An assessment of ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria

An assessment of ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An assessment of ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria Oyenike Oyeronke Ekekezie, Mayowa Omolabake Odofin, Foluke Adenike Olatona This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8875532/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Globally, antiretroviral therapy (ART) has saved millions of lives, enabling people living with HIV (PLHIV) lead longer and more productive lives, though they become more susceptible to non-communicable diseases (NCDs) later in life. However, despite therapeutic effectiveness, ART regimens have long been associated with metabolic complications. This study aims to assess ART-related factors as predictors of NCDs among adult patients on antiretroviral therapy attending tertiary health facilities in Lagos. Methods A descriptive cross-sectional study was conducted among 416 adult PLHIV attending two tertiary hospitals, using a multistage sampling method. Data was obtained using a pre-tested structured questionnaire adapted from the World Health Organization (WHO) STEPS Instrument, in addition to anthropometric and biomedical measurements. Descriptive, bivariate and multivariate analyses were carried out using IBM SPSS version 27. Results The mean age group of respondents was 49.13 ± 10.18years. Majority, 70.2% (n = 292) were female, and 54.1% (n = 225) married. The prevalence of obesity, hypertension, and diabetes was 37.3% (n = 155), 52.6% (n = 219), and 7.2% (n = 30) respectively; and over 70% of the respondents had at least one NCD. ART regimen was a predictor of obesity: patients on second-line ART regimen had 58.1% lower odds of obesity, compared with those on first-line regimen (aOR = 0.419, 95% CI: 0.219–0.801, P = 0.008). Hypertension was more prevalent among the patients on first-line ART regimen (54.6%%, χ²=3.287, P = 0.070), though not statistically significant. Conclusion This study suggests that ART regimen is a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. The identification of ART regimen type as a modifiable predictor of obesity among PLHIV has direct programmatic implications for the adoption of an integrated care model that addresses the dual epidemic of HIV and NCDs, especially in resource-poor countries. HIV antiretroviral therapy ART regimen first-line regimen non-communicable disease obesity hypertension diabetes mellitus Introduction Globally antiretroviral therapy (ART) has saved millions of lives, with a decline of 58% in deaths from AIDS-related causes from 2001 to 2020. 1 , 2 This has enabled people living with HIV (PLHIV) to lead longer and more productive lives, though they become more susceptible to NCDs later in life due to an interplay of aging, ART-related factors, and lifestyle. 3 , 4 , 5 , 6 Despite the progress made in treatment and prevention, HIV infection remains a significant public health problem, with 40.8 million people living with HIV globally as at the end of 2024, and 1.9 million people living with the virus in Nigeria, as of 2025. 2 , 7 The availability of improved ART treatment options has turned HIV into a manageable chronic condition, with marked improvement in survival and quality of life. 8 , 9 Key indicators of favorable long-term outcomes for patients on ART include optimal HIV viral suppression and immune system restoration. 10 However, despite therapeutic effectiveness, ART regimens have long been associated with metabolic complications like dyslipidaemia, insulin resistance, weight gain and bone demineralization. Generally, metabolic syndrome (MS) refers to a group of metabolic abnormalities, which includes three or more these criteria: abdominal obesity, high blood pressure, increased fasting glucose, increased triglycerides, and decreased high-density lipoproteins (HDLs). MS is associated with insulin resistance, proinflammatory and prothrombotic states; which increase cardiovascular disease (CVD) risk. 11 The resulting NCDs reduce quality of life; and increase mortality among PLHIV, eroding the gains of ART. 12 Muhammad et al. found in Northwest Nigeria that the prevalence of MS in patients receiving ART was 19.3% compared to 5.3% in ART-naive patients; with insulin resistance in 79.3% of the ART-exposed patients compared to the 25.0% ART-naive group. 13 Similarly, in a study among Tanzanian adults, glucose metabolism disorders were more prevalent among ART-exposed patients (32.7%) compared to ART-naive (8.0%) and control groups (7.2%); diabetes and impaired glucose tolerance were also more common in patients receiving ART. 14 Clinical and laboratory evidence have shown that ART can induce adverse metabolic complications, characterized by lipodystrophy, dyslipidemia, insulin resistance, central adiposity, increased risk of cardiovascular disease and atherosclerosis. 15 , 16 The dyslipidemia is characterized by hypercholesterolemia, hypertriglyceridemia, and decreased serum HDL, with or without increased serum LDL. 17 The older ART regimen are associated with higher metabolic toxicity, but are still used in resource-limited countries due to cost effectiveness. 18 Nucleoside reverse transcriptase inhibitors NRTIs (abacavir, lamivudine, zidovudine, emtricitabine, tenofovir), non-nucleoside reverse transcriptase inhibitors NNRTIs (nevirapine, efavirenz), and protease inhibitors PIs (lopinavir, ritonavir, atazanavir) are commonly recommended in the first-line regimens. 19 The lipid abnormalities associated with use of PIs are severe and more common than other classes of ARTs, sometimes resulting in discontinuation. 20 , 21 However, NNRTIs and NRTIs are reported to cause modest changes. 17,21,22 A cycle of events invariably ensues: the NCDs that result from ART metabolic toxicity complicates HIV disease management by affecting adherence to ART, and increasing the risk of drug-drug interactions. 3 , 4 , 5 , 23 In turn, poor ART adherence leads to suboptimal and slow immune recovery, characterised by low CD4 cell counts, and non-suppression of HIV viral load, increasing the NCD risk factors. 24 – 27 With the paradoxical intricacies surrounding ART in PLWHA, an assessment of ART-related factors as predictors of NCDs among adult patients on antiretroviral therapy attending tertiary health facilities in Lagos state will enable the prompt deployment of preventive measures, early detection and early onset of treatment of NCDs in this population. This is consistent with the integration of health services being canvassed to tackle the double disease burden of HIV-NCD, which will improve the overall well-being of the patients, by reducing morbidity and mortality rates, and decreasing HIV transmission within the community. Identification of these predictors will also help stakeholders make informed decisions in developing targeted interventions to address the dual disease burden. Despite the growing burden of NCDs, particularly in LMICs, studies on the predictors for NCDs among PLHIV remain limited. This gap is hindering the development of effective and efficient evidence-based strategies, targeted interventions, and policies for integrating HIV and NCD care and services, which is crucial for managing the dual disease burden, and improving health outcomes for this vulnerable population. 28 , 29 Lagos State, despite its relatively low HIV prevalence of 1.4% remains a priority area for the study due to its dense population, high internal migration, and complex socioeconomic structure, which collectively pose ongoing challenges for HIV prevention and care. 30 Methods Study design and setting This cross-sectional study was carried out between June and July 2025 in the Antiretroviral clinics of the departments of Haematology and Blood Transfusion of the Lagos University Teaching Hospital (LUTH), Idi Araba, and, the Lagos State University Teaching Hospital (LASUTH), Ikeja. These clinics were commissioned in 2004, to cater to children, adolescents, adults, pregnant women, both citizens and foreign nationals infected with HIV, under the auspices of the US President’s Emergency Plan for AIDS Relief (PEPFAR) program, with the Centre for Integrated Health Programs (CIHP) as the implementing partner in Nigeria. 31 , 32 , 33 Study Population : These consisted of HIV-positive patients attending ART clinics in LUTH and LASUTH, aged 18 years and above, and having documented HIV-positive results: either newly diagnosed ART-naïve or ART experienced. Those less than 18 years of age, with severe illness requiring urgent care, accessing care for pre- or post-exposure prophylaxis, and pregnant women (to avoid confounding metabolic changes) were excluded from the study. Sample size determination The minimum sample size (n) was determined using Cochran’s formula n=z 2 pq/d 2 . Z at 95% confidence level is 1.96; d is the margin of error at 5% (0.05), and p was the prevalence of obesity among PLHIV from a previous study in Nigeria (38.4%). 34 Accordingly, n = 363; with 10% contingency, the minimum sample size was 400. Four hundred and sixteen (416) eligible patients were recruited from the clinics within the two-month study period. Sampling technique A multistage sampling technique was used. Stage 1 was the purposive selection of the two tertiary hospitals in Lagos state, because they serve as the major ART treatment centers. The total number of eligible patients currently receiving ART at both facilities was the sampling frame. This served as the pool from which study participants were selected. Facility 1 (LUTH) 5,895 + Facility 2 (LASUTH) 5,526 = 11,421 patients. Stage 2 involved proportional allocation of the minimum sample size (400) across the two facilities. Facility 1 (LUTH) 206 + Facility 2 (LASUTH) 194 = 400 patients. Systematic random sampling was used in stage 3 to select the participants from each facility. The sampling interval (k) was determined by dividing the total population in the facility by the sample size desired from each facility. Facility 1 (LUTH) k = 5,895 / 206 = 29. Facility 2 (LASUTH) k = 5,526 / 194 = 29. A random number between 1 and the calculated interval of 29 was chosen by simple random sampling (balloting), to serve as the starting point, which was 10. Every tenth patient was recruited until the sample size was reached, excluding those that declined consent. Data collection : This was carried out on week days at the ART clinics. A recruitment schedule using simple random sampling (balloting) facilitated allocation of days for recruitment to the 2 facilities. A structured interviewer-administered questionnaire adapted from the WHO STEPS Instrument, a question-by-question guide approach to noncommunicable disease risk factor surveillance was used. 35 The electronic medical record database, Nigeria Medical Record System (NMRS) was also reviewed to confirm baseline patient information and comorbidities. The questionnaire had sections for socio-demographic information, NCD disease status, anthropometric and biomedical measurements. The study was introduced to the participants and their consent sought, while waiting to be seen by the physicians. A secluded area within the facility was used for face-to-face interview, followed by taking of measurements. Data was collected using Kobo Toolbox app on smartphones: an open-source platform for collecting, managing, and visualizing data. 36 Five ART nurses and two ART case managers were trained for two days on the study objectives, informed consent, the data collection process, and confidentiality. The questionnaire was pre-tested among twenty-nine patients attending the ART clinic at the General hospital Mushin, a secondary health facility. Study variables Independent variables: ART-related variables (viral load suppression, ART regimen, and ART duration) and sociodemographic variables (age-group, sex, level of education and income). Dependent variables: The presence or absence of obesity, hypertension, and diabetes. Data Analysis Data entered using the Kobo toolbox software was exported to IBM SPSS version 27 by IBM Corporation, Armonk, New York, United States. Descriptive analysis, such as frequencies, charts, and percentages were used to analyze socio-demographic data, prevalence of NCDs and ART-related factors. Bivariate analysis using Chi square test was used to test for significant relationships between variables. Thereafter, variables that had a P-value of < 0.2 were entered into the multivariate logistic regression model to determine the predictors of NCDs. 37 The results were presented using adjusted odds ratio and 95% confidence interval. A P-value of < 0.05 determined the level of statistical significance. Results The mean age group of respondents was 49.13 ± 10.18years. Majority, 70.2% (n = 292) were female, 54.1% (n = 225) married, and 81.5% (n = 339) Christian. Most, 48% (n = 200) attained secondary education, 64% (n = 266) were self-employed, and majority, 44.2% (n = 184) earned less than N50,000 monthly (low-income). The prevalence of obesity, hypertension, and diabetes was 37.3% (n = 155), 52.6% (n = 219), and 7.2% (n = 30) respectively; and over 70% of the respondents had at least one NCD. Viral load results were available for 407 of the 416 respondents. Of these 363 (89.2%) and 44 (10.8%) were virally suppressed (viral load < 1000 copies/mL), and not suppressed (≥ 1000copies/mL) respectively; 350 (84.1%) and 66 (15.9%) were on a first- and second-line ART regimen respectively; while 68 (16.3%), 104 (25%), and 244 (58.7) were on ART regimen for 10 years respectively. Table 1 Association between socio-demographic, ART-related factors and Obesity (n = 416) Variable Category Yes (%) No (%) Total n (%) χ² P value Age group 18–27 2 (12.5) 14 (87.5) 16 (100) 4.880 0.3 28–37 8 (33.3) 16 (66.7) 24 (100) 38–47 55 (39.6) 84 (60.4) 139 (100) 48–57 61 (38.9) 96 (61.1) 157 (100) 58–67 29 (36.3) 51 (63.7) 80 (100) Sex Female 110 (37.7) 182 (62.3) 292 (100) 0.070 0.79 Male 45 (36.3) 79 (63.7) 124 (100) Income Low 58 (31.5) 126 (68.5) 184 (100) 11.100 0.004 a Middle 35 (33.0) 71 (67.0) 106 (100) High 62 (49.2) 64 (50.8) 126 (100) Education None 16 (50.0) 16 (50.0) 32 (100) 4.21 0.379 Vocational 5 (50.0) 5 (50.0) 10 (100) Primary 16 (30.2) 37 (69.8) 53 (100) Secondary 75 (37.5) 125 (62.5) 200 (100) Tertiary 43 (35.5) 78 (64.5) 121 (100) Viral load status Suppressed 136 (37.5) 227 (62.5) 363 (100) b 0.192 0.662 Not suppressed 15 (34.1) 29 (65.9) 44 (100) b ART Regimen First-line 141 (40.3) 209 (59.7) 350 (100) 8.642 0.003 a Second-line 14 (21.2) 52 (78.8) 66 (100) ART Duration > 5 years 26 (38.2) 42 (61.8) 68 (100) 3.288 0.193 5–10 years 46 (44.2) 58 (55.8) 104 (100) > 10 years 83 (34.0) 161 (66.0) 244 (100) a Significant b Viral load results (n = 407) Obesity was significantly more prevalent among patients on first-line ART regimen (40.3%, χ2 = 8.642, p = 0.003), and the high-income earners (49.2%, χ²=11.100, p = 0.004). More virally suppressed patients, and those on ART therapy for 5–10 years were obese, though association was not significant (37.5%, χ2 = 0.192, p = 0.662) and (44.2%, χ2 = 3.288, p = 0.193) respectively. (Table 1 ). Table 2 Association between socio-demographic, ART-related factors and Hypertension (n = 416) Variable Category Yes (%) No (%) Total n (%) χ² P value Age group 18–27 4 (25.0) 12 (75.0) 16 (100) 18.438 0.001 a 28–37 9 (37.5) 15 (62.5) 24 (100) 38–47 62 (44.6) 77 (55.4) 139(100) 48–57 91 (58.0) 66 (42.0) 157(100) 58–67 53 (66.3) 27 (33.7) 80 (100) Sex Female 152 (52.1) 140 (47.9) 292(100) 0.14 0.712 Male 67 (54.0) 57 (46.0) 124(100) Income Low 100 (54.3) 84 (45.7) 126(100) 0.57 0.752 Middle 56 (52.8) 50 (47.2) 106(100) High 63 (50.0) 63 (50.0) 184(100) Education None 20 (62.5) 12 (37.5) 32 (100) 5.36 0.253 Vocational 7 (70.0) 3 (30.0) 10 (100) Primary 30 (56.6) 23 (43.4) 53 (100) Secondary 107 (53.5) 93 (46.5) 200(100) Tertiary 55 (45.5) 66 (54.5) 121(100) Viral load status Suppressed 195 (53.7) 168 (46.3) 363 (100) b 1.748 0.186 Not suppressed 19 (43.2) 25 (56.8) 44 (100) b ART Regimen First-line 191 (54.6) 159 (45.4) 350 (100) 3.287 0.070 Second-line 28 (42.4) 38 (57.6) 66 (100) ART Duration > 5 years 32 (47.1) 36 (52.9) 68 (100) 2.922 0.232 5–10 years 50 (48.1) 54 (51.9) 104 (100) > 10 years 137 (56.1) 107 (43.9) 244 (100) a Significant b Viral load results (n = 407) The prevalence of hypertension showed a significant upward trend with age, highest among the 58–67-year age group (66.3%, χ²=18.438, P = 0.001). More virally suppressed patients (53.7%, χ²=1.748, P = 0.186), on first-line regimen (54.6%%, χ²=3.287, P = 0.070), and on ART therapy for more than 10 years (56.1%, χ²=2.922, P = 0.232) had hypertension, though association was not significant. (Table 2 ). Table 3 Association between socio-demographic, ART-related factors and Diabetes Mellitus (n = 416) Variable Category Yes (%) No (%) Total n (%) χ² P value Age group 18–27 0 (0.0) 16 (100.0) 16 (100) 0.135 0.102 a 28–37 2 (8.3) 22 (91.7) 24 (100) 38–47 5 (3.6) 134 (96.4) 139 (100) 48–57 13 (8.3) 144 (91.7) 157 (100) 58–67 10 (12.5) 70 (87.5) 80 (100) Sex Female 22 (7.5) 270 (92.5) 292 (100) 0.019 0.837 Male 8 (6.5) 116 (93.5) 124 (100) Income Low 13 (7.1) 171 (92.9) 184 (100) 0.031 0.835 Middle 9 (8.5) 97 (91.5) 106 (100) High 8 (6.3) 118 (93.7) 126 (100) Education None 2 (6.3) 30 (93.7) 32 (100) 0.039 0.864 a Vocational 1 (10.0) 9 (90.0) 10 (100) Primary 5 (9.4) 48 (90.6) 53 (100) Secondary 14 (7.0) 186 (93.0) 200 (100) Tertiary 8 (6.6) 113 (93.4) 121 (100) Viral load status Suppressed 29 (8.0) 334 (92.0) 363 (100) b 0.230 a Not suppressed 1 (2.3) 43 (97.7) 44 (100) b ART Regimen First-line 25 (7.1) 325 (92.9) 350 (100) 0.800 a Second-line 5 (7.6) 61 (92.4) 66 (100) ART Duration > 5 years 5 (7.4) 63 (92.6) 68 (100) 2.434 0.312 a 5–10 years 4 (3.8) 100 (96.2) 104 (100) > 10 years 21 (8.6) 223 (91.4) 244 (100) a Fisher’s Exact value b Viral load results (n = 407) There was no statistically significant association between the explored factors and diabetes. (Table 3 ). Table 4 Predictors of NCDs among Respondents Variable B aOR 95% CI for aOR P value Lower Upper Obesity Income Low income 1 0.007 a Middle income 0.038 1.038 0.619 1.741 0.886 High income 0.708 2.030 1.261 3.269 0.004 a ART Regimen First-line 1 Second-line -0.870 0.419 0.219 0.801 0.008 a ART Duration > 5 years 1 0.638 5–10 years 1.239 0.656 2.337 0.509 > 10 years 0.984 0.555 1.745 0.957 Hypertension Age groups 18–27 years 1 0.005 a 28–37 years 0.354 1.424 0.341 5.940 0.628 38–47 years 0.637 1.890 0.563 6.350 0.303 48–57 years 1.175 3.238 0.970 10.814 0.056 58–67 years 1.498 4.471 1.275 15.683 0.019 a Viral load status Suppressed 1 Not suppressed -0.296 0.744 0.387 1.430 0.374 ART Regimen First-line 1 Second-line -0.402 0.669 0.387 1.158 0.151 Diabetes Age groups 18–27 years 1 0.231 28–37 years 18.805 146862316.311 0.000 0.999 38–47 years 17.914 60279308.934 0.000 0.999 48–57 years 18.798 145842439.114 0.000 0.999 58–67 years 19.257 230783639.917 0.000 0.998 Logistic regression revealed that ART regimen and monthly income were predictors of obesity. Patients on second-line ART regimen had 58.1% lower odds of obesity, compared with those on first-line regimen (aOR = 0.419, 95% CI: 0.219–0.801, P = 0.008); respondents in the high-income category had 2 times higher odds of being obese, compared with those in the low-income category (aOR = 2.030, 95% CI: 1.261–3.269, P = 0.004). Similarly, respondents in the oldest age-group of 58-67-year-olds had 4 times higher odds of having hypertension, compared with the youngest age-group of 18–27-year-olds (aOR = 4.471, 95% CI: 1.275–15.683, P = 0.019). None of the explored factors were found to be predictors of having diabetes mellitus. (Table 4 ). Discussion The objective of this study was to assess ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria. The prevalence among the respondents that are PLHIV for obesity, hypertension, and diabetes mellitus was 37.3%, 52.6%, and 7.2% respectively. ART regimen was a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. Income and age were also predictors of obesity and hypertension respectively: most prevalent among the high-income earners, and the 58–67-year age group, respectively. Our finding that obesity was more prevalent among patients on first-line ART regimen is consistent with other studies from Nigeria and Uganda, that reported increase in the BMI of PLHIV after initiating ART; and elevated rates of metabolic syndrome and its components among HIV-positive patients on ART. 34 , 38 , 39 , 40 , 41 A substantial weight gain in ART-naïve individuals starting first-line ART, and elevated rates of metabolic syndrome and its components among treatment-experienced PLHIV was reported in other studies. 34 , 38 , 42 We also found that hypertension was more prevalent among the patients on first-line ART regimen. Though this was not a statistically significant association, it is consistent with findings from a Northwestern Nigeria study, in which 90% of the ART- exposed group received first-line therapy. The prevalence of MS (hypertension being the most common feature) in the ART-exposed group was 19.3%, compared with 5.3% in the ART-naive group. Similarly, Dimala et al. found in a study involving 100 first-line ART exposed patients, and 100 ART-naive patients, that hypertension was significantly more prevalent in the ART-exposed patients than the ART-naive group; 38% and 19%, respectively (p = 0.003). These findings were also not statistically significant. 13 , 43 None of the explored factors were found to be predictors of diabetes mellitus. This could possibly be as a result of lack of effect size due to the small proportion of respondents (7.2%) that had diabetes in this study. This is dissimilar to findings in many studies that reported significantly higher prevalence of diabetes or hyperglycemia among ART-exposed patients. In a cross-sectional study of 200 PLHIV at Limbe Regional Hospital, Cameroon, those on first-line ART for > 12 months had a higher median diabetes risk score (2.30% vs 1.62%) and greater prevalence of high diabetes risk (31% vs 17%) compared with ART naïve counterparts. 44 A similar study found that MS was significantly more prevalent among the patients receiving first-line ART; with a quarter of the patients with MS having hyperglycemia. 45 Interestingly, duration of ART use and viral load suppression status were not significantly associated with obesity, or the other NCDs. This is in agreement with a South-Western Nigeria study that reported no association between ART status and NCDs, and other studies that reported duration of ART exposure was not significantly associated with insulin resistance or glucose metabolism disorders. 13 , 18 , 46 However, this contrasts with some longitudinal studies, which reported an increased cardiometabolic risk with longer ART exposure, and also runs contrary to the hypotheses that chronic immune activation might influence metabolic risk. 6 , 47 , 48 , 49 Though the use of older ART regimen with higher metabolic toxicity persists in resource-limited countries because cost effectiveness, there are newer classes of ART that have excellent suppression of viremia, without apparent toxic effects on lipid metabolism. 15 However, switching to these is not recommended in all cases, in order not to jeopardise viral suppression. 50 , 51 A 2017 study found that insulin resistance was less prevalent among patients using new antiretroviral regimens: 14% compared with 28% among patients on PIs. 52 However, in situations where newer drugs and/or regimens did not achieve the desired suppression, either because of viral resistance, lack of an immune response, or non-adherence to treatment, the older drug combinations, especially PI-containing regimens are used, with efforts made to choose the one with the least metabolic effects. 53 , 54 Limitations A longitudinal study design would have been preferable to infer causality. Over 20% of the CD4 count and baseline WHO staging data were missing, so these markers could not be reliably included in the study. This may have underestimated the assessment of the influence of HIV disease severity or immune suppression on NCD development. Conclusion This study suggests that ART regimen is a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. The identification of ART regimen type as a modifiable predictor of obesity among PLHIV has direct programmatic implications for the adoption of an integrated care model that addresses the dual epidemic of HIV and NCDs, especially in resource-poor countries. Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki. Ethics approval was obtained from the Health Research and Ethics Committee of the Lagos University Teaching Hospital (Approval No. ADM/DSCST/ HREC/APP/7324) and the Lagos State University Teaching Hospital (Approval No. LREC/06/10/2895). Permission to conduct the study was obtained from the heads of departments of Haematology and Blood Transfusion in the two facilities, Written informed consent was obtained from every participant, and confidentiality was maintained throughout the study. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Funding The authors funded the research. Author Contribution Conceptualization of the study and design by EOO, OMO, OFA; data acquisition, data analysis, and manuscript preparation by EOO, OMO; manuscript editing and manuscript review by EOO, OMO, OFA. Acknowledgement We want to express our gratitude to the participants that took part in the study. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Joint United Nations Programme on HIV/AIDS (UNAIDS). The Gap Report ISBN: 978-92-9253-062-4. 2014. https://www.unaids.org/en/resources/documents/2014/20140716_UNAIDS_gap_report Accessed on 24 Nov 2025. World Health Organization (WHO). Global HIV Program: HIV data and statistics. 2024. https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/strategic-information/hiv-data-and-statistics Accessed on 24 Nov 2025. Joint United Nations Program on HIV/AIDS (UNAIDS). Responding to the challenge of non-communicable disease. AIDS. 2013. https://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf Accessed on 24 Nov 2025. World Health Organization (WHO). Integration of noncommunicable diseases into HIV service packages. Tech Brief. 2023. https://www.who.int/publications/i/item/9789240073470 Accessed on 24 Nov 2025. Ge L, Tian X, Sun C, Hu P, Yu M. Pathogenesis of HIV-associated metabolic syndrome and clinical management recommendations. Int J Gen Med. 2025;18:5213–32. Moyo-Chilufya M, Maluleke K, Kgarosi K, Muyoyeta M, Hongoro C, Musekiwa A. The burden of non-communicable diseases among people living with HIV in Sub-Saharan Africa: a systematic review and meta-analysis. EClinicalMedicine. 2023;65:102255. National Agency for the Control of AIDS (NACA). 2025 Nigeria prevalence rate. 2025. https://naca.gov.ng/2025/nigeria-prevalence-rate/ Accessed on 03 Feb 2026. Trickey A, May MT, Vehreschild JJ, Obel N, Gill MJ, Crane HM et al. Antiretroviral Therapy Collaboration. Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV. 2017;4(8):e349–56. Smith CJ, Ryom L, Weber R, Morlat P, Pradier C, Reiss P, et al. Trends in underlying causes of death in people with HIV from 1999 to 2011 (D:A:D): a multicohort collaboration. Lancet. 2014;384(9939):241–8. Weijsenfeld AM, Blokhuis C, Stuiver MM, Wit FWNM, Pajkrt D. ATHENA observational HIV cohort. Longitudinal virological outcomes and factors associated with virological failure in behaviorally HIV-infected young adults on combination antiretroviral treatment in the Netherlands, 2000 to 2015. Medicine. 2019;98:e16357. Third Report of the National Cholesterol Education Program (NCEP). expert panel on detection, evaluation, and treatment of high blood cholesterol in adults. Adult Treatment Panel III final report. Circulation. 2002;106:3143–421. Jain RG, Furfine ES, Pedneault L, White AJ, Lenhard JM. Metabolic complications associated with antiretroviral therapy. Antiviral Res. 2001;51(3):151–77. Muhammad FY, Gezawa ID, Uloko A, Yakasai AM, Habib AG, Iliyasu G. Metabolic syndrome among HIV infected patients a comparative cross-sectional study in northwestern Nigeria. Diabetes Metab Syndr. 2017;11(Suppl 1):523–9. Maganga E, Smart LR, Kalluvya S, Kataraihya JB, Saleh AM, Obeid L, et al. Glucose metabolism disorders, HIV and antiretroviral therapy among Tanzanian adults. PLoS ONE. 2015;10:e0134410. Wohl DA, McComsey G, Tebas P, Brown TT, Glesby MJ, Reeds D, et al. Current concepts in the diagnosis and management of metabolic complications of HIV infection and its therapy. Clin Infect Dis. 2006;43:645–53. Sprinz E, Lazzaretti RK, Kuhmmer R, Ribeiro JP. Dyslipidemia in HIV-infected individuals. Braz J Infect Dis. 2010;14:575–88. Fisher SD, Miller TL, Lipshultz SE. Impact of HIV and highly active antiretroviral therapy on leukocyte adhesion molecules, arterial inflammation, dyslipidemia, and atherosclerosis. Atherosclerosis. 2006;185:1–11. World Health Organization. Update of recommendations on first-and second-line antiretroviral regimens. 2019. https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1 . Accessed on 03 Feb 2026. World Health Organization. Update of recommendations on first-and second-line antiretroviral regimens. 2019. https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1 . Accessed on 03 Feb 2026. Walmsley S, Bernstein B, King M, Arribas J, Beall G, Ruane P, et al. the M98-863 Study Team. Lopinavir–ritonavir versus nelfinavir for the initial treatment of HIV infection. N Engl J Med. 2002;346(26):2039–46. Dubé MP, Stein JH, Aberg JA, Fichtenbaum CJ, Gerber JG, Tashima KT, et al. Guidelines for the evaluation and management of dyslipidemia in human immunodeficiency virus (HIV)-infected adults receiving antiretroviral therapy: recommendations of the HIV Medicine Association of the Infectious Disease Society of America and the Adult AIDS Clinical Trials Group. Clin Infect Dis. 2003;37(5):613–27. Crane HM, Grunfeld C, Willig JH, Mugavero MJ, Van Rompaey S, Moore R, et al. Impact of NRTIs on lipid levels among a large HIV-infected cohort initiating antiretroviral therapy in clinical care. AIDS. 2011;25:185–95. UNAIDS. Responding to the Challenges of Non-communicable Disease. AIDS. 2013. https://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf Accessed 11 Feb 2026. Chepchirchir A, Jaoko W, Nyagol J. Risk indicators and effects of hypertension on HIV/AIDS disease progression among patients seen at Kenyatta hospital HIV care center. AIDS Care. 2017;30(5):544–50. Cropsey KL, Willig JH, Mugavero MJ, Crane HM, McCullumsmith C, Lawrence S, et al. Cigarette smokers are less likely to have undetectable viral loads: results from four HIV clinics. J Addict Med. 2016;10(1):13–9. Nguyen NTP, Tran BX, Hwang LY, Markham CM, Swartz MD, Vidrine JI, et al. Effects of cigarette smoking and nicotine dependence on adherence to antiretroviral therapy among HIV-positive patients in Vietnam. AIDS Care. 2016;28(3):359–64. Pokhrel KN, Gaulee Pokhrel K, Neupane SR, Sharma VD. Harmful alcohol drinking among HIV-positive people in Nepal: an overlooked threat to anti-retroviral therapy adherence and health-related quality of life. Glob Health Action. 2018;11(1):1441783. Nugent R, Barnabas RV, Golovaty I, Osetinsky B, Roberts DA, Bisson C, et al. Costs and cost-effectiveness of HIV/noncommunicable disease integration in Africa: from theory to practice. AIDS. 2018;32(1):S83–92. Patel P, Rose CE, Collins PY, Nuche-Berenguer B, Sahasrabuddhe VV, Peprah E, et al. Noncommunicable diseases among HIV-infected persons in low-income and middle-income countries: a systematic review and meta-analysis. AIDS. 2018;32(1):S5–20. National Agency for the Control of AIDS (NACA). Nigeria Prevalence. 2018. https://naca.gov.ng/nigeria-prevalence-rate/ Accessed on 2025 Nov 25. Federal Ministry of Health Nigeria. National Guidelines for HIV prevention, treatment and care. 2020. https://hivpreventioncoalition.unaids.org/en/resources/national-guidelines-hiv-prevention-treatment-and-care Accessed on 2025 Nov 24. U.S. Embassy and Consulate in Nigeria. President’s Emergency Plan for AIDS Relief (PEPFAR) program. 2025. https://ng.usembassy.gov/pepfar/ Accessed on 2025 Nov 25. Centre for Integrated Health Programs (CIHP). About Centre for Integrated Health Programs. https://cihpng.org/about-cihp/ Accessed on 2025 Nov 25. Jumare J, Dakum P, Sam-Agudu N, Memiah P, Nowak R, Bada F. Prevalence and characteristics of metabolic syndrome and its components among adults living with and without HIV in Nigeria: a single-centre study. BMC Endocr Disord. 2023;23:160. World Health Organization (WHO). Noncommunicable disease surveillance, monitoring and reporting: STEPS Manual. 2023. https://www.who.int/teams/noncommunicable-diseases/surveillance/systems-tools/steps/manuals Accessed on 2025 Nov 25. KoboToolbox. Intuitive and adaptable data tools to maximize your impact. 2025. https://www.kobotoolbox.org/ Accessed on 2025 Nov 25. Seyoum TF, Andualem Z, Yalew HF. Insecticide-treated bed net use and associated factors among households having under-five children in East Africa: a multilevel binary logistic regression analysis. Malar J. 2023;22:10. Amutuhaire W, Mulindwa F, Castelnuovo B, Brusselaers N, Schwarz JM, Edrisa M, et al. Prevalence of cardiometabolic disease risk factors in people with HIV initiating antiretroviral therapy at a high-volume HIV clinic in Kampala, Uganda. Open Forum Infect Dis. 2023;10(6):ofad241. Achwoka D, Mutave R, Oyugi JO, Achia T. Tackling an emerging epidemic: the burden of non-communicable diseases among people living with HIV/AIDS in sub-Saharan Africa. Pan Afr Med J. 2020;36:271. Isa SE, Oche AO, Kang'ombe AR, Okopi JA, Idoko JA, Cuevas LE, et al. Human Immunodeficiency Virus and risk of type 2 diabetes in a large adult cohort in Jos, Nigeria. Clin Infect Dis. 2016;63(6):830–5. Rimamnunra G, Utoo P, Ngwoke K, Bako I, Akwaras A, Swende L, et al. Prevalence of non-communicable diseases among HIV positive patients on antiretroviral therapy at a tertiary health facility in Makurdi, North-Central, Nigeria. Niger Health J. 2023;23(3):734–40. Bourgi K, Rebeiro PF, Turner M, Castilho JL, Hulgan T, Raffanti SP, et al. Greater weight gain in treatment-naive persons starting Dolutegravir-based antiretroviral therapy. Clin Infect Dis. 2020;70(7):1267–74. Dimala CA, Atashili ], Mbuagbaw JC, Wilfred A, Monekosso GL. Prevalence of hypertension in HIV/AIDS patients on highly active antiretroviral therapy (HAART) compared with HAART-naive patients at the Limbe regional hospital, Cameroon. PLoS ONE. 2016;11:e0148100. Dimala CA, Atashili J, Mbuagbaw JC, Wilfred A, Monekosso GL. A Comparison of the diabetes risk score in HIV/AIDS patients on highly active antiretroviral therapy (HAART) and HAART-naïve patients at the Limbe regional hospital, Cameroon. PLoS ONE. 2016;11(5):e0155560. Mbunkah HA, Meriki HD, Kukwah AT, Nfor O, Nkuo-Akenji T. Prevalence of metabolic syndrome in human immunodeficiency virus-infected patients from the South-West region of Cameroon, using the adult treatment panel III criteria. Diabetol Metab Syndr. 2014;6:92. Ogunmola OJ, Oladosu OY, Olamoyegun AM. Association of hypertension and obesity with HIV and antiretroviral therapy in a rural tertiary health centre in Nigeria: a cross-sectional cohort study. Vasc Health Risk Manag. 2014;10:129–37. Chukwuonye II, Ohagwu KA, Ogah OS, John C, Oviasu E, Anyabolu EN, et al. Prevalence of overweight and obesity in Nigeria: systematic review and meta-analysis of population-based studies. PLOS Glob Public Health. 2022;2(6):e0000515. Trachunthong D, Tipayamongkholgul M, Chumseng S, Darasawang W, Bundhamcharoen K. Burden of metabolic syndrome in the global adult HIV-infected population: a systematic review and meta-analysis. BMC Public Health. 2024;24(1):2657. Chinbuah S, Mensah EK, Onumah S, Abban F, Choi JY. Cardiovascular risk among people living with HIV in Ghana. Infect Chemother. 2025;57(2):238–47. Carr A, Hudson J, Chuah J, Mallal S, Law M, Hoy J. et. al. HIV protease inhibitor substitution in patients with lipodystrophy: a randomized, controlled, open-label, multicentre study. AIDS. 2001;15:1811–22. Prosperi MC, Fabbiani M, Fanti I, Zaccarelli M, Colafigli M, Mondi A. Predictors of first-line antiretroviral therapy discontinuation due to drug-related adverse events in HIV-infected patients: a retrospective cohort study. BMC Infect Dis. 2012;12:296. Araujo S, Bañón S, Machuca I, Moreno A, Pérez-Elías MJ, Casado IL. Prevalence of insulin resistance and risk of diabetes mellitus in HIV-infected patients receiving current antiretroviral drugs. Eur | Endocrinol. 2014;171:545–54. Arribas JR, Pulido F, Delgado R, Lorenzo A, Miralles P, Arranz A, et al. Lopinavir/ritonavir as single-drug therapy for maintenance of HIV-1 viral suppression: 48-week results of a randomized, controlled, open-label, proof-of-concept pilot clinical trial (OK Study). J Acquir Immune Defic Syndr. 2005;40:280–7. Patick AK, Potts KE. Protease inhibitors as antiviral agents. Clin Microbiol Rev. 1998;11:614–27. Additional Declarations No competing interests reported. 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Ekekezie","email":"data:image/png;base64,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","orcid":"","institution":"National Postgraduate Medical College of Nigeria","correspondingAuthor":true,"prefix":"","firstName":"Oyenike","middleName":"Oyeronke","lastName":"Ekekezie","suffix":""},{"id":607753245,"identity":"c8616651-a8c6-479d-876e-619e98fbb522","order_by":1,"name":"Mayowa Omolabake Odofin","email":"","orcid":"","institution":"College of Medicine, University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Mayowa","middleName":"Omolabake","lastName":"Odofin","suffix":""},{"id":607753246,"identity":"68b23a51-7885-4eb0-90bd-12364be3d254","order_by":2,"name":"Foluke Adenike Olatona","email":"","orcid":"","institution":"College of Medicine, University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Foluke","middleName":"Adenike","lastName":"Olatona","suffix":""}],"badges":[],"createdAt":"2026-02-13 21:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8875532/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8875532/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105563117,"identity":"8cee22b0-cc15-4950-8814-0c97802ad329","added_by":"auto","created_at":"2026-03-27 12:46:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1097468,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8875532/v1/44b1e644-6d11-4267-9e2e-9ea8acb843ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An assessment of ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally antiretroviral therapy (ART) has saved millions of lives, with a decline of 58% in deaths from AIDS-related causes from 2001 to 2020.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e This has enabled people living with HIV (PLHIV) to lead longer and more productive lives, though they become more susceptible to NCDs later in life due to an interplay of aging, ART-related factors, and lifestyle.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Despite the progress made in treatment and prevention, HIV infection remains a significant public health problem, with 40.8\u0026nbsp;million people living with HIV globally as at the end of 2024, and 1.9\u0026nbsp;million people living with the virus in Nigeria, as of 2025.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The availability of improved ART treatment options has turned HIV into a manageable chronic condition, with marked improvement in survival and quality of life.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Key indicators of favorable long-term outcomes for patients on ART include optimal HIV viral suppression and immune system restoration.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, despite therapeutic effectiveness, ART regimens have long been associated with metabolic complications like dyslipidaemia, insulin resistance, weight gain and bone demineralization. Generally, metabolic syndrome (MS) refers to a group of metabolic abnormalities, which includes three or more these criteria: abdominal obesity, high blood pressure, increased fasting glucose, increased triglycerides, and decreased high-density lipoproteins (HDLs). MS is associated with insulin resistance, proinflammatory and prothrombotic states; which increase cardiovascular disease (CVD) risk.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e The resulting NCDs reduce quality of life; and increase mortality among PLHIV, eroding the gains of ART.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Muhammad et al. found in Northwest Nigeria that the prevalence of MS in patients receiving ART was 19.3% compared to 5.3% in ART-naive patients; with insulin resistance in 79.3% of the ART-exposed patients compared to the 25.0% ART-naive group.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Similarly, in a study among Tanzanian adults, glucose metabolism disorders were more prevalent among ART-exposed patients (32.7%) compared to ART-naive (8.0%) and control groups (7.2%); diabetes and impaired glucose tolerance were also more common in patients receiving ART.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eClinical and laboratory evidence have shown that ART can induce adverse metabolic complications, characterized by lipodystrophy, dyslipidemia, insulin resistance, central adiposity, increased risk of cardiovascular disease and atherosclerosis.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The dyslipidemia is characterized by hypercholesterolemia, hypertriglyceridemia, and decreased serum HDL, with or without increased serum LDL.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e The older ART regimen are associated with higher metabolic toxicity, but are still used in resource-limited countries due to cost effectiveness.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Nucleoside reverse transcriptase inhibitors NRTIs (abacavir, lamivudine, zidovudine, emtricitabine, tenofovir), non-nucleoside reverse transcriptase inhibitors NNRTIs (nevirapine, efavirenz), and protease inhibitors PIs (lopinavir, ritonavir, atazanavir) are commonly recommended in the first-line regimens.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e The lipid abnormalities associated with use of PIs are severe and more common than other classes of ARTs, sometimes resulting in discontinuation.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e However, NNRTIs and NRTIs are reported to cause modest changes. \u003csup\u003e17,21,22\u003c/sup\u003e A cycle of events invariably ensues: the NCDs that result from ART metabolic toxicity complicates HIV disease management by affecting adherence to ART, and increasing the risk of drug-drug interactions.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e In turn, poor ART adherence leads to suboptimal and slow immune recovery, characterised by low CD4 cell counts, and non-suppression of HIV viral load, increasing the NCD risk factors.\u003csup\u003e\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWith the paradoxical intricacies surrounding ART in PLWHA, an assessment of ART-related factors as predictors of NCDs among adult patients on antiretroviral therapy attending tertiary health facilities in Lagos state will enable the prompt deployment of preventive measures, early detection and early onset of treatment of NCDs in this population. This is consistent with the integration of health services being canvassed to tackle the double disease burden of HIV-NCD, which will improve the overall well-being of the patients, by reducing morbidity and mortality rates, and decreasing HIV transmission within the community. Identification of these predictors will also help stakeholders make informed decisions in developing targeted interventions to address the dual disease burden. Despite the growing burden of NCDs, particularly in LMICs, studies on the predictors for NCDs among PLHIV remain limited. This gap is hindering the development of effective and efficient evidence-based strategies, targeted interventions, and policies for integrating HIV and NCD care and services, which is crucial for managing the dual disease burden, and improving health outcomes for this vulnerable population.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Lagos State, despite its relatively low HIV prevalence of 1.4% remains a priority area for the study due to its dense population, high internal migration, and complex socioeconomic structure, which collectively pose ongoing challenges for HIV prevention and care.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cstrong\u003eStudy design and setting\u003c/strong\u003e \u003cp\u003eThis cross-sectional study was carried out between June and July 2025 in the Antiretroviral clinics of the departments of Haematology and Blood Transfusion of the Lagos University Teaching Hospital (LUTH), Idi Araba, and, the Lagos State University Teaching Hospital (LASUTH), Ikeja. These clinics were commissioned in 2004, to cater to children, adolescents, adults, pregnant women, both citizens and foreign nationals infected with HIV, under the auspices of the US President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) program, with the Centre for Integrated Health Programs (CIHP) as the implementing partner in Nigeria.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Population\u003c/b\u003e: These consisted of HIV-positive patients attending ART clinics in LUTH and LASUTH, aged 18 years and above, and having documented HIV-positive results: either newly diagnosed ART-na\u0026iuml;ve or ART experienced. Those less than 18 years of age, with severe illness requiring urgent care, accessing care for pre- or post-exposure prophylaxis, and pregnant women (to avoid confounding metabolic changes) were excluded from the study.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSample size determination\u003c/strong\u003e \u003cp\u003eThe minimum sample size (n) was determined using Cochran\u0026rsquo;s formula n=z\u003csup\u003e2\u003c/sup\u003epq/d\u003csup\u003e2\u003c/sup\u003e. Z at 95% confidence level is 1.96; d is the margin of error at 5% (0.05), and p was the prevalence of obesity among PLHIV from a previous study in Nigeria (38.4%).\u003csup\u003e34\u003c/sup\u003e Accordingly, n\u0026thinsp;=\u0026thinsp;363; with 10% contingency, the minimum sample size was 400. Four hundred and sixteen (416) eligible patients were recruited from the clinics within the two-month study period.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSampling technique\u003c/strong\u003e \u003cp\u003eA multistage sampling technique was used. Stage 1 was the purposive selection of the two tertiary hospitals in Lagos state, because they serve as the major ART treatment centers. The total number of eligible patients currently receiving ART at both facilities was the sampling frame. This served as the pool from which study participants were selected. Facility 1 (LUTH) 5,895\u0026thinsp;+\u0026thinsp;Facility 2 (LASUTH) 5,526\u0026thinsp;=\u0026thinsp;11,421 patients. Stage 2 involved proportional allocation of the minimum sample size (400) across the two facilities. Facility 1 (LUTH) 206\u0026thinsp;+\u0026thinsp;Facility 2 (LASUTH) 194\u0026thinsp;=\u0026thinsp;400 patients. Systematic random sampling was used in stage 3 to select the participants from each facility. The sampling interval (k) was determined by dividing the total population in the facility by the sample size desired from each facility. Facility 1 (LUTH) k\u0026thinsp;=\u0026thinsp;5,895 / 206\u0026thinsp;=\u0026thinsp;29. Facility 2 (LASUTH) k\u0026thinsp;=\u0026thinsp;5,526 / 194\u0026thinsp;=\u0026thinsp;29. A random number between 1 and the calculated interval of 29 was chosen by simple random sampling (balloting), to serve as the starting point, which was 10. Every tenth patient was recruited until the sample size was reached, excluding those that declined consent.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e\u003cb\u003eData collection\u003c/b\u003e: This was carried out on week days at the ART clinics. A recruitment schedule using simple random sampling (balloting) facilitated allocation of days for recruitment to the 2 facilities. A structured interviewer-administered questionnaire adapted from the WHO STEPS Instrument, a question-by-question guide approach to noncommunicable disease risk factor surveillance was used.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e The electronic medical record database, Nigeria Medical Record System (NMRS) was also reviewed to confirm baseline patient information and comorbidities. The questionnaire had sections for socio-demographic information, NCD disease status, anthropometric and biomedical measurements. The study was introduced to the participants and their consent sought, while waiting to be seen by the physicians. A secluded area within the facility was used for face-to-face interview, followed by taking of measurements. Data was collected using Kobo Toolbox app on smartphones: an open-source platform for collecting, managing, and visualizing data.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Five ART nurses and two ART case managers were trained for two days on the study objectives, informed consent, the data collection process, and confidentiality. The questionnaire was pre-tested among twenty-nine patients attending the ART clinic at the General hospital Mushin, a secondary health facility.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy variables\u003c/h2\u003e \u003cp\u003eIndependent variables: ART-related variables (viral load suppression, ART regimen, and ART duration) and sociodemographic variables (age-group, sex, level of education and income).\u003c/p\u003e \u003cp\u003eDependent variables: The presence or absence of obesity, hypertension, and diabetes.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData Analysis\u003c/strong\u003e \u003cp\u003eData entered using the Kobo toolbox software was exported to IBM SPSS version 27 by IBM Corporation, Armonk, New York, United States. Descriptive analysis, such as frequencies, charts, and percentages were used to analyze socio-demographic data, prevalence of NCDs and ART-related factors. Bivariate analysis using Chi square test was used to test for significant relationships between variables. Thereafter, variables that had a P-value of \u0026lt;\u0026thinsp;0.2 were entered into the multivariate logistic regression model to determine the predictors of NCDs.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e The results were presented using adjusted odds ratio and 95% confidence interval. A P-value of \u0026lt;\u0026thinsp;0.05 determined the level of statistical significance.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean age group of respondents was 49.13\u0026thinsp;\u0026plusmn;\u0026thinsp;10.18years. Majority, 70.2% (n\u0026thinsp;=\u0026thinsp;292) were female, 54.1% (n\u0026thinsp;=\u0026thinsp;225) married, and 81.5% (n\u0026thinsp;=\u0026thinsp;339) Christian. Most, 48% (n\u0026thinsp;=\u0026thinsp;200) attained secondary education, 64% (n\u0026thinsp;=\u0026thinsp;266) were self-employed, and majority, 44.2% (n\u0026thinsp;=\u0026thinsp;184) earned less than N50,000 monthly (low-income). The prevalence of obesity, hypertension, and diabetes was 37.3% (n\u0026thinsp;=\u0026thinsp;155), 52.6% (n\u0026thinsp;=\u0026thinsp;219), and 7.2% (n\u0026thinsp;=\u0026thinsp;30) respectively; and over 70% of the respondents had at least one NCD.\u003c/p\u003e \u003cp\u003eViral load results were available for 407 of the 416 respondents. Of these 363 (89.2%) and 44 (10.8%) were virally suppressed (viral load\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL), and not suppressed (\u0026ge;\u0026thinsp;1000copies/mL) respectively; 350 (84.1%) and 66 (15.9%) were on a first- and second-line ART regimen respectively; while 68 (16.3%), 104 (25%), and 244 (58.7) were on ART regimen for \u0026lt;\u0026thinsp;5 years, 5\u0026ndash;10 years, and \u0026gt;\u0026thinsp;10 years respectively.\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\u003eAssociation between socio-demographic, ART-related factors and Obesity (n\u0026thinsp;=\u0026thinsp;416)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eNo (%) Total n (%) χ\u0026sup2; P 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 group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3\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\u003e28\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84 (60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u0026ndash;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u0026ndash;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51 (63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\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\u003e110 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e182 (62.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e292 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.79\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79 (63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126 (68.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003csup\u003ea\u003c/sup\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\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71 (67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106 (100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64 (50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\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\u003e16 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.379\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\u003eVocational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78 (64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e227 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363 (100) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.662\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\u003eNot suppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (100) \u003csup\u003eb\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141 (40.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e209 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e350 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003csup\u003ea\u003c/sup\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\u003eSecond-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52 (78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42 (61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.193\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\u003e5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e161 (66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e244 (100)\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Significant \u003csup\u003eb\u003c/sup\u003e Viral load results (n\u0026thinsp;=\u0026thinsp;407)\u003c/p\u003e \u003cp\u003eObesity was significantly more prevalent among patients on first-line ART regimen (40.3%, χ2\u0026thinsp;=\u0026thinsp;8.642, p\u0026thinsp;=\u0026thinsp;0.003), and the high-income earners (49.2%, χ\u0026sup2;=11.100, p\u0026thinsp;=\u0026thinsp;0.004). More virally suppressed patients, and those on ART therapy for 5\u0026ndash;10 years were obese, though association was not significant (37.5%, χ2\u0026thinsp;=\u0026thinsp;0.192, p\u0026thinsp;=\u0026thinsp;0.662) and (44.2%, χ2\u0026thinsp;=\u0026thinsp;3.288, p\u0026thinsp;=\u0026thinsp;0.193) respectively. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between socio-demographic, ART-related factors and Hypertension (n\u0026thinsp;=\u0026thinsp;416)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eNo (%) Total n (%) χ\u0026sup2; P 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 group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003csup\u003ea\u003c/sup\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\u003e28\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (44.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u0026ndash;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91 (58.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u0026ndash;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\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\u003e152 (52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140 (47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e292(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.712\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.752\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\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106(100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\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\u003e20 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.253\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\u003eVocational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107 (53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93 (46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66 (54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121(100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195 (53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e168 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363 (100) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.186\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\u003eNot suppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (100) \u003csup\u003eb\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e191 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e159 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e350 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.070\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\u003eSecond-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (57.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.232\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\u003e5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e107 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e244 (100)\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Significant \u003csup\u003eb\u003c/sup\u003e Viral load results (n\u0026thinsp;=\u0026thinsp;407)\u003c/p\u003e \u003cp\u003eThe prevalence of hypertension showed a significant upward trend with age, highest among the 58\u0026ndash;67-year age group (66.3%, χ\u0026sup2;=18.438, P\u0026thinsp;=\u0026thinsp;0.001). More virally suppressed patients (53.7%, χ\u0026sup2;=1.748, P\u0026thinsp;=\u0026thinsp;0.186), on first-line regimen (54.6%%, χ\u0026sup2;=3.287, P\u0026thinsp;=\u0026thinsp;0.070), and on ART therapy for more than 10 years (56.1%, χ\u0026sup2;=2.922, P\u0026thinsp;=\u0026thinsp;0.232) had hypertension, though association was not significant. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between socio-demographic, ART-related factors and Diabetes Mellitus (n\u0026thinsp;=\u0026thinsp;416)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eNo (%) Total n (%) χ\u0026sup2; P 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 group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003csup\u003ea\u003c/sup\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\u003e28\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22 (91.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e134 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u0026ndash;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144 (91.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u0026ndash;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\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\u003e22 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e270 (92.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e292 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.837\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e171 (92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.835\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\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97 (91.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106 (100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118 (93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\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\u003e2 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30 (93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.864\u003csup\u003ea\u003c/sup\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\u003eVocational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (100)\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 \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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48 (90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\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\u003e186 (93.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e113 (93.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e334 (92.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363 (100) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.230\u003csup\u003ea\u003c/sup\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\u003eNot suppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (100) \u003csup\u003eb\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e325 (92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e350 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003csup\u003ea\u003c/sup\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\u003eSecond-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63 (92.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.312\u003csup\u003ea\u003c/sup\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\u003e5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100 (96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104 (100)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e223 (91.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e244 (100)\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Fisher\u0026rsquo;s Exact value \u003csup\u003eb\u003c/sup\u003e Viral load results (n\u0026thinsp;=\u0026thinsp;407)\u003c/p\u003e \u003cp\u003eThere was no statistically significant association between the explored factors and diabetes. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of NCDs among Respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eaOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e95% CI for aOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eObesity\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\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003cp\u003e0.007\u003csup\u003ea\u003c/sup\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\u003eMiddle income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.886\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\u003eHigh income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003cp\u003e0.638\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\u003e5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.509\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\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge groups\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;27 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003cp\u003e0.005\u003csup\u003ea\u003c/sup\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\u003e28\u0026ndash;37 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.628\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\u003e38\u0026ndash;47 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.303\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\u003e48\u0026ndash;57 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.056\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\u003e58\u0026ndash;67 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.019\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot suppressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond-line\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge groups\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;27 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\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 \u003cp\u003e0.231\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\u003e28\u0026ndash;37 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146862316.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\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\u003e38\u0026ndash;47 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60279308.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\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\u003e48\u0026ndash;57 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145842439.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\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\u003e58\u0026ndash;67 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230783639.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.998\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\u003eLogistic regression revealed that ART regimen and monthly income were predictors of obesity. Patients on second-line ART regimen had 58.1% lower odds of obesity, compared with those on first-line regimen (aOR\u0026thinsp;=\u0026thinsp;0.419, 95% CI: 0.219\u0026ndash;0.801, P\u0026thinsp;=\u0026thinsp;0.008); respondents in the high-income category had 2 times higher odds of being obese, compared with those in the low-income category (aOR\u0026thinsp;=\u0026thinsp;2.030, 95% CI: 1.261\u0026ndash;3.269, P\u0026thinsp;=\u0026thinsp;0.004). Similarly, respondents in the oldest age-group of 58-67-year-olds had 4 times higher odds of having hypertension, compared with the youngest age-group of 18\u0026ndash;27-year-olds (aOR\u0026thinsp;=\u0026thinsp;4.471, 95% CI: 1.275\u0026ndash;15.683, P\u0026thinsp;=\u0026thinsp;0.019). None of the explored factors were found to be predictors of having diabetes mellitus. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe objective of this study was to assess ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria. The prevalence among the respondents that are PLHIV for obesity, hypertension, and diabetes mellitus was 37.3%, 52.6%, and 7.2% respectively. ART regimen was a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. Income and age were also predictors of obesity and hypertension respectively: most prevalent among the high-income earners, and the 58\u0026ndash;67-year age group, respectively.\u003c/p\u003e \u003cp\u003eOur finding that obesity was more prevalent among patients on first-line ART regimen is consistent with other studies from Nigeria and Uganda, that reported increase in the BMI of PLHIV after initiating ART; and elevated rates of metabolic syndrome and its components among HIV-positive patients on ART.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e A substantial weight gain in ART-na\u0026iuml;ve individuals starting first-line ART, and elevated rates of metabolic syndrome and its components among treatment-experienced PLHIV was reported in other studies.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e We also found that hypertension was more prevalent among the patients on first-line ART regimen. Though this was not a statistically significant association, it is consistent with findings from a Northwestern Nigeria study, in which 90% of the ART- exposed group received first-line therapy. The prevalence of MS (hypertension being the most common feature) in the ART-exposed group was 19.3%, compared with 5.3% in the ART-naive group. Similarly, Dimala et al. found in a study involving 100 first-line ART exposed patients, and 100 ART-naive patients, that hypertension was significantly more prevalent in the ART-exposed patients than the ART-naive group; 38% and 19%, respectively (p\u0026thinsp;=\u0026thinsp;0.003). These findings were also not statistically significant.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNone of the explored factors were found to be predictors of diabetes mellitus. This could possibly be as a result of lack of effect size due to the small proportion of respondents (7.2%) that had diabetes in this study. This is dissimilar to findings in many studies that reported significantly higher prevalence of diabetes or hyperglycemia among ART-exposed patients. In a cross-sectional study of 200 PLHIV at Limbe Regional Hospital, Cameroon, those on first-line ART for \u0026gt;\u0026thinsp;12 months had a higher median diabetes risk score (2.30% vs 1.62%) and greater prevalence of high diabetes risk (31% vs 17%) compared with ART na\u0026iuml;ve counterparts.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e A similar study found that MS was significantly more prevalent among the patients receiving first-line ART; with a quarter of the patients with MS having hyperglycemia.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInterestingly, duration of ART use and viral load suppression status were not significantly associated with obesity, or the other NCDs. This is in agreement with a South-Western Nigeria study that reported no association between ART status and NCDs, and other studies that reported duration of ART exposure was not significantly associated with insulin resistance or glucose metabolism disorders.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e However, this contrasts with some longitudinal studies, which reported an increased cardiometabolic risk with longer ART exposure, and also runs contrary to the hypotheses that chronic immune activation might influence metabolic risk.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThough the use of older ART regimen with higher metabolic toxicity persists in resource-limited countries because cost effectiveness, there are newer classes of ART that have excellent suppression of viremia, without apparent toxic effects on lipid metabolism.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e However, switching to these is not recommended in all cases, in order not to jeopardise viral suppression.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e A 2017 study found that insulin resistance was less prevalent among patients using new antiretroviral regimens: 14% compared with 28% among patients on PIs.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e However, in situations where newer drugs and/or regimens did not achieve the desired suppression, either because of viral resistance, lack of an immune response, or non-adherence to treatment, the older drug combinations, especially PI-containing regimens are used, with efforts made to choose the one with the least metabolic effects.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eA longitudinal study design would have been preferable to infer causality. Over 20% of the CD4 count and baseline WHO staging data were missing, so these markers could not be reliably included in the study. This may have underestimated the assessment of the influence of HIV disease severity or immune suppression on NCD development.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study suggests that ART regimen is a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. The identification of ART regimen type as a modifiable predictor of obesity among PLHIV has direct programmatic implications for the adoption of an integrated care model that addresses the dual epidemic of HIV and NCDs, especially in resource-poor countries.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The study was conducted in accordance with the Declaration of Helsinki. Ethics approval was obtained from the Health Research and Ethics Committee of the Lagos University Teaching Hospital (Approval No. ADM/DSCST/ HREC/APP/7324) and the Lagos State University Teaching Hospital (Approval No. LREC/06/10/2895). Permission to conduct the study was obtained from the heads of departments of Haematology and Blood Transfusion in the two facilities, Written informed consent was obtained from every participant, and confidentiality was maintained throughout the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors funded the research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization of the study and design by EOO, OMO, OFA; data acquisition, data analysis, and manuscript preparation by EOO, OMO; manuscript editing and manuscript review by EOO, OMO, OFA.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe want to express our gratitude to the participants that took part in the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJoint United Nations Programme on HIV/AIDS (UNAIDS). The Gap Report ISBN: 978-92-9253-062-4. 2014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unaids.org/en/resources/documents/2014/20140716_UNAIDS_gap_report\u003c/span\u003e\u003cspan address=\"https://www.unaids.org/en/resources/documents/2014/20140716_UNAIDS_gap_report\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 24 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO). Global HIV Program: HIV data and statistics. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/strategic-information/hiv-data-and-statistics\u003c/span\u003e\u003cspan address=\"https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/strategic-information/hiv-data-and-statistics\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 24 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoint United Nations Program on HIV/AIDS (UNAIDS). Responding to the challenge of non-communicable disease. AIDS. 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf\u003c/span\u003e\u003cspan address=\"https://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 24 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO). Integration of noncommunicable diseases into HIV service packages. Tech Brief. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240073470\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240073470\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 24 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGe L, Tian X, Sun C, Hu P, Yu M. Pathogenesis of HIV-associated metabolic syndrome and clinical management recommendations. Int J Gen Med. 2025;18:5213\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoyo-Chilufya M, Maluleke K, Kgarosi K, Muyoyeta M, Hongoro C, Musekiwa A. The burden of non-communicable diseases among people living with HIV in Sub-Saharan Africa: a systematic review and meta-analysis. EClinicalMedicine. 2023;65:102255.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Agency for the Control of AIDS (NACA). 2025 Nigeria prevalence rate. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://naca.gov.ng/2025/nigeria-prevalence-rate/\u003c/span\u003e\u003cspan address=\"https://naca.gov.ng/2025/nigeria-prevalence-rate/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 03 Feb 2026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrickey A, May MT, Vehreschild JJ, Obel N, Gill MJ, Crane HM et al. Antiretroviral Therapy Collaboration. Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV. 2017;4(8):e349\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith CJ, Ryom L, Weber R, Morlat P, Pradier C, Reiss P, et al. Trends in underlying causes of death in people with HIV from 1999 to 2011 (D:A:D): a multicohort collaboration. Lancet. 2014;384(9939):241\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeijsenfeld AM, Blokhuis C, Stuiver MM, Wit FWNM, Pajkrt D. ATHENA observational HIV cohort. Longitudinal virological outcomes and factors associated with virological failure in behaviorally HIV-infected young adults on combination antiretroviral treatment in the Netherlands, 2000 to 2015. Medicine. 2019;98:e16357.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThird Report of the National Cholesterol Education Program (NCEP). expert panel on detection, evaluation, and treatment of high blood cholesterol in adults. Adult Treatment Panel III final report. Circulation. 2002;106:3143\u0026ndash;421.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJain RG, Furfine ES, Pedneault L, White AJ, Lenhard JM. Metabolic complications associated with antiretroviral therapy. Antiviral Res. 2001;51(3):151\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuhammad FY, Gezawa ID, Uloko A, Yakasai AM, Habib AG, Iliyasu G. Metabolic syndrome among HIV infected patients a comparative cross-sectional study in northwestern Nigeria. Diabetes Metab Syndr. 2017;11(Suppl 1):523\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaganga E, Smart LR, Kalluvya S, Kataraihya JB, Saleh AM, Obeid L, et al. Glucose metabolism disorders, HIV and antiretroviral therapy among Tanzanian adults. PLoS ONE. 2015;10:e0134410.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWohl DA, McComsey G, Tebas P, Brown TT, Glesby MJ, Reeds D, et al. Current concepts in the diagnosis and management of metabolic complications of HIV infection and its therapy. Clin Infect Dis. 2006;43:645\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSprinz E, Lazzaretti RK, Kuhmmer R, Ribeiro JP. Dyslipidemia in HIV-infected individuals. Braz J Infect Dis. 2010;14:575\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFisher SD, Miller TL, Lipshultz SE. Impact of HIV and highly active antiretroviral therapy on leukocyte adhesion molecules, arterial inflammation, dyslipidemia, and atherosclerosis. Atherosclerosis. 2006;185:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Update of recommendations on first-and second-line antiretroviral regimens. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1\u003c/span\u003e\u003cspan address=\"https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on 03 Feb 2026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Update of recommendations on first-and second-line antiretroviral regimens. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1\u003c/span\u003e\u003cspan address=\"https://apps.who.int/iris/bitstream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on 03 Feb 2026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalmsley S, Bernstein B, King M, Arribas J, Beall G, Ruane P, et al. the M98-863 Study Team. Lopinavir\u0026ndash;ritonavir versus nelfinavir for the initial treatment of HIV infection. N Engl J Med. 2002;346(26):2039\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDub\u0026eacute; MP, Stein JH, Aberg JA, Fichtenbaum CJ, Gerber JG, Tashima KT, et al. Guidelines for the evaluation and management of dyslipidemia in human immunodeficiency virus (HIV)-infected adults receiving antiretroviral therapy: recommendations of the HIV Medicine Association of the Infectious Disease Society of America and the Adult AIDS Clinical Trials Group. Clin Infect Dis. 2003;37(5):613\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrane HM, Grunfeld C, Willig JH, Mugavero MJ, Van Rompaey S, Moore R, et al. Impact of NRTIs on lipid levels among a large HIV-infected cohort initiating antiretroviral therapy in clinical care. AIDS. 2011;25:185\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNAIDS. Responding to the Challenges of Non-communicable Disease. AIDS. 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf\u003c/span\u003e\u003cspan address=\"https://www.unaids.org/sites/default/files/media_asset/responding-to-the-challenge-of-non-communicable-diseases_en.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed 11 Feb 2026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChepchirchir A, Jaoko W, Nyagol J. Risk indicators and effects of hypertension on HIV/AIDS disease progression among patients seen at Kenyatta hospital HIV care center. AIDS Care. 2017;30(5):544\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCropsey KL, Willig JH, Mugavero MJ, Crane HM, McCullumsmith C, Lawrence S, et al. Cigarette smokers are less likely to have undetectable viral loads: results from four HIV clinics. J Addict Med. 2016;10(1):13\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen NTP, Tran BX, Hwang LY, Markham CM, Swartz MD, Vidrine JI, et al. Effects of cigarette smoking and nicotine dependence on adherence to antiretroviral therapy among HIV-positive patients in Vietnam. AIDS Care. 2016;28(3):359\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePokhrel KN, Gaulee Pokhrel K, Neupane SR, Sharma VD. Harmful alcohol drinking among HIV-positive people in Nepal: an overlooked threat to anti-retroviral therapy adherence and health-related quality of life. Glob Health Action. 2018;11(1):1441783.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNugent R, Barnabas RV, Golovaty I, Osetinsky B, Roberts DA, Bisson C, et al. Costs and cost-effectiveness of HIV/noncommunicable disease integration in Africa: from theory to practice. AIDS. 2018;32(1):S83\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel P, Rose CE, Collins PY, Nuche-Berenguer B, Sahasrabuddhe VV, Peprah E, et al. Noncommunicable diseases among HIV-infected persons in low-income and middle-income countries: a systematic review and meta-analysis. AIDS. 2018;32(1):S5\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Agency for the Control of AIDS (NACA). Nigeria Prevalence. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://naca.gov.ng/nigeria-prevalence-rate/\u003c/span\u003e\u003cspan address=\"https://naca.gov.ng/nigeria-prevalence-rate/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFederal Ministry of Health Nigeria. National Guidelines for HIV prevention, treatment and care. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hivpreventioncoalition.unaids.org/en/resources/national-guidelines-hiv-prevention-treatment-and-care\u003c/span\u003e\u003cspan address=\"https://hivpreventioncoalition.unaids.org/en/resources/national-guidelines-hiv-prevention-treatment-and-care\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Embassy and Consulate in Nigeria. President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) program. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ng.usembassy.gov/pepfar/\u003c/span\u003e\u003cspan address=\"https://ng.usembassy.gov/pepfar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCentre for Integrated Health Programs (CIHP). About Centre for Integrated Health Programs. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cihpng.org/about-cihp/\u003c/span\u003e\u003cspan address=\"https://cihpng.org/about-cihp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJumare J, Dakum P, Sam-Agudu N, Memiah P, Nowak R, Bada F. Prevalence and characteristics of metabolic syndrome and its components among adults living with and without HIV in Nigeria: a single-centre study. BMC Endocr Disord. 2023;23:160.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO). Noncommunicable disease surveillance, monitoring and reporting: STEPS Manual. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/teams/noncommunicable-diseases/surveillance/systems-tools/steps/manuals\u003c/span\u003e\u003cspan address=\"https://www.who.int/teams/noncommunicable-diseases/surveillance/systems-tools/steps/manuals\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoboToolbox. Intuitive and adaptable data tools to maximize your impact. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kobotoolbox.org/\u003c/span\u003e\u003cspan address=\"https://www.kobotoolbox.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed on 2025 Nov 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeyoum TF, Andualem Z, Yalew HF. Insecticide-treated bed net use and associated factors among households having under-five children in East Africa: a multilevel binary logistic regression analysis. Malar J. 2023;22:10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmutuhaire W, Mulindwa F, Castelnuovo B, Brusselaers N, Schwarz JM, Edrisa M, et al. Prevalence of cardiometabolic disease risk factors in people with HIV initiating antiretroviral therapy at a high-volume HIV clinic in Kampala, Uganda. Open Forum Infect Dis. 2023;10(6):ofad241.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAchwoka D, Mutave R, Oyugi JO, Achia T. Tackling an emerging epidemic: the burden of non-communicable diseases among people living with HIV/AIDS in sub-Saharan Africa. Pan Afr Med J. 2020;36:271.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsa SE, Oche AO, Kang'ombe AR, Okopi JA, Idoko JA, Cuevas LE, et al. Human Immunodeficiency Virus and risk of type 2 diabetes in a large adult cohort in Jos, Nigeria. Clin Infect Dis. 2016;63(6):830\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRimamnunra G, Utoo P, Ngwoke K, Bako I, Akwaras A, Swende L, et al. Prevalence of non-communicable diseases among HIV positive patients on antiretroviral therapy at a tertiary health facility in Makurdi, North-Central, Nigeria. Niger Health J. 2023;23(3):734\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBourgi K, Rebeiro PF, Turner M, Castilho JL, Hulgan T, Raffanti SP, et al. Greater weight gain in treatment-naive persons starting Dolutegravir-based antiretroviral therapy. Clin Infect Dis. 2020;70(7):1267\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimala CA, Atashili ], Mbuagbaw JC, Wilfred A, Monekosso GL. Prevalence of hypertension in HIV/AIDS patients on highly active antiretroviral therapy (HAART) compared with HAART-naive patients at the Limbe regional hospital, Cameroon. PLoS ONE. 2016;11:e0148100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimala CA, Atashili J, Mbuagbaw JC, Wilfred A, Monekosso GL. A Comparison of the diabetes risk score in HIV/AIDS patients on highly active antiretroviral therapy (HAART) and HAART-na\u0026iuml;ve patients at the Limbe regional hospital, Cameroon. PLoS ONE. 2016;11(5):e0155560.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMbunkah HA, Meriki HD, Kukwah AT, Nfor O, Nkuo-Akenji T. Prevalence of metabolic syndrome in human immunodeficiency virus-infected patients from the South-West region of Cameroon, using the adult treatment panel III criteria. Diabetol Metab Syndr. 2014;6:92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgunmola OJ, Oladosu OY, Olamoyegun AM. Association of hypertension and obesity with HIV and antiretroviral therapy in a rural tertiary health centre in Nigeria: a cross-sectional cohort study. Vasc Health Risk Manag. 2014;10:129\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChukwuonye II, Ohagwu KA, Ogah OS, John C, Oviasu E, Anyabolu EN, et al. Prevalence of overweight and obesity in Nigeria: systematic review and meta-analysis of population-based studies. PLOS Glob Public Health. 2022;2(6):e0000515.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrachunthong D, Tipayamongkholgul M, Chumseng S, Darasawang W, Bundhamcharoen K. Burden of metabolic syndrome in the global adult HIV-infected population: a systematic review and meta-analysis. BMC Public Health. 2024;24(1):2657.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChinbuah S, Mensah EK, Onumah S, Abban F, Choi JY. Cardiovascular risk among people living with HIV in Ghana. Infect Chemother. 2025;57(2):238\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarr A, Hudson J, Chuah J, Mallal S, Law M, Hoy J. et. al. HIV protease inhibitor substitution in patients with lipodystrophy: a randomized, controlled, open-label, multicentre study. AIDS. 2001;15:1811\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProsperi MC, Fabbiani M, Fanti I, Zaccarelli M, Colafigli M, Mondi A. Predictors of first-line antiretroviral therapy discontinuation due to drug-related adverse events in HIV-infected patients: a retrospective cohort study. BMC Infect Dis. 2012;12:296.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAraujo S, Ba\u0026ntilde;\u0026oacute;n S, Machuca I, Moreno A, P\u0026eacute;rez-El\u0026iacute;as MJ, Casado IL. Prevalence of insulin resistance and risk of diabetes mellitus in HIV-infected patients receiving current antiretroviral drugs. Eur | Endocrinol. 2014;171:545\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArribas JR, Pulido F, Delgado R, Lorenzo A, Miralles P, Arranz A, et al. Lopinavir/ritonavir as single-drug therapy for maintenance of HIV-1 viral suppression: 48-week results of a randomized, controlled, open-label, proof-of-concept pilot clinical trial (OK Study). J Acquir Immune Defic Syndr. 2005;40:280\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatick AK, Potts KE. Protease inhibitors as antiviral agents. Clin Microbiol Rev. 1998;11:614\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV, antiretroviral therapy, ART regimen, first-line regimen, non-communicable disease, obesity, hypertension, diabetes mellitus","lastPublishedDoi":"10.21203/rs.3.rs-8875532/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8875532/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlobally, antiretroviral therapy (ART) has saved millions of lives, enabling people living with HIV (PLHIV) lead longer and more productive lives, though they become more susceptible to non-communicable diseases (NCDs) later in life. However, despite therapeutic effectiveness, ART regimens have long been associated with metabolic complications. This study aims to assess ART-related factors as predictors of NCDs among adult patients on antiretroviral therapy attending tertiary health facilities in Lagos.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional study was conducted among 416 adult PLHIV attending two tertiary hospitals, using a multistage sampling method. Data was obtained using a pre-tested structured questionnaire adapted from the World Health Organization (WHO) STEPS Instrument, in addition to anthropometric and biomedical measurements. Descriptive, bivariate and multivariate analyses were carried out using IBM SPSS version 27.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age group of respondents was 49.13\u0026thinsp;\u0026plusmn;\u0026thinsp;10.18years. Majority, 70.2% (n\u0026thinsp;=\u0026thinsp;292) were female, and 54.1% (n\u0026thinsp;=\u0026thinsp;225) married. The prevalence of obesity, hypertension, and diabetes was 37.3% (n\u0026thinsp;=\u0026thinsp;155), 52.6% (n\u0026thinsp;=\u0026thinsp;219), and 7.2% (n\u0026thinsp;=\u0026thinsp;30) respectively; and over 70% of the respondents had at least one NCD. ART regimen was a predictor of obesity: patients on second-line ART regimen had 58.1% lower odds of obesity, compared with those on first-line regimen (aOR\u0026thinsp;=\u0026thinsp;0.419, 95% CI: 0.219\u0026ndash;0.801, P\u0026thinsp;=\u0026thinsp;0.008). Hypertension was more prevalent among the patients on first-line ART regimen (54.6%%, χ\u0026sup2;=3.287, P\u0026thinsp;=\u0026thinsp;0.070), though not statistically significant.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study suggests that ART regimen is a predictor of obesity, as it was more prevalent among the patients on first-line regimen. Though hypertension was also more prevalent among these patients, the association was not significant. The identification of ART regimen type as a modifiable predictor of obesity among PLHIV has direct programmatic implications for the adoption of an integrated care model that addresses the dual epidemic of HIV and NCDs, especially in resource-poor countries.\u003c/p\u003e","manuscriptTitle":"An assessment of ART-related factors as predictors of non-communicable diseases among adult patients on antiretroviral therapy in tertiary hospitals in Lagos State, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 20:06:22","doi":"10.21203/rs.3.rs-8875532/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-02T17:12:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T14:34:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47076240241185796708306976956579083758","date":"2026-03-25T09:09:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321450265275599141423374703897302034180","date":"2026-03-25T08:37:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213423877920068909572213229102218147347","date":"2026-03-23T10:37:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256324960437290212656794617364702827262","date":"2026-03-20T16:02:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T16:25:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-18T08:37:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T06:04:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-17T06:01:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-13T21:31:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3804ad35-d358-4420-9318-256522dd62dc","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T20:06:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 20:06:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8875532","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8875532","identity":"rs-8875532","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}