypertensive therapy; (iii) prior clinician-documented hypertension in the medical record. \u003cb\u003eControls\u003c/b\u003e (non-hypertensive). PLHIV with no prior hypertension diagnosis, not on antihypertensives, and mean seated BP\u0026thinsp;\u0026lt;\u0026thinsp;140/90 mmHg at the index visit. Index date. The calendar date of the qualifying BP assessment. All exposures (e.g., cumulative ART duration) and time-varying covariates were computed up to the index date.\u003c/p\u003e\n\u003ch3\u003eII. 4. Sampling strategy\u003c/h3\u003e\n\u003cp\u003eWe enrolled consecutive eligible cases during routine visits. For each case, we randomly selected two controls (1:2 ratio) from eligible PLHIV seen within the same calendar week, using a computer-generated list to limit temporal confounding. We chose an unmatched design to avoid overmatching, preserve statistical power, and allow adjusted estimation for key factors (age, BMI, ART classes, etc.). No participant was enrolled more than once.\u003c/p\u003e\u003cp\u003eII. 5. \u003cem\u003eExposures and covariates\u003c/em\u003e\u003c/p\u003e\u003cp\u003e1. \u003cb\u003ePrimary exposure: long-term ART\u003c/b\u003e\u003c/p\u003e\u003cp\u003e- Cumulative ART duration (years, continuous) and categorized as \u0026lt;\u0026thinsp;15 and \u0026ge;\u0026thinsp;15 years.\u003c/p\u003e\u003cp\u003e- Therapeutic line categorized as First-line treatment (dolutegravir) and Second-line treatment.\u003c/p\u003e\u003cp\u003e2. \u003cb\u003ePriori covariates (potential confounders)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAge, sex, education, smoking (never/former/current), alcohol use (AUDIT-C\u0026thinsp;\u0026ge;\u0026thinsp;3 women/\u0026ge;4 men), physical activity (IPAQ-short: low/moderate/high), BMI and obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;), waist circumference (central obesity per WHO/IDF: \u0026ge;94 cm men, \u0026ge;\u0026thinsp;80 cm women), diabetes (fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL, HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% or medication), dyslipidemia (abnormal fasting lipids or treatment), chronic kidney disease (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/1.73 m\u0026sup2; using CKD-EPI 2021, race-free), family history of hypertension, self-reported high salt intake, time since HIV diagnosis, WHO stage at ART initiation, nadir and current CD4 count, viral load suppression (\u0026lt;\u0026thinsp;200 copies/mL), and concomitant medications affecting BP (systemic corticosteroids, NSAIDs, hormonal contraception).\u003c/p\u003e\n\u003ch3\u003eII. 6. Data sources and measurements\u003c/h3\u003e\n\u003cp\u003eData abstraction. Sociodemographic, clinical, HIV and pharmacy data were extracted from electronic medical records and pharmacy databases using a standardized case report form and harmonized SOPs. Abstractors were trained and certified in the SOPs. Blood pressure measurement. Validated automated oscillometric device (ISO 81060-2 compliant); appropriate cuff size; participant seated, arm supported at heart level; 5-minute rest; no caffeine/tobacco/exercise within 30 minutes. Three readings 1\u0026ndash;2 minutes apart; the mean of the last two classified BP. Devices were calibrated weekly.\u003c/p\u003e\u003cp\u003eAnthropometrics. Weight (calibrated scale), height (stadiometer) to compute BMI; waist circumference measured at the midpoint between the lower rib and iliac crest at end-expiration; two readings averaged. Laboratory assays. Fasting blood draws (glucose, lipid profile, creatinine) and HIV labs (CD4 count, viral load) within \u0026plusmn;\u0026thinsp;90 days of the index date, processed in a certified laboratory with external quality control. eGFR calculated using CKD-EPI 2021.\u003c/p\u003e\n\u003ch3\u003eII. 7. Sample size\u003c/h3\u003e\n\u003cp\u003eAssuming a 1:2 case: control ratio, two-sided α\u0026thinsp;=\u0026thinsp;0.05, 80% power, an expected odds ratio (OR)\u0026thinsp;=\u0026thinsp;1.8 for long-term ART (\u0026ge;\u0026thinsp;10 vs\u0026thinsp;\u0026lt;\u0026thinsp;10 years), and 30% exposure prevalence among controls, the Fleiss formula for unmatched case\u0026ndash;control studies yields\u0026thinsp;\u0026ge;\u0026thinsp;366 participants (122 cases, 244 controls). Allowing 10% incomplete data, the target sample was ~\u0026thinsp;406. All eligible patients during the study period were considered; the final analytic sample is reported in Results.\u003c/p\u003e\n\u003ch3\u003eII. 8. Quality assurance and bias minimization\u003c/h3\u003e\n\u003cp\u003eTo minimize potential biases, several methodological safeguards were implemented. Selection bias was addressed by sampling controls from the same source population and time window as the cases, using a random selection process. Measurement bias was mitigated using standardized blood pressure measurement protocols, comprehensive staff training and supervision, periodic re-audits of 10% of records, and regular calibration of measurement devices. To reduce information bias, key exposures such as antiretroviral therapy (ART) duration and adherence, along with clinical covariates, were extracted from traceable electronic sources, thereby limiting recall bias. Confounding was controlled using a pre-specified strategy based on a directed acyclic graph (DAG), complemented by multivariable adjustment, sensitivity analyses, and propensity score weighting.\u003c/p\u003e\n\u003ch3\u003eII. 9. Statistical analysis\u003c/h3\u003e\n\u003cp\u003eData was analyzed using IBM SPSS Statistics version 29 and R version 4.3.2 for advanced analyses.\u003c/p\u003e\u003cp\u003eA descriptive approach was first used to characterize the study population (cases vs. controls) using means and standard deviations for normally distributed continuous variables, medians and interquartile ranges (IQR) for skewed variables, and frequencies and percentages for categorical variables. Bivariate comparisons between cases and controls were performed using the student\u0026rsquo;s t-test or the Mann\u0026ndash;Whitney U test for continuous variables, and the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables. For the main analysis, an unmatched logistic regression model was used to identify factors associated with hypertension (HTN), defined as an average blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg or current antihypertensive treatment. The main exposure variable, duration of antiretroviral therapy (ART), was modeled as a continuous variable using restricted cubic splines (3 to 4 knots) to explore the non-linear dose\u0026ndash;response relationship between duration of exposure and HTN risk.\u003c/p\u003e\u003cp\u003eCovariates included in the multivariable model were selected based on a predefined causal diagram (DAG) and included: age, sex, body mass index (BMI), abdominal obesity, alcohol and tobacco use, physical activity, salt and cube intake, presence of diabetes, estimated glomerular filtration rate (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/1.73 m\u0026sup2;), viral suppression, and treatment line according to cumulative exposure duration. Adjusted odds ratios (aORs) and their 95% confidence intervals (95% CI) were calculated for each factor. Prespecified interactions (ART duration \u0026times; BMI, ART duration \u0026times; sex, ART duration \u0026times; treatment line) were tested, and predicted marginal effects were visualized as dose\u0026ndash;response curves. Sensitivity analyses included redefining HTN (\u0026ge;\u0026thinsp;130/80 mmHg), restricting the sample to patients with viral suppression, and excluding individuals on corticosteroids or non-steroidal anti-inflammatory drugs.\u003c/p\u003e\u003cp\u003eFinally, diagnostics for multicollinearity (Variance Inflation Factor), discrimination (AUC-ROC), and calibration (slope and interception, calibration curve) were performed. Multiple imputation using chained equations (MICE, m\u0026thinsp;=\u0026thinsp;20) was applied for variables with more than 5% missing data. Results were presented as comparative tables (crude and adjusted ORs) and figures (aOR forest plots, dose\u0026ndash;response curves, interaction effects). The robustness of associations was assessed by calculating E-values for the main aORs to estimate potential sensitivity to unmeasured confounding.\u003c/p\u003e\n\u003ch3\u003eII. 10. Ethics 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) N\u003csup\u003e0\u003c/sup\u003e:\u003cb\u003eCEN000633/CRERSHC/2023\u003c/b\u003e 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 (\u003cb\u003eN02023/265/AR/MINSANTE/SG/DHCY/UAF\u003c/b\u003e) on May 8, 2023, prior to the commencement of data collection. All methods were performed in accordance with the relevant guidelines and regulations, including the principles of the Declaration of Helsinki, Good Clinical Practice (GCP) standards, and the national ethical framework governing human health research in Cameroon.\u003c/p\u003e"},{"header":"III. Results","content":"\u003cp\u003e\u003cem\u003eCharacteristics of Study Participants\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn the study, 460 patients, including 199 (43,3%) cases and 261 (56,7%) controls, met the inclusion criteria as illustrated by the following diagram. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e The analysis of sociodemographic and biological characteristics revealed that hypertensive cases were significantly older than controls, with 92.5% aged 40 years or older compared to 78.5% among controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Sex distribution was similar between groups, with a predominance of females in both categories (p\u0026thinsp;=\u0026thinsp;0.428). Neither marital status nor education level was significantly associated with hypertension (p\u0026thinsp;=\u0026thinsp;0.135 and p\u0026thinsp;=\u0026thinsp;0.128, respectively). In contrast, employment status showed a significant association (p\u0026thinsp;=\u0026thinsp;0.037): cases were more frequently unemployed, while controls included a higher proportion of salaried individuals. The family history of hypertension was strongly associated with hypertensive status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a markedly higher frequency among cases. HIV stage at initiation did not differ significantly between the two groups (p\u0026thinsp;=\u0026thinsp;0.091). Finally, body mass index was associated with hypertension (p\u0026thinsp;=\u0026thinsp;0.024), with a higher proportion of obesity among cases, whereas normal weight was more frequently observed among controls.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eA: Sociodemographic and Biological Characteristics of Participants by Hypertension Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCases n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControls n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15 (7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56 (21.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e71 (15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e184 (92.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e205 (78.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e389 (84.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e142 (71.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e196 (75.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e338 (73.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.428\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57 (28.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e122 (26.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eMarital status.\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46 (23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e76 (29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e122 (26.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.135\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCohabiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38 (14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e58 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e86 (43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e94 (36.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e180 (39.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e87 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e23 (5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.128\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64 (32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69 (26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e133 (28.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102 (51.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e153 (58.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e255 (55.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e49 (10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55 (27.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e82 (31.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e137 (29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32 (16.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e97 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e75 (37.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79 (30.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e154 (33.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37 (18.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35 (13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e72 (15.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eHIV stage at initiation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e93 (46.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e142 (54.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e235 (51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.052\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e81 (40.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e78 (29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e159 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage III/IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41 (15.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e66 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eBMI category (WHO)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObesity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55 (27.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51 (19.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e106 (23.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68 (34.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e120 (46.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e188 (40.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76 (38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e90 (34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e166 (36.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e below, which presents the distribution of participants according to antiretroviral treatment (ART) characteristics by hypertension status, shows a significant association between ART duration and hypertension (p-value\u0026thinsp;=\u0026thinsp;0.007). Among cases, 41.2% of individuals were aged 15 years and older, compared to only 28.7% among controls. The comparison of median durations supports this finding: the median duration of ART exposure was longer among cases (12.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 years) than among controls (10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 years), indicating approximately two additional years of exposure among hypertensive patients. In contrast, this study did not identify any significant association between treatment lines and the categories of the most recent viral load results.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eB : Characteristics Related to Antiretroviral Therapy (ART) by Hypertension Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCases n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControls n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eCurrent treatment line\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1st line\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e157 (78.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e219 (83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e376 (81.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.209\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2nd/3rd line\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (16.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84 (18.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eLatest viral load class\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.194\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUndetectable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e150 (75.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e207 (79.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e357 (77.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (9.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDuration on ART\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e117 (58.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e186 (71.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e303 (65.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82 (41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75 (28.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e157 (34.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eMedian duration (years, \u0026plusmn;SD): Cases\u0026thinsp;=\u0026thinsp;12.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5; Controls\u0026thinsp;=\u0026thinsp;10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003cb\u003eC\u003c/b\u003e below shows that no dietary habit was significantly associated with hypertension. However, two variables showed a trend toward statistical significance. First, salt and seasoning cube intake (p\u0026thinsp;=\u0026thinsp;0.054) revealed a counterintuitive result: a higher proportion of controls (63.6%) reported consuming salt and cubes in their daily diet compared to cases (54.3%). Second, the variable related to fruit and vegetable consumption also approached significance (p\u0026thinsp;=\u0026thinsp;0.060).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eC: Dietary Habits, Physical Activity, Tobacco and Alcohol Use by Hypertension Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCases n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControls n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSalt and seasoning cubes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (45.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95 (36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e186 (40.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.054\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108 (54.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e166 (63.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e274 (59.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eFruit and vegetable consumption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (17.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87 (19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeekly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (50.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e141 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e242 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBiweekly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (13.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79 (17.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThree times a week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49 (10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInactive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106 (53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e138 (53.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e244 (53.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.653\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (20.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51 (19.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92 (20.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMonthly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21 (4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41 (9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh / Optimal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (13.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59 (12.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eTobacco use\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e175 (87.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e218 (83.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e393 (85.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.232\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67 (14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e138 (30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.997\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOccasional\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63 (31.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84 (32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e147 (32.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMonthly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeekly / Daily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69 (26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e121 (26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eMultivariable Analysis of Factors Associated with Hypertension Among PLHIV\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe results of the multivariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e highlight several statistically significant associations between certain clinical and behavioral characteristics and the presence of hypertension (HTN) among people living with HIV (PLHIV). These associations remain generally robust after adjustment for major confounding factors. \u003cb\u003eAge\u003c/b\u003e: Participants under 40 years had a significantly lower adjusted odds ratio (aOR) compared to those aged 40 and above (aOR\u0026thinsp;=\u0026thinsp;0.37; 95% CI: 0.19\u0026ndash;0.69; p\u0026thinsp;=\u0026thinsp;0.002), indicating an approximately 63% lower likelihood of having hypertension, all else being equal. This result is expected given the central role of age in cardiovascular risk and the vascular aging observed over time in PLHIV. \u003cb\u003eObesity\u003c/b\u003e: Compared to individuals with normal weight, obese participants had nearly twice the odds of hypertension (aOR\u0026thinsp;=\u0026thinsp;1.96; 95% CI: 1.18\u0026ndash;3.28; p\u0026thinsp;=\u0026thinsp;0.010). This association supports the involvement of the metabolic phenotype in the pathophysiology of hypertension among PLHIV, through plausible mechanisms involving insulin resistance, low-grade inflammation, and neurohormonal activation. \u003cb\u003eFruit and vegetable consumption\u003c/b\u003e: Unexpectedly, several frequency categories were associated with lower odds of hypertension compared to the reference category \u0026ldquo;biweekly (2\u0026times;/week)\u0026rdquo;: weekly (aOR\u0026thinsp;=\u0026thinsp;0.46; 95% CI: 0.26\u0026ndash;0.79; p\u0026thinsp;=\u0026thinsp;0.005), rarely (aOR\u0026thinsp;=\u0026thinsp;0.42; 95% CI: 0.22\u0026ndash;0.81; p\u0026thinsp;=\u0026thinsp;0.010), and three times a week (aOR\u0026thinsp;=\u0026thinsp;0.40; 95% CI: 0.18\u0026ndash;0.86; p\u0026thinsp;=\u0026thinsp;0.021). Although statistically significant, these associations appear counterintuitive and may reflect misclassification bias (self-reporting), unmeasured residual confounding, or contextual differences in dietary practices. They warrant further analysis and, if necessary, verification of variable coding and reference category. \u003cb\u003eAttenuated signals after adjustment\u003c/b\u003e: Some associations observed in the bivariate analysis did not persist clearly in the multivariable model. HIV stage II (vs. stage I) was associated with an increased crude risk (cOR\u0026thinsp;=\u0026thinsp;1.59; 95% CI: 1.06\u0026ndash;2.38; p\u0026thinsp;=\u0026thinsp;0.026) but lost statistical significance after adjustment (aOR\u0026thinsp;=\u0026thinsp;1.48; 95% CI: 0.96\u0026ndash;2.28; p\u0026thinsp;=\u0026thinsp;0.079). Similarly, ART duration\u0026thinsp;\u0026ge;\u0026thinsp;15 years (vs. \u0026lt;15 years) was associated with increased crude risk (cOR\u0026thinsp;=\u0026thinsp;1.74; 95% CI: 1.18\u0026ndash;2.57; p\u0026thinsp;=\u0026thinsp;0.005), which attenuated to borderline significance in the adjusted model (aOR\u0026thinsp;=\u0026thinsp;1.50; 95% CI: 0.99\u0026ndash;2.30; p\u0026thinsp;=\u0026thinsp;0.059). This attenuation suggests that the apparent relationship between prolonged ART exposure and hypertension may be partly explained by correlated factors such as age, BMI, or treatment regimen. In summary, these findings underscore the predominance of metabolic (e.g., obesity) and aging-related determinants in the development of hypertension among PLHIV, while also calling for caution in interpreting unexpected associations related to dietary behaviors. They support the need to systematically integrate hypertension screening and management into HIV care pathways, in line with public health approaches targeting non-communicable diseases (e.g., WHO HEARTS package). Given the case\u0026ndash;control study design, the reported associations should not be interpreted as causal, but rather as indicators of intervention and operational research priorities.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBivariate and Multivariate Analysis of Factors Associated with Hypertension among PLHIV\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eBivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eMultivariable analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eaOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge category\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.16\u0026ndash;0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.19\u0026ndash;0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.41\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCohabiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.31\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.13\u0026ndash;1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.64\u0026ndash;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.99\u0026ndash;5.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.97\u0026ndash;6.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u0026ndash;2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.91\u0026ndash;2.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.124\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.50\u0026ndash;1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.61\u0026ndash;2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOccupational status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.79\u0026ndash;2.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14\u0026ndash;3.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.15\u0026ndash;4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInitial HIV stage\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06\u0026ndash;2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.96\u0026ndash;2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage III/IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.53\u0026ndash;1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.803\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.54\u0026ndash;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.968\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI category\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97\u0026ndash;2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.92\u0026ndash;2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObesity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.18\u0026ndash;3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.18\u0026ndash;3.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eViral load class\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUndetectable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.50\u0026ndash;1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.52\u0026ndash;1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u0026ndash;3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.95\u0026ndash;3.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration on ART\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.18\u0026ndash;2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.99\u0026ndash;2.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSalt/cube consumption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.47\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFruit consumption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTwice per week (ref)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOnce per week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.32\u0026ndash;0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.26\u0026ndash;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.27\u0026ndash;0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.22\u0026ndash;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThree times per week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21\u0026ndash;0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.18\u0026ndash;0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eAssessment of Collinearity and Model Performance\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the \u003cem\u003eGeneralized Variance Inflation Factor\u003c/em\u003e (GVIF) values for the variables included in the model. Since all values were below the critical threshold of 5, \u003cb\u003eno concerning multicollinearity\u003c/b\u003e was detected, confirming the statistical independence of the covariates and the robustness of the model.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneralized Variance Inflation Factor (GVIF) for Variables Included in the Model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTerm\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGVIF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdjusted GVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration on ART category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit and vegetable consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViral load class\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial HIV stage (merged)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe \u003cb\u003eROC curve\u003c/b\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) shows an \u003cem\u003eArea Under the Curve\u003c/em\u003e (AUC) of \u003cb\u003e0.689\u003c/b\u003e, indicating a \u003cb\u003emoderate discriminative ability\u003c/b\u003e. Thus, the model correctly distinguishes about \u003cb\u003e69% of hypertension cases\u003c/b\u003e among PLHIV followed up at the Central Hospital of Yaound\u0026eacute;, demonstrating acceptable predictive performance for an epidemiological model.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"IV. Discussion","content":"\u003cp\u003e\u003cem\u003eOverview of main findings\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn this case\u0026ndash;control study of 460 adults PLHIV receiving care at the Central Hospital of Yaounde, HTN clustered with older age and obesity, whereas the apparent association with longer ART exposure (\u0026ge;\u0026thinsp;15 years) attenuated after multivariable adjustment. Sociodemographic factors such as education and marital status were not independently associated with HTN. Several frequency categories of fruit and vegetable intake showed lower odds of HTN than the biweekly reference; given reliance on self-report and the pattern across categories, these findings should be interpreted cautiously. Model diagnostics indicated no concerning multicollinearity (all GVIF\u0026thinsp;\u0026lt;\u0026thinsp;5) and a moderate discriminative performance (AUC‑ROC 0.689). Collectively, these results are consistent with the evolving cardiometabolic profile observed among aging PLHIV in sub‑Saharan Africa and support the integration of NCD prevention and control within HIV services[\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eComparison with previous studies\u003c/em\u003e\u003c/p\u003e\u003cp\u003eOur findings that age and adiposity are dominant correlates of HTN align with studies from sub‑Saharan Africa and beyond, which report higher HTN prevalence in older PLHIV and strong contributions from metabolic risk factors[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The borderline association between longer ART duration and HTN, significant in bivariate analysis but attenuated after adjustment, mirrors mixed evidence: in some cohorts, prolonged ART coincides with HTN via weight gain and metabolic shifts, while in others the effect diminishes after controlling for age and BMI[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This pattern suggests intertwined pathways (aging, weight trajectories, regimen composition) rather than a uniform pharmacologic effect of ART.\u003c/p\u003e\u003cp\u003e\u003cem\u003eBiological and pathophysiological interpretation\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe age and hypertension gradient likely reflects cumulative vascular aging and endothelial dysfunction, processes accentuated by chronic immune activation and low‑grade inflammation in treated HIV. The strong obesity and HTN association is biologically plausible via insulin resistance, adipokine imbalance, oxidative stress, and neurohormonal activation pathways described in PLHIV as survival improves and weight trajectories change[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eImplications for clinical practice and public health\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThese data argue for systematic HTN screening and management embedded in HIV care, aligned with WHO calls to close the global HTN treatment gap and to scale standardized primary‑care packages (HEARTS). Simplified treatment protocols, reliable antihypertensive supply, task sharing, and routine monitoring within HIV clinics can increase detection and control. Regional implementations show that team‑based care, treatment intensification algorithms, and data feedback loops improve blood‑pressure control at scale, approaches directly portable to HIV settings[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eModel validity and interpretation\u003c/em\u003e\u003c/p\u003e\u003cp\u003eCollinearity diagnostics revealed no problematic multicollinearity (all GVIF\u0026thinsp;\u0026lt;\u0026thinsp;5), supporting coefficient stability[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The AUC‑ROC of 0.689 indicates moderate discrimination\u0026mdash;better than chance yet improvable. Enhancements could include richer dietary quantification, biochemical markers (e.g., lipids, HbA1c), refined ART exposure metrics (e.g., cumulative class‑specific duration), and interaction testing (age \u0026times; BMI, ART \u0026times; BMI). Methodological references generally consider AUC values\u0026thinsp;\u0026asymp;\u0026thinsp;0.60\u0026ndash;0.70 as moderate and \u0026gt;\u0026thinsp;0.80 as strong for clinical decision‑making[\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eStrengths and limitations\u003c/em\u003e\u003c/p\u003e\u003cp\u003eStrengths include a well‑defined case\u0026ndash;control design, standardized BP measurement within an HIV care setting, and rigorous multivariable modeling with collinearity diagnostics. The sample reflects real‑world ART exposure patterns and provides locally relevant evidence for Cameroon, where HTN and HIV burdens intersect. Limitations include the observational design (no causal inference), potential recall and classification bias in self‑reported diet and lifestyle, and residual confounding (e.g., sodium quantification, lipid and renal parameters) that were unavailable or imperfectly captured. The single‑center context may constrain generalizability, and the model\u0026rsquo;s moderate AUC suggests that key predictors remain unmeasured or that the phenotype is inherently multifactorial.\u003c/p\u003e\u003cp\u003e\u003cem\u003eResearch and programmatic perspectives\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFuture research should prioritize prospective cohorts to delineate temporal relationships among ART exposure, weight trajectories, and HTN incidence; incorporate mechanistic biomarkers (endothelial, inflammatory, metabolic); and evaluate HEARTS‑aligned implementation strategies within HIV clinics, tracking BP control, treatment intensification, and patient‑reported outcomes. Cluster‑randomized or stepped‑wedge designs could quantify the impact of integrated HTN\u0026ndash;HIV care on control rates and cardiovascular events, while economic evaluations can inform scaling in resource‑constrained settings[18,28,33].\u003c/p\u003e"},{"header":"V. Conclusion","content":"\u003cp\u003eAmong PLHIV in routine care in Yaound\u0026eacute;, 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 influ-enced the conduct of the study and write-up of this manuscript\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study was entirely self-funded by the family of Mr. Nang Nang Francis Duhamel. No external financial support was received.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFDNN, APK, JPJ T, CK, SPC and AD designed the study. FDNN, JPJT, PJC, RMI, FAO and FDN contributed to the overall study conduct and data collection. FDNN, FAO and FTLB performed data analysis and illustration. FDNN, CK, SPC and APK drafted the manuscript. All coauthors had full access to the data, reviewed the final version of the manuscript, and accepted responsibility for submission for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgement\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. et al. Hypertension among people living with human immunodeficiency virus in sub-Saharan Africa: a systematic review and meta-analysis. \u003cem\u003eSci. 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Med.\u003c/em\u003e \u003cb\u003e4\u003c/b\u003e (2), 627\u0026ndash;635 (2013).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Long-term antiretroviral therapy, hypertension, HIV, case-control study, Cameroon","lastPublishedDoi":"10.21203/rs.3.rs-7821718/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7821718/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSurvival gains under ART have shifted morbidity among PLHIV toward non-communicable diseases, with HTN emerging in sub-Saharan Africa. In Cameroon, evidence from routine HIV care is limited and integration of HTN services is uneven. We aimed to identify factors associated with HTN among PLHIV in Yaounde to inform standardized HTN care within HIV services.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a case-control study at the Central Hospital of Yaound\u0026eacute; (n\u0026thinsp;=\u0026thinsp;460; 199 HTN cases, 261 controls). Cases were defined as SBP/DBP\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg or current antihypertensive therapy; controls had BP\u0026thinsp;\u0026lt;\u0026thinsp;140/90 mmHg without therapy. We collected sociodemographic, clinical, antiretroviral therapy (ART), viral-load, and lifestyle data. Group differences used standard statistical tests. Multivariable logistic regression and adjusted a priori for age, sex, BMI, ART duration, HIV stage at initiation, viral-load class, and lifestyle factors estimated adjusted odds ratios (aOR, 95% CI). Collinearity was assessed via GVIF (cutoff\u0026thinsp;=\u0026thinsp;5) and model discrimination by ROC/AUC. Two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denoted significance; reporting followed STROBE.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 460 PLHIV, hypertensive cases were older (\u0026ge;\u0026thinsp;40 y: 92.5% vs 78.5%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and more often obese (27.6% vs 19.5%; p\u0026thinsp;=\u0026thinsp;0.024). Family history of HTN was more frequent in cases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and employment differed (unemployed/retired more common among cases; p\u0026thinsp;=\u0026thinsp;0.037). Sex, marital status, education, HIV stage at initiation, treatment line, and recent viral-load class were not associated (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In adjusted models, age\u0026thinsp;\u0026lt;\u0026thinsp;40 y was inversely associated with HTN (aOR 0.37; 95% CI 0.19\u0026ndash;0.69; p\u0026thinsp;=\u0026thinsp;0.002), while obesity increased odds (aOR 1.96; 95% CI 1.18\u0026ndash;3.28; p\u0026thinsp;=\u0026thinsp;0.010). Longer ART exposure (\u0026ge;\u0026thinsp;15 y) showed borderline evidence (aOR 1.50; 95% CI 0.99\u0026ndash;2.30; p\u0026thinsp;=\u0026thinsp;0.059). No dietary variable retained significance; lower odds across some fruit/vegetable frequencies versus the biweekly reference likely reflect measurement or residual confounding. Diagnostics indicated no concerning multicollinearity (all GVIF\u0026thinsp;\u0026lt;\u0026thinsp;5) and moderate discrimination (AUC 0.689).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn routine HIV care in Yaound\u0026eacute;, HTN clustered with aging and adiposity, while the apparent effect of long ART exposure attenuated after adjustment. Findings support embedding standardized HTN screening and management and including weight management and lifestyle counseling within HIV services (WHO HEARTS) and encourage prospective studies to test integrated models and clarify causal pathways.\u003c/p\u003e","manuscriptTitle":"Interactions between long-term Antiretroviral Therapy and Risk of Hypertension among People Living with HIV in an Urban HIV Clinic in Cameroon, 2024: A Case-control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 10:07:54","doi":"10.21203/rs.3.rs-7821718/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ad56f7c6-c3db-4d3d-8721-222f64032497","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57268473,"name":"Health sciences/Cardiology"},{"id":57268474,"name":"Health sciences/Diseases"},{"id":57268475,"name":"Health sciences/Health care"},{"id":57268476,"name":"Health sciences/Medical research"},{"id":57268477,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-12-29T18:23:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-05 10:07:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7821718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7821718","identity":"rs-7821718","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}